2 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

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4 2 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

5 CONTENTS Contents...3 List of Tables...5 List of Figures...6 Forward...7 Contributor List Introduction Objectives Methodology Modelling Approach Software Used AIDS Epidemic Model (AEM) Version Spectrum version Sources of Data Demographic Data Behavioural and Epidemiological Data of Key Populations Key Population Size Estimates Projection Process - AEM Population Worksheet Heterosexual Worksheet PWID Worksheet (Injection Drug Users) MSM Worksheet Waria Worksheet Epidemic Worksheet HIV Prevalence Worksheet Adult ART Worksheet Projection Process - Spectrum Results HIV Prevalence among Population aged 15 years in Indonesia, Number of key population members living with HIV (PLHIV), ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

6 4.3 Number of new infections among key population members, Total number of PLHIV, new infections and AIDS-related deaths ART among adult PLHIV HIV among children ART among children Prevention of mother to child transmission (PMTCT) Summary of Estimates: 2014 and 2016 Epidemic Updates Limitations Recommendations for future Modelling work References Annexes...50 Annex 1: Procedures used to produce national estimates of key parameters for 2015 and trends over time for input into AEM...50 Annex 2: Inventory of Data Input to AEM Spreadsheets 2016 Epidemic Update...52 Annex 3. Parameter Values used in the Final AEM Model after Fitting...74 Annex 4. Estimation and Projection of People Living with HIV, New HIV Infections, AIDS Deaths and ART Needs among Adults and Children by Gender in Indonesia, Annex 5. Estimation and Projection of People Living with HIV, New HIV Infections, AIDS Deaths and ART Needs among Adults age 15 years old by Gender in Indonesia, Annex 6. Estimation and Projection of People Living with HIV, New HIV infections, AIDS Deaths and ART Needs among Children age 0-14 years old by Gender in Indonesia, Annex 7. Estimation and Projection of People Living with HIV, New HIV infections, AIDS Deaths and ART Needs among Adults age 15 years old in Papua and Non-Papua, Annex 8. New HIV Infections among Adults Age Group 15 years old by Risk Population in 32 Provinces (Non-Papua), years Annex 9. New HIV Infections among Adults Age Group 15 years old by Risk Population in Tanah Papua years ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

7 list of tables Table 3.1: Updated KAP Population Size Estimates, Table 3.2: FSW General non-papua...16 Table 3.3: FSW General Papua...16 Table 3.4: FSW Group 1 & Group 2 non-papua...17 Table 3.5: FSW Group 1 & Group 2 Papua...18 Table 3.6: Clients of FSW non-papua...20 Table 3.7: Clients of FSW Papua...20 Table 3.8: Population Engaging in Casual Sex non-papua...21 Table 3.9: Population Engaging in Casual Sex Papua...21 Table 3.10: Spouses and Regular Partners non-papua...22 Table 3.11: Male PWID Injecting Behaviors non-papua...23 Table 3.12: Male PWID Sexual Behaviors non-papua...24 Table 3.13: Men who have Sex with Men General non-papua...25 Table 3.14: Men who have Sex with Men Group 1 & 2 non-papua...27 Table 3.15: Men who have Sex with Men visiting Sex Workers non-papua...28 Table 3.16: Male Sex Workers non-papua...29 Table 3.17: Transgenders General non-papua...30 Table 3.18: Transgenders Sexual Behaviors non-papua...31 Table 3.19: Transgenders - Client Make-up non-papua...32 Table 3.20: Transgenders engaging in Casual Sex - Sexual Behaviors non-papua...33 Table 3.21: Transgenders Sex Workers Partner Make-up for those with CPs non-papua...34 Table 3.22: Transgenders with Regular Partners - Sexual Behaviors non-papua...35 Table 3.23: Transgenders Sex Workers Regular Partner Make-up non-papua...36 Table 3.24: HIV Prevalence among KAPs non-papua...37 Table 3.25: HIV Prevalence among KAPs and General Population Papua...37 Table 3.26: Number of Adults Receiving ART non-papua...37 Table 3.27: Number of Adults Receiving ART Papua...38 Table 4.1: Table 4.2: Table 4.3: Estimates and Projection of PLHIV by Key Population in Indonesia, Years (AEM result)...41 Estimates and Projection of New HIV Infections by Key Population in Indonesia, Years (AEM result)...42 Summary of differences in key results 2014 vs Modelling...46 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

8 list of figures Figure 3.1: Flow of HIV Epidemic Modelling in Indonesia Figure 4.1: Estimates and Projection of HIV Prevalence among Population Aged 15 years in Indonesia, Years (AEM result)...40 Figure 4.2: Comparison of New Infections from 2014 & 2016 HIV Mathematical... Modelling, (AEM result)...43 Figure 4.3: Estimates and Projection of PLHIV, AIDS Deaths and New HIV Infections among Population Aged 15 years in Indonesia, (AEM result)...43 Figure 4.4: Estimates and Projection of PLHIV and ART Needs among Population Aged 15 Years in Indonesia, (AEM result)...44 Figure 4.5: Estimates and Projection of PLHIV, AIDS Deaths and New HIV Infections among Children Aged 0-14 Years in Indonesia, (Spectrum result)...44 Figure 4.6: Estimates and Projection of PLHIV and ART Needs among Children Aged 0-14 Years in Indonesia, (Spectrum result)...45 Figure 4.7: Estimates and Projection of HIV Prevalence among Pregnant Women in Indonesia, (Spectrum result)...45 Figure 4.8: Estimates and Projection of PMTCT Service Needs in Indonesia, (Spectrum result) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

9 Forward The estimates and projections of the HIV/AIDS epidemic are needed to describe the needs of services for prevention, care, support and treatment programs as well as assessing the potential of new HIV infections that can be prevented, and when performing analysis of costs that have been and will be invested in the response to control HIV and AIDS. Estimates and Projections of HIV/AIDS in Indonesia in is a continuation of the report of Estimates and Projections of HIV/AIDS issued by the Ministry of Health in This book describes a comprehensive situation and can understand in relation to the number of people with HIV AIDS to the district level. Results of Modelling in showed here are about 559,894 people living with HIV for the year 2011 and 812,798 people for the year While the estimated number of new infections in 2011 are 72,294 and 96,480 for The results of Modelling in showed estimates as many as 630,147 people living with HIV for 2015 and 652,349 for 2020, meanwhile the estimated number of new infections are 53,460 for 2015 and slightly decreased to 48,529 for 2020 This estimation and projection of HIV/AIDS written report has received input from various parties. This estimation methodology and results have been reviewed by a group of experts and presented to stakeholders. With the limitations that exist in the calculation of these estimates and projections, the result is the best result that can be obtained with the data available at the time the calculation is done. We express our deepest appreciation to all parties for the attention, assistance and contribution in the preparation, implementation, and improvement of the estimations and projections activities. Hopefully this book useful in the HIV/AIDS control program, not only for the Ministry of Health, but also to all work partners of HIV/AIDS control. Jakarta, February 2017 Director General Disease Control and Prevention dr. H. Mohamad Subuh, MPPM NIP ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

10 Contributor List Working Group Ari Wulan Sari Ministry of Health Asep Eka Nur Hidayat National AIDS Commission Dwi Rahmadini - National AIDS Commission Fatien Hamamah National AIDS Commission Fetty Wijayanti WHO Indonesia Office Lely Wahyuniar UNAIDS Indonesia Office Rizky Hasby Ministry of Health Viny Sutriani Ministry of Health Yori Novrianto FHI 360 Consultants/Writers Wiwath Peerapanatapokin Robert Magnani Leonita Agustine Contributors Siti Nadia Tarmizi Ministry of Health Endang Budi Hastuti Ministry of Health Triya Novita Dinihari Ministry of Health Irawati Panca Ministry of Health Sarikasih Harefa Ministry of Health Victoria Indrawati Ministry of Health Fabio De Mesquita WHO Indonesia Office Beatricia Iswari WHO Indonesia Office Tiara Nisa WHO Indonesia Office Kin Chou UNAIDS Regional Office 8 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

11 1 INTRODUCTION The importance of countries knowing their epidemic as a prerequisite for success in defeating HIV is widely accepted, and is clearly recognized in Indonesia. Both as a means of supporting program planning and assessing progress in containing and eventually ending HIV and AIDS in Indonesia, the Ministry of Health (MOH) periodically updates its official epidemiologic projections concerning HIV and AIDS. Updates were undertaken in 2008, 2012 and 2014 (report published in February of 2015). The present document was prepared to update the epidemic situation taking into account new data that have since become available, most notably the 2015 Integrated Biological-Behavioral Surveillance Survey IBBS) among HIV Key Populations (KPs) and the updated population size estimates for KP for HIV prepared by the MOH in mid ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

12 2 OBJECTIVES The objective of HIV epidemic Modelling in Indonesia 2016 exercise is to provide a comprehensive picture of the current situation of the HIV epidemic and a projection that can be used by stakeholders for planning an improved and focused HIV and AIDS control program in Indonesia. In addition, the epidemic model will also serve as a reference for evaluating the efficacy of various HIV and AIDS control programs that are already running, and will also strengthen advocacy programs and build a greater commitment among stakeholders that are directly or indirectly involved. The purpose of the present report is to (1) provide detailed documentation as to the methods used in undertaking the 2016 epidemiologic update and (2) disseminate the updated results. 10 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

13 3 METHODOLOGY A Technical Working Group (TWG) was established by the MOH Sub-Directorate for HIV AIDS & STDs in collaboration with the National AIDS Commission (NAC) in September 2016 to carry out the epidemiologic Modelling work needed to produce an updated epidemiologic projection. This TWG was charged of updating the previous HIV/AIDS Modelling undertaken in 2014 by inputting new data and rerunning the epidemiologic projections. Members of the TWG consisted of staff from the national MOH, NAC, UNAIDS, WHO, and FHI Modelling Approach The Modelling approach used in the 2016 update was in most respects the same as was used in prior HIV epidemiologic updates in Indonesia. The basic steps were: Review new data available since the last update with regard to the information they provide on levels and trends in key parameters; Input the new data into the AIDS Epidemic Model (AEM) and make adjustments to parameters entered in prior updates as needed in order to make them consistent with the latest data; Run AEM and assess the fit of the model results with regard to how well the projected trends in HIV prevalence correspond to the available data, and make adjustments as needed to make the model fit adequately; Export selected information from AEM to the Spectrum AIDS Impact Model (AIM) and use the AIM software to produce estimates related to related to PMTCT; and Make final adjustments as needed based to the Spectrum AIM results to make them consistent with the AEM results. Figure 3.1: Flow of HIV Epidemic Modelling in Indonesia STRUCTURE Demographic Data Program Statistics Epidemic Patterns Demoghrapic and Epidemic Calculations Mother-to-child tranmission Child Model Adult Model Results Number HIV+ New Infections AIDS dealts Need for ART Need for PMTCT Surveillance and Survey Data Source : UNAIDS 2010 Prevalence / incidence trend EPP or AEM ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

14 In view of the differences in evolution of HIV in Tanah Papua vs. the rest of the country, separate updated projections were prepared for Tanah Papua and non-papua (referred to as 32 province model), as was done in prior Modelling exercises. The Papua and non- Papua results were then combined into a single set of results for Indonesia as a whole. A major challenge in the Modelling update was to try to the extent possible to produce estimates that represent or characterize the HIV situation in the entire country. This task is made difficult by the fact that the key source of data for tracking the epidemic in Indonesia is periodic surveys undertaken in a relatively modest number of districts (that is, the Integrated Biological-Behavioral Surveys IBBS). In this regard, several steps were taken to try to improve the accuracy of the projections in the 2016 update. First, estimated levels of and trends in key parameters were calculated at the provincial level and aggregated to the national level using provincial population weights derived from the recent key population size estimation update for each relevant KP sub-population. This is expected to produce more accurate estimates than the less formal averaging procedure used in prior epidemic updates. Second, smaller cities and districts for which IBBS data were not available were more explicitly taken into account in the 2016 update. This was accomplished by assigning a weight for such districts based upon the revised key population sizes and using parameter estimates for the smaller of the cities/districts for which IBBS data were available in lieu of actual data. Finally, the 2016 update took advantage of the longer time series of data from key districts resulting from the 2015 IBBS to more formally reassess trends in key parameters during the period (note: 2007 was the first large-scale IBBS undertaken in Indonesia). Trends between these dates were mathematically smoothed in order to reduce noise in the data resulting from the fact that KP district sample sizes in the respective rounds of IBBS were modest. Further details on the procedures used to produce the final 2015 estimates of key biological and behavioral parameters, as well as trends over time in these, is described in detail in Annex 1. Annex 2 documents the sources of data and specific values produced in the 2016 epidemic update exercise Software Used The bulk of the Modelling work was undertaken using the AIDS Epidemic Model (AEM) software. However, for undertaking projections for PMTCT and ART treatment of children, the Spectrum AIDS Impact Model (AIM) software package was used. The decision to use Spectrum was based on the more refined estimation capabilities of Spectrum AIM vs. AEM for these program areas, which tend to receive a higher level of priority in general population than concentrated HIV epidemics. As scaling up PMTCT and ART treatment of children were viewed as strategic priorities in the SRAN, the added complexities of using two software packages was felt to be justified. Consistency between AEM and Spectrum AIM results was ensured by importing incidence figures from the AEM projections into Spectrum AIM in order to calculate projections pertaining to PMTCT and children. 12 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

15 AIDS Epidemic Model (AEM) Version 4.12 AEM has six main worksheets (Population, Heterosexual, IDU, MSM, Waria, Epidemic and HIV Prevalence) for data input, and few more additional worksheets to accommodate the results of calculations and adjustments made in the AEM program. The AEM calculations take into account the disaggregation by gender (male and female). AEM Modelling was used to produce 2015 estimates and projections to the year 2030 of the following parameters: - Cumulative and yearly total number of people living with HIV and the number of HIV/AIDS-related deaths, - Distribution of PLHIV by age and by year, - Number of new HIV infections and number of PLHIV for each key population (FSW, MSM, MSW, PWID, Waria, Clients), among the general population (by gender), and among children (by gender), and - The number of new infections by route of transmission. The definition of the estimating tool AEM about was so called the low risk population has been changed to non-key population, since they are very high risk of contracting HIV, even outside of the traditional KP are sexual partners of SW, sexual partner of PWID, sexual partner of bisexual males, former SW among sectors Spectrum version 5.4 The Spectrum suite of tools includes all of the following linked policy models: Demographic Projections (DemProj), Family Planning (FamPlan), AIDS Impact Model (AIM), Resources for the Awareness of Population Impacts on Development software (RAPID), Lives Saved Tool (LiST), GOALS, and Resource Needs Model (RNM). The working group used the DemProj and AIM software for this exercise Sources of Data The Working Group used the data sets below in developing the national HIV/AIDS estimates for 2015 and projections to 2030: Demographic data The demographic data used in the 2016 Modelling update consisted of population size and distribution estimates from Central Statistics Board (BPS), updated using data from the 2015 Inter-Censal Survey (SUPAS), also undertaken by the BPS. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

16 Behavioral and Epidemiological Data of Key Populations The following data sources were consulted with regard to setting key behavioral and epidemiologic parameters: a. Integrated Biological and Behavioral Surveillance (IBBS) survey among IDUs, FSW, High Risk Men, Waria and MSM, MoH Indonesia: 2007, 2009, 2011, 2013, and b. General Population IBBS in Tanah Papua: 2006 and c. AIDS Cases Report, MoH Indonesia d. HIV/AIDS program data through e. HIV Sentinel Surveillance Report on FSW, IDUs and High Risk Men, MoH Indonesia Note, however, that due to concerns about data quality, the TWG relied almost exclusively on IBBS data from the year 2007 forward Key Population Size Estimates Population size estimates for KPs were updated earlier in 2016 by a Technical Working Group formed by the MOH. The updated size estimates were used in the 2016 updated HIV epidemiologic projections. The results are shown in the table below. Table 3.1: Updated Key Population Size Estimates, 2016 Population Lower Bound Point Upper Bound FSW 128, , ,313 MSM 648, , ,840 Waria 13,038 38,928 89,640 PWID 14,016 33,492 88,812 Client FSW 4,415,788 5,254,663 6,167,873 Client Waria 327, , , Projection Process - AEM The technical working group developed two AEM models, referred to as the 32 Provinces Module and the Tanah Papua Module, respectively, in order to generate estimates and projections of key HIV-related parameters in the population aged years and HIV prevalence for the population ages 50 and above from The two models were subsequently combined to yield a set of national estimates. The process began by updating the data input into the AEM worksheets as described below. Assumptions and data from prior updates were left intact unless indicated below. 14 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

17 It will be noted that in order to fit the AEM projections with observed data on HIV prevalence, it is often necessary to change some of the input parameters. The figures reported in the remainder of this section of the report were the figures that were initially input into AEM prior to fitting. The final values used in the fit AEM model are provided in Annex Population Worksheet The Population Worksheet is filled with demographic data such as the population aged 15 years and above and the population aged years, by gender (male and female). As was noted earlier, all demographic data used were sourced from the Central Statistics Bureau (BPS). These numbers are used in AEM to develop estimates and projections related to HIV/AIDS in 32 provinces and Tanah Papua Heterosexual Worksheet This Worksheet contains data on sexual risk taking and health seeking behaviors among (1) Female Sex Workers (FSW), (2) Clients of FSW and the (3) general population of women aged years. The data sources and assumptions used to fill the heterosexual worksheet were: Female Sex Workers (FSW) Percent of adult females who sell sex This parameter was estimated from the several KP size estimation exercises that have been conducted over the years. These exercises yielded estimates of the number of FSW in the country, which were divided by the estimated number of females of reproductive age. The value entered into the AEM Worksheet was 0.33%, which consistent with the available estimates was assumed to be constant over time. Percent of FSW who are in high and low intensity categories This parameter was estimated from KP mapping data. Mapping exercises to date have mapped Direct and Indirect FSW separately. Direct FSW (DFSW) refers to women who sell sex as their primary source of livelihood, while Indirect FSW (IFSW) have other means of livelihood but sell sex to supplement their incomes. DFSW are usually found at brothels, lokalisasi and some massage parlors, while IDFSW are found at bars, Karaoke bars and other entertainment venues. Earlier IBBS data indicated that Direct FSW tended to have larger numbers of clients and to not use condoms any more frequently than IDFSW, and thus are in general exposed to greater risk of HIV transmission. Given the recent trend in Indonesia of lokalisasi being closed by local governments and thus forcing FSW to pursue clients via other means and in different venues, a decision was taken during the 2016 key population size estimation exercise to do away with the distinction between Direct and Indirect FSW. Thus, the 2016 size estimates were for all FSW. However, as the optimal application of AEM distinguishes ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

18 between FSW with regard to exposure to risk and the distinction between DFSW and IDFSW was retained in the 2015 IBBS, the epidemic update used DFSW to correspond to High Intensity FSW, the designation that will in now being used by the MOH, and Low Intensity FSW. The intent remains the same to distinguish between FSW that are at higher and lower levels of risk based upon their sexual and health seeking behaviors. The parameters below were entered into AEM separately for high and low intensity FSW. Table 3.2: FSW General Non-Papua Female Sex Workers - General Percent of females aged who sell sex 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% Percent of female sex workers in group % 54.4% 54.4% 54.4% 50.1% 45.8% 41.5% 37.2% 32.9% Movement from group 1 to group 2 each year 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% Table 3.3: FSW General Papua Female Sex Workers - General Percent of females aged who sell sex 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% Percent of female sex workers in group % 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% Movement from group 1 to group 2 each year 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% The following three parameters were set based upon levels and trends observed in the IBBS series from 2007 to The first two parameters were left unchanged from prior epidemic updates for High Intensity FSW, while a modest downward trend observed in recent IBBS among Low Intensity FSW was input into AEM. A modest upward trend in the average duration of selling sex was observed for both groups of FSW and was input into AEM. The values input into AEM for Non-Papua (and Papua) for the years are shown in Table 3.4 and 3.5 below. Average number of clients per day among FSW Working days per week Average duration selling sex 16 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

19 Table 3.4: FSW Group 1 & Group 2 N`on-Papua Female Sex Workers group (FSW1) / population (in thousands) Number of clients per day female sex worker group 1 Days worked per week female sex workers group 1 Percent condom use with 56.5% 57.9% 59.4% 61.1% 62.8% 65.3% 67.7% 70.0% 72.4% clients - FSW group 1 Average duration selling sex in group 1 (years) STI prevalence among female 36.8% 36.8% 36.8% 36.8% 36.8% 34.6% 32.4% 30.2% 28.0% sex worker group 1 Female Sex Workers group (FSW2) / population (in thousands) Number of clients per day female sex worker group 2 Days worked per week female sex workers group 2 Percent condom use with 53.1% 53.3% 53.4% 53.6% 53.7% 53.9% 54.0% 54.2% 54.3% clients - FSW group 2 Average duration selling sex in group 2 (years) STI prevalence among female 18.7% 18.7% 18.7% 18.7% 18.7% 17.5% 16.4% 15.3% 14.2% sex worker group 2 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

20 Table 3.5: FSW Group 1 & Group 2 Papua Female Sex Workers group (FSW1) / population (in thousands) Number of clients per day female sex worker group 1 Days worked per week female sex workers group 1 Percent condom use with 66.1% 69.5% 72.8% 74.8% 76.8% 81.6% 86.4% 90.5% 94.5% clients - FSW group 1 Average duration selling sex in group 1 (years) STI prevalence among female 27.9% 27.9% 27.9% 27.9% 27.9% 23.5% 19.0% 15.0% 11.0% sex worker group 1 Female Sex Workers group (FSW2) / population (in thousands) Number of clients per day female sex worker group 2 Days worked per week female sex workers group 2 Percent condom use with 63.0% 65.0% 67.0% 68.9% 70.8% 72.9% 75.1% 75.1% 75.1% clients - FSW group 2 Average duration selling sex in group 2 (years) STI prevalence among female 18.8% 18.8% 18.8% 18.8% 18.8% 15.8% 12.8% 10.1% 7.4% sex worker group 2 Percent condom use with clients National estimates of the percentage of both higher and lower frequency FSW using condoms at last sex were calculated as weighted averages based upon data from the five IBBS surveys undertaken between 2007 and For cities/districts in which 2009 and/or 2013 IBBS data were available (but not 2015), levels and trends from 2007 to 2015 were estimated by extrapolating and back-extrapolating from the available IBBS data taking into account trends in the cities/district for which three rounds of IBBS data (2007, 2011 and 2015) were available. Levels and trends for cities/districts with three rounds of IBBS data were estimated directly from the IBBS data. HIV prevalence estimates for provinces in which no IBBS data were available 18 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

21 was assumed to approximate the level and trend in smaller cities/districts for which data were available. A national estimate was then calculated by weighting the sub-group estimates by key population size and summing them to yield a national figure. Provincial estimates of numbers of higher and lower frequency FSW derived from the recent key population size estimation update serving as weights. This was undertaken separately for the 32 non-papuan provinces (in the aggregate) and for the Tanah Papua (two provinces), and then the two sets of estimates were combined weighted by estimated key population size. The input values are shown in Table 3.4 and 3.5 above. Sexually Transmitted Infection (STI) prevalence among FSW National estimates of the percentage of both higher and lower frequency FSW with Sexually Transmitted Infections (STIs) were calculated as averages using data from the five IBBS surveys undertaken between 2007 and Gonorrhea was chosen as an index STI given its sensitivity to sexual risk taking. Gonorrhea prevalence estimates from larger cities (i.e., those covered in the 2007, 2011 and 2015 IBBS were averaged with estimates from the smaller cities covered in the 2009 and 2013 IBBS, and the average values for higher and lower frequency FSW were input into AEM. Estimates were calculated separately for Papua and non-papua. The input values are shown in Table 3.4 and 3.5 above. Clients of FSW Percentage of males aged years visiting sex workers in last year As with FSW, this parameter was estimated from the several key population size estimation exercises that have been conducted over the years. These exercises yielded estimates of the number of men who had visited a sex worker in the last year, which was then divided by the estimated number of males of reproductive age. Average duration of being a client No data are available for this parameter for Indonesia. It was thus set at seven (7) years based on data from Thailand. Percentage of adult males who are circumcised For non-papua, the 80% figure used was reported in the 2012 DHS. For Papua, we used the data from the 2006 and 2013 Papua General Population IBBS to estimate the parameter for Tanah Papua (16.7%). ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

22 Table 3.6: Clients of FSW Non-Papua Clients of Female Sex 4,768 4,829 4,885 4,935 4,991 5,047 5,101 5,150 5,196 Workers / population (in thousands) Percent of males aged % 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% who visited FSW in the last year Average duration buying sex (years) Percent of adult males who 80% 80% 80% 80% 80% 80% 80% 80% 80% are circumcised Table 3.7: Clients of FSW Papua Clients of Female Sex Workers / population (in thousands) Percent of males aged % 9.0% 9.0% 8.3% 7.6% 6.9% 6.1% 5.4% 4.7% who visited FSW in the last year Average duration buying sex (years) Percent of adult males who 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% are circumcised Population engaging in casual sex For the three parameters below, information from several sources was taken into account, but in the absence of direct data the parameter estimates are based upon strong assumptions. Percent of males and females engaging in casual sex in the last year Percent condom use in casual sex Average number of sex contacts in last year 20 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

23 The values input into AEM are documented in Table 3.8 and 3.9 below. Table 3.8: Population engaging in Casual Sex Non-Papua Percent of males engaging in 2.8% 2.8% 2.8% 4.8% 6.8% 6.8% 6.8% 6.8% 6.8% casual sex in the last year Percent of females engaging in 1.0% 1.0% 1.0% 1.5% 2.0% 2.0% 2.0% 2.0% 2.0% casual sex in the last year Percent condom use in casual 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% sex Average number of sex contacts in the last year (male) Table 3.9: Population engaging in Casual Sex Papua Percent of males engaging in 30.0% 30.0% 30.0% 26.3% 22.5% 18.8% 15.0% 15.0% 15.0% casual sex in the last year Percent of females engaging 10.0% 10.0% 10.0% 8.8% 7.5% 6.3% 5.0% 5.0% 5.0% in casual sex in the last year Percent condom use in casual 12.6% 12.6% 12.6% 16.2% 19.8% 23.5% 27.1% 27.1% 27.1% sex Average number of sex contacts in the last year (male) Sex with spouses and regular partners For the two parameters below, no new data were available for the 2016 update, and thus the Non-Papua parameter estimates from the 2014 epidemic update were retained. Number of sexual contacts with spouses or regular partners Percent condom with spouses or regular partners For Papua, the working group used data from the 2013 Papua General Population IBBS to set these parameters. The number of sexual contacts with spouse or regular partner per week was 1.2, and the percentage of condom use with spouse or regular partner is 3.4%, using the data of condom use at marital sex from the 2013 IBBS Papua. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

24 Sexually Transmitted Infection (STI) prevalence in adult population There are unfortunately no reliable data available on STI prevalence in the general population in Indonesia. As input into AEM, the working group used the observed prevalence of gonorrhea among PWID as proxy for general population STI prevalence (0.8%) for non-papua. For Papua, where STI data for PWID are not available, we adjusted the national estimate of STI prevalence of gonorrhea by the Papua/non- Papua ratio of syphilis prevalence general population men and women to yield a general population estimate of gonorrhea prevalence for Papua. Table 3.10: Spouses and Regular Partners Non-Papua Sex with spouses or regular partners (RP) Number of sexual contacts with spouse or RP (per week) Percent condom use with 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% spouses or regular partners STI prevalence in adult 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% population PWID Worksheet (Injection Drug Users) This worksheet is only completed for estimating and projecting in the 32 provinces model and was left blank for Tanah Papua. The number of female PWID in Indonesia was thought to be sufficiently small that they would not have a major impact on the HIV epidemic in Indonesia, and were thus not taken into account in the epidemic update. Male PWID injecting behaviors Percent of adult male population who inject drugs This parameter was estimated from the 2016 key population size estimation update. This provided the numerator of the parameter, which was then divided by the estimated number of males age. See Table 3.11 for parameter estimates from No new data were available for the following two parameters, and thus they were left unchanged from the last epidemic update. Percent of male IDUs in high-risk networks IDU mortality (crude mortality per year in %) 22 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

25 The values input into AEM for these parameters are shown in Table 3.11 below. Percent of PWID who often and always sharing material last week This parameter was updated based upon data from the 2015 IBBS. See Table 3.11 for the 2015 estimate and smoothed parameter estimates from 2007 to Percent of all injections shared (among those who share) The 2015 IBBS did not provide a basis for changing the parameter value from the last epidemic update, and thus it was left unchanged. Number of injections per day 2105 IBBS data suggested a slight increase in this parameter. Values for are shown in Table Average duration of injecting behavior (in years) Sharing to non-sharing movement per year The 2015 IBBS did not provide a basis for changing the two above parameters from the last epidemic update, and thus they were left unchanged see Table 3.11 below. Table 3.11: Male PWID Injecting Behaviors Non-Papua Male IDU - Injecting Behaviors / population Percent of males age % 0.19% 0.16% 0.14% 0.11% 0.11% 0.09% 0.07% 0.05% who inject drugs Percent of male IDUs in 70.0% 70.0% 70.0% 70.0% 70.0% 70.0% 70.0% 70.0% 70.0% high-risk networks IDU mortality (crude mortality 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% per year in %) Percent of male IDUs who 46.8% 46.8% 46.8% 44.4% 42.0% 36.0% 30.0% 27.0% 24.0% share needles Percent of all injections shared 70.0% 70.0% 70.0% 70.0% 72.0% 72.0% 72.0% 72.0% 72.0% (among those who share) Number of injections per day Average duration of injecting behavior (in years) Sharing to non-sharing 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% movement per year ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

26 Male PWID sexual behaviors Percent of male IDUs visiting female sex workers The 2015 IBBS data suggested a continuing decline in the percent of male PWID availing of the services of FSW. This parameter is estimated to have fallen to 15.5% in See table 3.12 for further information. Data from the 2015 IBBS indicated the continuation of a gradual upward trend in the following two indicators. This trend is documented in Table 3.12 below. Percent condom use with female sex worker group 1 Percent condom use with female sex worker group 2 The 2015 IBBS did not provide a basis for changing the values for the following two parameters, and thus they were left unchanged see Table 3.12 below. Percent condom use with spouse or regular partner Number of contacts with regular partners (per week) Table 3.12: Male PWID Sexual Behaviors Non-Papua Male Injecting Drug Users Sexual Behaviors Percent of male IDUs visiting 40.9% 36.7% 32.5% 28.3% 24.2% 22.0% 19.8% 17.7% 15.5% female sex workers Percent condom use with 67.0% 66.7% 66.5% 66.2% 65.9% 65.9% 65.9% 65.9% 65.9% female sex worker group 1 Percent condom use with 68.0% 64.7% 61.5% 58.2% 54.9% 54.9% 54.9% 54.9% 54.9% female sex worker group 2 Percent condom use with 14.0% 21.1% 28.2% 35.3% 42.4% 42.4% 42.4% 42.4% 42.4% spouse or regular partner Number of contacts with regular partners (per week) MSM Worksheet This Worksheet compiles data related to the size and risk-taking and health-seeking behaviors on MSM in the 32 non-papuan provinces. As there are insufficient data on MSM in Papua, MSM in Papua were not included in the epidemic update. The MSM population size in Papua was thus set to zero in AEM. 24 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

27 MSM General Percent of adult males engaging in same-sex behavior This parameter was estimated from the 2016 key population size estimation update. This provided the numerator of the parameter, which was then divided by the estimated number of males age from the official BPS population projections and estimates. The 2016 estimate of 1.1% was applied retrospectively. Percent of MSM who are in reachable and unreachable categories Reachable MSM, sometimes referred to as visible MSM, are those who frequent public locations to search for and meet sex partners, and can thus be reached via face-to-face outreach and can be captured in mapping exercises. The venues they frequent are locations that tend to be captured in mapping exercises. Unreachable MSM are those that tend not be found at such public locations and tend to search for sex partners via internet or through personal networks. An estimated 27.7% of MSM fall into the Reachable category based upon 2015 IBBS data on the percentage of MSM that has been contacted by an outreach worker. Parameters for MSM were entered into AEM separately for the reachable and unreachable categories. Shift from the reachable to the unreachable category (percent) No new data were available for this parameter, and it was thus left unchanged from the last epidemic update (10%). Table 3.13: Men who have Sex with Men General Non-Papua Men who have Sex with Men General Percent of males aged % 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% engaging in same-sex behavior Percent of MSM in risk group % 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% Shift from MSM group 1 to 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% group 2 MSM Risk Taking Behaviors Percent engaging in anal sex in the last year - MSM Number of anal sex contacts last week (among those having anal sex) - MSM Average duration of same-sex behavior (years) MSM ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

28 The values entered into AEM for the three parameters below were based upon data from the 2015 IBBS. Reachable and non-reachable MSM were assumed to have the same values for the first and third of these parameters. With regard to anal sex contacts in the week prior to the 2015 IBBS, non-reachable MSM were assumed to anal sex contact rates that were only one-fifth of those of reachable MSM. See Table 3.14 below for the AEM input values. Percent of MSM with female partners 2015 IBBS data indicate, for reasons that are not clear, a continuing decline in the percent of MSM having sex with female as well as male partners. The survey data indicated that this percent fell to 28.5% in The trend from 2009 to 2015 was smoothed based upon the IBBS data for those years. No new information was available for non-reachable MSM, so the parameter input for this sub-population was left unchanged from the prior epidemic update at 33%. Percent condom use in anal sex with MSM 2015 IBBS data indicate a continuing increase in the percent of MSM using condoms when having anal sex. The 2015 IBBS indicated that this percent had increased to 74.4% in The trend from 2007 to 2015 was smoothed based upon the IBBS data for those years. No new information was available for non-reachable MSM, and accordingly this parameter was left unchanged from the prior epidemic update at 60%. STI prevalence among MSM STI prevalence (gonorrhea) among reachable MSM in 2015 was estimated from the 2015 IBBS as the weighted average of observed prevalence rates among reachable MSM in larger and smaller cities/districts, with size estimates from the 2016 size estimation update being used as weights. This procedure produced an estimate for 2015 of 18%. Cities/districts for which no estimates were available were assigned the average prevalence in the four smallest cities for which data were available. No new information was available for non-reachable MSM. Consistent with above assumption concerning sexual contacts among non-reachable vs. reachable MSM, the parameter was set at 3.7% (one-fifth or 20% of the rate for reachable MSM of 18%). 26 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

29 Table 3.14: Men who have Sex with Men Group 1 & 2 Non-Papua Men who have Sex with Men group 1 (MSM1) / population Percent engaging in anal sex 73.4% 73.2% 73.0% 72.9% 72.7% 72.7% 72.7% 72.7% 72.7% in the last year - MSM1 Number of anal sex contacts last week (among those having anal sex) - MSM1 Average duration of same-sex behavior (years) - MSM1 Percent of MSM1 with female 50.0% 50.0% 50.0% 45.1% 40.2% 39.1% 38.0% 33.2% 28.5% partners Percent condom use in anal 46.3% 49.6% 52.9% 56.6% 60.3% 64.5% 68.6% 71.5% 74.4% sex with MSM1 STI prevalence among MSM1 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% Men who have Sex with Men group 2 (MSM2) / population Percent engaging in anal sex 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% in the last year - MSM2 Number of anal sex contacts last week (among those having anal sex) - MSM2 Average duration of same-sex behavior (years) - MSM2 Percent of MSM2 with female 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% partners Percent condom use in anal 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% sex with MSM2 STI prevalence among MSM2 3.7% 3.7% 3.7% 3.7% 3.7% 3.7% 3.7% 3.7% 3.7% MSM visiting sex workers The 2015 IBBS provided no evidence of a need to change the following five (5) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.15 for AEM input values. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

30 Percent of reachable MSM visiting male sex workers Percent of unreachable MSM visiting male sex workers Ratio of frequency of visiting MSW (unreachable MSM /reachable MSM) Percent of reachable MSM visiting female sex workers Percent of unreachable MSM visiting female sex workers Table 3.15: Men who have Sex with Men visiting Sex Workers Non-Papua MSM visiting (male and female) sex workers Percent of MSM1 visiting male 19.8% 19.5% 19.2% 18.8% 18.5% 18.5% 18.5% 18.5% 18.5% sex workers Percent of MSM2 visiting male 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% sex workers Ratio of frequency of visiting MSW (group 2 / group 1) Percent of MSM1 visiting 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% female sex workers Percent of MSM2 visiting 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% female sex workers Percent condom use in anal 53.0% 53.5% 54.0% 57.8% 61.7% 61.7% 61.7% 61.7% 61.7% sex with male sex workers Percent condom use with 60.3% 61.7% 63.1% 64.5% 65.9% 65.9% 65.9% 65.9% 65.9% Female sex worker group 1 (FSW1) Percent condom use with 61.2% 59.6% 58.1% 56.5% 54.9% 54.9% 54.9% 54.9% 54.9% female sex worker group 2 (FSW2) Based upon 2015 IBBS data indicating increased condom use more or less across the board in comparison with earlier rounds of IBBS, the values for the three parameters were set to reflect this trend (although the trend is only slightly upward): Percent condom use in anal sex with male sex workers Percent condom use with Female sex worker group 1 (FSW1) Percent condom use with female sex worker group 2 (FSW2) 28 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

31 Male Sex Workers The 2015 IBBS provided no evidence of a need to change the following seven (7) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.16 for AEM input values. Percent of males aged who sell sex Average duration selling sex (in years) Shift from MSM1 to MSW Shift from MSM2 to MSW Percent of MSW reporting anal sex with clients in the last year Number of anal sex contacts last week (for MSW with anal sex) Percent MSW visiting female sex workers in the last year Table 3.16: Male Sex Workers Non-Papua Male Sex Workers Percent of males aged % 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% who sell sex Average duration selling sex (in years) Shift from MSM1 to MSW 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% Shift from MSM2 to MSW 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Percent of MSW reporting anal 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% sex with clients in the last year Number of anal sex contacts last week (for MSW with anal sex) STI prevalence among male 13.4% 15.2% 17.1% 20.5% 24.0% 24.4% 24.8% 25.6% 26.5% sex workers Percent MSW visiting female 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% sex workers in the last year Percent MSW with female 72.5% 68.9% 65.2% 56.9% 48.6% 44.4% 40.2% 40.7% 41.2% regular partners in the last year STI prevalence among male sex workers STI prevalence (gonorrhea) among MSW in 2015 was estimated from the 2015 IBBS to be 26.5%, continuing a slightly upward trend over time. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

32 Percent MSW with female regular partners in the last year 2015 IBBS data indicate, for reasons that are not clear, a continuing long-term decline in the percent of MSW having sex with regular female partners in the previous year. The survey data indicated that this percent fell to 41.25% in 2015, up slightly from 40.2% in the 2013 IBBS Waria Worksheet Transgender population- general Percent of males aged who are transgender This parameter was calculated using the population size estimate from the 2016 update as the numerator and the official BPS estimate of the number of males years of age as the denominator. This yielded an estimate of 0.06% for Percent of Transgenders who sell sex Percent of Transgenders who engage in casual sex but not sex work The two parameters above were estimated from the several IBBS that have been undertaken in Indonesia. The estimated values, which appear to be more or less constant over time, were 75.9% of Transgenders selling sex and 10.0% engaging in casual sex but not sex work. Percent of Transgenders who have regular partners only The value for this parameter was calculated as a residual from the previous two items (the three parameters add to 100%). Table 3.17: Transgenders General Non-Papua Transgender population General Percent of males aged % 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% who are transgender Percent of Transgenders who 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% sell sex Percent of Transgenders who 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% engage in casual sex but not sex work Percent of Transgenders who 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% have regular partners only 30 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

33 Transgender Sex Workers Sexual Behaviors The 2015 IBBS provided no evidence of a need to change the following five (5) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.18 for AEM input values. Percent of transgender sex workers engaging in anal sex with clients Number of anal sex contacts last week with clients (for those having anal sex) Percent of anal sex contacts with clients which are receptive Average duration selling sex (in years) Percent condom use in anal sex with clients Anal STIs (%) among transgenders who sell sex STI prevalence (gonorrhea) among Transgenders in 2015 was estimated from the 2015 IBBS as the average of observed prevalence rates in the cities/districts for which data were available. This procedure produced an estimate for 2015 of 13.9%, continuing a decline that appears to have begun after The estimated Transgender prevalence rates from 2011 to 2015 were smoothed in order to more reliably capture this apparent trend. Table 3.18: Transgenders Sexual Behaviors Non-Papua Transgender Sex Workers Sexual Behaviors Percent of transgender sex 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% workers engaging in anal sex with clients Number of anal sex contacts last week with clients (for those having anal sex) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% with clients which are receptive Average duration selling sex (in years) Percent condom use in anal 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% sex with clients Anal STIs (%) among 26.8% 26.8% 26.8% 26.8% 26.8% 23.4% 20.1% 17.0% 13.9% transgenders who sell sex ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

34 Transgender Sex Workers - Client Make-up The 2015 IBBS data when compared with data from prior rounds of IBBS indicated modest trends for the following three parameters, and adjustments were made accordingly see Table Percent of TG clients who are low-risk heterosexual males Percent of TG clients who are also clients of female sex workers Percent of TG clients who are MSM Percent of TG clients who are male IDU This parameter was calculated as a residual based upon the values of the three prior parameters (the four parameters must add to 100%). Table 3.19: Transgenders - Client Make-up Non-Papua Transgender Sex Workers Client Make-up Percent of TG clients who are 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% low-risk heterosexual males Percent of TG clients who are 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% also clients of female sex workers Percent of TG clients who are 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% MSM Percent of TG clients who are 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% male IDU Transgenders engaging in Casual Sex - Sexual Behaviors Number of Transgenders having sex with Casual Partners but not selling sex This parameter was estimated by multiplying the percent of Transgenders reporting having sex with casual partners but not selling sex in the 2015 IBBS times the estimated size of the Transgender population in Indonesia from the 2016 key population size update. The 2015 IBBS provided no evidence of a need to change the following six (6) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.20 for AEM input values. 32 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

35 Percent of TGs with casual sex partners who engage in anal sex Number of anal sex contacts last week (for TGs having anal sex with CPs) Percent of anal sex contacts which are receptive Percent condom use in anal sex for those with casual partners Anal STIs (%) among transgenders who have casual partners Percent of annual shift from TGs engaging in casual sex to TGs with RP only Table 3.20: Transgenders engaging in Casual Sex - Sexual Behaviors Non-Papua Transgenders engaging in Casual Sex - Sexual Behaviors Percent of TGs with casual sex 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% partners who engage in anal sex Number of anal sex contacts last week (for TGs having anal sex with CPs) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% which are receptive Percent condom use in anal 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% sex for those with casual partners Anal STIs (%) among 10.42% 10.08% 9.75% 9.41% 9.07% 9.07% 9.07% 9.07% 9.07% transgenders who have casual partners Percent of annual shift from 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% TGs engaging in casual sex to TGs with RP only Transgender Sex Workers - Partner Make-up for those with CPs The 2015 IBBS provided no evidence of a need to change the following four (4) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.21 for AEM input values. Percent of anal sex partners who are low-risk heterosexual males Percent of anal sex partners who are also clients of female sex workers Percent of anal sex partners who are MSM Percent of anal sex partners who are male IDU (calculated from previous 3 rows) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

36 Table 3.21: Transgenders Sex Workers Partner Make-up for those with CPs Non-Papua Transgender Sex Workers - Partner Make-up for those with CPs Percent of anal sex partners 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% who are low-risk heterosexual males Percent of anal sex partners 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% who are also clients of female sex workers Percent of anal sex partners 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% who are MSM Percent of anal sex partners 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% who are male IDU Transgenders with Regular Partners - Sexual Behaviors Number of Transgenders with regular partners only This parameter was estimated by multiplying the percent of Transgenders reporting having a regular partner but not selling sex or having casual partners in the 2015 IBBS times the estimated size of the Transgender population in Indonesia from the 2016 key population size update. The 2015 IBBS provided no evidence of a need to change the following five (5) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.22 for AEM input values. Percent of TGs with regular partners who engage in anal sex Number of anal sex contacts with RPs last week (for TGs having anal sex with RPs) Percent of anal sex contacts with RPs which are receptive Percent condom use in anal sex with regular partners Anal STIs (%) among transgenders who have regular partners only 34 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

37 Table 3.22: Transgenders with Regular Partners - Sexual Behaviors Non-Papua Transgenders with Regular Partners (RP) - Sexual Behaviors Percent of TGs with regular partners who engage in anal 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% sex Number of anal sex contacts with RPs last week (for TGs having anal sex with RPs) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% with RPs which are receptive Percent condom use in anal 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% sex with regular partners Anal STIs (%) among transgenders who have 5.21% 5.04% 4.87% 4.70% 4.54% 4.54% 4.54% 4.54% 4.54% regular partners only Transgender Sex Workers - Regular Partner Make-up (sums to 100%) The 2015 IBBS provided no evidence of a need to change the following four (4) parameters from those used in the last epidemic update, and accordingly they were left unchanged. See Table 3.23 for AEM input values. Percent of anal sex partners who are low-risk heterosexual males Percent of anal sex partners who are also clients of female sex workers Percent of anal sex partners who are MSM Percent of anal sex partners who are male IDU (calculated from previous 3 rows) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

38 Table 3.23: Transgenders Sex Workers Regular Partner Make-up Non-Papua Transgender Sex Workers - Regular Partner Make-up Percent of anal sex partners who are low-risk heterosexual 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% males Percent of anal sex partners who are also clients of female 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% sex workers Percent of anal sex partners 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% who are MSM Percent of anal sex partners 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% who are male IDU Epidemic Worksheet This worksheet contains data related to STI and HIV/AIDS. These data are generally very limited. Therefore, the data such as STI distribution by age group and the probability of mother-to-child transmission are taken from another Southeast Asia country (Thailand). Data on fertility by age group were obtained from the 2012 Indonesia Demographic Health Survey (IDHS), whereas data on the probability of HIV transmission from high-risk populations and the start year of the epidemic are the results of the Modelling adjustment with existing HIV surveillance data HIV Prevalence Worksheet This Worksheet contains HIV prevalence data from high risk populations in 32 provinces (in the aggregate) and Tanah Papua, respectively. The data originate from HIV sentinel surveillance carried out by District Health Offices, VCT service sites, and IBBS data from 2007, 2009, 2011, 2013 and General population HIV prevalence data were also available for Tanah Papua for 2006 and Prevalence estimates for 2015 were required for all KPs, as well as for the general population. Estimates for KPs for 2015 for some cities/districts could be taken directly from the 2015 IBBS. For other cities/districts, only data from the 2009 and/ or 2013 IBBS were available. However, for most of the districts in the country no direct survey-based estimates of prevalence were available. The general approach adopted for deriving national estimates of HIV prevalence and trends for each KP was to produce separate estimates for the three sub-groups of cities/districts enumerated above and then calculate a national estimate by weighting the sub-group estimates by key population size and summing them to yield a national figure. Key population size estimates from the 2016 update exercise were used in the calculations. This was done separately for the 31 non-papua provinces (in the aggregate) and for the Tanah Papua (two provinces), and then combining the two sets of estimates weighted by estimated key population size. 36 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

39 For cities/districts in which 2009 and/or 2013 IBBS data were available (but not 2015), levels and trends from 2007 to 2015 were estimated by extrapolating and backextrapolating from the available IBBS data taking into account trends in the cities/ district for which three rounds of IBBS data (2007, 2011 and 2015) were available. HIV prevalence estimates for provinces in which no IBBS data were available was assumed to approximate the level and trend in smaller cities/districts for which at least some data were available. Table 3.24: HIV Prevalence among KPs Non-Papua Direct FSW 5.94% 5.97% 6.03% 6.11% 6.13% Indirect FSW 2.19% 2.22% 2.26% People who Inject Drugs 36.06% 33.93% 32.36% 31.47% 28.79% Men who Have Sex with Men 3.22% 4.75% 6.36% 13.23% 20.25% Male Sex Workers 7.55% 6.38% 15.44% 12.96% 30.71% Waria 11.46% 11.44% 11.14% 10.89% 10.65% Table 3.25: HIV Prevalence among KPs and General Population Papua Direct FSW 17.70% 17.91% 17.57% 16.72% 15.92% Indirect FSW 7.00% General Population Males 2.90% 2.30% General Population Females 1.80% 2.20% Adult ART Worksheet This worksheet collects data on numbers of adults receiving ART, in total and by KP. The source of data input into AEM was MoH program data. The input values from are shown in Table 3.26 and 3.27 below. Table 3.26: Number of Adults Receiving ART Non-Papua Number of adults receiving ART Male 388 3,385 5,059 6,834 10,154 12,421 14,956 18,266 21,721 27,513 34,536 Female 153 1,391 2,174 3,077 4,785 6,112 7,663 9,779 11,628 16,288 20,446 TOTAL 542 4,776 7,234 9,912 14,939 18,533 22,619 28,044 33,349 43,801 54,982 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

40 Table 3.27: Number of Adults Receiving ART Papua Number of adults receiving ART Male ,279 2,005 2,484 Female ,113 1,539 2,441 3,025 TOTAL ,407 2,091 2,818 4,446 5, Projection Process - Spectrum AEM results obtained as described above were then used as input for the Spectrum software suite to project some of the consequences of AEM HIV incidence and prevalence estimates. As was indicated earlier, two (2) Spectrum policy models were used: Demographic Projection (DemProj) and the AIDS Impact Model (AIM). Demographic projections in Spectrum relied on Indonesia Population Projection data from Statistics Indonesia Board for The sources of the demographic data input into the Spectrum DemProj module were as follows: Population size and composition: The same demographic data that were used in AEM were input into AIM. Life expectancy was estimated from model life tables incorporated into the Spectrum DemProj module. Values for the Age Specific Fertility Rate (ASFR), Total Fertility Rate (TFR) and Sex Ratio of Births (SRB) were all based on the 2012 Indonesia Demographic Health Survey (IDHS) and the Central Statistics Bureau (BPS) Indonesia Population Projection International migration: Values for these parameters were set based upon data from the BPS Indonesia Population Projection Book The data related to HIV and AIDS epidemiology used in the Spectrum AIM module were derived as follows: HIV prevalence among adult population (15-49 years old) uses the output of two AEM modules (Papua and Non-Papua) that have been compiled. Starting years of epidemic uses the output from Non-Papua AEM module. This module was chosen because it contained more comprehensive data on highrisk population than either Papua and also adjustments of the HIV prevalence from surveillance results among several key populations. Progression of HIV into AIDS requiring ART and deaths of PLHIV as a result of not receiving ART treatment was set, following recommendations from UNAIDS, based upon the median time from the initial infection until AIDS related death without ART. For adults, it is assumed to be 10 years (9.6 years for men and 10.4 years for women) and for children it is assumed there is a more rapid progression toward death. 38 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

41 Age distribution of HIV and AIDS by year uses figures provided by the AEM- Spectrum module for a country with a concentrated HIV epidemic in certain populations. The Sex Ratio of people with HIV and AIDS was calculated from the distribution of AIDS cases reported to MoH. The Ratio of Total Fertility Rate of HIV-infected and non HIV-infected women uses figures provided by the Spectrum AIM module. The number of people living with HIV (PLHIV) receiving antiretroviral therapy was obtained from Ministry of Health Sub-Directorate of AIDS & STD monitoring data from After all, required data were entered into the Spectrum AIM software, AIM calculated key HIV epidemic impact indicators estimates and made projections. The estimates were of particular interest for the 2016 HIV epidemic update: HIV prevalence for the population ages Number of PLHIV, including children Number of new infections, including children PMTCT coverage ART coverage, including children The Spectrum AIM calculations were then compared with those from AEM, and adjustments made to the Spectrum AIM estimates to cause them to be consistent with parameter estimates from AEM. It was agreed that some estimates and projections from Spectrum AIM module would not be included in this report, such as the impact of the HIV epidemic on the tuberculosis epidemic and the number of children orphaned by AIDS. The rationale for this was that (1) the calculation of these indicators in the Spectrum software were based on epidemiological studies in Africa and (2) some of the required data is not available in Indonesia. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

42 4 RESULTS 4.1 HIV Prevalence among Population aged 15 years in Indonesia, Based upon the data and assumptions described above, the AEM projection estimates indicate that the HIV prevalence among the population ages 15 years and above was 0.33% in 2015 and will fall slightly to 0.32% in 2020 (Figure 4.1). Figure 4.1: Estimates and Projection of HIV Prevalence among Population Aged 15 years in Indonesia, Years (AEM result) 1.00 HIV Prevalence (%) Year 4.2 Number of key population members living with HIV (PLHIV), Table 4.1 displays 2015 AEM estimates and projections to the year 2020 of the number of people living with HIV (PLHIV) among key populations (KPs). Projections to 2020 indicate that the total number of MSM living with HIV will increase from 87,275 in 2015 to 111,902. Other groups projected to witness an increase in the number of PLHIV are male sex workers (from 6,200 to 7,664) and non-kp women (from 206,586 to 222,076). The number of PLHIV among the other KPs is projected to remain level or decline slightly by The overall number of key populations living with HIV will increase from 613,435 in 2015 to 631,635 in 2018, and is projected to peak at 632,480 in 2019 before beginning to declining. 40 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

43 Table 4.1: Estimates and Projection of PLHIV by Key Population in Indonesia, Years (AEM result) Key Population Number of PLHIV Infections Direct Female Sex Workers (FSW 4,646 4,537 4,410 4,271 4,130 3,993 Group 1) Indirect Female Sex Workers (FSW 3,677 3,699 3,677 3,623 3,550 3,466 Group 2) Clients of FSW 107, ,789 97,876 93,338 89,120 85,215 Men who have sex with men (MSM) 87,275 92,325 97, , , ,902 * Male Sex Workers (MSW) 6,200 6,540 6,846 7,129 7,400 7,664 People who inject drugs (PWID) 9,147 8,492 8,321 8,166 8,034 7,923 Transgenders (Waria) 3,975 3,919 3,853 3,780 3,706 3,633 Non-KP men 184, , , , , ,652 Non-KP women 206, , , , , ,076 Total 613, , , , , ,524 * Part of the MSM worksheet, however the estimates and projection were separated with consideration of MSW have a higher risk than other MSM 4.3 Number of new infections among key population members, The 2015 AEM estimate of the number of new HIV infections is 49,199, with the majority of these coming from non-kp women (17,117 new infections) followed by clients of FSW (both direct and indirect) with 12,647 new HIV infections, and MSM with 10,194 new infections. The other KP groups will have new cases of HIV infections had between 260 and 4000 new cases. New HIV infections among MSM are projected to increase from 10,194 in 2015 to 12,040 in The other two groups that are projected to have an increase in the number of new infections from 2015 to 2020 are MSW (from 2,002 to 2,308) and PWID from (616 to 701). The incidence of new infections is projected to remain stable or decrease for other groups. Overall, the AEM projection is that the overall number of new infections will decrease from 49,199 in 2015 and 44,604 in a 9% decrease in 5 years. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

44 Table 4.2: Estimates and Projection of New HIV Infections by Key Population in Indonesia, Years (AEM result) Key Population Number of New HIV Infections Direct Female Sex Workers (FSW 1,223 1,101 1,057 1, Group 1) Indirect Female Sex Workers (FSW Group 2) Clients of FSW 12,647 11,588 11,338 11,041 10,723 10,400 Men who have sex with men (MSM) 10,194 10,447 10,876 11,284 11,669 12,040 * Male Sex Workers (MSW) 2,002 2,088 2,143 2,197 2,253 2,308 People who inject drugs (PWID) Transgenders (Waria) Non-KP men 4,198 3,913 3,887 3,850 3,803 3,746 Non-KP women 17,117 16,033 15,283 14,590 13,980 13,440 Total 49,199 46,905 46,357 45,729 45,147 44,604 * Part of the MSM worksheet, however the estimates and projection were separated with consideration of MSW have a higher risk than other MSM Figure 4.2 compares the level and distribution of new HIV infections by KP in the 2014 and 2016 epidemiologic updates. As may be observed, the 2016 update presents quite a different profile than the 2014 update, especially with regard to projections going forward. The 2014 update suggested that the HIV epidemic had for the most part stabilized with regard to numbers of new HIV infections for all groups except MSM. However, at then current levels of intervention coverage and effectiveness, it was projected that the number of new infections would continue to grow through 2030, with MSM accounting for the bulk of the increasing number of annual new infections. The 2016 update on the other hand indicates that the epidemic has already peaked for all groups except MSM, among whom the projected number of new infections is projected to continue to grow, albeit at a slower rate that had been projected in The primary factors underlying the revised epidemic trajectory consist of (1) lower estimated KP population sizes for MSM and Clients of FSW, (2) increased condom use across most KPs, (3) lower STI prevalence among most KPs, and (4) increased ART coverage. 42 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

45 Figure 4.2: Comparison of New Infections from 2014 & 2016 HIV Mathematical Modelling, (AEM result) Modelling Modelling Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun Total number of PLHIV, new infections and AIDS-related deaths Figure 4.3 displays in a single figure the AEM projections of numbers of PLHIV, new infections and AIDS-related deaths from 2015 to The total number of PLHIV 15+ years of age is projected to peak at 632,480 in 2019, but then to fall to 631,524 by The annual number of new HIV infections is projected to decline steadily from 49,199 in 2015 to 44,604 in In contrast, pending further increases in ART coverage and adherence the number of AIDS-related deaths in the adult population is projected to increase from 36,936 in 2015 to 45,560 in Figure 4.3: Estimates and Projection of PLHIV, AIDS Deaths and New HIV Infections among Population Aged 15 years in Indonesia, (AEM result) PLHIV AIDS Death & New HIV Infection AIDS Death Year New HIV Infection PLHIV ART among adult PLHIV The number of persons aged 15 years in need of ART was estimated to be 321,235 in 2015, rising to 372,240 in 2020 (estimates from AEM) (Figure 4.4). ART needs among adult PLHIV were estimated using the Strategic Use of ARV (SUFA) criteria. The number of PLHIV receiving ART is projected to increase from 60,301 (18.8% of persons eligible for treatment) in 2015 to 68,719 (18.5% of eligible persons) in Both projections will be useful in guiding future program planning for ART supply in ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

46 Figure 4.4: Estimates and Projection of PLHIV and ART Needs among Population Aged 15 Years in Indonesia, (AEM result) PLHIV % receiving ART PLHIV need ART Year PLHIV receiving ART PLHIV % receiving ART Note: * Denominator for HIV coverage: PLHIV who are eligible for ART, based on SUFA criteria. 4.6 HIV among children The projected number of children living with HIV and AIDS shows an increasing trend from 16,712 in 2015 to 20,825 in At the same time, the number of new infections among children is projected to trend slightly downward, reflecting both slightly declining general population HIV prevalence and the impact of PMTCT program efforts. AIDSrelated deaths among children are projected to reach a peak of 2,526 deaths in 2019 and then start to decline. Figure 4.5: Estimates and Projection of PLHIV, AIDS Deaths and New HIV Infections among Children Aged 0-14 Years in Indonesia, (Spectrum result) PLHIV AIDS Death & New HIV Infection Year AIDS Death New HIV Infection PLHIV 0 44 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

47 4.7 ART among children ART need among children living with HIV was estimated at 12,869 in 2015 and projected to be 13,374 in 2020 (estimates from Spectrum using the SUFA criteria) (Figure 4.6). Both the number of children PLHIV receiving ART and ART coverage among children are projected to stabilize between 2015 and Figure 4.6: Estimates and Projection of PLHIV and ART Needs among Children Aged 0-14 Years in Indonesia, (Spectrum result) PL HIV % receiving ART Year PLHIV need ART PLHIV receivingart PLHIV % receiving ART 4.8 Prevention of mother to child transmission (PMTCT) Spectrum AIM produced as estimate of HIV prevalence among pregnant women in 2015 and projections to Prevalence was estimated to be 0.32% in 2015 and is projected to reach a peak at 0.33% in 2016 and 2017 before beginning to declining (Figure 4.7). Figure 4.7: Estimates and Projection of HIV Prevalence among Pregnant Women in Indonesia, (Spectrum result) 1.00 HIV Prevalence (%) Year ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

48 As shown in Figure 4.8, the number of HIV positive pregnant women is projected to decrease from 15,614 in 2015 to 14,298 in The number of mothers receiving Prevention of Mother to Child Transmission service needs is projected to reach a peak of 1,727 in 2016, but decrease to 1,539 in An estimated 10.33% mothers received PMTCT in This figure is projected to increase slightly to 10.76% in Figure 4.8: Estimates and Projection of PMTCT Service Needs in Indonesia, (Spectrum result) HIV Positive Pregnant Women Year HIV Positive Pregnant Women Mothers receiving PMTCT % receiving PMTCT % Receiving PMTCT 4.9. Summary of Estimates: 2014 and 2016 Epidemic Updates The changes in estimates of key parameters resulting from the 2016 Modelling update (vs. the 2014 Modelling work) are summarized in Table 4.3 below. Table 4.3: Summary of differences in key results 2014 vs Modelling Parameter Modelling Modelling Number of new HIV infections ,875 51,141 Number of new HIV infections ,829 50,569 Number of PLHIV , ,443 Number of PLHIV , ,363 Total HIV-related deaths ,029 40,158 Total HIV-related deaths ,913 42,921 Number of persons eligible for ART 2016* 351, ,622 Number of persons eligible for ART , ,275 Number of persons on ART ,592 64,252 Number of persons on ART ,663 67,659 Strategic Use of ARV for Program Policy implemented beginning in ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

49 5 LIMITATIONS The limitations of the 2016 Modelling work are largely those faced in most, if not all, epidemic Modelling exercises. The main issues concern data limitations in relation to data required by AEM and Spectrum AIM. Notable among these are the following: Lack of a functioning sentinel surveillance mechanism, resulting in reliance on periodic large-scale surveys (i.e., IBBS) to provide crucial information. This results in data being available for a limited number of cities and districts, making the production of estimates at the national level a challenge. The fact that not all KPs were covered in each city/district in the IBBS conducted to data further complicates accurate estimation. Limited time series data from IBBS, making discerning trends over time a challenge even for those cities and districts for which data are available. Only in the 12 cities and districts that were covered in the 2007, 2011 and 2015 IBBS were data at three points in time available. Data at two points in time were available for an additional 13 cities and districts. Extremely limited general population data. Country-specific data on key parameters of the AEM were, as in many countries, not available for Indonesia for example, HIV incidence rates by KP or population sub-group. As a result, it was necessary to use default values built into AEM that are based upon the compilation of existing from other Asian countries. The extent to which epidemic patterns in Indonesia correspond to those in the Asia region as whole is uncertain, but considerable research went into this issue during the development of AEM. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

50 6 Recommendations for future Modelling work To ensure that the models outputs are close to reality, there is urgent need to generate information needed for Modelling through collection of quality program data. The accuracy of both KP population size estimates and epidemic modelling would be greatly improved by having mapping data from more cities and districts. 48 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

51 7 REFERENCES 1. Central Statistics Bureau Indonesia and Ministry of Health Indonesia Report on Results of Behavioral Surveillance Survey in Indonesia. Jakarta: s.n., Ministry of Health Indonesia Report on Results of Study of Prevalence of Reproductive Tract Infections among FSW, Indonesia Jakarta: MoH, Ministry of Health Indonesia HIV Infection Risk Behavior Situation in Indonesia, Results of Behavioral Surveillance Survey Jakarta: s.n., Ministry of Health Indonesia Guidelines for HIV Sentinel Surveillance, Second Generation HIV Surveillance. Jakarta: MoH, Ministry of Health Indonesia Risk Behavior and HIV Prevalence in Tanah Papua Directorate General of CDC & EH, Ministry of Health Indonesia Report on Real Integrated Biological and Behavioral Survey Jakarta: MoH, Ministry of Health Indonesia RI Integrated Biological and Behavioral Survey. Directorate General of CDC & EH, Ministry of Health Indonesia Mathematic Model of HIV Epidemic in Indonesia Directorate General of CDC & EH, Ministry of Health Indonesia Estimates the Most at Risk Population of HIV Directorate General of CDC & EH, Ministry of Health Indonesia Report on Results of Survey of Prevalence of Reproductive Tract Infections among FSW in Kupang, Samarinda, Pontianak, Yogyakarta, Timika, Makassar and Tangerang Jakarta: MoH, Ministry of Health Indonesia Report on Result of Integrated Biological and Behavioral Survey Jakarta: MoH, Ministry of Health Indonesia Report on Result of Integrated Biological and Behavioral Survey Jakarta: MoH, World Health Organization Guidelines for Second Generation HIV Surveillance: an update: Know your epidemic. Geneva: WHO, Ministry of Health Indonesia Size Estimation of Key Affected Populations (KAPs). Jakarta: MoH, Ministry of Health Indonesia Report on Result of Integrated Biological and Behavioral Survey Jakarta: MoH, Ministry of Health Indonesia Integrated Biological & Behavioral Surveillance (IBBS) in General Population in Tanah Papua, 2013 (PowerPoint slides). 17. Ministry of Health Indonesia Result of Integrated Biological and Behavioral Survey 2015 (PowerPoint slides) 18. Ministry of Health Indonesia Report of 2016 Size Estimation of Key Populations (KPs). ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

52 ANNEX 1 Procedures used to produce national estimates of key parameters for 2015 and trends over time for input into AEM The 2015 IBBS, like prior rounds of IBBS, was designed as a surveillance mechanism to track trends in key indicators in selected cities/districts over time. This design is suboptimal for producing true national estimates as it features data for only a modest number of cities/districts that were not randomly chosen. Nevertheless, national estimates were desired for the 2016 epidemic update, and accordingly an estimation approach was devised to enable this while at the same time maintaining the surveillance mechanism begun with the 2007 IBBS. The general approach adopted for deriving national estimates of key AEM parameters for each KP was to produce separate estimates for (1) the cities/districts for which data were available these are primarily the larger cities/districts that have been the primary focus of HIV control efforts to date, and (2) cities/districts for which IBBS data were not available these are primarily smaller cities/districts that have not been deemed as being among the highest risk districts, and most have not been targeted for GF ATM funding support (note, however, that some albeit a minority of cities/districts in this group are indeed recipients of GF ATM funds). Mean parameter estimates for the smaller of the cities/districts for which IBBS data were available were used in lieu of actual data for cities/districts for which no IBBS data were available. A national estimate was then calculated by weighting the sub-group estimates by KP population size estimates from the 2016 size estimation update and summing them to yield a national figure. This was done separately for the 32 non-papuan provinces (in the aggregate) and for the Tanah Papua (two provinces), and then combining the two sets of estimates weighted by estimated KP population size. This is expected to produce more accurate national estimates than the less formal averaging procedure used in prior epidemic updates. The procedure is illustrated below in the case of the indicator Proportion of Transgenders Using a Condom at Last Commercial Sex. IBBS data were available for a total of nine (9) cities/districts in 2015 (years for which IBBS data were available are highlighted in yellow). Five (5) of these were from the largest cities/districts that were the earliest focus of HIV control efforts in Indonesia and for which three (3) rounds of IBBS data are available 2007, 2011 and IBBS data were also available for four (4) smaller cities/districts (2009 and 2013) that were among the second wave for priority attention beginning with GF ATM Round 9. The 2015 estimates from the 2015 IBBS data are shown in the 2015 column of the table. The 2015 estimate for cities/districts for which IBBS data were not available (labelled The Rest in the table) was calculated by taking the mean of the four smaller cities/ districts. The national estimate for 2015 was derived by taking the parameter estimates shown for 2015, weighting them by the estimated population size of Transgenders shown in the right-most column of the table, and summing them to yield the national estimate. 50 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

53 Table A1.1: Illustrative Calculation of National Estimate of the Proportion of Transgenders Using Condom at Last Commercial Sex Condom Use (Last Sex) District Estimate (Province) Largest Cities/ Jakarta 85,00 86,95 88,89 78,32 67, Districts Kota Bandung 82,00 79,65 77,30 82,59 87, Size Kota Semarang 68,00 55,16 42,31 34,86 27, Kota Malang 69,00 67,45 65,90 68,37 70, Kota Surabaya 86,00 86,09 86,18 87,64 89, Smaller Cities/ Kota Palembang 30,86 30,86 46,43 62,00 73, Districts Kota Pontianak 62,61 77,19 83,10 89,00 89, Kota Makassar 47,37 58,40 75,70 93,00 93, Kota Samarinda 30,01 35,47 43,74 52,00 54, The rest 42,71 50,48 62,24 74,00 77, Weighted average 53,70 57,25 63,57 71,27 73, The 2016 epidemic update took advantage of the longer time series of data from key districts resulting from the 2015 IBBS to more formally reassess trends in key parameters during the period (note: 2007 was the first large-scale IBBS undertaken in Indonesia). Trends between these dates were mathematically smoothed in order to reduce noise in the data resulting from the fact that KP district sample sizes in the respective rounds of IBBS were modest. For cities/districts in which 2009 and/or 2013 IBBS data were available (but not 2015), levels and trends from 2007 to 2015 were estimated by extrapolating and back-extrapolating from the available IBBS data taking into account trends in the cities/district for which three rounds of IBBS data (2007, 2011 and 2015) were available. HIV prevalence estimates for provinces in which no IBBS data were available was assumed to approximate the level and trend in smaller cities/ districts for which at least some data were available. ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

54 ANNEX 2 Inventory of Data Input to AEM Spreadsheets 2016 Epidemic Update Heterosexual Behaviors and STI Behavioral inputs to AEM for the heterosexual population Category Female Sex Workers / population (thousands) - Baseline 2014: Input AEM: 2007 = 208.7, 2009 = 215.2, 2011 = 221.6, 2013 = 227.8, and 2015 = Baseline 2016: Data obtained: Non-Papua = percent of females aged who sell sex 0.33%; population females aged in ; Papua = percent of females aged who sell sex 0.19%; population female aged in Calculation: Population FSW for Non-Papua = 0.33%* /1000=243.4; for Papua = 0.19%* /1000=2.5 Input AEM: Non Papua put the number in 2030 = 243.4; and the rest copy paste transpose from sheet population AEM; and 2030, 2035, 2040, 2045 & 2050 just copy paste one by one; 2007 = 206.8, 2009 = 211.9, 2011 = 216.6, 2013 = 220.9, 2015 = 224.7, and 2030 = 243.4; Papua put the number in 2030 = 2.5; and the rest copy paste transpose from sheet population AEM; and 2030, 2035, 2040, 2045 & 2050 juts copy paste one by one; 2007 = 1.8, 2009 = 1.9, 2011 = 1.9, 2013 = 2.0, 2015 = 2.1, and 2030 = 2.5; Data source: Census 2010; Data Demography Spectrum (Indonesia Spectrum AEM Sep16.PJNZ). Female Sex Workers General Percent of females aged who sell sex - Baseline 2014: Data obtained: FSWs (direct & indirect) ; female population age Non-Papua Calculation: / = 0.34%, 0.35% (2011) Input AEM : 0.33% (all year) Data source : Size estimation of MARP, MoH Baseline 2016: Data obtained: total population FSW Non-Papua ; population females aged ; total population FSW Papua ; population females aged ; Calculation: percent of females aged who sell sex in Non-Papua = /68,064,500 = 0.33%; Papua = 2.100/ = 0.19%; Input AEM : Non-Papua = 0.33% (all year); Papua = 0.19% (all years). Data source : Size estimation of KPs, MoH 2016; Data Population AEM. 52 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

55 Percent of female sex workers in group 1 (higher frequency) - Baseline 2014: Data obtained: Direct FSW 106,011; FSWs (direct & indirect) 214,054 Calculation: 106,011/214,054 = 49.53% Input AEM : 49.53% (2009); 54% (2011) Data source : Size estimation of MARP, MoH Baseline 2016: Data obtained: total population FSW Non-Papua ; total DFSW size from (total size estimates per province*dfsw weight per province) Non-Papua ; total population FSW Papua ; total DFSW size from (total size estimates per province*dfsw weight per province) Papua 793; Calculation: / = 32.9%; 793/2.100 = 37.7%; Input AEM: Non-Papua = 32.9% (all years); Papua = 37.7% Data source: Size estimation of KPs, MoH 2016; Data Mapping, NAC Movement from group 1 to group 2 each year - Baseline 2014: No data available. Use default data from Thailand Baseline Projection Input AEM = 1% (All years) - Baseline 2016: Assumed: keep the balance of FSW size Input AEM = 1% (All years) Female Sex Workers group 1 (FSW1) / population (in thousands) - Baseline 2016: Data obtained: total population FSW ; percent FSW in group % Calculation: *32.9% = 73.9 Number of clients per day - FSW group 1 - Baseline 2014: Data obtained: BSS ; BSS ; IBBS (clients per week: 8; # workday per week: 3.8. # clients per day: 8/3.8 = 2.1, Average = ( )/3 = 1.9); IBBS 2011 Papua 1.7 (clients per week:9 #workday per week: (23/30*7) = 5.4 #client per day: 9/5.4 =1.7, Average = ( )/4 =1.9); IBBS 2011 Non-Papua 1.7 (clients per week:9 #workday per week: (23/30*7) = 5.4 #client per day: 9/5.4 =1.7, Average = ( )/4 =1.9). Input AEM = 1.9 (All years) Data source: BBS 2002, 2004, IBBS 2009, 2011 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

56 - Baseline 2016: Data obtained: number of clients per week (Mean) / days worked per week. Calculation: /6.1 = 1.5; /6.1 = 1.3; /5.4 = 1.6; /5.6 = 1.1; /5.4 = 1.6. Input AEM = 1.5 (all year s) average from 2007 to 2015 Data source: IBBS 2007, 2009, 2011, 2013, Days worked per week - FSW group 1 - Baseline 2014: Data obtained: BSS 2004 = working days per month 22; months per year 8.6; weeks per year 52; days per week 8.6x22/52 = 3.6. IBBS 2009 = working days per month 25; months per year 8; weeks per year 52; days per week 8x25/52 = 3.8. Average = ( )/2 = 3.7. IBBS 2011= workday per month 23.33; day per month 30; work day per week 23.33/30*7 = 5.4. Average )/3 = 4.3. IBBS 2011 Non-Papua= workday per month 23.27; day per month 30; work day per week 23.27/30*7 = 5.4. Average ( )/3 = 4.3. IBBS 2011 Papua = workday per month 23.8; day per month 30; work day per week 23.8/30*7 = 5.5. Average ( )/3 = 4.3. Input AEM : 4.3 (all years) Data source : BSS 2004, IBBS 2009, IBBS Baseline 2016: Data obtained: 2007 = Non-Papua 6.1 (mean), 6.25 (median); Papua 6.24 (mean), 6.5 (median); 2009 per month = Non-Papua (mean), 26 (median); Papua (mean), 26 (median); 2011 = Non-Papua 5.4; Papua 5.5; 2013 = Non Papua 5.64 (mean), 5.75 (median); Papua 5.93 (mean), 6.25 (median); 2015 = Non Papua 5.42; Papua Input AEM: 5.7 (all year s) average from 2007 to 2015 Data source: IBBS 2007, 2009, 2011, 2013, Percent condom use with clients - FSW group 1 - Baseline 2014: Data obtained: increasing condom use as an impact of promotion condom in work place (national consensus in August 2008); Input AEM: 1986 = 5%; 1990 = 5%; 1993 = 13%; 1996 = 36%; 2000 = 41%; 2003 = 58%; 2007 = 67%; 2009 = 60%; 2011 = 73.6%; 2011 = 67.3%. Data source: DHS Indonesia 1985 (% of condom use for family planning); Household survey (national consensus in August 2008); BSS 1996; BSS 2000 in 3 cities; BSS 2002 & 2004 (last sex) in 13 cities; IBBS 2007 (last sex); IBBS 2009 (last sex); IBBS 2011 (last sex) - Non-Papua; IBBS 2011 (last sex) - Papua. 54 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

57 - Baseline 2016: Data obtained: weighted last sex condom use DFSW Non-Papua = ; ; Calculated: *0.95 = 53.7%; *0.8 = 57.9% #2007 to 2015 interpolate and % Input AEM: 2005 = 45.0%; 2007 = 53.7%; 2009 = 54.7%; 2011 = 55.8%; 2013 = 56.8%; 2015 = 57.9% Data source: Size estimation of M/Key Population, MoH 2016; IBBS 2007, 2009, 2011, 2013, 2015; Average duration selling sex in group 1 (years) - Baseline 2014: Data obtained: BSS 2004 = % of FSW worked <12 months 27.75%; Duration 1/27.75% = 3.6; IBBS 2009 = % of FSW worked <12 months 35%; Duration 1/35% = 2.9; Average duration /2 = 3.25; IBBS 2011 = % of FSW worked <12 months 33.63%; Duration 1/33.63% = 2.97; Average duration /3=3.16; IBBS 2011 Non- Papua 1/34.29% = 2.92; IBBS 2011 Papua 1/27.82% = Input AEM = 3.16 (All years) Data source: BSS 2004; IBBS 2009, Baseline 2016: Data obtained: selling sex up to interview time in group 1 (years) (Median)*2 = 2007 Non-Papua 1*2 = 2; Papua 2*2 = 4; 2009 Non-Papua 1*2 = 2; Papua 2*2 = 4; 2011 Non-Papua 3*2 = 6; Papua 3*2 = 6; 2013 Non Papua 2*2 = 4; Papua 3*2 = 6; 2015 Non Papua 2*2 = 4; Papua 4*2 = 8. Calculation: 2007 = 3.3 (baseline 2014) interpolate up to 2015 = 4 (2*2). Input AEM : 2007 = 3.3; 2009 = 3.5; 2011 = 3.7; 2013 = 3.8; 2015 = 4.0 Data source : IBBS 2007, 2009, 2011, 2013, STI prevalence among FSW group 1 - Baseline 2014: Data obtained: Calculated from adjusted % FSW infected by NG and or CT in area survey of Java Island; RTI Study 2003 & 2005 in 7 cities excluded Papua (% of direct FSW infected by NG and or CT); RTI study in 12 cities, excluded Papua (% direct FSW with infected NG). Input AEM: 2003 = 39%; 2007 = 32%; 2009 = 37%; 2011 = 51.13%; 2011 = 57.11% Data source: Survey among FSW; National consensus in August 2008; IBBS 2009, 2011 Papua & Non-Papua. - Baseline 2016: Data obtained: gonorrhea big; gonorrhea small Calculation: average between gonorrhea big and gonorrhea small Input AEM: 2000 = 60%; 2007 = 36.8%; 2009 = 36.8%; 2011 = 36.8%; 2013 = 32.4%; 2015 = 28.0% ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

58 Female Sex Workers group 2 (FSW2) / population (in thousands) - Baseline 2016: Data obtained: total population FSW ; percent FSW in group % Calculation: *67.1% = Number of clients per day - FSW group 2 - Baseline 2014: Data obtained: clients per week Calculated: average number of client per day from 4 surveys in 2002, 2004, 2007 and 2009 among indirect FSW; Note: working days/month 22; working months/year 9; working days/week (9x22)/52 week = 3.8 days/week. - BSS 2002/2003 (3.5 clients per week /3.8 days per week) = 0.92 clients/day) - BSS 2004/2005 (4.2 clients per week /3.8 days per week) = 1.11 clients/day) - IBBS 2007 (3.29 clients per week /3.8 days per week) = 1.84 clients/day) - IBBS 2009 (4 clients per week/4.5 days per week) = 0.88; Average = ( )/4 = IBBS 2011: #3 clients per week #23 workdays per month, #workday per week (23/30*7) = 5.37 #clients per day (3/5.37) =0.84; Average = (0, )/5 = IBBS 2011 (WPSTL Non-Papua): #3.3 clients per week #23.21 workdays per month, #workday per week (23.21/30*7) = 5.42, #clients per day (3.3/5.42) = IBBS 2011 (WPSTL Papua): #2.06 clients per week #24.33 workdays per month, #workday per week (24.33/30*7) =5.67, #clients per day (3.3/5.67) = 0.58; Average = (0, )/4 = 0.88 Input AEM = 1.12 (All years) - Baseline 2016: Data obtained: number of clients per week (Mean) / days worked per week. Calculation: /6.2 = 0.8; /6.5 = 0.6; /5.8 = 0.6; /5.5 = 0.7; /5.7= 0.7 Input AEM : 2007 = 0.8; 2009 = 0.6; 2011 = 0.6; 2013 = 0.7; 2015 = 0.7 Data source : IBBS 2007, 2009, 2011, 2013, Days worked per week FSW group 2 - Baseline 2014: Data obtained: BSS 2004 = working days per month 22; months per year 8.6; weeks per year 52; Calculated: day worked per week = 8.6x26/52 = 3.6; IBBS 2009 = working days per month 26; months per year 9; weeks per year 52; 56 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

59 Calculated: day worked per week = 9x26/52 = 4.5; Average = ( )/2 = IBBS 2011: clients per week 3; working days per month 23; day worked per week (23/30*7) = 5.37; Average = ( )/3=4.49 IBBS 2011 Non-Papua = Average ( )/3 = 4.51; IBBS 2011 Papua = Average ( )/3 =4.59; IBBS 2007 = working days 25; off work weeks 7; weeks/total work weeks 49; total week 52; Calculation: 25/30*7*49/52; IBBS 2011 = same calculation. Input AEM : 4.49 (All years); updated: 2007 = 5; 2011 = 2.7 Data source : BSS 2004, IBBS 2007, IBBS 2009, IBBS Baseline 2016: Data obtained: 2007 Non Papua (Mean) = 6.24; Papua (Mean) = 6.55; 2009 used day worked per month in Non Papua (Mean) = 26.22; calculated: 26.22/number per week 4 = 6.555; Papua (Mean) = 25.83; calculated: 25.83/number per week 4 = 6.457; 2011 used day worked per month in Non Papua (Mean) = 23.21; calculated: 23.21/number per week 4 = ; Papua (Mean) = 24.33; calculated: 24.33/number per week 4 = ; 2013 Non Papua (Mean) = 5.5; Papua (Mean) = 6.05; 2015 used day worked per month in Non Papua (Mean) = 23.19; calculated: 23.19/number per week 4 = ; Papua (Mean) = 25.09; calculated: 25.09/number per week 4 = Input AEM: 2007 = 6.24; 2009 = 6.6; 2011 = 5.8; 2013 = 5.5; 2015 = 5.8 Data source: IBBS 2007; IBBS 2009; IBBS 2011; IBBS 2013; IBBS 2015 Percent condom use with clients - FSW group 2 - Baseline 2014: Data obtained: DHS Indonesia 1985 % of condom use for family planning; Increasing condom use as an impact of promotion condom in work place national consensus in August 2008; household survey national consensus in August Input AEM: 1986 = 5%; 1990 = 5%; 1993 = 13%; 1996 = 36%; 2000 = 38%; 2003 = 55%; 2007 = 68%; 2009 = 63%; 2011 = 60.7%; 2011 = 62.3%; 2011 = 57.74%; 2011 = 37.37%; 2011 = 31.92%. Data source: BSS 1996, BSS 2000 in 3 cities, BSS 2002 & 2004 (last sex) in 13 cities; IBBS 2007 (last sex), IBBS 2009 (last sex), IBBS 2011 (last sex), IBBS 2011 (last sex Non-Papua), IBBS 2011 (last sex Papua), IBBS 2011 (week consistent Non-Papua), IBBS 2011 (week consistent Papua). - Baseline 2016: Data obtained: percent condom use with client FSW1 53.7%*0.8 = 42.96%; Note: all years % condom use FSW1* with 0.8 Input AEM: 2007 = 42.96%; 2011 = 44.6%; 2015 = 46.3% Data source: IBBS 2007; IBBS 2009; IBBS 2011; IBBS 2013; IBBS 2015 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

60 Average duration selling sex in group 2 (years) - Baseline 2014: Data obtained: BSS 2004 = % of FSW worked <12 months) 34.9%; calculation: 1/34.9% = 2.9 IBBS 2009 = % of FSW worked <12 months) 44%; calculation: 1/44% = 2.27; Average = ( )/2 = 2.59 IBBS 2011 = % of FSW worked <12 months) 37.86%; calculation: 1/37.86%=2.64 Input AEM: 2.64 (All years) - Baseline 2016: Data obtained: selling sex up to interview time in group 2 (years) (Median)*2 = 2007 Non-Papua 1*2 = 2; Papua 1*2 = 2; 2009 Non-Papua 1*2 = 2; Papua 0*2; 2011 Non Papua 2*2 = 4; Papua 2*2 = 4; 2013 Non Papua 2*2 = 4; Papua 1*2 = 2; 2015 Non Papua 2*2 = 4; Papua 2*2 = 4. Calculation: 2007 = (baseline 2014) interpolate up to 2015 = 4 (2*2). Input AEM : 2007 = ; interpolate up to 2015 = 4.0 Data source : IBBS 2007, 2009, 2011, 2013, STI prevalence among FSW group 2 - Baseline 2014: Data obtained: RTI Study 2003 in 7 cities any Gonorrhea and or Chlamydia; RTI study 2005; IBBS 2007 (NG); IBBS 2009 (NG); IBBS 2011 (CTNG), non-papua; IBBS 2011 (CTNG), Non-Papua; Average: IBBS Average of STI =18% Input AEM: 2003 = 35%; 2005 = 31%; 2007 = 13.91%; 2009 = 22%; 2011 = 49.52%; 2011 = 39.6%; updated 2013 = 18%, but interpolate from (30%-18%). Data source: - Baseline 2016: Data obtained: using number gonorrhea big in %; number of STI prevalence among FSW group %; number of STI prevalence among FSW group %; number of STI prevalence among FSW group %; Calculation: in 2007 used 2011 = 18.65%; 2009 used 2011 = 18.65%; 2011 used number of gonorrhea big size IBBS 2011 = 18.65%; 2013 = 32.4%*18.65%/36.8% = 16.4%; 2015 = 28.0%*18.65%/36.8% = 14.15%; Input AEM: 2007 = 18.65%; 2009 = 18.65%; 2011 = 18.65%; 2013 = 16.4%; 2015 = 14.15% Data source: IBBS 2007, 2009, 2011, 2013, ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

61 Clients of FSWs Clients of FSW / population (in thousands) The results of the 2016 KP Size Estimation exercise were used as input for this parameter. The national calculation was 5,254,663 clients (95% CI = 4,415,788 6,167,873) Input to AEM: 2015 non-papua: 5,195,579; 2015 Papua: 59,084 Percent of males aged who visited FSW in the last year - Baseline 2014: Data obtained: clients = ; male population age Non-Papua = Calculation: / = 5% Non-Papua Input AEM : 5% (All years); 2011 = 11.7 Data source : size estimation of Most at Risk Population, MoH Baseline 2016: Data obtained: client FSW Non-Papua ; population males aged (2015) Calculation: / = 9.1% Input AEM : 9.1% (all years) Data source : size estimation of HIV key populations, MoH 2016 Average duration buying sex (years) - Baseline 2014: Data obtained: no data available, use default data from Thailand baseline projection to reduce the epidemic, to make the different pattern on IDFSW and FSW. Input AEM: 10.0 (All years); updated = 7% - Baseline 2016: Input AEM: used baseline 2014 = 7.0 (all years) Percent of adult males who are circumcised - Baseline 2014: Data obtained: data assumed 80% of adult males are Moslem (DHS 2007), assumed all adult males Moslem circumcised Input AEM: 80% (All years) - Baseline 2016: Input AEM: used baseline 2014 = 80% (all years) Population engaging in Casual Sex Males engaging in casual sex / population (thousands) - Baseline 2016: Data obtained: percent of males engaging in casual sex in the last year 6.8%; population males aged Calculated: population males engaging in casual sex in 2030 = 6.8%* /1000 = ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

62 Input AEM: put the number in 2030 = 5.158; and the rest copy paste transpose from sheet population AEM; and 2030, 2035, 2040, 2045, & 2050 just copy paste one by one = 1.779, 2009 = 1.822, 2011 = 4.516, 2013 = 4.615, 2015 = and 2030 = Data source: Census 2010; Data Demography Spectrum (Indonesia Spectrum AEM Sep16.PJNZ). Females engaging in casual sex / population (thousands) - Baseline 2016: Data obtained: percent of females engaging in casual sex in the last year 2.0%; population females aged Calculated: population females engaging in casual sex in 2030 = 2.0%* /1000 = Input AEM: put the number in 2030 = 1.475; and the rest copy paste transpose from sheet population AEM; and 2030, 2035, 2040, 2045, & 2050 just copy paste one by one = 626, 2009 = 642, 2011 = 1.312, 2013 = 1.338, 2015 = and 2030 = Data source: Census 2010; Data Demography Spectrum (Indonesia Spectrum AEM Sep16.PJNZ). Percent of males engaging in casual sex in the last year - Baseline 2014: Data obtained: Calculation: proportion of HRM visiting sex worker adjusted by proportion of HRM in the population male %; % HRM having casual sex 5% x = 2.83% Input AEM: 2009 = 2.83% Data source: IBBS Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: = 2.8%; 2010 = 4.8%; = 6.8% Percent of females engaging in casual sex in the last year - Baseline 2014: Data obtained: data given from national consensus meeting on August 2008 Input AEM: 2007 = 0.3% - Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: = 1%; 2010 = 1.5%; = 2.0% Percent condom use in casual sex - Baseline 2014: Data obtained: 2002 = BSS in 13 cities 1%; 2004 = BSS in 13 cities 17%; 2007 = IBBS 10 cities; no scale up program on condom in Indonesia and limited condom available 18.2%; Note: Data obtained is % condom use at last casual sex among high risk man Input AEM: 2002 = 1%; 2004 = 17%; 2007 = 18.2% 60 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

63 - Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: = 1%; 2003 = 9%; 2004 = 17%; 2005 = 17.4%; 2006 = 17.8%; = 18.2% Average number of sex contacts in the last year (male) - Baseline 2014: Data obtained: IBSS 2004 in 13 cities (data given from MoH). Average number of sexual contact among male worker = 2 Input AEM: 2004 = 2 - Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: 12.0 (all years) Spouses and Regular Partners Sex with spouses or regular partners (RP) Number of sexual contacts with spouse or RP (per week) - Baseline 2014: Data obtained: no data available. Use default data from Thailand baseline projection Input AEM: 1.0 (All years) - Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: 1.0 (all years) Percent condom use with spouses or regular partners - Baseline 2014: Data obtained: DHS 2003 Input AEM: 2003 = 1.3% - Baseline 2016: Data obtained: no changes used baseline 2014 Input AEM: 1.3% (all years) STI prevalence in adult population - Baseline 2014: Data obtained: assumed from the STI cases reported among adult, data given from MoH. Input AEM: 2003 = 0.2% - Baseline 2016: Data obtained: assumed from STI Prevalence PWID Gonorrhea same with general population Input AEM: gonorrhea big PWID = 0.8% (all years) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

64 Male Same-Sex Behaviors and STI Behavioral inputs to AEM for men having sex with men Category Men who have Sex with Men - General Percent of males aged engaging in same-sex behaviour 2014 : No data input 2016 : Fitting #Size Estimate : #Data spectrum for Male age in 2015 : Data obtained : / = 0,0109 Input AEM : 1.1% Data Source : Size Estimate MSM 2016 : Data Census 2010 : Spectrum File Percent of MSM in risk group : 27.7% based upon the # of MSM that had been contacted by an outreach workers in the past year, which was used as a proxy indicator for reachability Shift from MSM group 1 to group 2 Estimate (10%) based upon regional data Men who have Sex with Men group 1 (MSM1) / population Percent engaging in anal sex in the last year - MSM1 No data input for this category Number of anal sex contacts last week (among those having anal sex) - MSM1 No data input for this category Average duration of same-sex behavior (years) - MSM1 No data input for this category Percent of MSM1 with female partners 2014 : No data input 2016 : Fitting IBBS #2007 : 50,0% #2009 : 50,0% #2011 : 40,2% #2013 : 38,0% #2015 : 28,5% : use data 2007 : use data 2015 Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent condom use in anal sex with MSM : No data input 2016 : Proportion last sex condom use MSM, 2007: Proportion per province from (IBBS 2007*size estimates MSM/100) #Total proportion: ; #Total size estimates of MSM: 754,310 Data Obtained : / *100 = 46.26% : Proportion last sex condom use MSM, 2009: Proportion per province from (IBBS 2009*size estimates MSM/100) #Total proportion: ; #Total size estimates of MSM: 754,310 Data Obtained : / *100 = 52.85% 62 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

65 : Proportion last sex condom use MSM, 2011: Proportion per province from (IBBS 2011*size estimates MSM/100) #Total proportion: ; #Total size estimates of MSM: 754,310 Data Obtained : / *100 = 60.33% : Proportion last sex condom use MSM, 2013: Proportion per province from (IBBS 2013*size estimates MSM/100) #Total proportion: ; #Total size estimates of MSM: 754,310 Data Obtained : / *100 = 68.59% : Proportion last sex condom use MSM, 2015: Proportion per province from (IBBS 2015*size estimates MSM/100) #Total proportion: ; #Total size estimates of MSM: 754,310 Data Obtained : / *100 = 74.42% Input AEM : 2007: 46.3% ; 2009: 52.85% ; 2011: 60.3% ; 2013: 68.6% ; 2015: 74.42% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 : Size estimation of KP. MoH 2016 STI prevalence among MSM : No data input 2016 : Gonorrhoea IBBS 2007: 19.7; 2009: 17; 2011: 20.8; 2013: 21.1; 2015: 12.7 Data obtained : Average(19.7;17;20.8;21.1;12.7) = 18.26% Input AEM : 18.26% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Men who have Sex with Men group 2 (MSM2) / population Percent engaging in anal sex in the last year MSM2 No data input for this category Number of anal sex contacts last week (among those having anal sex) MSM2 No data input for this category Average duration of same-sex behavior (years) MSM2 No data input for this category Percent of MSM2 with female partners No data input for this category Percent condom use in anal sex with MSM2 No data input for this category STI prevalence among MSM : No data input 2016 : #STI Prevalence among MSM1/5 (assume by consultant) #18.3/5 = 3.7% Input AEM : 3.7% ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

66 Data Source : STI Prevalence among MSM1 : IBBS , 2015 : IBBS 2009, 2013 MSM visiting (male and female) sex workers Percent of MSM1 visiting male sex workers No data input for this category Percent of MSM2 visiting male sex workers No data input for this category Ratio of frequency of visiting MSW (group 2 / group 1) No data input for this category Percent of MSM1 visiting female sex workers No data input for this category Percent of MSM2 visiting female sex workers No data input for this category Percent condom use in anal sex with male sex workers No data input for this category Percent condom use with Female sex worker group 1 (FSW1) 2014 : No data input 2016 : Use #Percent condom use with clients - FSW group 1 Input AEM : 57.9% Percent condom use with female sex worker group 2 (FSW2) 2014 : No data input 2016 : Use #Percent condom use with clients - FSW group 2 Input AEM : 46.3% Male Sex Workers Percent of males aged who sell sex 2014 : No data input 2016 : #Size Estimate MSM 2016 : #MSM who sells sex in the past year and have 10 or more partners in the past month (IBBS) : 9.6% #Projection Number for Male age in 2015 : 68,727,200 #20,878*9.6% = 20,043 #20,043/68,727,200 = Input AEM : 0.03% Data Source : Size Estimate MSM 2016 : Projection Number of 2015 : IBBS , 2015 : IBBS 2009, 2013 Average duration selling sex (in years) 2014 : No data input 2016 : #Average duration selling sex (in years) Median 2011: 6; 2013: 3; 2015: 4 Average (6,3,4)*2 = 8.7 Input AEM : ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

67 Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Shift from MSM1 to MSW No data input for this category Shift from MSM2 to MSW No data input for this category Percent of MSW reporting anal sex with clients in the last year No data input for this category Number of anal sex contacts last week (for MSW with anal sex) No data input for this category STI prevalence among male sex workers 2014 : No data input 2016 : STI Prevalence #2007 : 13.4% #2009 : 17.1% #2011 : 24.0% #2013 : 24.8% #2015 : 26.5% : use data 2007 : use data 2015 Input AEM : 2007 : 13.4%; 2009 : 17.1%; 2011 : 24.0%; 2013 : 24.8%; 2015 : 26.5% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent MSW visiting female sex workers in the last year 2014 : No data input 2016 : #Percent MSW visiting female sex workers in the last year #2007 : #2009 : Average (16.56, 29.79)/100 = Input AEM : 23.17% Data Source : IBBS 2007 : IBBS 2009 Percent MSW with female regular partners in the last year 2014 : No data input 2016 : IBBS #2007 : 72.5% #2009 : 65.2% #2011 : 48.6% #2013 : 40.2% #2015 : 41.2% : use data 2007 : use data 2015 Input AEM : 2007 : 72.5%; 2009 : 65.2%; 2011 : 48.6%; 2013 : 40.2%; 2015 : 41.2% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

68 Injecting Drug Use Behaviors Behavioral inputs to AEM for Injecting Drug Users and Injecting Sex Workers Male IDU - Injecting Behaviours / population Percent of males age who inject drugs 2014 : Size estimation of MARP. MoH & NAC 2006 : Size estimation of MARP. MoH 2009 Data obtained: # IDUs: 105,784; #male population non-papua age 15-49: 59,379,236 Calculation: 105,784/59,379,236 = 0.18% 0.30% (2006); 0.18% (2009) 2016 : #Size Estimate IDU 2012: 74,326 #Projection Number for Male age in 2012 : 66,764,400 #74,326/66,764,400 = : #Size Estimate IDU 2015 : 33,492 #Projection Number for Male age in 2015 : 68,727,200 #33,492/68,727,200 = Input AEM : 2012 : 0.11%; 2015 : 0.05% Data Source : Size Estimate IDU 2012 : Size Estimate IDU 2016 : Data Census 2010 : Spectrum File Percent of male IDUs in high-risk networks 2014 : 50% ( ) Referred to the HIV prevalence among IDUs during : Interpolate : 74% (2009) : 36.4% (2011) IBBS : No data input for this category IDU mortality (crude mortality per year in %) 2014 : 1.0% (All years) No data available. Use default data from Thailand Baseline Projection 2016 : No data input for this category Percent of male IDUs who share needles 2014 : 60% (2002) BSS ; 56% (2007) IBBS 2007 : Update 39*1.2=45.1% (2007); update 25*1.2=35% (2009) IBBS 2007 (often and always sharing material last week) multiply by 1.2 (same until 2009) Note the adjustment because we need last year so we make it 20% higher : 13.3% (2011) IBBS 2011 (Last day injection) 2016 : Needle Sharing in the past week (2015), Assumed PWID in Indonesia 1.2; Needle Sharing in the past year *1.2 = : use baseline 2014 Input AEM : 24.0% (2015) Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent of all injections shared (among those who share) 2014 : 70% (All years) No data available. Use default data from Thailand Baseline Projection 2016 : No data input for this category 66 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

69 Number of injections per day 2014 : 2 (2007, IBBS 2007); 1.89 (2009, IBBS 2009); 1.6 (2011, IBBS 2011) Last day injection 2016 : #Average Bigger Set 2007 : 2; 2011 : 1.6; 2015 : 1.69; 2009 : =average (1.6,2) = 1.8; 2013 : =average (1.69,1.6) = : #Average Smaller Set 2009 : 1.89; 2013 : 3; 2007 = 2009 : 1.89; 2011 : =average (3,1.89) = 2.445; 2015 = 2013 : 3 : #Average National (=average (bigger set, smaller set) 2007 : (=average (2, 1.89) = : (=average (1.8, 1.89) = : (=average (1.6, 2.445) = : (=average (1.645, 3) = : (=average (1.69, 3) = : #Number of injections per day 2007 : 2; 2009 : 1.9; 2011 : 1.6 (use bigger set 2011, because national number too high); 2013 : 1.6 (use bigger set 2013, because national number too high); 2015 : 2.3 Input AEM : 2007 : 2; 2009 : 1.9; 2011 : 1.6; 2013 : 1.6; 2015 : 2.3 Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Average duration of injecting behaviour (in years) 2014 : 10.0 (All years) Assumed is double of IBBS 2007 and IBBS 2009 : 7.00 (2011) IBBS : use baseline : 10.8; 2009: 12.4; 2011: 14.0; 2013: 14.0; 2015: 14.0 Data Source : AEM 2014 Sharing to non-sharing movement per year 2014 : 10% (2004, BSS 2004); 20% (2007) IBBS Data from national consensus in : No data input for this category Male Injecting Drug Users - Sexual Behaviors Percent of male IDUs visiting female sex workers 2014 : 34% (2009) IBBS : IBBS 2015: 15.5%; 2011 : 24.2% (use baseline 2014); Interpolate from Input AEM : 15.5% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent condom use with female sex worker group : 67% (2007) IBBS Assumed is equal to client; 60% (2009, IBBS 2009) 2016 : Use #Percent condom use with clients - FSW group 1 Input AEM : 57.9% (2015) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

70 Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent condom use with female sex worker group : 68% (2007) IBBS Assumed is equal to client; 63% (2009, IBBS 2009) 2016 : Use #Percent condom use with clients - FSW group 2 Input AEM : 46.3% (2015) Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent condom use with spouse or regular partner 2014 : 14% (2007) IBBS Data given from MoH; 33% (2009, IBBS 2009 Last Sex) 2016 : No data input for this category Number of contacts with regular partners (per week) 2014 : 1 (All years) Quoted from Regional s recommendation : No data input for this category Female IDU - Injecting Behaviours / population (thousands) Percent of females age who inject drugs No data input for this category Percent of female IDUs in high-risk networks No data input for this category Percent of female IDUs who share needles No data input for this category Percent of all injections shared (among those who share) No data input for this category Number of injections per day No data input for this category Average duration of injection (in years) No data input for this category Sharing to non-sharing movement per year No data input for this category Female Injecting Drug Users - Sexual Behaviours Percent whose regular partners also inject drugs No data input for this category Percent condom use with spouse or regular partner No data input for this category Number of contacts with regular partners (per week) No data input for this category Injecting FSW group 1 (ISW1) / population (thousands) Percent of female sex workers in group 1 who inject drugs 2014 : 1% (All years) IBBS 2007.Data given from MoH 2016 : No data input for this category 68 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

71 Percent of injecting FSW in group 1 in high-risk networks 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Percent of injecting FSW in group 1 who share injections 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Percent of all injections shared (among those who share) 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Number of injections per day for injecting FSW in group : 2 (2007) IBBS 2007 (2). Assumed the injection behavior not different between man and woman IDUs : (2009) IBBS 2009 (1.898). Assumed the injection behavior not different between man and woman IDUs 2016 : No data input for this category Average duration of injecting for FSW in group : 5.0 (2007, IBBS 2007); 5.0 (2009, IBBS 2007) 2016 : No data input for this category Percent condom use with clients - Injecting FSW in group : 58% (2003, BSS 2002); 67% (2007, IBBS 2007); 60% (2009, IBBS 2009 Represent by the heterosexual behavior among direct sex worker) 2016 : No data input for this category Injecting FSW group 2 (ISW2)/ population (thousands) Percent of female sex workers in group 2 who inject drugs 2014 : 2% (All years) BSS 2004.national consensus in : No data input for this category Percent of injecting FSW in group 2 in high-risk networks 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Percent of injecting FSW in group 2 who share injections 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Percent of all injections shared (among those who share) 2014 : 0% (All years) No data available. Assumed 0% due the number of population very small 2016 : No data input for this category Number of injections per day for injecting FSW in group : 2 (2007) IBBS 2007 (2). Assumed the injection behavior not different between man and woman IDUs ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

72 : (2009) IBBS 2009 (1.898). Assumed the injection behavior not different between man and woman IDUs 2016 : No data input for this category Average duration of injecting for FSW in group : 5.0 (2007, IBBS 2007); 5.0 (2009, IBBS 2009) 2016 : No data input for this category Percent condom use with clients - Injecting FSW in group : 58% (2003, BSS 2002); 67% (2007, IBBS 2007); 60% (2009, IBBS 2009 Represent by the heterosexual behavior among direct sex worker) 2016 : No data input for this category Transgendered Populations Behavioral inputs to AEM for Transgenders Transgender population - General Percent of males aged who are transgender 2014 : 0.60% 2016 : #Size Estimate IDU 2015 : 38,928 #Projection Number for Male age in 2015 : 68,727,200 #38,928/68,727,200 = Input AEM : 0.06% (2015) Data Source : Size Estimate Transgender 2016 : Data Census 2010 : Spectrum File Percent of Transgenders who sell sex 2014 : 95% (Consensus) 2016 : IBBS #2007 : 87.0% #2009 : 63.0% #2011 : 80.76% #2013 : 80.0% #2015 : 68.9% Average (87.0, 63.0, 80.76, 80.0, 68.9)/100 = /100 = Input AEM : 75.9% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent of Transgenders who engage in casual sex but not sex work No data input for this category Percent of Transgenders who have regular partners only (calculated from previous 2 rows) 2014 : No data input 2016 : fitting 1-Percent of Transgenders who sell sex; Percent of Transgenders who engage in casual sex but not sex work Input AEM : 14.1% (All years) 70 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

73 Transgender Sex Workers - Sexual Behaviours Percent of transgender sex workers engaging in anal sex with clients 2014 : 95% (Consensus) 2016 : No data input in this category Number of anal sex contacts last week with clients (for those having anal sex) 2014 : 3.47 (All years) Average mean of number of client anal sex per week from IBBS : 2,6 (2013)4 (2011), 3.89(2009), 3,1 (2007)= 3.47 (all years) 2016 : IBBS #2007 : 2 #2009 : 2 #2011 : 5 #2013 : 4 #2015 : 2 Average (2, 2, 5, 4, 2) = 3 Input AEM : 3 (2015) Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent of anal sex contacts with clients which are receptive 2014 : 90% (All years) (Consensus, mostly TG are receptive but about 10% may bought to be penetrative.) 2016 : No data input in this category Average duration selling sex (in years) 2014 : 20 (All years) IBBS (average year-start year)x 2 = (32-19) x2=20an (adjusted we cut out the 0-1 years). After fitting 2016 : IBBS - Average duration selling sex (in years) (median) #2007 : 10 #2009 : 9 #2011 : 11 #2013 : 9 #2015 : 13 Average (10, 9, 11, 9, 13)*2 = 10.4*2 = 20.8 Input AEM : 20.8 Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Percent condom use in anal sex with clients 2014 : 15 (All years) 2016 : No data input in this category Anal STIs (%) among transgenders who sell sex 2014 : No data input 2016 : IBBS #2007 : 26.8% #2009 : 26.8% #2011 : 26.8% #2013 : 20.1% #2015 : 13.9% : : 50% : after 2015 : 13.9% Input AEM : 2007 : 26.8%; 2009 : 26.8%; 2011 : 26.8%; 2013 : 20.1%; 2015 : 13.9% Data Source : IBBS 2007, 2011, 2015 : IBBS 2009, 2013 Transgender Sex Workers - Client Make-up (sums to 100%) Percent of TG clients who are low-risk heterosexual males 2014 : 45% (All years) > IBBS 2016 : Fitting 80.0% (2005); 82.5% (2010) Assumed by consultant Input AEM : 80.0% (2005); 82.5% (2010) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

74 Percent of TG clients who are also clients of female sex workers 2014 : 30% (All years) 2016 : Fitting 5.0% (2005); 10.0% (2010) Assumed by consultant Input AEM : 5.0% (2005); 10.0% (2010) Percent of TG clients who are MSM 2014 : 20% (All years) 2016 : Fitting 10.0% (2005); 2.5% (2010) Assumed by consultant Input AEM : 10.0% (2005); 2.5% (2010) Percent of TG clients who are male IDU (calculated from previous 3 rows) 2014 : 20% (All years) 2016 : Fitting 1 Sum(Percent of TG clients who are low-risk heterosexual males; Percent of TG clients who are also clients of female sex workers; Percent of TG clients who are MSM) in same year Input AEM : 5.0% (2015) Transgenders engaging in Casual Sex - Sexual Behaviours Percent of TGs with casual sex partners who engage in anal sex 2014 : 95% (All years) 2016 : No data input in this category Number of anal sex contacts last week (for TGs having anal sex with CPs) 2014 : 0.6 (All years) 2016 : No data input in this category Percent of anal sex contacts which are receptive 2014 : 90% (All years) 2016 : No data input in this category Percent condom use in anal sex for those with casual partners 2014 : 37 ( ) IBBS 2007, , 2013; 55% (2013) Use the average from ; 46% (2007); 31% (2009); 34% (2011) Average = : No data input in this category Anal STIs (%) among transgenders who have casual partners 2014 : 15% (All years) IBBS 2016 : No data input in this category Percent of annual shift from TGs engaging in casual sex to TGs with RP only 2014 : 5% (Assumption the shift is low) 2016 : No data input in this category Transgender Sex Workers - Partner Make-up for those with CPs (sums to 100%) Percent of anal sex partners who are low-risk heterosexual males 2014 : 45% (All years) Assumption same with Transgender Sex Workers - Client Make-up (sums to 100%) 2016 : No data input in this category Percent of anal sex partners who are also clients of female sex workers 2014 : 30% (All years) Assumption same with Transgender Sex Workers - Client Make-up (sums to 100%) 2016 : No data input in this category 72 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

75 Percent of anal sex partners who are MSM 2014 : 20% (All years) Assumption same with Transgender Sex Workers - Client Make-up (sums to 100%) 2016 : No data input in this category Percent of anal sex partners who are male IDU (calculated from previous 3 rows) 2014 : 5% 2016 : Fitting 1 Sum(Percent of anal sex partners who are low-risk heterosexual males; Percent of anal sex partners who are also clients of female sex workers; Percent of anal sex partners who are MSM) in same year Input AEM : 5.0% (2015) Transgenders with Regular Partners (RP) - Sexual Behaviours Percent of TGs with regular partners who engage in anal sex 2014 : 95% 2016 : No data input in this category Number of anal sex contacts with RPs last week (for TGs having anal sex with RPs) 2014 : 0.30% 2016 : No data input in this category Percent of anal sex contacts with RPs which are receptive 2014 : 90% 2016 : No data input in this category Percent condom use in anal sex with regular partners 2014 : Assumption 1/3 with Percent condom use in anal sex for those with casual partners Transgender Sex Workers - Client Make-up (sums to 100%) 2016 : No data input in this category Anal STIs (%) among transgenders who have regular partners only 2014 : 7.5 (All years) 2016 : No data input in this category Transgender Sex Workers - Regular Partner Make-up (sums to 100%) Percent of anal sex partners who are low-risk heterosexual males 2014 : 45% Assumption ½ with casual 2016 : No data input in this category Percent of anal sex partners who are also clients of female sex workers No data input in this category Percent of anal sex partners who are MSM No data input in this category Percent of anal sex partners who are male IDU (calculated from previous 3 rows) 2014 : No data input 2016 : Fitting 1 Sum(Percent of anal sex partners who are low-risk heterosexual males; Percent of anal sex partners who are also clients of female sex workers; Percent of anal sex partners who are MSM) in same year Input AEM : 5.0% (2015) ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

76 ANNEX 3 Parameter Values used in the Final AEM Model after Fitting Table A3.1 FSW General Non-Papua Female Sex Workers - General Percent of females aged % 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% 0.33% who sell sex Percent of female sex workers 50.1% 47.9% 45.8% 43.6% 41.5% 39.3% 37.2% 35.0% 32.9% in group 1 Movement from group 1 to 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% group 2 each year Table A3.2: FSW General Papua Female Sex Workers - General Percent of females aged % 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% 0.19% who sell sex Percent of female sex workers 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% 37.7% in group 1 Movement from group 1 to 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% group 2 each year Table A3.3: FSW Group 1 & Group 2 Non-Papua Female Sex Workers group 1 (FSW1) / population (in thousands) Number of clients per day female sex worker group 1 Days worked per week - female sex workers group 1 Percent condom use with 53.7% 54.2% 54.7% 55.3% 55.8% 56.3% 56.8% 57.4% 57.9% clients - FSW group 1 Average duration selling sex in group 1 (years) STI prevalence among female 36.8% 36.8% 36.8% 36.8% 36.8% 35.8% 34.8% 33.8% 32.8% sex worker group 1 Female Sex Workers group 2 (FSW2) / population (in thousands) Number of clients per day female sex worker group 2 Days worked per week - female sex workers group 2 Percent condom use with 42.9% 43.4% 43.8% 44.2% 44.6% 45.1% 45.5% 45.9% 46.3% clients - FSW group 2 Average duration selling sex in group 2 (years) STI prevalence among female 12.9% 12.9% 12.9% 12.9% 12.9% 12.5% 12.2% 11.8% 11.5% sex worker group 2 74 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

77 Table A3.4: FSW Group 1 & Group 2 Papua Female Sex Workers group 1 (FSW1) / population (in thousands) Number of clients per day female sex worker group 1 Days worked per week - female sex workers group 1 Percent condom use with clients - FSW group % 51.7% 53.7% 55.8% 57.9% 60.0% 62.0% 64.1% 66.2% Average duration selling sex in group 1 (years) STI prevalence among female 27.9% 27.9% 27.9% 27.9% 27.9% 25.1% 22.2% 19.4% 16.5% sex worker group 1 Female Sex Workers group 2 (FSW2) / population (in thousands) Number of clients per day female sex worker group 2 Days worked per week - female sex workers group 2 Percent condom use with 50.4% 51.6% 52.8% 54.0% 55.3% 56.5% 57.7% 58.9% 60.1% clients - FSW group 2 Average duration selling sex in group 2 (years) STI prevalence among female 18.8% 18.8% 18.8% 18.8% 18.8% 16.9% 15.0% 13.0% 11.1% sex worker group 2 Table A3.5: Clients of FSW Non-Papua Clients of Female Sex Workers / population 4,768 4,829 4,885 4,935 4,991 5,047 5,101 5,150 5,196 (in thousands) Percent of males aged % 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% 7.6% who visited FSW in the last year Average duration buying sex (years) Percent of adult males who 80% 80% 80% 80% 80% 80% 80% 80% 80% are circumcised ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

78 Table A3.6: Clients of FSW Papua Clients of Female Sex Workers / population (in thousands) Percent of males aged who visited FSW in the last 9.0% 9.0% 9.0% 8.3% 7.6% 6.9% 6.1% 5.4% 4.7% year Average duration buying sex (years) Percent of adult males who are 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% 16.7% circumcised Table A3.7: Population engaging in Casual Sex Non-Papua Percent of males engaging in 2.8% 2.8% 2.8% 4.8% 6.8% 6.8% 6.8% 6.8% 6.8% casual sex in the last year Percent of females engaging in 1.0% 1.0% 1.0% 1.5% 2.0% 2.0% 2.0% 2.0% 2.0% casual sex in the last year Percent condom use in 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% 18.2% casual sex Average number of sex contacts in the last year (male) Table A3.8: Population engaging in Casual Sex Papua Percent of males engaging in 30.0% 30.0% 30.0% 26.3% 22.5% 18.8% 15.0% 15.0% 15.0% casual sex in the last year Percent of females engaging in 10.0% 10.0% 10.0% 8.8% 7.5% 6.3% 5.0% 5.0% 5.0% casual sex in the last year Percent condom use in casual 12.6% 12.6% 12.6% 16.2% 19.8% 23.5% 27.1% 27.1% 27.1% sex Average number of sex contacts in the last year (male) Table A3.9: Spouses and Regular Partners Non-Papua Sex with spouses or regular partners (RP) Number of sexual contacts with spouse or RP (per week) Percent condom use with 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% 1.3% spouses or regular partners STI prevalence in adult 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% population 76 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

79 Table A3.10: Male PWID Injecting Behaviors Non-Papua Male IDU - Injecting Behaviors / population Percent of males age % 0.19% 0.16% 0.14% 0.11% 0.11% 0.09% 0.07% 0.05% who inject drugs Percent of male IDUs in 55.0% 55.0% 55.0% 55.0% 55.0% 55.0% 55.0% 55.0% 55.0% high-risk networks IDU mortality (crude mortality 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% per year in %) Percent of male IDUs who 50.6% 48.7% 46.8% 44.4% 42.0% 37.2% 32.4% 27.7% 22.9% share needles Percent of all injections shared 70.0% 70.0% 70.0% 70.0% 72.0% 72.0% 72.0% 72.0% 72.0% (among those who share) Number of injections per day Average duration of injecting behavior (in years) Sharing to non-sharing 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% movement per year Table A3.11: Male PWID Sexual Behaviors Non-Papua Male Injecting Drug Users Sexual Behaviors Percent of male IDUs visiting 40.9% 36.7% 32.5% 28.3% 24.2% 22.0% 19.8% 17.7% 15.5% female sex workers Percent condom use with 53.7% 54.2% 54.7% 55.3% 55.8% 56.3% 56.8% 57.4% 57.9% female sex worker group 1 Percent condom use with 42.9% 43.4% 43.8% 44.2% 44.6% 45.1% 45.5% 45.9% 46.3% female sex worker group 2 Percent condom use with 14.0% 21.1% 28.2% 35.3% 42.4% 42.4% 42.4% 42.4% 42.4% spouse or regular partner Number of contacts with regular partners (per week) Table A3.12: Men who have Sex with Men General Non-Papua Men who have Sex with Men General Percent of males aged engaging in same-sex behavior 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% 1.1% Percent of MSM in risk group % 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% 27.7% Shift from MSM group 1 to group % 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

80 Table A3.13: Men who have Sex with Men Group 1 & 2 Non-Papua Men who have Sex with Men group 1 (MSM1) / population Percent engaging in anal sex 73.4% 73.2% 73.0% 72.9% 72.7% 72.7% 72.7% 72.7% 72.7% in the last year - MSM1 Number of anal sex contacts last week (among those having anal sex) - MSM1 Average duration of same-sex behavior (years) - MSM1 Percent of MSM1 with female 50.0% 50.0% 50.0% 45.1% 40.2% 39.1% 38.0% 33.2% 28.5% partners Percent condom use in anal 44.0% 45.9% 47.9% 49.8% 51.7% 53.7% 55.6% 57.6% 59.5% sex with MSM1 STI prevalence among MSM1 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% 18.3% Men who have Sex with Men group 2 (MSM2) / population Percent engaging in anal sex 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% 72.7% in the last year - MSM2 Number of anal sex contacts last week (among those having anal sex) - MSM2 Average duration of same-sex behavior (years) - MSM2 Percent of MSM2 with female 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% 33.2% partners Percent condom use in anal 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% 60.0% sex with MSM2 STI prevalence among MSM2 6.1% 6.1% 6.1% 6.1% 6.1% 6.1% 6.1% 6.1% 6.1% Table A3.14: Men who have Sex with Men visiting Sex Workers Non-Papua MSM visiting (male and female) sex workers Percent of MSM1 visiting male 19.8% 19.5% 19.2% 18.8% 18.5% 18.5% 18.5% 18.5% 18.5% sex workers Percent of MSM2 visiting male 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% 6.2% sex workers Ratio of frequency of visiting MSW (group 2 / group 1) Percent of MSM1 visiting 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% female sex workers Percent of MSM2 visiting 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% 10.2% female sex workers Percent condom use in anal 53.0% 53.5% 54.0% 57.8% 61.7% 61.7% 61.7% 61.7% 61.7% sex with male sex workers Percent condom use with Female 53.7% 54.2% 54.7% 55.3% 55.8% 56.3% 56.8% 57.4% 57.9% sex worker group 1 (FSW1) Percent condom use with Female 42.9% 43.4% 43.8% 44.2% 44.6% 45.1% 45.5% 45.9% 46.3% sex worker group 2 (FSW2) 78 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

81 Table A3.15: Male Sex Workers Non-Papua Male Sex Workers Percent of males aged % 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% 0.03% who sell sex Average duration selling sex (in years) Shift from MSM1 to MSW 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% Shift from MSM2 to MSW 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Percent of MSW reporting anal 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% 82.0% sex with clients in the last year Number of anal sex contacts last week (for MSW with anal sex) STI prevalence among male 13.4% 15.2% 17.1% 20.5% 24.0% 24.4% 24.8% 25.6% 26.5% sex workers Percent MSW visiting female 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% 23.2% sex workers in the last year Percent MSW with female 72.5% 68.9% 65.2% 56.9% 48.6% 44.4% 40.2% 40.7% 41.2% regular partners in the last year Table A3.16: Transgenders General Non-Papua Transgender population General Percent of males aged % 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% who are transgender Percent of Transgenders who sell sex 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% 75.9% Percent of Transgenders who 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% engage in casual sex but not sex work Percent of Transgenders who 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% 14.1% have regular partners only ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

82 Table A3.17: Transgenders Sexual Behaviors Non-Papua Transgender Sex Workers Sexual Behaviors Percent of transgender sex workers engaging in anal sex 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% with clients Number of anal sex contacts last week with clients (for those having anal sex) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% with clients which are receptive Average duration selling sex (in years) Percent condom use in anal 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% 75.0% sex with clients Anal STIs (%) among 26.8% 26.8% 26.8% 26.8% 26.8% 23.4% 20.1% 17.0% 13.9% transgenders who sell sex Table A3.18: Transgenders - Client Make-up Non-Papua Transgender Sex Workers Client Make-up Percent of TG clients who are 81.0% 81.5% 82.0% 82.5% 82.5% 82.5% 82.5% 82.5% 82.5% low-risk heterosexual males Percent of TG clients who are also clients of female sex 7.0% 8.0% 9.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% workers Percent of TG clients who are 7.0% 5.5% 4.0% 2.5% 2.5% 2.5% 2.5% 2.5% 2.5% MSM Percent of TG clients who are 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% male IDU Table A3.19: Transgenders engaging in Casual Sex - Sexual Behaviors Non-Papua Transgenders engaging in Casual Sex - Sexual Behaviors Percent of TGs with casual sex partners who engage in anal sex 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% Number of anal sex contacts last week (for TGs having anal sex with CPs) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% which are receptive Percent condom use in anal sex 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% 56.3% for those with casual partners Anal STIs (%) among transgenders 8.92% 8.92% 8.92% 8.92% 8.92% 7.80% 6.69% 5.66% 4.63% who have casual partners Percent of annual shift from TGs engaging in casual sex to 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% TGs with RP only 80 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

83 Table A3.20: Transgenders Sex Workers Partner Make-up for those with CPs Non-Papua Transgender Sex Workers - Partner Make-up for those with CPs Percent of anal sex partners who are low-risk heterosexual 81.0% 81.5% 82.0% 82.5% 82.5% 82.5% 82.5% 82.5% 82.5% males Percent of anal sex partners who are also clients of female 7.0% 8.0% 9.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% sex workers Percent of anal sex partners 7.0% 5.5% 4.0% 2.5% 2.5% 2.5% 2.5% 2.5% 2.5% who are MSM Percent of anal sex partners 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% who are male IDU Table A3.21: Transgenders with Regular Partners - Sexual Behaviors Non-Papua Transgenders with Regular Partners (RP) - Sexual Behaviors Percent of TGs with regular partners who engage in anal 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% sex Number of anal sex contacts with RPs last week (for TGs having anal sex with RPs) Percent of anal sex contacts 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% 90.0% with RPs which are receptive Percent condom use in anal 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% 18.8% sex with regular partners Anal STIs (%) among transgenders who have regular 4.46% 4.46% 4.46% 4.46% 4.46% 3.90% 3.35% 2.83% 2.31% partners only Table A3.22: Transgenders Sex Workers Regular Partner Make-up Non-Papua Transgender Sex Workers Regular Partner Make-up Percent of anal sex partners who 81.0% 81.5% 82.0% 82.5% 82.5% 82.5% 82.5% 82.5% 82.5% are low-risk heterosexual males Percent of anal sex partners who are also clients of female 7.0% 8.0% 9.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% sex workers Percent of anal sex partners 7.0% 5.5% 4.0% 2.5% 2.5% 2.5% 2.5% 2.5% 2.5% who are MSM Percent of anal sex partners 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% who are male IDU ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

84 ANNEX 4 Estimation and Projection of People Living with HIV, New HIV Infections, AIDS Deaths and ART Needs among Adults and Children by Gender in Indonesia, PLHIV New HIV Infections AIDS Deaths ART Needs Male 407, , , , , ,683 Female 223, , , , , ,667 Total 630, , , , , ,349 Male 32,098 31,024 31,295 31,402 31,446 31,437 Female 21,361 20,116 19,274 18,474 17,752 17,091 Total 53,460 51,141 50,569 49,876 49,197 48,529 Male 27,089 27,379 28,928 30,111 30,989 31,550 Female 12,223 12,779 13,992 14,979 15,839 16,532 Total 39,313 40,158 42,921 45,090 46,828 48,083 Male 232, , , , , ,266 Female 89,159 95, , , , ,974 Children 12,869 13,359 13,653 13,723 13,615 13,374 Total 334, , , , , , ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

85 ANNEX 5 Estimation and Projection of People Living with HIV, New HIV Infections, AIDS Deaths and ART Needs among Adults age 15 years old by Gender in Indonesia, PLHIV New HIV Infections AIDS Deaths ART Needs Male 398, , , , , ,990 Female 214, , , , , ,534 Total 613, , , , , ,524 Male 29,917 28,856 29,139 29,279 29,372 29,428 Female 19,282 18,049 17,218 16,450 15,775 15,176 Total 49,199 46,905 46,357 45,729 45,147 44,604 Male 25,876 26,143 27,674 28,831 29,698 30,261 Female 11,059 11,594 12,793 13,755 14,604 15,298 Total 36,936 37,737 40,468 42,586 44,302 45,560 Male 232, , , , , ,266 Female 89,159 95, , , , ,974 Total 321, , , , , ,240 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

86 ANNEX 6 Estimation and Projection of People Living with HIV, New HIV infections, AIDS Deaths and ART Needs among Children age 0-14 years old by Gender in Indonesia, PLHIV New HIV Infections AIDS Deaths ART Needs Male 8,588 9,169 9,697 10,129 10,463 10,693 Female 8,123 8,672 9,174 9,589 9,910 10,133 Total 16,712 17,841 18,871 19,718 20,373 20,825 Male 2,181 2,168 2,156 2,123 2,074 2,009 Female 2,079 2,067 2,056 2,024 1,977 1,915 Total 4,261 4,236 4,212 4,147 4,050 3,925 Male 1,213 1,236 1,254 1,280 1,291 1,289 Female 1,164 1,185 1,199 1,224 1,235 1,234 Total 2,377 2,421 2,453 2,504 2,526 2,523 Male Female Total 12,869 13,359 13,653 13,723 13,615 13, ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

87 ANNEX 7 Estimation and Projection of People Living with HIV, New HIV infections, AIDS Deaths and ART Needs among Adults age 15 years old in Papua and Non-Papua, PLHIV New HIV Infections AIDS Deaths ART Needs Papua 60,530 60,131 59,257 57,988 56,427 54,652 Non-Papua 552, , , , , ,871 Total 613, , , , , ,524 Papua 3,478 3,154 2,964 2,794 2,641 2,503 Non-Papua 45,721 43,751 43,393 42,935 42,506 42,101 Total 49,199 46,905 46,357 45,729 45,147 44,604 Papua 3,404 3,553 3,838 4,063 4,202 4,277 Non-Papua 33,532 34,184 36,629 38,523 40,100 41,282 Total 36,936 37,737 40,468 42,586 44,302 45,560 Papua 25,042 26,178 26,852 27,123 27,069 26,754 Non-Papua 296, , , , , ,485 Total 321, , , , , ,240 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

88 ANNEX 8 New HIV Infections among Adults Age Group 15 years old by Risk Population in 32 Provinces (Non-Papua), years Pemodelan Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun Pemodelan Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun 86 ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

89 ANNEX 9 New HIV Infections among Adults Age Group 15 years old by Risk Population in Tanah Papua years Modelling Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun Modelling Pelanggan PPS LSL TG WPS Non-PK Laki-laki Non-PK Perempuan Penasun ESTIMATES AND PROJECTION OF HIV/AIDS IN INDONESIA

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