NATIONAL ESTIMATES OF HIV INFECTIONS. August National Centre for AIDS and STD Control Teku, Kathmandu

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1 NATIONAL ESTIMATES OF HIV INFECTIONS 2009 NEPAL August 2010 National Centre for AIDS and STD Control Teku, Kathmandu

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3 NATIONAL ESTIMATES OF HIV INFECTIONS 2009 NEPAL August 2010 National Centre for AIDS and STD Control Teku, Kathmandu

4 National Centre for AIDS and STD Control (NCASC), 2010 ISBN : All rights reserved. The document may, however, reviewed, quoted, or translated in part or full provided the source (NCASC) is fully acknowledged. The document may not be sold or used for any kinds of commercial purposes without prior written approval from the National Centre for AIDS and STD Control (NCASC). NCASC does not warrant that the information contained in this publication is complete and correct, and shall not be liable for any damages incurred as a result of its use.

5 Foreword Estimation of HIV prevalence in the country has been carried out every two years since 2003 by the National Centre for AIDS and STD Control, Ministry of Health and Population as a mark to show the importance accorded to understanding and monitoring the progression of HIV and AIDS in the country and tracking the national response to the epidemic. From 2008 onwards, Nepal was able to meet the minimum data requirements to use Estimation and Projection Package (EPP) in a concentrated epidemic setting at national level. This includes availability of good quality HIV surveillance data, with at least three points, from at least three consistent sites amongst the populations that are at increased risk to HIV, and also have at least one data point from ANC attendees. As a result, in 2009, for the first time, the EPP software was used to generate national HIV estimates against the Workbook model used in the previous three rounds of estimates. Using a combination of EPP and Spectrum provided us not only with estimates of the current burden of HIV infections (for example, adult HIV prevalence) in the country, but also future projections that allows us to better design HIV prevention programmes and treatment, care and support interventions for people infected with and affected by HIV. One of the key outputs of this modelling is to identify key programme needs like ART needs, mothers requiring PMTCT services, etc, which guide evidence-informed planning, programming and resource allocation for interventions. As with the previous exercises, the 2009 estimation process involved a number of consultative meetings and workshops with a large group of experts and stakeholders to ensure optimum understanding of the data and generation of reliable and accurate estimates. I am pleased to present and share this report, which I know, without a doubt, will prove to be a very important reference document to inform HIV polices, planning, programming and reviews. Lastly, I would like to express my gratitude to all the people involved in the 2009 estimates process and preparation of this report, namely Deepak Kumar Karki, Laxmi Bilas Acharya and Alankar Malviya. The technical support provided by UNAIDS, WHO and FHI is highly appreciated and gratefully acknowledged. Kathmandu, August 2010 Dr. Krishna Kumar Rai Director National Centre for AIDS and STD Control

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7 National Estimates of HIV Infections Nepal 2009 Acknowledgments National Centre for AIDS and STD Control (NCASC) would like to express its deep gratitude and acknowledgement to UNAIDS Secretariat, World Health Organization and Family Health International for the technical support they provided throughout this lengthy and extended HIV infection estimation process. A special thanks goes to UNAIDS Secretariat for their support in the estimation process and printing of this report. NCASC thanks to the Central Bureau of Statistics (CBS), USAID/Nepal, Nepal Red Cross Society, Estimation Technical Team (ETT): Mr. Deepak Kumar Karki, Surveillance Officer, NCASC Dr. Laxmi Bilas Acharya, Strategic Information Advisor, ASHA Project/ FHI Mr. Alankar Malviya, Monitoring & Evaluation Advisor, UNAIDS Dr. Min Thwe, Medical Officer (HIV/ AIDS), WHO Estimation Advisory Group (EAG): Dr. Krishna Kumar Rai, Director, NCASC Mr. Dilli Raman Adhikari, Senior Public Health Officer, NCASC Ms. Sujeeta Bajracharya, M&E Officer, NCASC Mr. Dhurba Raj Ghimire Statistical Officer, HMIS Section, DoHS Mr. Nabin Shrestha, Statistics Officer, Central Bureau of Statistics Dr. Anna McCauley, Senior Public Health Advisor, USAID/Nepal Ms. Salina Tamang, Programme Manager, Blue Diamond Society Dr. Amod Poudyal, Associate Professor/Bio-Statistician, Department of Community Medicine and Family Health, Institute of Medicine ART and PMTCT sites and other nongovernmental organisations for their collaborative effort and invaluable participation in deriving comprehensive, quality data to generate HIV estimates. NCASC strongly believes that the outputs of this exercise will assist the country in making data-driven and evidence-informed decisions and ultimately strengthen the national response to HIV and AIDS. NCASC acknowledges the contribution of the following: Dr. Lochana Shrestha, Senior HIV/ AIDS Co-ordinator (Technical), Save the Children Dr. Pulkit Choudhary, Programme Manager, Family Planning Association of Nepal Mr. Rajeev Kafle, President, National Association of People Living with HIV/AIDS in Nepal Mr. Anan Pun, President, Recovering Nepal Dr. Atul Dahal, National Professional Officer (HIV/AIDS), WHO Documentation and Write-up: Mr. Deepak Kumar Karki, Surveillance Officer, NCASC Ms. Sujeeta Bajracharya, M&E Officer, NCASC Mr. Alankar Malviya, M&E Advisor, UNAIDS Ms. Shriya Pant, Consultant, UNAIDS Data Support by: Ms. Bhim Kumari Pariyar, M&E Assistant, NCASC Mr. Dharmendra Lekhak, Data Manager, NCASC Mr. Keshab Deuba, Consultant, WHO Ms. Bobby Rawal Basnet, Data Officer, UNAIDS v

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9 National Estimates of HIV Infections Nepal 2009 Abbreviations and Acronyms AIDS ANC ART ARV BDS CBS DoHS ETT EAG EPP FHI FPAN FSW HIV HSCB IBBS IDU MARP MoHP MMR MSM MSW MTCT NAP+N NCASC PLHIV PMTCT SCUS SI-TWG STI TB TFR UNAIDS USAID WHO Acquired Immune Deficiency Syndrome Antenatal Care Anti-Retroviral Therapy Anti-Retroviral Blue Diamond Society Central Bureau of Statistics Department of Health Services Estimation Technical Team Estimation Advisory Group Estimation and Projection Package Family Health International Family Planning Association of Nepal Female Sex Worker Human Immunodeficiency Virus HIV/AIDS and STI Control Board Integrated Biological and Behavioural Surveillance Injecting Drug User Most-At-Risk Population Ministry of Health and Population Maternal Mortality Ratio Men who have Sex with Men Male Sex Worker Mother-to-Child Transmission of HIV National Association of People Living with HIV/AIDS in Nepal National Centre for AIDS and STD Control People Living with HIV Prevention of Mother-to-Child Transmission of HIV Save the Children USA Strategic Information-Technical Working Group Sexually Transmitted Infections Tuberculosis Total Fertility Rate Joint United Nations Programme on HIV and AIDS United States Agency for International Development World Health Organisation vii

10 National Estimates of HIV Infections Nepal 2009 Table of Contents Foreword Acknowledgments Abbreviations and Acronyms Table of Contents Executive Summary iii v vii viii xi Chapter 1: Introduction Background of HIV Infections Estimates HIV Infections Estimation in Nepal 1 Chapter 2: HIV Epidemic in Nepal 3 Chapter 3: Methods and Process of Estimation Methodological Steps in Estimating HIV Infections and Measuring Impact Data Sources Projection, Curve Fitting and Exporting to Spectrum Limitations 13 Chapter 4: Data Input for EPP Populations at Risk, Population Size and HIV Prevalence ART Programme Data 22 Chapter 5: National HIV Infections Estimates EPP Results Trend in Adult (15-49) HIV Prevalence and Incidence Spectrum Results Generating Impact Data for National Planning Uncertainty Analysis 28 Chapter 6: Conclusion and Recommendations 29 References 33 ANNEX 1: Work Flow of the HIV Infections Estimates Process 37 ANNEX 2: Source of Population Size Estimates, ANNEX 3: Uncertainty Analysis 38 ANNEX 4: Summary of 2007 Estimates 40 viii

11 National Estimates of HIV Infections Nepal 2009 List of figures Figure 1: Four HIV Epidemic Zones of Nepal ( ) 4 Figure 2: Second Generation Surveillance and M&E 7 Figure 3: Estimation Process, Figure 4: Generating EPP Curve 11 Figure 5: Distribution of Estimated HIV Infections by Population Groups (15+ years), Figure 6: Distribution of Estimated HIV Infections by Population Groups (15+ years): Figure 7: Number of Estimated HIV Infections Vs. Estimated HIV Prevalence, Figure 8: Incidence Distribution by Population Groups (15+ years): Figure 9: Adult (15-49) HIV Prevalence, Figure 10: Adult (15-49) HIV Incidence, Figure 11: Adult (15-49) HIV Prevalence, 2009 (Plasusibility Bounds of 5% & 95% Intervals) 28 List of tables Table 1: HIV Epidemic Zones for Infections Estimation, District Names and High Risk Groups (2003, 2005 and 2007; and Suggestive of 2009) 5 Table 2: Risk Groups and Level of HIV Prevalence for HIV Infections in Nepal 5 Table 3: Risk Characteristics and At Risk Turnover Assigned Among Population Groups 11 Table 4: EPP Input Data Sources 12 Table 5: Spectrum Input Data Sources 12 Table 6: FSWs Related Input Data for EPP 16 Table 7: IDUs Related Input Data for EPP 17 Table 8: MSM Related Input Data for EPP 18 Table 9: Clients of FSW Related Input Data for EPP 19 Table 10: Migrants Related Input Data for EPP 20 Table 11: Remaining Females Related Input Data for EPP 21 Table 12: Remaining Males Related Input Data for EPP 22 Table 13: Number of Adults on ART: Input Data for EPP 22 Table 14: HIV Infections Estimates 2009 by Age Groups and Sex 23 Table 15: HIV Infections Estimates 2009 by Population Groups 24 Table 16: Selected Major Indicators of HIV Infections Estimation, Table 17: Impact Results from Spectrum, ix

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13 National Estimates of HIV Infections Nepal 2009 Executive Summary Since 2003, National Centre for AIDS and STD Control has been producing reports on National Estimate of HIV in Nepal. The estimate has been revised at every twoyear interval, as in the global practice. The report include key information such as total numbers of people living with HIV in the country, number of new infections occurred in the given year, and number of deaths due to AIDS in the given year. These estimates are especially useful to understand the HIV and AIDS epidemic and to monitor the response, inform policy making, planning, and resource mobilization and is an excellent tool for evidence informed advocacy. As per the recommendations from WHO and UNAIDS, the Workbook model of estimation method was being used in 2003, 2005, and 2007 estimation processes. The recommendation to use Workbook model was made due to the fact that Nepal s HIV epidemic has been classified as concentrated epidemic. The workbook method requires minimal data inputs so as to generate HIV point prevalence figure for the given year. But, in 2009, due to the availability of more information with improved quality, Estimation and Projection Package (EPP) software has been used in the estimation process. EPP not only produces more robust results, but also describe the evolution of adult HIV prevalence over the time. In addition data out puts of EPP can be directly incorporated into more advanced software known as Spectrum. This can further generate projections on Anti-Retroviral (ARV) and Prevention of Mother-To-Child Transmission (PMTCT) of HIV needs, HIV incidence, and AIDS deaths that could happen in future. Although, inputs used in EPP software were mostly of country specific parameters, some were based on the assumptions using global proxies since the necessary information is not available in the country. This may have hindered the accuracy of results. Another limitation might be due to the use of behavioural change parameters as uncertainty analysis option of EPP is not available for use in concentrated epidemic scenario. Other limitations that might have affected the accuracy of 2009 estimates include the use of size estimates data for Most-At- Risk Populations (MARPs) that generated from limited studies, inadequate of HIV prevalence data among general population, lack of disaggregated data at the sub national level, methodological inconsistencies in Integreted Biological and Behavioural Surviellance (IBBS) studies and non existence of sentinel surveillance amongst Antenatal Care (ANC) attendees, Sexually Transmitted Infection (STI) patients, amongst others. Key Findings EPP estimated that adult (15-49) prevalence of Nepal at December 2009 was 0.39%, amounting for a total of 63,528 people living with HIV in the country. This includes 3,544 children within 0-14 years and 59,984 individuals with age 15 years and above. Women accounted for 28.6% of total infected population. Also, 7,481 individuals of age 50 years and above living with HIV. The proportionate distribution of population groups amongst total 59,984 estimated HIV infections of age xi

14 National Estimates of HIV Infections Nepal years and above was as follows: migrants (29.4%); Men who have Sex with Men (6.2%); clients of Female Sex Workers (5.0%); Injecting Drug Users (4.2%); and FSWs (1.0%). Remaining male and female populations, who were classified as low risk populations, accounted for 26.2% and 28.0%, respectively (Figure 5). Female partners and spouses of MARPs and migrants were included in the remaining female and male categories as they do not falls under any of the MARPs population group. Although migrants, in the numeric terms, took the largest single share in the total number of estimated HIV infections, IDUs was the population group that had highest (8.9%) estimated HIV prevalence for 2009 followed by MSM (2.6%), FSWs (1.9%), migrants (1.2%), clients of FSWs (0.4%), remaining male (0.2%) and female populations (0.2%) (Figure 7). It is notable that migrants, remaining male and remaining female sub-population groups have contributed the majority in the total estimated number of HIV infection (prevalence pool). This is due to their disproportionately bigger population sizes, in contrast to that of the MARPs. However, the main drivers of the epidemics are, in fact, the MARPs including migrants and clients of sex workers due to their high level of HIV prevalence and behavioural factors that associated with and contributed to HIV transmission. The high prevalence rates among IDUs, MSM, migrants and clients of FSWs signify a clear need to expand the intervention programmes amongst these MARPs. At the same time, the apparent transfer of the HIV load to the remaining male and female populations also necessitates strengthening interventions targeting these vulnerable groups. The occurence of largest number of new HIV infections per year (incidence) was estimated to be 6,954 in After one decade, it was decreased by 31.6% to 4,760 in 2009 (Figure 8). As previously mentioned, Spectrum modelling was used to generate impact related results. It showed that approximately 17,000 people are in need of ART, where eligibility is at CD4 count of 200, which increases dramatically to 32,267 (in 2011) when eligibility changes to CD4 count of 350. Indeed, Nepal is due to follow the recommendation of eligibility change to 350, which will result in a 1.6 fold increase in the number of people in need of ART. This factor signals additional human and other resources required to allocate accordingly and the need to increase preparedness in terms of the delivery of institutional mechanisms for timely and adequate provision of ART. Spectrum also showed that the number of mothers requiring PMTCT prophylactic ART has been declining over the years since 2000 and currently stands at 1,228 (2009). On the other hand, the cumulative number of children living with HIV has increased, clearly indicating the importance of increasing access to PMTCT services that are linked with maternal and child health, reproductive health and family planning services, as HIV amongst children in Nepal is transmitted primarily from mother to child. xii

15 1 Introduction 1.1 Background of HIV Infections Estimates WHO and UNAIDS regularly produce estimates at national, regional and global levels every alternate year to estimate the numbers of people living with HIV, people who have been newly infected and who have died of AIDS, based on sources of available pertinent data. These include sentinel surveillance among key populations at higher risk of HIV infections, surveys of pregnant women attending antenatal clinics, population based surveys (conducted at the household level), as well as other surveillance information. Country level estimates are published every alternate year in the form of epidemiological updates which contribute to the finalisation of regional and global estimates. The generation of these estimates are the result of exhaustive, multi-stakeholder consultative processes. More importantly, they are tremendously useful to understand the HIV and AIDS epidemic and monitor the response, inform policy making, planning, and resource mobilisation. It is an excellent tool for evidence-informed advocacy. For countries with concentrated epidemic like Nepal, estimates are based on studies conducted among key populations at high risk of exposure to HIV, including injecting drug users (IDUs), female sex workers (FSWs), men who have sex with men (MSM), clients of FSWs and high risk migrants abroad who are potential clients of FSWs at the place of destination. Moreover, data from other secondary sources and ongoing programmes that provide services are also used in the estimation and projection of HIV infections. 1.2 HIV Infections Estimation in Nepal To ensure that Nepal effectively and appropriately responds to the epidemic and to ensure evidence informed planning and implementation of HIV and AIDS response programmes, it is crucial to understand the burden of the epidemic. As such, since 2003, the National Centre for AIDS and STD Control (NCASC) has taken the lead in producing estimates of the number of people living with HIV in Nepal every alternate year in line with the publication of global epidemiological update by UNAIDS and WHO. Prior to 2003, UNAIDS and WHO produced country estimates through indirect methods for regional and country specific planning purposes. Tracking the HIV prevalence in the country not only allows for appropriate evaluation of the national response to the epidemic, but also helps project targets for future interventions such as the number of adults and children in need of anti-retroviral (ARV), mothers that require prevention of mother-to-child transmission (PMTCT) services, resource mobilisation and advocacy. 1

16 National Estimates of HIV Infections Nepal 2009 The 2009 HIV infections estimates report provides an in-depth description and analysis of issues such as the characteristic of the epidemic in the country, who and how many people are getting infected, how these numbers will help forecast targets for future interventions and finally, what the possible policy implications are. Estimates of HIV prevalence amongst adults (age 15-49) have been used as the indicator to monitor the impact of interventions carried out to date in the country. These estimates use a range of relevant data sources, including: sentinel surveillance amongst MARPs; surveys of pregnant women attending ante-natal care clinics; populationbased surveys; routine case reports; and official birth and death records. In other words, they are classified as either (1) population data (such as Nepal National Census and Population Projections and Demographic Health Surveys) or (2) HIV prevalence data (such as Integrated Bio- Behavioural Surveillance surveys). Workbook Model to Estimation and Projection Package As per UNAIDS recommendations, countries with low-level/concentrated epidemics were advised to use the Workbook model until 2006 to generate HIV infections estimates, which Nepal has followed for all three previous rounds of estimations. In 2006, EPP, a software tool already in use for generalised epidemics, was also suggested for concentrated epidemics, provided adequate data availability. However, in 2007, due to insufficient data points, Nepal reverted to the Workbook model. Increases in the availability, quality and robustness of data over the past several years meant that in 2009, the country s infections estimation were derived using EPP. Nepal also used EPP to contribute to the global estimates of 2008 (epidemiological update 2009). Advantage of Estimation and Projection Package The previously used Workbook model utilises comparatively limited data sets and produces point prevalence, which only generates prevalence for a given year. In contrast, because EPP uses expanded sets of data points, including the use of repeated rounds of population-based surveys such as integrated bio-behavioural surveillance (IBBS), improved programme data and better methods of analysis, Nepal s 2009 estimates are more robust than previous estimations. Moreover, EPP not only describes the evolution of adult HIV prevalence over time, but also provides the input for Spectrum which makes projections for the future with regards to treatment needs, HIV incidence, AIDS deaths, etc. Estimation Process 2009 The infection estimates process was lengthy and consisted of numerous consultations and workshops. A fourmember Estimation Technical Team (ETT) was created to carry out the technical tasks of computing the estimates using computer models such as EPP and Spectrum. ETT in turn, was responsible for continually sharing their findings with the Estimation Advisory Group (EAG) comprising of individuals from NCASC and other agencies. For detailed information on the estimation process, please refer to Annex 1. Since the previous rounds of estimates were produced using regional/sub-national data sets by means of the Workbook model and because the use of EPP for this year s estimates did not allow for comparability, regional workbooks (using Workbook model) were used to validate or triangulate the findings of this EPP exercise to enhance our confidence in this year s estimates. 2

17 HIV Epidemic in Nepal 12 HIV Epidemic in Nepal The first AIDS case in Nepal was reported in Since then, the HIV epidemic in the country has gradually evolved from a low-prevalence to concentrated epidemic. As of 2009, national estimates indicate that approximately 63,528 adults and children are infected with HIV, with an estimated overall prevalence of 0.39% in the adult population (15-49 years). The estimates depict an apparently mixed epidemic scenario with the relatively low risk male and female population representing almost 54% of the burden of HIV infections, while the major drivers of the epidemic remain IDUs, MSM, FSWs and clients of FSWs. Migrants alone accounted for about 30% of HIV infections, while 16% of HIV infections were estimated amongst the high risk groups such as IDUs, MSM, FSWs and their clients. Since 1988 till August 2010, a total of 16,262 HIV cases were reported to NCASC. This cumulative number means 16,262 HIV positive cases have been reported to NCASC thus far. About 31% of the reported HIV cases comprised of women aged years. Young people (15-24 years) accounted for about 17% of the total reported HIV infections whereas more than three-fourth of total reported cases were from the age groups. Children (0-14) represented 6.5% of the reported infections. Three high risk groups (IDUs: 16%; FSWs: 5% and MSM: 1%) share 22% of total reported infections, whereas clients of FSWs and housewives account for 44% and 26% of the cases respectively. As in other countries in the region, IDUs, MSM, FSWs and their clients belong to the most-at-risk population in Nepal. Moreover, labour migrants are also considered to be at higher risk of HIV as a significant proportion of this population have unprotected sex with multiple partners when they are abroad. Data from the 2008 IBBS survey estimated that 1.1% of the labour migrants to India from 11 western and mid to far western districts of Nepal were infected with HIV. Although HIV prevalence amongst the labour migrants to India dropped slightly from 1.9% in 2006 (FHI/New ERA/SACTS, 2006d) to 1.1% in 2008 (NCASC/FHI/New ERA/ SACTS 2008c), this sub population bears the largest burden of HIV infections. This is primarily because of the large number of labour migrants estimated in the country. Estimates of HIV prevalence amongst FSWs ranged from 2.2% to 3% across various regions in the country (FHI/ ACNielsen/SACTS, 2009a). About 3.8% of MSM are infected with HIV in Kathmandu, whereas the infection load among male sex workers (MSW) 3

18 N ationa l E stimates o f H I V I nfections N epa l is 5.2% (FHI/New ERA/SACTS, 2009e). Vulnerability to HIV is also high amongst young people aged as 72% of females and 56% of males have yet to acquire comprehensive HIV knowledge (HSCB/NCASC 2010). The 2008 IBBS study amongst Nepali migrants travelling to Indian cities for work found that approximately 16% of men engaged in high risk sexual behaviours while in India and frequently visited sex workers (NCASC/FHI/New ERA/SACTS 2008c). Amongst the most-at-risk populations, MSWs are the sub-group that show the highest rates (65%) of individuals testing for HIV and who know the results. Conversely, it was found that utilisation of voluntary counselling and testing of HIV amongst other MARPs was relatively low, with the lowest amongst migrants, with 13.8% (HSCB/NCASC, 2010). Epidemic Zones and Risk Groups Since 2003, Nepal has been divided into four epidemic zones based on different epidemic characteristics Figure 1: Four HIV Epidemic Zones of Nepal ( ) Kathmandu valley Highway districts Far western hills Remaining hills 4 such as distribution of most-at-risk populations, mobility links, and exposure to potentially risk-prone environment for HIV infections particular to those regions (Figure 1 and Table 1). During the 2005 and 2007 national estimation of HIV infections exercises, the need to redefine the epidemic zones was articulated to more accurately describe the epidemics. Updating the size of high risk population groups and its distribution across the country was a felt need as the first step for revisiting the definition of epidemic zones. Mapping exercises leading to the size estimation of the risk groups by district have already begun, which would help to revisit the definition of HIV epidemic zones in Nepal by early This will ensure increased robustness with regards to local planning of the AIDS response. HIV surveillance in Nepal: Role of Second Generation Surveillance and M&E in HIV Estimation and Projection Nepal has adopted the second generation surveillance system (SGS) to collect, compile and analyse strategic information needed for understanding to the HIV

19 HIV Epidemic in Nepal Table 1: HIV Epidemic Zones for Infections Estimation, District Names and High Risk Groups (2003, 2005 and 2007; and Suggestive of 2009) Epidemic Regions Number, Location and Name of Districts High Risk Groups Leading to the Epidemic 1. Kathmandu Valley 2. Highway Districts 3. Far-Western Hill Districts 4. Remaining Hill Districts 3 districts in the Kathmandu valley (Kathmandu, Lalitpur, Bhaktapur) 26 districts along Mahendra, Prithvi and Pokhara-Butwal highway (Jhapa, Morang, Sunsari, Saptari, Siraha, Dhanusha, Mahottari,Sarlahi, Rautahat, Bara, Parsa, Chitwan, Dhading, Makawanpur,Syanja, Kaski, Palpa, Rupendehi, Kapilbastu, Dang, Banke, Bardiya,Kailali, Kanchanpur, Tanahu, Nawalparasi) 7 hill districts of the Far-western development region (Bajura, Bajhang, Accham, Doti, Dadeldhura, Baitadi, Darchula) 39 districts (Taplejung, Panchthar, Ilam, Dhankuta, Tehrathum, Sankhuwasabha, Bhojpur, Solukhumbu, Okhaldunga, Khotang, Udayapur, Sindhuli, Ramechhap, Dolkha, Sindhupalchowk, Kavrepalanchok, Nuwakot, Rasuwa, Gorkha, Lamjung, Manang, Mustang, Myagdi, Parbat, Baglung, Gulmi, Arghakhanchi, Puthan, Rolpa, Rukum, Salyan, Surkhet, Dailekh, Jajarkot, Dolpa, Jumla, Kalikot, Mugu, Humla) IDUs, FSWs and MSM/TG FSWs, clients of FSW and IDUs. Anecdotal existence of migrants and MSM/TG are also present in this region. Migrants, FSWs, clients of FSWs and MSM/TG Migrants, clients of FSWs This epidemic zone was also classified as a low HIV prevalence zone. The current risk group classification and their HIV prevalence, in 2009, are outlined in Table 2 below. Table 2: Risk Groups and Level of HIV Prevalence for HIV Infections in Nepal Population Groups Current Level of HIV Prevalence and Year Sources High Risk Groups IDUs FSWs MSM Truckers (potential clients of FSWs) Labour Migrants Wives of Migrants Tuberculosis Patients Returned Trafficked Girls and Women Low Risk Groups Remaining Males Remaining Females Kathmandu: 20.7% (2009) Pokhara: 3.4% (2009) Eastern Terai: 8.1% (2009) Western and Far-Western Terai: 8.0% (2009) Kathmandu: 2.2% (2008) Pokhara: 3.0% (2008) 22 Terai Highway Districts: 2.3% (2009) Kathmandu: 3.8% (2009) Terai Highway Districts: 0.0% (2009) Far-West: 0.8% (2008) West: 1.1% (2008) Far-West: 3.3% (2008) 2.4% (2007) 38.0% (2007) 0.09% (2009) 0.2% (2009) FHI/New ERA/SACTS, 2009a FHI/New ERA/SACTS, 2009b FHI/New ERA/SACTS, 2009c FHI/New ERA/SACTS, 2009d NCASC/FHI/New ERA/SACTS, 2008b NCASC/FHI/New ERA/SACTS, 2008a FHI/ACNielsen/SACTS/National Reference Laboratory, 2009a FHI/New ERA/SACTS, 2009e FHI/ACNielsen/SACTS, 2009b NCASC/FHI/New ERA/SACTS, 2008c NCASC/FHI/New ERA/SACTS, 2008d National TB Centre: Sentinel Surveillance Report, 2008 Silverman et al., 2007 Nepal Red Cross Society (NRCS): Blood Transfusion Service, 2009 NCASC: Programme Monitoring Data,

20 National Estimates of HIV Infections Nepal 2009 epidemic and designing, monitoring and evaluating the national response, as a key strategic element in strengthening the national strategic information system. The national strategy is to strengthen the SGS system depicted in Figure 2. NCASC is leading the HIV surveillance activities in Nepal and has formed a national HIV Strategic Information Technical Working Group (SI-TWG), a group of technical people in the field of HIV surveillance, programme, monitoring and evaluation and research. SI-TWG provides technical advice on SI issues. Specifically, SI- TWG s contribution is focused on planning, designing and monitoring HIV surveillance activities; and using and promoting surveillance, research and programme data to understand the epidemic and monitor the response. The key data sources used in the SGS of Nepal are (1) HIV and AIDS routine case reports, (2) HIV prevalence surveys, (3) STI surveillance, (4) behavioural surveillance among high-risk groups, (5) population size of high risk groups, (6) routine programme monitoring and evaluation data, and (7) data from other programmes (Tuberculosis (TB), PMTCT, blood donors) and researches. Nepal conducts IBBS surveys amongst key high risk groups (IDUs, FSWs, Clients of FSWs, MSM, and male labour migrants) at regular intervals. Amongst IDUs, MSM and labour migrants, IBBS studies are conducted every alternate year, while amongst FSWs and truckers in every three years period. These surveys are the sole data source for HIV prevalence and behavioural information on the risk groups for analyzing HIV epidemic in Nepal. Apart from surveillance data, routine programme monitoring data from voluntary counselling and testing of HIV (VCT), anti-retroviral therapy (ART), prevention of mother-to-child transmission (PMTCT) services and diagnosis and treatment of sexually transmitted infections are compiled and analysed. Sentinel surveillance activities are yet to be re-started in Nepal, except for the routine sentinel surveillance for HIV prevalence amongst new TB cases. In addition, HIV positivity amongst PMTCT clients and blood donors are being used as a proxy for estimating and projecting HIV prevalence amongst the remaining female and male population. In addition to the data sources mentioned above, the Nepal Demographic and Health Surveys (NDHS) is another source of knowledge and behavioural data amongst the general population in Nepal. Being a country with a concentrated epidemic and having estimated adult HIV prevalence at less than 0.5%, Nepal has thus far not included HIV testing in the NDHS. Data results from Spectrum modelling have also been used as a source of data for the SGS of Nepal. Size of the population at risk of HIV is one of the key strategic information demanded by the SGS. It is the basic information to assess the size and characteristics of the current and potential future HIV epidemic and its burden in the country. Moreover, estimating population size of the high risk groups is itself a complex exercise that demands triangulation of many techniques and data. It is, thus, a major strategic information in designing the national response setting targets and measuring coverage of interventions and formulate scale-up plan for the 6

21 HIV Epidemic in Nepal effective interventions. Nepal has no long history of conducting robust studies to estimate the size of mostat-risk-populations. At times studies in selected geographic areas and often infrequently are conducted, and no functional systematic plan is in place. For the first time, NCASC and HIV and STI Control Board (HSCB) are jointly leading the exercise on size estimation of MAPRs in all 75 districts of the country. This study has two parts: (i) mapping of the MARPs and (ii) size estimation based on information collected during the mapping. Figure 2: Second Generation Surveillance and M&E STI surveillance Behavioural surveillance HIV serosurveillance High risk population size estimation HIV and AIDS case reporting Data management Monitoring and evaluation Data analysis and synthesis HIV estimates and projections Use of data for action 7

22 8 National Estimates of HIV Infections Nepal 2009

23 Methods of Estimation and Process Followed 13 Methods and Process of Estimation 3.1 Methodological Steps in Estimating HIV Infections and Measuring Impact The first step was to ensure all basic data needed for the estimation was collected. Next, a combination of Estimation and Projection Package (EPP) and Spectrum was utilized to generate the 2009 estimates of HIV infections (Figure 3). EPP was used for estimating HIV prevalence and incidence while Spectrum was used to estimate HIV infections and generate AIDS impact figures. Figure 3: Estimation Process, 2009 Step 1: EPP Input Data: Population size and HIV prevalence data Routine programme data (ART coverage data and routine HIV case reports) Projected curves and selected the best fit curve Output: Results read and wrote to Spectrum (incidence and prevalence of HIV estimates by sex and population groups) Step 2: Spectrum Inputs: Demographic parameters (first year population, life expectancy, total fertility rate (TFR), age specific fertility rate, sex ratio, infant mortality rate, age and sex distribution of migrants) (for details please refer to chapter 4) HIV incidence (15-49) Proportion of survivals on ART HIV progression (ART eligibility for treatment at CD4 200, switching eligibility at CD4 350 by 2011; application of non- IDU driven epidemic pattern) MTCT (breast feeding, maternal mortality ratios, abortions, TFR reduction) Outputs: HIV infection estimates ART needs PMTCT needs Cotrimoxazole needs AIDS deaths AIDS Orphans 9

24 National Estimates of HIV Infections Nepal 2009 Estimation and Projection Package (EPP) 2009 is a computer software tool used to estimate and project adult HIV prevalence from available surveillance data. It was created to allow for the construction of epidemic curves, which is an essential step to estimating the levels and trends in the epidemic and its impact. This is carried out through the collection and subsequent entry of surveillance data and estimates of the size of high and low risk population groups into the EPP software (Figure 3). Source: KnowledgeCentre/HIVData/Epidemiology/EPI_ software2009.asp Spectrum Version 3.54 is a computer modelling system consisting of a number of modules for reproductive health areas. The Demographic Projection (DemProj) and AIDS Impact Model (AIM) modules are used specifically for HIV and AIDS. Prevalence projections generated by EPP are used as input data to calculate the impact of the epidemic. The DemProj projects the population for an entire country or region by age and sex, based on assumptions about fertility, mortality and migration. AIM is used for projecting the impact of the AIDS epidemic, including the number of people living with HIV, new infections, AIDS deaths by age and sex, number of adults in need of antiretroviral treatment and the number of AIDS orphans. Source: cfm?id=software&get=spectrum Spectrum Version 3.54 To optimally utilise EPP, it is important that certain conditions are met and they include the following: Clearly defined, key non-overlapping population groups in the epidemic and its geographic breakdown, if regional or provincial estimates are to be produced; Clearly defined population characteristics; Known HIV prevalence data and population size for each sub-group or regional sub-epidemic, including availability of good quality HIV surveillance data for at least 3 points from at least 3 consistent sites amongst the populations that are at increased risk to HIV, and at least 1 data point from ANC attendees. EPP Application in Nepal Applying the EPP model for concentrated epidemics like Nepal is a challenge. The required minimum points of pertinent data on HIV prevalence and population size for all risk groups from reliable sources is usually lacking. In this context, Nepal was considered one unit and only national-level estimates were produced. That means estimations were not disaggregated by epidemiological regions of Nepal as presented in the previous rounds of estimations (2003, 2005 and 2007). Similarly, no urban and rural breakdowns were made, but sub-population groups were assumed to be distributed into urban and rural areas across country. The average number of years after which a person at high risk stops a particular behaviour is known as turnover period (in years). Assigning a reasonable period of turnover among key population groups used in EPP is very critical. Despite ceasing their risky behaviour, it is important that this turnover period is measured, as that risk and their contribution to the transmission of HIV infections need to be assigned and applied onto the general population at low risk. The population sub-group characteristics and turnover that were defined and applied into EPP are detailed in Table 3. It should be noted that all sub-populations were assumed to be distributed amongst rural and urban settings. 10

25 Methods of Estimation and Process Followed Table 3: Risk Characteristics and At Risk Turnover Assigned Among Population Groups Population Groups Risk Characteristics At-Risk Turnover Assigned to IDUs MSM/TG FSWs Truckers as Clients of FSWs Labour Migrants Remaining Male Population Remaining Female Population High risk group High risk group High risk group High risk group Low risk group* Low risk group Low risk group 5-year turnover period. After turnover, HIV prevalence assigned to the remaining male population. No turnover, no assignment. 2.1-year turnover period. After turnover, HIV prevalence assigned to the remaining female population. 10-year turnover period. After turnover, HIV prevalence assigned to the remaining male population. 10-year turnover period. After turnover, HIV prevalence assigned to the remaining male population. Not applicable. Not applicable. Note: * Although current IBBS studies amongst migrants cover the migrant population at large, the studies specify that only a sub-section, not the entire migrant population, is in fact, at high risk of HIV. How EPP Works The following outlines EPP s model parameters (Figure 4): r controlling the rate of growth f0 the proportion of new risk population entrants t0 the start year of the epidemic φ behavioural change parameter An additional variable is added for concentrated epidemics: d average time (duration) in group Figure 4: Generating EPP Curve % H I V + t o r f o o d Source: NCASC 2010 After defining the geographic areas, specifying sub-populations, demographic parameters and entering relevant population size, HIV surveillance data and ART programme data, an epidemiological model is fitted. Then large numbers of curves were generated and the best fit curve was chosen. This curve, along with national population estimates and epidemiological assumptions is the input to Spectrum for calculating HIV incidence, number of people living with HIV (PLHIV), new AIDS cases, AIDS deaths, ART needs, etc. 11

26 National Estimates of HIV Infections Nepal Data Sources EPP Data Sources The following data sources served as input into EPP to derive adult HIV prevalence (Table 4). Table 4: EPP Input Data Sources Input Parameters 1. Population Size by Risk Groups High risk groups (clients of FSWs, IDUs, MSM/TG, and FSWs) Low risk groups (migrants) Remaining male populations Remaining female populations 2. Average time spent (in years) in the population group (IDUs, FSWs, clients of FSW, migrants) 3. HIV Prevalence Data High risk groups (clients of FSWs, IDUs, MSM/TG, FSWs) Low risk group (migrants) Remaining male populations Remaining female populations 4. Adult ART Coverage 1st line 2nd line % of survivals 5. Progression from HIV infection to need for ARV treatment 6. Population based surveys amongst population groups (large and more representative HIV prevalence surveys other than the routine surveillance surveys. e.g. DHS+) Sources of Data Population size estimation studies (Central Bureau of Statistics [CBS] 2007 for IDUs; National Estimates of HIV Infections 2007 Report for the remaining groups) Projected population using 2001 CBS absentee population data Projected population using 2001 CBS population data Projected population using 2001 CBS population data IBBS surveys: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009 IBBS surveys: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009 IBBS surveys: 2002, 2006, 2008 Nepal Red Cross Society: Blood Bank Data NCASC: PMTCT Programme Data NCASC: ART programme data NCASC: ART programme data Inbuilt literature (default values) Default values for normal pattern Not available Spectrum Data Sources The types of input data used in Spectrum are detailed in Table 5 with their sources. Table 5: Spectrum Input Data Sources Input Parameters 1. Demographic parameters (first year population, life expectancy, total fertility rate, age specific fertility rate, sex ratio, infant mortality rate, age and sex distribution of migrants) 2. HIV incidence (15-49) 3. MTCT (breast feeding, MMR, abortions, TFR reduction) 4. Proportion of survivals on ART 5. HIV progression (ART eligibility for treatment at CD4 equal or less than 200 and less than 350 switching eligibility by 2011) Sources of Data Population monograph of Nepal, 2003; Nepal Demographic and Health Survey (NDHS), 2006 EPP Output NDHS 2006; default values of model assumptions Default values of model assumptions ART programme data, National ART Guidelines, WHO 2010 advisory on ART 12

27 Methods of Estimation and Process Followed Other parameters relevant to Nepal that were applied model assumptions (default values) include: Sex distribution of new infections applying to concentrated, non-idu epidemic patterns Distribution of HIV positive pregnant women by treatment regimen including infant feeding options and effectiveness Percentage of adult survival after initiation of ART Effectiveness of ART for children 0-14 TB incidence with and without HIV Orphan distribution pattern amongst high risk populations applied to concentrated and low level epidemics 3.3 Projection, Curve Fitting and Exporting to Spectrum EPP has the advantage of generating multiple curves to fit existing input data. The model also allows us to calibrate the curves based on triangulation with other available data and experience of programming in the country. In Nepal, this facility was used to generate curves (Bayesian Melding) by making initial guesses of up to 400 curves and chose the best fitting curve to fit into EPP for each sub-group. In some groups, the country team applied suitable calibration factors to match the programme experience in the country. Lastly, the output of EPP was then exported to Spectrum. 3.4 Limitations Model Related Limitations A large part of the epidemiological assumptions are based on global proxies due to lack of Nepal-specific data. Despite availability of uncertainty analysis while fitting the curves in EPP, this option is currently not available for concentrated epidemic modelling. This resulted an inability in using recent behavioural change information for projection of the best fitting curve (φ) Data Related Limitations The country has experienced major movements and changes in the population - due in large part to internal political instability - since the last census was conducted in Consequently, the upcoming census in 2011 may show a different scenario with regards to population growth and demographics of the country. Most of the HIV prevalence data come from areas of the country where HIV prevention programmes are in place. As a result, the situation outside the covered project areas (districts) is largely unknown. Thus, these figures do not represent the wider population. There have been no regular and scientific population size estimate exercises conducted on MARPs (however, there were few mapping and size estimation of FSWs and IDUs exercised in selected sites in the past). Therefore, bold assumptions and extrapolations - such as using simple multiplier and/or projections methods have been used to derive size. There is a lack of sufficient data disaggregated at the sub-national level to fit the curves from EPP. Therefore, prevalence by regions has not been estimated in this year s report. Despite conducting a number of IBBS studies amongst different MARP groups over the years, the methods have not been standardised nor are they consistent from one IBBS study to the next, resulting in limited comparability. 13

28 National Estimates of HIV Infections Nepal 2009 As HIV prevalence data for the general population are not available from population based surveys, blood bank data and PMTCT programme data have been used as proxies for remaining males and females, respectively. This may result in the under-estimation of males with HIV and over-estimation of HIV positive females, because of programming biases incurred. Routine sentinel surveillance conducted among ANC attendees, STI patients, TB patients and highrisk groups in representative study locations would provide better alternatives in terms of data quality and consistency to be used in EPP, and produce more accurate estimates, but such surveillance activities are yet to be carried out in Nepal. In the absence of adequate data disaggregated by sub-populations on ARV from previous years, the current 2009 estimates were used to make assumptions about the proportion of sub-groups on ARV in the years prior to However, with the national database nearing completion, there will be increased availability of accurate data to populate the model for future rounds of estimations. 14

29 Input for EPP 14 Data Input for EPP 4.1 Populations at Risk, Population Size and HIV Prevalence Nepal s National HIV/AIDS Strategy ( ) has classified as FSWs, IDUs, MSM, clients of FSWs and labour migrants as most-at-risk or high risk populations; all other urban and rural population groups are categorised as populations at lower risk. The 2009 report will retain the most-at-risk populations but will classify remaining males, remaining females and migrants as low-risk populations Female Sex Workers (FSW) Sex work and brothels are illegal in Nepal. However, sex workers operate across the country, particularly along the major highways, main cities and border towns in the south. In addition, a number of women return from India having had worked as sex workers there. A combination of patriarchal traditions, conventional assumptions about women s appropriate role in society, low levels of education, and perceived low economic value have meant that FSWs are particularly stigmatised. These factors are thought responsible for FSW s limited access to information about reproductive health and safe sex practices. It is these cultural, social and economic constraints that not only bar female sex workers from negotiating with their clients with regards to condom use, but also pose significant barriers to seek treatment for STIs and HIV. Female Sex Workers are women aged 16 years and above who have received money or goods in exchange for sexual services in the last 12 months. They are classified as establishment-based, homebased and street-based. Risk factors include the inconsistent use of condoms by clients, coupled with the gap between HIV knowledge and behavioural practices (i.e. health care seeking behaviours) of FSWs. The hidden nature of FSWs makes them a difficult population to reach with intervention programmes, resulting in low utilisation of prevention services such as testing and counselling for HIV. Consequently, being unaware about their HIV status means they can involuntarily act as potential conduits to transmit HIV to their sexual partners, due to the low utilisation of condoms in such relationships. FSW Size Estimates A number of studies carried out by CREHPA, New ERA, Save the Children and FHI have attempted to estimate the number of FSWs in few cities and districts of Nepal. Existing studies are limited to the major cities and highway districts where FSWs are considered to be concentrated, thus little is known about the size of FSWs in rural locales. 15

30 National Estimates of HIV Infections Nepal 2009 Table 6: FSWs Related Input Data for EPP Locations Survey Years HIV Prevalence (%) References Kathmandu Valley Pokhara Valley 22 Terai Highway Districts * SACTS, 1992 SACTS, 1995 SACTS, 1996 NCASC, 1997 FHI/SACTS, 2001 FHI/SACTS, 2001 FHI/New ERA/SACTS, 2005a FHI/New ERA/SACTS, 2006a NCASC/FHI/New ERA/SACTS, 2008b NCASC, 2001 FHI/New ERA/SACTS, 2004a FHI/New ERA/SACTS, 2006c NCASC/FHI/New ERA/SACTS, 2008a FHI/New ERA/SACTS, 2000 FHI/New ERA/SACTS,2004b FHI/New ERA/SACTS, 2006a FHI/ACNielsen/SACTS, 2009b Note: * conducted in 16 Terai Highway districts. In the absence of new size estimation studies, the size of FSWs for 2009 was derived by applying the population growth rate to the 2007 estimated population size. This projection estimated 32,137 FSWs in Nepal for For details of the size estimates of all MARPs, please refer to Annex 2. FSW HIV Prevalence IBBS studies representing FSWs in the Kathmandu valley have been conducted since According to the results, HIV prevalence in the Kathmandu valley, Pokhara valley and 22 Terai highway districts have remained stable. The small fluctuation in HIV prevalence amongst FSWs in Kathmandu and Pokhara in 2004, 2006 and 2008; and in 2003, 2006 and 2009 in 22 Terai highway districts are not statistically significant. The most recent IBBS 2008 and 2009 showed a 2.2%, 3% and 2.3% HIV prevalence in Kathmandu, Pokhara and 22 Terai districts respectively (Table 6). A specific network of FSWs in Kathmandu was detected in 1992 by the STD/AIDS Counselling and Training Service (SACTS) as a result of several HIV prevalence studies carried out amongst street-based FSWs. These studies estimated less than 1% HIV prevalence in Similar studies conducted amongst that specific network showed continued growth in HIV prevalence (2.7% in 1995; 8.7% in 1996; 16% in 1997; and 17.3% in 1999) (Table 6). It needs to clarified that these studies are not comparable with IBBS studies conducted in Kathmandu from 2004, mainly because of the difference in sampling methods used Injecting Drug Users (IDU) Despite being the first developing country to establish a harm reduction programme with needle exchange for injecting drug users, prevalence within this group still remains one of the highest amongst all MARPs. The burden Injecting Drug Users are defined as individuals - both male and female that have injected various drugs by intravenous or intramuscular routes for non-medical purposes in the last 12 months. 16

31 Input for EPP of injecting drug use is especially heavy in Kathmandu and along the highway districts. Studies show that high unemployment rates and lack of economic opportunities leads to increased drug use, especially amongst the poorer classes. Injecting of drugs using contaminated needles is the primary factor in the spread of HIV amongst IDUs. Drug use can further contribute to risky sexual behaviour, resulting in HIV transmission as IDUs act as a bridge to the general, low-risk population by engaging in unprotected sex with their low-risk spouses or partners. This is the case for both male and female IDUs. IDU Size Estimates Prior to 2001, estimates of the size of IDUs in the country were not based on scientific studies or estimation methods. A comprehensive ethnographic study was carried out for the first time amongst IDUs in 2001 (CREHPA, 2002) and in 2004, the first IBBS study was conducted followed by two others in 2007 and The estimated size of IDUs in 2009 was 28,439. IDU HIV Prevalence Since the 1990s, various studies have attempted to estimate the prevalence of HIV amongst IDUs in Nepal. In 1995, NCASC reported an estimated HIV prevalence of less than 2%. In 1999, another study concluded prevalence was 40%, a substantial increase in just 4 years (Karki BB, 2000). IBBS studies conducted in the four epidemiological regions have demonstrated that prevalence amongst IDUs has consistently been amongst the highest of all MARPs, albeit the steady decrease found in all regions. In 2009 prevalence amongst IDUs were as follows: 27.7%, 5.1%, 12.6% and 9.5% in Kathmandu, Pokhara, Eastern Terai districts and Western Terai districts, respectively (Table 7). It is important to note that while there has been a drastic drop in the number of IDUs with HIV in 2009 compared to 2005, they are not fully comparable due to the different methodologies used in the various rounds of IBBS surveys. Table 7: IDUs Related Input Data for EPP Locations Survey Years HIV Prevalence (%) References Kathmandu Valley Pokhara Valley Eastern Terai Districts Western Terai Districts * * * * Crofts N., 1998 Crofts N., 1998 FHI/New ERA/SACTS, 2002a FHI/New ERA/SACTS, 2005c FHI/New ERA/SACTS, 2008a FHI/New ERA/SACTS, 2009a FHI/New ERA/SACTS, 2003b FHI/New ERA/SACTS, 2005d FHI/New ERA/SACTS, 2008b FHI/New ERA/SACTS, 2009b FHI/New ERA/SACTS, 2003a FHI/New ERA/SACTS, 2005b FHI/New ERA/SACTS, 2007a FHI/New ERA/SACTS, 2009c FHI/New ERA/SACTS, 2005e FHI/New ERA/SACTS, 2007b FHI/New ERA/SACTS, 2009d Note: * Adjusted for EPP curve fitting only to smoothen the curve. The IBBSs measured 20.7% in Kathmandu, 3.4% in Pokhara, 8.1% in Eastern Terai districts and 8.0% in Western Terai districts among IDUs in

32 National Estimates of HIV Infections Nepal Men who have Sex with Men (MSM) Social factors, cultural pressure including the strain of having to conform to traditional male roles, along with the stigma attached to homosexuality in Nepal have resulted in a large number of MSM leading heterosexual lifestyles. This social construct and discrimination has resulted in difficulties in reaching MSM with HIV and AIDS programmes and consequently, HIV prevalence amongst MSM is significantly high. Of great concern is the fact that a majority of MSM are married or in long-term heterosexual relationships, which puts their spouses or partners at an increased risk of contracting HIV. This is in large part due to the very small percentage of MSM utilising condoms with their partners. MSM Size Estimates There have been a disconcertingly limited number of studies conducted to estimate the size of MSM in the country. For the first time in 2003, a mapping and size estimation study of MSM in Kathmandu valley was conducted by CREHPA, BDS and FHI. They ranged the number of MSM between 6,000 and 8,000 (CREHPA/BDS/FHI/SACTS, 2004). By using population and programme coverage data from IBBS surveys, Blue Diamond Society (an organisation working for the rights of sexual minorities) and in conjunction with the capture-recapture method to estimate size, the 2003 estimates report concluded that between Men who have Sex with Men are biological males, 16 years or older, who have engaged in sexual relationships (oral and/or anal) with another biological male, at least once in the past 12 months. They are classified as (1) male sex workers or MSWs and (2) non- MSWs. MSWs are defined as males who have had sexual relations with another male in exchange for money or other commodities. Non- MSWs are males who have had sexual relations with another male without receiving cash payment or other commodities. 1-3% of the adult male population in Nepal are MSM. In 2009 it was estimated that there are approximately 140,691 MSM in the country. MSM HIV Prevalence The first IBBS survey carried out amongst MSM in Kathmandu put HIV prevalence at 3.9% (FHI/CREHPA, 2005). Two more rounds of IBBS were conducted in 2007 and 2009, also in Kathmandu, which estimated HIV prevalence as 3.3% (FHI/New Era/SACTS, 2008) and 3.8% respectively (FHI/New Era/SACTS, 2009) (Table 8).One of biggest limitations regarding MSM related data is that IBBS surveys have been conducted in Kathmandu only, therefore, data pertaining to MSM in other areas have been largely assumed, based on HIV prevalence in Kathmandu. Table 8: MSM Related Input Data for EPP Locations Survey Years HIV Prevalence (%) References Kathmandu Valley FHI/CREHPA, 2005 FHI/New ERA/SACTS, 2008c FHI/New ERA/SACTS, 2009e 18

33 Input for EPP Clients of FSW This sub-group ranges from transport workers, to uniformed personnel, civil servants, IDUs, daily wage labourers and businessmen, amongst others. Because of the heterogeneous constitution of this sub-group, the probability of infecting the general population is considerably high. Indeed, as is the case with other MARPs, clients act as a bridge to spread HIV to the general, low-risk population as a majority of them are in otherwise long-term relationships with their wives or girlfriends. Clients of FSW Size Estimates There have been no formal studies conducted to estimate the number of clients of FSWs in Nepal. However, the 2003 Infection Estimates Report attempted to estimate their size based on information gathered from FSWs. Subsequently in 2005, 2007 and 2009, their size was projected by applying a population growth factor to the previous year s size estimates. In 2009, the numbers of clients of FSWs were estimated to be around 727,421. In addition, to put into perspective the scale of the situation, albeit not specifically that of Nepal, it has been estimated that for every 10 woman in Asia that sells sex, at least 75 men buy it (Commission on AIDS in Asia, 2008). Clients of Female Sex Workers are defined as individuals who receive sexual services in exchange for cash or other commodities. pertain only to transport workers or truckers, thus not fully representative of all clients of FSWs. The 1999 IBBS survey indicated 1.5% prevalence amongst 400 truck drivers in 16 highway districts. This increased to 1.8% in 2004 (FHI/New ERA/ SACTS. 2004b), after which prevalence has dropped from 1% in 2006 (FHI/New ERA/SACTS 2006e) to 0.25% in 2009 (FHI/ ACNielsen/SACTS 2009b) (Table 9) Migrants Migration of young males, especially from the Far-Western regions of Nepal has rapidly increased in recent years, highlighted by the increasing political instability and lack of economic opportunities. Indeed, IBBS results have demonstrated that 59.7% and 67.8% of males below the age of 20 from the Western and Mid-Far Western regions respectively, migrate to urban areas of Nepal, India, the Middle East and South-East Asia (NCASC/New ERA/ SACTS/2008c). Migration to India is especially common, underscored by the easy open-border access. Clients of FSW HIV Prevalence As is the case with their size, very few studies have been conducted that provide information on HIV prevalence amongst clients of FSW and where they do exist such as IBBS surveys they Migrants are defined as clients of sex workers abroad. They are generally classified as high or low risk those who visit sex workers and those who do not respectively. Table 9: Clients of FSW Related Input Data for EPP Locations Survey Years HIV Prevalence (%) References 22 Terai Districts * FHI/New ERA/SACTS, 2000 FHI/New ERA/SACTS, 2004b FHI/New ERA/SACTS, 2006e FHI/ACNielsen/SACTS, 2009b Note: * Adjusted for EPP curve fitting only to smoothen the curve. The IBBS measured a zero percent prevalence among truckers in

34 National Estimates of HIV Infections Nepal 2009 It should be noted at this point that migration in and of itself is not a direct risk factor for acquiring HIV, but it creates conditions that makes the migrant engage in risky behaviour that can lead to the potential contraction of the virus. Not all migrants visit sex workers while away and as such, the entire migrant population cannot be identified as a group at higher risk for acquiring and transmitting HIV. However, it has been demonstrated that 11% and 23% in the Western and Mid-Far Western districts, respectively, have visited sex workers in India and Nepal. This has tremendous implications on transmission patterns; as such behaviour not only puts the migrants at an increased risk of acquiring HIV, but also significantly increases the probability of infecting the low-risk population groups their spouses. Migrants Size Estimates There have been no research or scientific studies designed exclusively to estimate the size of migrants in the country. While it does not accurately identify the number of migrants, in 2001, the Nepal Population Census and Community Level Research carried out by CARE/FHI discovered that 27.5% of adults males in the Far-Western hill districts were absent for at least six months and approximately 10% of adult men were residing in India for at least 6 months (NCASC, 2008). In 2009, it was estimated that there are 1,485,499 migrants in the country. Migrant HIV Prevalence A study conducted in 2002 found alarming 8-10% HIV prevalence amongst returned migrants from Mumbai, while showing a considerably lower 0.7% prevalence amongst non-migrants (FHI/ New ERA/SACTS, 2002b). Similarly, the 2006 IBBS survey discovered higher prevalence amongst migrants from the Mid-Far Western districts who had visited sex-workers (8.2%) while in India versus those who had not (0.8%). IBBS results in 2008 found a 2.3% and 2.4% prevalence in the West and Mid- Far West, respectively amongst those coming back from Mumbai. However, overall prevalence in the Mid-Far West declined from 2.8% to 0.8%, while a slight increase from 1.1% to 1.4% was seen in the West (Table 10) Remaining Females As previously mentioned, a vast majority of male IDUs, MSM, clients of FSWs and migrants are married or in otherwise long-term relationships. These extension of sexual partnerships into numerous networks, coupled with low condom use, multiple and/or concurrent sexual partners and limited treatment seeking behaviour makes for a conducive environment in which HIV can transmit to women who are otherwise at low-risk. While it was the first round of IBBS conducted amongst spouses of migrants - therefore not fully applicable to all remaining females - and was carried Table 10 : Migrants Related Input Data for EPP Locations Survey Years HIV Prevalence (%) References Mid-Far Western Districts Western Districts FHI/New ERA/SACTS, 2002 FHI/New ERA/SACTS, 2006 NCASC/FHI/New ERA/SACTS, 2008c FHI/New ERA/SACTS, 2006 NCASC/FHI/New ERA/SACTS, 2008c 20

35 Input for EPP out only in 4 Far-Western districts, the survey in 2008 provided an important source of data for HIV size and prevalence within what has been considered a low-risk population group. An estimated total of 17,466 wives of migrants were listed in the 4 districts, out of which 400 were selected for the survey and within which a 3.3% HIV prevalence was found (NCASC/FHI/New ERA/SACTS, 2008d). Remaining Females Size Estimates and HIV Prevalence As mentioned above, remaining females comprise of women whose husbands or long-term sexual partners are clients of FSWs or male IDUs have had sex with or are classified as MSM or MSW. Because there have not been regular nor scientific research carried out amongst women at lower risk, in 2009, HIV prevalence data amongst ANC attendees were used as a proxy to reflect prevalence amongst remaining females. Prevalence amongst remaining females in 2009 was estimated at 0.2% (Table 11) and a standard population growth factor was applied to the previous year s remaining population size to obtain size estimates on remaining females, which resulted in an estimation of 7,488, Remaining Males Remaining males include the husband or partners of MARPs such as FSWs or female IDUs. IBBS studies conducted amongst FSWs report an overwhelmingly low 9.3% percent of consistent condom use with their husbands or partners other than their clients, while with their clients this shot up to 84.8% (FHI/ACNielsen/ SACTS, 2009a). Notwithstanding the encouraging sign of positive behavioural changes vis-à-vis high condom utilisation with clients, FSW s behaviour with their non-client partners is of great concern. Such variations in behaviour have enormous implications on HIV transmission patterns, because while FSWs may be showing increased awareness about HIV transmission, it highlights the need for consistent and regular condom use with all sexual partners, not just their clients. Remaining Males Size Estimates and HIV Prevalence To date, HIV prevalence amongst low-risk, remaining males have not been formally researched or studied about. Neither have remaining males been specifically categorised in all three previous estimates reports. As such, the 2009 HIV prevalence amongst this group have been generated Table 11 : Remaining Females Related Input Data for EPP Locations Survey Years HIV Prevalence (%) Sources Blood Banks Antenatal Care Sites NRCS, 1999 NRCS, 2003 NRCS, 2005 NCASC PMTCT Programme Monitoring Data, 2006 NCASC PMTCT Programme Monitoring Data, 2007 NCASC PMTCT Programme Monitoring Data, 2008 NCASC PMTCT Programme Monitoring Data,

36 National Estimates of HIV Infections Nepal 2009 using blood bank data from the Nepal Red Cross Society. In 2009, there was an estimated prevalence of 0.09% (Table 12). By applying the standard population growth factor, the number of remaining males was estimated at 6,839, ART Programme Data ART programme data was collected from existing ART sites and a normal pattern of progression from HIV infection to need for treatment was applied, with the eligibility criteria to enrol for ARV at CD It has been estimated that in 2009, there were 3,574 enrolled in the ART programme, on both 1 st and 2 nd line ARV treatment (Table 13). As seen in Table 13, the number of adults on ART has consistently increased since the programme was rolled-out, with 3,552 adults on 1 st line regimen in However, the number of people on 2 nd line regimen has only slightly increased to 22. The distribution of ART amongst subpopulations were estimated based on the ART programme data collected from 4 ART sites in Kathmandu and 4 ART sites in the Far-Western region. The distributions are as follows: IDUs: 20%; MSM: 6%; Female Sex Workers: 5%; Clients of FSW: 22%; Migrants: 22%; Remaining Males: 2%; Remaining Females: 23%. Table 12 : Remaining Males Related Input Data for EPP Locations Survey Years HIV Prevalence (%) Sources Central Blood Bank NRCS 2005: Blood Transfusion Service, 2005 NRCS 2007: Blood Transfusion Service, 2007 NRCS 2008: Blood Transfusion Service, 2008 NRCS 2009: Blood Transfusion Service, 2009 Table 13: Number of Adults on ART: Input Data for EPP ART Regimens Years Number of People Sources 1 st Line 2 nd Line ,333 2,536 3, ART Routine Programme Data, 2005 ART Routine Programme Data, 2006 ART Routine Programme Data, 2007 ART Routine Programme Data, 2008 ART Routine Programme Data, 2009 ART Routine Programme Data, 2005 ART Routine Programme Data, 2006 ART Routine Programme Data, 2007 ART Routine Programme Data, 2008 ART Routine Programme Data,

37 National HIV Infections Estimates National HIV Infections Estimates EPP Results The total HIV infections estimate for 2009 is 63,528. Out of the total estimated infections, 3,544 are children of 0-14 years age group (5.6%), with the remaining 59,983 are adults of age 15 years and above (94.4%) (Table 14). Similarly, 7,481 infections are amongst people over the age of 50 years (11.7%). As the epidemic ages and with increased availability of effective Anti-retroviral Therapy for many who need it, an increasing number of people will fall into this category, and without suitable strategies, there will be significant challenges to health systems increasing pressure to make wise policy choices. By sex, almost two-thirds of the infections have occurred among males (65%), and around 29% of infections are shared by women in the reproductive age group (15-49). Figure 5: Distribution of Estimated HIV Infections by Population Groups (15+ years), 2009 Labour migrants 30% Remaining male 28% FSWs 1% IDUs 4% Clients FSWs 5% MSM/ TG 6% Remaining female 26% Migrants accounted for 29.4% of total HIV infections in the country followed by remaining females, remaining males, MSM, clients of FSWs, IDUs and FSWs with 28.0%, 26.2%, 6.2%, 5.0%, 4.2% and 1.0% respectively (Figure 5 and Table 15). Table 14: HIV Infections Estimates 2009 by Age Groups and Sex Age Groups Total Total 1,470 1, ,686 6,733 9,375 10,005 9,373 8,065 6,265 4,107 2, ,528 Estimated HIV Infections in Nepal Male ,514 3,993 5,764 6,480 6,412 5,711 4,482 2,922 1, ,509 Female ,172 2,741 3,611 3,526 2,961 2,354 1,784 1, ,019 23

38 National Estimates of HIV Infections Nepal 2009 Table 15: HIV Infections Estimates 2009 by Population Groups Population Sub-Groups (Age 15+ years)* IDUs MSM FSWs Clients of FSWs Migrants Remaining Male Population (15 years and above) Remaining Female Population (15 years and above) Total Total Population (Age 15+ years) a 28, ,691 32, ,421 1,485,499 6,839,077 7,488,215 16,741,479 Estimated HIV Infections (15+ years) a 2,534 3, ,996 17,653 15,697 16,800 59,984 Note: * EPP 2009 demands the population groups with age 15+ years, for HIV Infection Estimation. Share of Total HIV Infections (%) 4.2% 6.2% 1.0% 5.0% 29.4% 26.2% 28.0% 100% Sexual transmission (through unprotected sex) has remained a dominant mode of HIV tranmission since the start of the epidemic in Nepal. Indeed, in 2009, 16% of the total estimated infections were amongst MARPs, whereas low risk male and female populations represented 54% of the infections. Migrants accounted for about 30% of infections (Figure 6). Although IDUs do not account for the largest share of total estimated HIV infections, prevalence amongst the said group is the highest in comparison to other MARPs, which in 2009 reached 8.9%, followed by MSM, FSWs, migrants and clients of FSWs and remaining male and female populations, with 2.6%, 1.9%, 1.2%, 0.4%, 0.2% and 0.2%, respectively (Figure 7). In terms of the share of total estimated HIV infections, migrants account for the largest with 17,653, followed by remaining females and males, MSM, clients of FSWs, IDUs and FSWs with 16,800, 15,697, 3,699, 2,996, 2,534 and 605 respectively. It shows more than 90% of HIV infections are occured through sexual transmission. Albeit large number of infections are among low risk population, the key drivers of the epidemic are the most at risk population groups. Based on the output of modelling it was observed that about half of total estimated HIV infection in the country was from the remaining male and female population. It is notable that the proportion of remaining female population in the total estimated HIV in the country across the time remains Figure 6: Distribution of Estimated HIV Infections by Population Groups (15+ years): ,000 70,000 60,000 Female remaining population Migrants FSWs IDUs Male remaining population Clients of FSWs MSM 50,000 40,000 54% 30,000 20,000 30% 10, % Source: NCASC

39 National HIV Infections Estimates 2009 Figure 7: Number of Estimated HIV Infections Vs. Estimated HIV Prevalence, 2009 Estimated HIV Infentions(#) 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Source: NCASC , Injecting Drug Users (IDUs) 3,699 Men who have Sex with Men (MSM)/TG Female Sex Workers (FSWs) 2, Clients of FSWs 18,890 Labour Migrants 17,898 Remaining Male Population 16,906 Remaining Female Population Estimated HIV Prevalence (%) more or less stable approximately since 1992 (Figure 6). However, it is noteworthy that this proportion was derived mainly from one of the single most important parameters i.e. HIV prevalence among remaining female population that was further multiplied by the number of total adult female population in the country that do not fall into any of the high risk categories (Table 2). The high proportion of HIV among remaining female population could be because of potential bias occurred using PMTCT data. The limitation of use of PMTCT data for general population prevalence in the actions of survillience data amongst general women should be kept in mind while interpretating the result. 5.2 Trend in Adult (15-49) HIV Prevalence and Incidence Time trend analysis of HIV prevalence amongst adults shows a decline in the past several years and estimates that prevalence is currently 0.39% (Figure 9). The peak in HIV prevalence was sometime in 2001, after which the curve slowly started stabilising. Spectrum output shows, the largest number of new infections per year (incidence) (6,954) was projected sometime in After one decade, the incidence has decreased by 31.6% to 4,760 in 2009 (Figure 8). Figure 8: Incidence Distribution by Population Groups (15+ years): ,000 7,000 6,000 5,000 IDUs MSM Clients of FSWs Female Sex workers Male Remaining Population Female Remaining Population Migrants 4,000 3,000 2,000 1, Source: NCASC

40 National Estimates of HIV Infections Nepal 2009 Figure 9: Adult (15-49) HIV Prevalence, % Source: NCASC 2010 Figure 10: Adult (15-49) HIV Incidence, % Source: NCASC 2010 Table 16: Selected Major Indicators of HIV Infections Estimation, 2009 Indicators Value (2009) Adult (15-49) HIV prevalence Young Adult (15-24) HIV prevalence Proportion of women living with HIV Proportion of women and girls living with HIV Average number of new infections per year Average number of new infections per day Average number of new infections amongst children (0-14) per year Average number of AIDS deaths per year Average number of AIDS deaths among children (0-14) per year Average number of AIDS deaths among children (0-4) per year Total number of AIDS orphans till 2009 Average number of AIDS orphans per year 0.39% (0.3% - 0.5%) 0.17% (0.09% %) 28.6% 6.2% 4, , ,

41 National HIV Infections Estimates 2009 Table 17: Impact Results from Spectrum, 2009 Impact Results Value (2009) People (15+ years) in need of ART, st line therapy Newly needing 1 st line therapy 2 nd line therapy Children (0-14 years) in need of ART Total number of HIV+ pregnant women PMTCT requiring mothers (ARVs and prophylaxis) All AIDS orphans Annual Total AIDS deaths Annual Young Adult (15-24) deaths Annual Adult (15-49) deaths 18,930 (eligibility at CD4 less than 200) 30,960 (eligibility at CD4 less than 350) 17,310 (eligibility at CD4 less than 200) 5,160 (eligibility at CD4 less than 200) 22 1,635 1,445 1,228 21,947 (19,157 paternal orphans; 6,320 maternal orphans; 4,115 double orphans) 4,701 (3,163 males; 1,538 females) 274 (168 males; 106 females) 3,562 (2,392 males; 1,170 females) 5.3 Spectrum Results Generating Impact Data for National Planning Spectrum (version 3.54) was used to generate impact related results where population input parameters were updated with current available statistics and epidemic projections of HIV in terms of incidence was imported from EPP. Spectrum results depicted that women aged comprised 28.6% of the total number of adults living with HIV in 2009 in Nepal (Table 16). Out of approximately 4,760 estimated new infections per year or incidence, 468 were amongst children. Similarly, the average number of new HIV infection per day was 13. Spectrum also estimated 4,701 AIDS related deaths per year. The keys selected impact results are outlined in Table 17. For more details (with upper and lower ranges) from the year , please refer to Annex 3. Anti-Retroviral Treatment Needs In 2009, an estimated 18,930 adults were in need of 1 st line ARV drugs. Following WHO recommended ART eligibility change from CD4 count 200 to CD4 count 350, the number of people in need of ARV will increase dramatically. For example, the number of people requiring 1 st line drugs was 17,310 (2009) but with the change in eligibility, it increased to 32,267 (2011). The change in ART eligibility, which will come into effect in the near future, indicates that the government must take immediate and effective action vis-à-vis increasing the availability of ARVs to ensure universal access to appropriate and timely treatment. PMTCT Needs HIV infection from an HIV positive mother to her child during pregnancy, delivery or breastfeeding is called mother-to-child transmission (MTCT). In an effort to stop the transmission of HIV from mothers to their babies, Nepal launched the PMTCT programme in Spectrum analysis shows that the number of mothers requiring PMTCT services has been in decline since However, the cumulative number of children living with HIV has increased. As such, it is of utmost importance that access to PMTCT services, with linkages to maternal and child health care, reproductive health and family planning services are expanded, especially in the hard-to-reach geographical locations. 27

42 National Estimates of HIV Infections Nepal 2009 Orphans Orphans, in the context of HIV and AIDS, are defined as children below the age of 18 who have lost at least one parent to AIDS. Analysis shows a consistent increase in the number of children orphaned over the years. In 2009, the estimated cumulative number of orphans was 22,000, up from 11,000 in This increase is attributed in large part to the marked improvement in the method, quality and quantity of data collection, which have made the numbers more accurate. In addition, children that have been identified as orphans in 2000 are similarly counted as orphans in, for example, AIDS Related Deaths AIDS is an immunological disorder, whereby the immune system is compromised by the HIV virus. As such, one does not die of AIDS, but rather from associated opportunistic infections that arise because of the weakened immune system. Estimations show that there was a steady increase in AIDS deaths up until 2007, when the number of deaths totalled 4,913, after which it fell to 4,701 in This coincides with the fact that the national ARV programme began in 2004, after which a statistically significant drop in incidence undoubtedly took some time to manifest. Indeed, 2007 marks the year whereby a decline in AIDS deaths becomes apparent. 5.4 Uncertainty Analysis The Spectrum model provides information on the uncertainty of HIV infections estimates and allows for the creation of ranges depending on the plausibility bounds chosen. Uncertainty analysis was performed to the key output parameters, for example, HIV prevalence, ART needs, AIDS deaths, etc. This was done by generating thousands of incidence curves adjusted for the year 2008, using a double logistic fit assuming appropriate, quality data (- 40%, + 60%). The result of uncertainty analysis is presented within plausibility bounds of 5% and 95% intervals (see Annex 3 for more details). The more data points available, the narrower the plausibility bounds, thus reflecting a higher confidence in the results. The following is an example of uncertainty analysis performed on adult HIV prevalence for illustration purposes. Adult HIV prevalence is measured at 0.39% with a lower bound of 0.30% and an upper bound of 0.48% (Figure 11). It is important to note that all the above results (sections 5.2 and 5.3) depict the median 50% values. Figure 11: Adult (15-49) HIV Prevalence, 2009 (Plasusibility Bounds of 5% & 95% Intervals) Lower 2.50% Mediam 50% Upper % Source: NCASC

43 Conclusion and Recommendations 16 Conclusion and Recommendations The HIV epidemic in Nepal is evolving, showing a stabilizing or decreasing trend amongst some MARPs. The population groups that driving the epidemic rapidly, based on the HIV prevalence and potential of engaging into the risk behaviour to HIV, remains the MARPs: IDUs, FSWs, MSM/MSW, and, of course, migrant population. So it is imperative to have scale up of prevention programs along with care and support activities for theses population groups. Even though the proportion of remaining low risk females among total HIV estimate is high, the mere fact of main risk factor for most of these women is having unprotected sex with a spouse or partner, who may also probably don t know their HIV status too. It has created serious concerns and major programmatic implications. Thus, it is imperative to devise an innovative programme reaching to prevent women in reproductive age group their spouses and sexual partners. Making people with undiagnosed infections know their status is critical. Another striking feature observed from the output of modelling is that, if to added up the proportions, more than 50% of the total estimated number of HIV were contributed by remaining male, migrants (majority were male), and clients. The commonality of these three groups, which are males, is their risk factor for HIV: mainly unprotected sexual exposure with infected person, although the possibility of smaller proportion of them from drug use related HIV infection and other multiple risk factors cannot be ruled out. One important fact is that many of the clients of direct and indirect sex workers, despite having risk factor for HIV, have been misclassified into the remaining males. This is because people usually do not want to disclose the status of having sex before and outside of marriage regardless of protected or unprotected sex in nature. Besides, IBBS among labour migrants to neighbouring country has indicated that the most predominant risk factor, again, is having unprotected sex with an infected person - mostly sex workers. All these facts enquire how to prevent men in general population getting HIV through unprotected sex with an infected partner. This might be one of the biggest challenges in containing the HIV epidemic in Nepal: like looking for something that cannot easily identifiable and yet they are there. Perhaps intervention programs that are designed based on the frequent consultation with the possible beneficiary population in a given geographic area might help. Moreover it is urgent to know better on where 29

44 National Estimates of HIV Infections Nepal 2009 and what are the sources of new HIV infections among their sexual partners who mostly are commercial and significantly in casual nature. These will help how to prevent them from getting HIV, and to what extent those infected with HIV could know their HIV status. To address the current data gaps and response needs, following key recommendations are drawn. Intensify Programmes amongst MARPs Targeted interventions towards MARPs need further intensification, both in terms of coverage and effectiveness so that the epidemic can be contained within the sub groups and not spread further into the larger general low risk populations. Indeed, the trend of HIV spreading to spouses and partners of individuals at high risk is of great concern. With regard to low risk HIV positive females, the consequences are even more severe, due to the increased probability of transmitting the virus to their child. Data clearly shows that this likelihood is quickly manifesting into reality, with the increasing number of children living with HIV, unlike the decline of HIV positive adults. It is important for Nepal to develop strategies and approaches to identify the high risk migrants - who are being recognised as the primary bridging population for the implementation of effective strategies. At the same time, appropriate strategies need to be developed to improve access of preventive services amongst low risk groups, which includes increasing coverage of testing and counselling services through improved and enhanced targeting and strategic positioning. Preparedness for Scale up of ARV Services and Linkage with Prevention and Support Programmes Analysis shows an increased number of HIV infections among older people (above the age of 49), due to the maturing of the HIV epidemic in Nepal over the span of twenty years and because ART has been available for more than half a decade. The increasing number of older HIV positive individuals will further demand comprehensive ART (treatment, care and support) services. Furthermore, under the revised WHO guidelines on ART, there is going to be an approximate 1.6 times increase in the number of people in need of ARV, which would demand strengthening of health system including additional human and other resources to be allocated and increased preparedness in terms of the delivery of institutional mechanisms, in a sustainable manner. TB is one of the most common opportunistic infections among HIV infected persons particularly at the late stage of disease. Together with the emergence of drug resistant TB, activities should be implemented to address this issue as well. Linking PMTCT into MCH and Sexual and Reproductive Health Programmes The national PMTCT programme, for the large part, remains vertically operated through hospitals, in spite of numerous calls to link it to other sexual and reproductive health programmes. To ensure the shift from a project based to programme based approach, the national PMTCT programme needs to be integrated with broader maternal and child health and family planning services. Integration will ensure a wider reach and coverage of PMTCT services to mothers in need. 30

45 Conclusion and Recommendations Improve Data Quality An increase in the collection and robustness of quality data and data coverage is also needed. As has been recommended in previous estimation reports, it is essential that the government re initiate sentinel surveillance, such as surveillance amongst antenatal care attendees which can provide invaluable data on low risk females and patients with sexually transmitted infections. To monitor the extent of HIV infection transmission from MARPs to the general population, the quality of routine programme monitoring data needs to be enhanced, along with the set up a management information system. Understanding the evolution of the epidemic can also be enhanced by increasing the number of qualitative studies carried out in the country. As of now, Nepal does not have adequate sub national level data to support robust generation of region specific HIV prevalence data. As a consequence, it is absolutely essential to increase generation of sub national data in order to ensure that future EPP projections can inform region-specific, local level programming. Along the same lines, to ensure increased accuracy of EPP results, it is important that data from a multitude of sources and methods are triangulated to improve its confidence. Capacity Building for Epidemic Modelling and Analysis The estimation process should also utilize advanced modelling and epidemic analysis using models like Asian Epidemic Model (AEM) to ascertain the efficacy of interventions, to factor in their impact on epidemic curves and for long term planning. For this, it is important to carry out capacity building exercises and to include epidemic modelling and analysis as part of routine programmes. 31

46 32 National Estimates of HIV Infections Nepal 2009

47 National Estimates of HIV Infections Nepal 2009 References Commission on AIDS in Asia, Redefining AIDS in Asia: Crafting an Effective Response. Report of the Commission on AIDS in Asia. New Delhi: Oxford Press. CREHPA/BDS/FHI/SACTS, Social Mapping and Size Estimation of Men-having- Sex-with-Men in Kathmandu Valley. A Rapid Assessment and Update. Kathmandu. Crofts N, Injecting Drug Use and HIV Infection in Asia. AIDS 12 (Suppl. B), p. S87. FHI/ACNielsen/SACTS, 2009a. Integrated Biological and Behavioural Surveillance Survey (IBBS) Among Female Sex Workers in 22 Terai Highway Districts of Nepal. Kathmandu. FHI/ACNielsen/SACTS, 2009b. Integrated Biological and Behavioural Surveillance Survey (IBBS) Among Truckers in 22 Terai Highway Districts of Nepal. Kathmandu. FHI/CREHPA, A Situation Assessment of Intravenous Drug Users in Kathmandu Valley: A Focused Ethnographic Study. Kathmandu. FHI/CREHPA, 2005, Integrated Bio-Behavioral Survey (IBBS) Among MSM Population in Kathmandu Valley. Kathmandu. FHI/New ERA/SACTS, STD and HIV Prevalence Survey among Female Sex Workers and Truckers on Highway Routes in the Terai, Nepal May Kathmandu. FHI/New ERA/SACTS, 2002a. Behavioral and Sero Prevalence Survey Among Injecting Drug Users (IDUs) in Kathmandu December Kathmandu. FHI/New ERA/SACTS, 2002b. HIV/STI Prevalence and Risk Factors among Migrant and Non-Migrant Males of Achham District in Far-Western Nepal. Kathmandu. FHI/New ERA/SACTS, 2002c. HIV/STI Prevalence and Risk Factors among Migrant and Non-Migrant Males of Kailali District in Far-Western Nepal. Kathmandu FHI/New ERA/SACTS, 2003a. Behavioral And Sero Prevalence Survey among Injecting Drug Users (IDUs) in Eastern Nepal November Kathmandu. FHI/New ERA/SACTS, 2003b. Behavioral and Sero Prevalence Survey among Injecting Drug Users (IDUs) In Pokhara Valley November Kathmandu. FHI/New ERA/SACTS, 2004a. Integrated Bio-behavioral Survey (IBBS) among Female Sex Workers and Behavioral Surveillance Survey (BSS) among Clients in Pokhara Valley Kathmandu. FHI/New ERA/SACTS, 2004b. Integrated Bio-behavioral Survey (IBBS) among Female Sex Workers and Truckers along the Terai Highway Routes Covering 22 Districts of Nepal July Kathmandu. 33

48 National Estimates of HIV Infections Nepal 2009 FHI/New ERA/SACTS, 2005a. Integrated Bio-behavioral Survey (IBBS) among Female Sex Workers and Behavioral Surveillance Survey (BSS) among Clients in Kathmandu Valley Kathmandu. FHI/New ERA/SACTS, 2005b. Integrated Bio-Behavioral Survey (IBBS) among Male Injecting Drug Users (IDUs) in Eastern Terai Kathmandu. FHI/New ERA/SACTS, 2005c. Integrated Bio-Behavioral Survey (IBBS) among Male Injecting Drug Users (IDUs) in Kathmandu Valley Kathmandu. FHI/New ERA/SACTS, 2005d. Integrated Bio-Behavioral Survey (IBBS) among Male Injecting Drug Users (IDUs) in Pokhara Kathmandu. FHI/New ERA/SACTS, 2005e. Integrated Bio-Behavioral Survey (IBBS) among Male Injecting Drug Users (IDUs) in Western To Far Western Terai Kathmandu. FHI/New ERA/SACTS, 2006a. Integrated Bio-Behavioral Survey among Female Sex Workers in East-West Highways Covering 22 Districts of Nepal Round III Kathmandu. FHI/New ERA/SACTS, 2006b. Integrated Bio-Behavioral Survey among Female Sex Workers Kathmandu Valley Round II Kathmandu. FHI/New ERA/SACTS, 2006c. Integrated Bio-Behavioral Survey among Female Sex Workers Pokhara Valley Round II Kathmandu. FHI/New ERA/SACTS, 2006d. Integrated Bio-Behavioural Survey among Male Labour Migrants in 11 Districts in Western and Mid-Far Western Regions of Nepal. Kathmandu. FHI/New ERA/SACTS, 2006e. Integrated Bio-Behavioral Survey among Truckers in East-West Highways Round III Kathmandu. FHI/New ERA/SACTS, 2007a. Integrated Bio-behavioral Survey (IBBS) among Injecting Drug Users in Eastern Terai Kathmandu. FHI/New ERA/SACTS, 2007b. Integrated Bio-behavioral Survey (IBBS) among Male Injecting Drug Users (IDUs) in the Western and the Far-Western Terai Kathmandu. FHI/New ERA/SACTS, 2008a. Integrated Bio-behavioral Survey (IBBS) among Injecting Drug Users in Kathmandu Valley Kathmandu. FHI/New ERA/SACTS, 2008b. Integrated Bio-Behavioral Survey (IBBS) among Injecting Drug Users in Pokhara Valley Kathmandu. FHI/New ERA/SACTS, 2008c. Integrated Bio-behavioral Survey (IBBS) among Men who have Sex with Men in the Kathmandu Valley Kathmandu. 34

49 National Estimates of HIV Infections Nepal 2009 FHI/New ERA/SACTS, 2009a. Integrated Biological and Behavioral Surveillance Survey (IBBS) among Injecting Drug Users in Kathmandu Valley Round IV Kathmandu. FHI/New ERA/SACTS, 2009b. Integrated Biological and Behavioral Surveillance Survey (IBBS) among Injecting Drug Users in Pokhara Valley Round IV Kathmandu. FHI/New ERA/SACTS, 2009c. Integrated Biological and Behavioral Surveillance Survey (IBBS) among Male Injecting Drug Users (IDUs) in the Eastern Terai of Nepal Round IV Kathmandu. FHI/New ERA/SACTS, 2009d. Integrated Biological and Behavioral Surveillance Survey (IBBS) among Male Injecting Drug Users (IDUs) in Western to Far-Western Terai of Nepal Round III Kathmandu. FHI/New ERA/SACTS, 2009e. Integrated Biological and Behavioral Surveillance Survey (IBBS) among Men who have Sex with Men (MSM)) in the Kathmandu Valley Round III Kathmandu. FHI/SACTS, Kathmandu Female Sex Workers Sero Prevalence Study (March August 2001). Kathmandu. FHI/SACTS, Kathmandu Sex Workers Sero Prevalence Study (March August 2001). Kathmandu. HSCB/NCASC, UNGASS Country Progress Report Nepal Kathmandu. Karki BB, Rapid Assessment among Drug Users in Nepal. AIDS Watch 5 (20), p.3. NCASC Ministry of Health and Population Nepal Government, National Estimates of Adult HIV Infections Nepal Kathmandu. NCASC Ministry of Health His Majesty s Government of Nepal, National Estimates of Adult HIV Infections Nepal Kathmandu. NCASC, National Estimates of HIV Infections Nepal Kathmandu. NCASC/Central Bureau of Statistics Government of Nepal National Planning Commission, Nepal in Figures Kathmandu. NCASC/FHI/New ERA/SACTS, 2008a. Integrated Biological and Behavioral Surveillance Survey among Female Sex Workers Pokhara Valley Round III Kathmandu. NCASC/FHI/New ERA/SACTS, 2008b. Integrated Biological and Behavioral Surveillance Survey among Female Sex Workers Kathmandu Valley Round III Kathmandu. NCASC/FHI/New ERA/SACTS, 2008c. Integrated Biological and Behavioural Surveillance Survey among Male Labour Migrants in 11 Districts in Western and Mid-Far Western Regions of Nepal Round II Kathmandu. 35

50 National Estimates of HIV Infections Nepal 2009 NCASC/FHI/New ERA/SACTS, 2008d. Integrated Biological and Behavioural Surveillance Survey among Wives of Migrant Laborers in Four Districts of Far Western Regions of Nepal - Round I Kathmandu. NCASC, Situation Analysis of HIV/AIDS in Nepal. National Centre for AIDS and STD Control. Kathmandu. Silverman J. et al., HIV Prevalence and Predictors of Infection in Sex-Trafficked Nepalese Girls and Women. JAMA 298 (5), p.536. United Nations Development Programme, Human Development Report Overcoming Barriers: Human Mobility and Development. New York: Palgrave Macmillan. 36

51 National Estimates of HIV Infections Nepal 2009 ANNEX 1: Work Flow of the HIV Infections Estimates Process 19 March 2010 Concept note shared with Strategic Information Technical Working Group (SI-TWG) and comments received 25 March 2010 Estimation Technical Team (ETT) workshop held 26 March 2010 Process update shared with SI-TWG 4 April 2010 Draft results shared with Estimation Technical Team (ETT), Estimation Advisory Group (EAG), and National Centre for AIDS and STD Control (NCASC) 6 April 2010 Draft results shared with SI-TWG and comments received 8 April 2010 Final results shared with SI-TWG, EAG and wider stakeholders including government, civil society, donors and media 11 April 2010 Country estimates submitted to UNAIDS headquarters in Geneva to contribute to global estimates 15 July 2010 Nepal confirmed final country estimates to global HIV and STI surveillance group and UNAIDS 28 and 29 July 2010 Final report preparation technical workshop held 5 and 6 August 2010 Validation and finalization of report during national SI retreat with key stakeholders at national level 37

52 National Estimates of HIV Infections Nepal 2009 ANNEX 2: Source of Population Size Estimates, 2009 Population Groups Estimated Size Sources IDUs MSM FSWs Clients of FSW Migrants Remaining Males Remaining Females 28, ,691 32, ,421 1,485,499 6,839,077 7,488,215 CBS, 2007 Application of population growth rate to 2007 size estimates Application of population growth rate to 2007 size estimates Application of population growth rate to 2007 size estimates CBS, 2001 absentee population and projected data CBS population and projected data CBS population and projected data ANNEX 3: Uncertainty Analysis 1. Total number of estimated HIV infections amongst adults and children: Year Lower bound 16,717 20,287 23,805 27,298 30,933 34,451 37,840 41,197 44,346 47,054 49,190 51,146 52,370 53,163 54,031 54,180 54,016 53,391 52,590 52,291 51,414 50,591 49,115 46,973 44,728 42,692 Median 19,744 23,905 28,043 32,168 36,270 40,317 44,266 48,052 51,594 54,820 57,660 60,065 61,960 63,292 64,087 64,376 64,373 64,126 63,828 63,528 63,358 63,092 62,517 62,337 62,487 62,916 Upper bound 24,852 30,231 35,537 39,960 44,203 48,235 52,629 57,307 61,170 64,628 67,542 70,103 72,363 74,332 75,574 76,445 76,676 76,715 76,808 77,322 77,498 77,948 78,866 80,205 82,768 85, New HIV infections (adults and children): Year Lower bound 5,169 5,172 5,053 4,976 4,808 4,540 4,220 3,835 3,368 2,879 2,399 2,003 1,628 1, Median 6,906 6,792 6,577 6,275 5,961 5,625 5,313 5,050 4,876 4,760 4,633 4,608 4,691 4,771 4,862 4,967 Upper bound 8,366 8,372 8,122 7,800 7,480 7,118 6,989 7,025 7,045 7,159 7,280 7,479 7,628 7,849 8,045 8,356 38

53 National Estimates of HIV Infections Nepal ART needs: Year Adult (15+) Children Lower bound Median Upper bound Lower bound Median Upper bound 9,113 11,267 13, ,049 1,679 10,028 12,250 14, ,125 1,789 10,929 13,172 15, ,191 1,877 11,724 14,016 16, ,247 1,954 12,411 14,767 17, ,290 2,015 13,053 15,412 18, ,318 2,060 13,651 15,946 18, ,334 2,090 14,184 16,400 19, ,595 2,523 14,653 16,830 19, ,620 2,577 15,207 17,299 19, ,635 2,619 15,863 17,917 20, ,965 3,246 22,195 30,406 38, ,818 3,038 22,547 30,547 38, ,773 2,928 23,082 30,249 37, ,773 2,839 23,696 30,199 37, ,786 2,842 23,681 30,337 37,920 1,130 1,821 2, Mothers needing PMTCT (ARVs and Prophylaxis): Year Lower bound Median 1,656 1,655 1,630 1,585 1,526 1,448 1,373 1,318 1,269 1,228 1,188 1,156 1,121 1,093 1,066 1,050 Upper bound 2,623 2,603 2,585 2,511 2,469 2,359 2,217 2,142 2,106 2,049 2,021 1,998 2,009 2,057 2,073 2, Annual AIDS deaths: Year Lower bound 2,954 3,240 3,513 3,768 3,991 4,186 4,202 4,212 4,119 4,019 3,826 3,778 3,666 3,389 3,192 3,036 Median 3,651 3,961 4,249 4,511 4,742 4,924 4,919 4,913 4,805 4,701 4,461 4,544 4,947 4,642 4,410 4,241 Upper bound 4,488 4,811 5,113 5,374 5,603 5,777 5,741 5,730 5,602 5,487 5,268 5,494 6,321 6,024 5,772 5,514 39

54 National Estimates of HIV Infections Nepal 2009 ANNEX 4: Summary of 2007 Estimates Overall adult HIV prevalence in Nepal was estimated at 0.49%. There were an estimated total of 69,790 people living with HIV. Approximately one in three was women. Groups highest at risk of HIV were IDUs, MSM, FSW and their clients, which highlighted the need to continue focus of prevention efforts amongst the said groups. Based on the epidemiological regions of Nepal, it was found that approximately 50% of all estimated infections occur along the Highway districts; 16% in Kathmandu Valley; 16% in the Far-West region; and 19% in the Remaining Hills. The distribution of estimated HIV infections across different MARP groups were as follows: FSW: 0.7; MSM: 3.6%; IDU: 7.4%; Clients of FSW: 14.4%; Migrants: 38.8%. Approximately 21% of estimated infections were found amongst low-risk rural women - most likely the wives of migrants - indicating the need to strengthen prevention efforts targeting these groups, as such trends signal the worrying trend of HIV spreading to the general population. Strategies are needed to address prevention needs amongst migrants and their spouses including: firstly, better access to these mobile populations and secondly, strengthen behaviour change communication to reduce engagement in risky behaviours abroad and simultaneously initiate prevention programmes amongst the spouses. 456 new HIV infections emerged amongst children under the age of 14 An estimated 19,366 PLHIV were in need of ARV 2007 estimations included the following limitations: Estimates of size and HIV prevalence amongst MSM outside of Kathmandu Valley was not available; Reliable data on size and prevalence of HIV amongst migrants was also lacking; Sentinel surveillance amongst ANC attendees and STI patients have not been carried out since 2001, therefore the most appropriate proxy for general population prevalence was not available; There exists a lot of data and studies on HIV prevalence and high-risk groups in urban areas, but very little is known about the situation in rural areas. Although it is acknowledged that the Highway district carries the major burden of the epidemic, it was concluded that better understanding of who is infected and the modes of transmission in the other regions are required. This was to ensure appropriate prevention plans and programmes and ensure the availability of care, treatment and support to everyone that needs it. In other words, programmes that focus on IDUs, MSM, FSWs and their clients should be expanded to increase coverage, while at the same time, maintaining the quality and intensity of prevention efforts. Similarly, interventions targeting migrants and their spouses need to be scaled-up and concentrated on migration-heavy areas. Note: For more information, see National Estimates of HIV Infections, 2007, NCASC Also visit 40

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