6/19/2014. Typhoid fever disease burden estimates. Methods: Revisiting the global burden of typhoid fever. Methodology- Ivanoff et al.

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1 Typhoid fever disease burden estimates Methods: Revisiting the global burden of typhoid fever Dr. Vittal Mogasale, MBBS, MPH, PhD International Vaccine Institute Ivanoff et al. (1994): 16.6 million cases and 580,000 deaths Crump et al. (2004): 21.6 million cases and 216,000 deaths Buckle et al. (2012): 26.9 million cases and 269,000 deaths Lozano et al. (2012); Murray et al. (2012): 190,000 deaths (Typhoid and Paratyphoid) 12.2 million DALY lost IHME estimates (2014?) IVI estimates (2014; under review Lancet ID) 11.8 vs.20.5 million cases; 129,000 vs 223,000 deaths 2 Methodology- Ivanoff et al. (1994) Based on an international workshop on typhoid fever-1986 No methodology presented Incidence/10 5 Cases (10 6 ) Deaths Africa ,000 Asia ,000 Latin America ,000 Oceania Developed Total ,198 Methodology- Crump et al 2004 Review of population based blood culture (BC) confirmed incidence (1954 to 2000) Prospective studies only Incidence extrapolated to country & regions 22 studies from 13 countries; Africa (3), Asia (7), Europe (7) Assumptions: CFR= 1%; BC sensitivity=50% 3 4 1

2 Methodology- Buckle et al Methodology- GBD studies 2012 Systematic review for population based BC confirmed incidence studies Prospective studies and annual reports Incidence extrapolated to country & regions 25 studies; 5 from Africa, 15 from Asia Assumptions: CFR= 1%; BC sensitivity=50% Includes non-bc studies (Lutui et al 1999; Dunn 2005) Includes model based results (Chen et al 2007) Multiple publications from same sites Missing studies (Owais et al 2010) 5 Specific methodology for typhoid fever is not published Sates natural history model for incidence, prevalence and mortality Only DALYs and deaths are presented in GBD paper Estimation of number of cases (GBD 2013) on going and not published 6 GBD 2013 approach: unpublished Modelling incidence via Bayesian metaregression (Dismod tool) Incidence data from cohort studies and national surveillance data (BC confirmed) Model uses proportion of population has access to improved water Correction for passive surveillance in model Data from 35 sources; Asia (21), Africa (10) Assumption: BC sensitivity 55% Detailed methods and results are not available 7 Analysis gaps in previous publications Population based estimates Several studies published after Crump. et al 4 studies published after Buckle et al Local heterogeneity e.g. Regional differences were considered, but the derived estimates were applied to whole country Risk differences e.g. No studies considered high or low risk within region/country; important for risk-based strategies Case fatality rate e.g. Does it make sense to apply same CFR (1%)? globally, when factors associated with CFR vary 8 2

3 Identification Screening Eligibility Inclusion Identification Screening Eligibility Inclusion Systematic literature Review- typhoid incidence Systematic literature Review- blood culture (BC) sensitivity Systematic literature Review -risk factor related to water BC sensitivity correction Risk factor correction Community representative typhoid incidence studies (field sites) Incidence in At risk population Site specific incidence Corrected site specific incidence Age specific incidence extrapolated to UN region Incidence in high-risk population Study specific correction for operational issues Age distribution correction No correction Review: prospective TF incidence-1990 to 2013 Records from PubMed (n=1,834) Records from Embase (n=2,230) Records after removal of duplication (n=3,491) Additional records from WHO/PAHO (n=256)) Records screened (n = 3,747) Records excluded (n=3,635) Full text articles assessed for eligibility (n=112) Literature Review-case fatality rate Weak evidence Risk factor adjusted Overall incidence cases Typhoid deaths Sensitivity analysis Risk factor un-adjusted Overall incidence cases Typhoid deaths 9 Studies included in qualitative synthesis (n=35) Studies included in quantitative synthesis (n=22) Full text articles excluded with reasons(n=77) Data Availability Review: access to improved water 22 papers, 20 distinct sites Records from PubMed (n=292) Records from Embase (n=425) Records after removal of duplication (n=610) Additional records from WHO/PAHO (n=82) Records screened (n = 692) Full text articles assessed for eligibility (n=80) Records excluded (n=612) Full text articles excluded with reasons (n=58) Studies included in qualitative synthesis (n=30) E Africa 3 N Africa 2 W Africa1 S Africa 1 S Asia-5 SE Asia-4 E Asia-2 11 Studies included in quantitative synthesis (n=18) Final inclusion for meta-analysis (n=12) 3

4 Identification Screening Eligibility Inclusion Access to improved water: meta-analysis Review: blood culture sensitivity Records from PubMed (n=2,005) Records from Embase (n=3,142) Records after removal of duplication (n=4,720) Additional records from WHO/PAHO (n=165) Records screened (n = 4,722) Full text articles assessed for eligibility (n=90) Records excluded (n=4,632) Full text articles excluded with reasons (n=49) If a water source was microbiologically unsafe (WHO definition, >1 CFU/mL Escherichia coli), it was considered unimproved Base case analysis: OR =2.44; 95% CI Sensitivity analysis=no risk factor correction 13 Studies included in qualitative synthesis (n=41) Studies included in quantitative synthesis (n=10) Exclusion in meta-analysis (n=0) Final inclusion for meta-analysis (n=10) Blood culture sensitivity-weighted average Extrapolation Base case analysis =61%; 95% CI 52%-70.3% Sensitivity analysis=50%; 95% CI 40%-60% 15 *Excluded North America, Europe and Australian region 16 4

5 Incidence/100,000 Results Typhoid fever incidence map Higher incidence rates in W, E, and Middle African regions Lower incidence rates in Asian, American, S. African regions Revised analysis and with risk factor correction Revised analysis and without risk factor correction Extrapolated from 1980s studies in Chile and South Africa Crump extrapolation with 2010 population structure Typhoid fever case fatality rate Difficult to collect from community based studies One study in our review has CFR In absence of data most common value used is 1% Hospital based CFR data is available More evidence to say rest of the world compared to Africa has lower CFR CFR in hospitalized cases: weighted average 28 studies from countries Crump et al 2008 data CFR=2.77%; 95%CI =1.95%; 3.59%

6 Hospitalization rate: weighted average Bootstrapping for sensitivity analysis 13 estimates from review H rate=7.7%; 95%CI =4.3%; 11.1% 21 For conservative estimates assumed no deaths outside hospitals Estimated overall CFR = hospitalization rate*cfr among hospitalized Bootstrapping for 1000 times based on random CFR and random hospitalization rate Estimated mean overall CFR, 2.5 & 97.5 percentiles for sensitivity limits (0.43%, 0.49%, 0.55%) Base case assumption: 0.55%, 1%, 1.95% 22 CFR- sensitivity analysis assumptions High CFR Beta-PRT (0.55%, 1%, 1.95%) Typhoid fever burden-ivi estimate Region Median CI Lower CI Upper Low CFR Beta-PRT (0.43%, 0.49%, 0.55%) Africa Asia Latin America/Caribbean Total cases Total deaths Cases Deaths Cases Deaths Cases Deaths 3,090,395 2,504,427 3,829,277 33,490 19,294 53,147 8,616,595 6,886,651 11,161,349 93,377 53, , , , ,933 1,908 1,085 3,128 11,883,047 9,925,551 14,751, ,775 75, ,

7 Millions Greatest sources of uncertainty Typhoid cases: scenario analysis Risk factor correction Blood culture sensitivity Case fatality rate (deaths only) Studies/age groups with high incidence rates, which are extrapolated to large populations % BC sensitivity & RF adjusted 61%BC sensitivity & RF unadjusted 50% BC sensitivity & RF unadjusted Buckle et al estimation 2013 Extrapolation of Crump et al to 2010 population 0 Episodes Typhoid deaths: sensitivity analysis Limitations 350, , , , , ,000 50, , , , , ,046 76,589 61% BC sensitivity & RF adjusted 61%BC sensitivity & RF unadjusted 50% BC sensitivity & RF unadjusted Buckle et al estimation 2013 Extrapolation of Crump et al to 2010 population 61% BC sensitivity & RF adjusted & Low CFR One correction factor- access to improved water, applied throughout regions No recent data from Latin America Uses English language (However, Buckle et al 2013 did not find any additional publications in Spanish, Italian, French and Portuguese) Limited information for CFR estimation African data will be improved with TSAP results 0 Deaths

8 Summary of IVI estimates Questions Incidence estimate is reduced compared to previous estimate Risk factor correction & blood culture sensitivity Deaths comparable to previous studies, potentially lower when sensitivity analysis was done Approach is useful in estimating population impact and cost-effectiveness of risk based vaccination strategies Should we use risk-factor corrected disease burden or uncorrected? IVIR-AC s critical view and recommendations on Extrapolation methods of data points Risk factor adjustment CFR Sensitivity of blood culture Research gaps to be addressed in short term