{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:44:39Z","timestamp":1785545079712,"version":"3.56.0"},"reference-count":30,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Public Health Surveill"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Accurate population size estimates (PSE) of key populations\u2014those disproportionately affected by HIV\u2014are critical to forecast need and inform HIV prevention and treatment programs, though they can be difficult to ascertain due to low visibility of these groups. In Zambia, reliable estimates on the number of people who inject drugs are limited, inhibiting public health response.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We sought to estimate the population size of people who inject drugs in 3 large cities in Zambia, assess how PSEs vary across different estimation methods, and explore the strengths and limitations of each approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We applied 2-source capture-recapture (2S-CRC), 3-source capture-recapture (3S-CRC), and successive sampling population size estimation (SS-PSE) methods in Lusaka, Livingstone, and Ndola, Zambia. 3S-CRC methods included location-based 2S-CRC in combination with a respondent-driven sampling (RDS) survey. Data were collected from November 2021 to February 2022 and analyzed using a Bayesian nonparametric latent class model. SS-PSEs were produced using the RDS recruitment and network sizes. Kruskal tests and general linear models were used to examine sociodemographic and behavioral factors associated with being captured in 2S-CRC among RDS participants. Final city population estimates, incorporating 3S-CRC and SS-PSE with imputed visibility estimates, were generated using a Bayesian consensus estimator.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Bayesian consensus PSEs ranged between 0.5% and 1.8% of the adult male population and were below 1% of the total adult population in each city. Consensus estimates were highest in Lusaka (3700, 95% credible interval [CRI] 1500\u20107500), followed by Ndola (2200, 95% CRI 1600\u20102900) and Livingstone (1200, 95% CRI 900\u20101,900). There was variability in estimates by method, with SS-PSE with imputed visibility generally providing the lowest estimates across cities, excluding Lusaka. Across methods, PSEs and uncertainty bounds (95% confidence interval [CI] or CRI depending on method) ranged from 1510 (95% CRI 1030\u20102070) to 4350 (95% CI 1410\u201018,890) in Lusaka, 360 (95% CI 290\u2010530) to 2620 (95% CRI 1510\u20104680) in Livingstone, and 760 (95% CI 390\u20103060) to 4030 (95% CRI 960\u20105480) in Ndola. In all cities, fewer recaptures occurred in capture 3 (RDS) than with location sampling via 2S-CRC. Though results varied across cities, RDS participants captured through 2S-CRC differed from those captured solely through RDS in sociodemographic and behavioral risk factors, including housing, education, injection or needle sharing frequency, time since last injection, receipt of drug treatment, and experience with a peer educator in at least one city.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study used rigorous methods to produce PSEs in Zambia, and is the first to produce these for major geographies in the country. Through RDS, 3S-CRC reached people who inject drugs with distinct characteristics that were less accessible via location-based sampling (2S-CRC), yielding a PSE that may better reflect the population and informing the Bayesian consensus estimate. Findings from this study can guide program planning and future surveillance activities.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/66551","type":"journal-article","created":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T21:13:32Z","timestamp":1753910012000},"page":"e66551-e66551","source":"Crossref","is-referenced-by-count":0,"title":["Estimating the Population Size of People Who Inject Drugs in 3 Cities in Zambia: Capture-Recapture, Successive Sampling, and Bayesian Consensus Estimation Methods"],"prefix":"10.2196","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5119-5811","authenticated-orcid":false,"given":"Lauren","family":"Parmley","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1699-4324","authenticated-orcid":false,"given":"Giles","family":"Reid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0013-0206","authenticated-orcid":false,"given":"Joyce J","family":"Neal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7008-6691","authenticated-orcid":false,"given":"Brave","family":"Hanunka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3004-6742","authenticated-orcid":false,"given":"Leigh","family":"Tally","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4285-4293","authenticated-orcid":false,"given":"Lophina","family":"Chilukutu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9788-8399","authenticated-orcid":false,"given":"Tepa","family":"Nkumbula","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8942-9379","authenticated-orcid":false,"given":"Chipili","family":"Mulemfwe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7962-2711","authenticated-orcid":false,"given":"Lazarous","family":"Chelu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3757-5738","authenticated-orcid":false,"given":"Ray","family":"Handema","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3408-3321","authenticated-orcid":false,"given":"John","family":"Mwale","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2721-276X","authenticated-orcid":false,"given":"Kennedy","family":"Mutale","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1044-4209","authenticated-orcid":false,"given":"Lloyd","family":"Mulenga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6611-9002","authenticated-orcid":false,"given":"Anne F","family":"McIntyre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5816-8197","authenticated-orcid":false,"given":"Neena M","family":"Philip","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9080-9036","authenticated-orcid":false,"given":"Hannah","family":"Chung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9748-9273","authenticated-orcid":false,"given":"Maria","family":"Lahuerta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,7,30]]},"reference":[{"key":"R1","unstructured":"The urgency of now: AIDS at a crossroads. UNAIDS. 2024. URL: https:\/\/www.unaids.org\/sites\/default\/files\/media_asset\/2024-unaids-global-aids-update_en.pdf [Accessed 28-05-2025]"},{"issue":"1S","key":"R2","doi-asserted-by":"publisher","first-page":"e34","DOI":"10.1097\/QAI.0000000000003340","article-title":"New HIV infections among key populations and their partners in 2010 and 2022, by world region: a multisources estimation","volume":"95","author":"Korenromp","journal-title":"J Acquir Immune Defic Syndr"},{"issue":"5","key":"R3","doi-asserted-by":"publisher","first-page":"e659","DOI":"10.1016\/S2214-109X(23)00057-8","article-title":"Epidemiology of injecting drug use, prevalence of injecting-related harm, and exposure to behavioural and environmental risks among people who inject drugs: a systematic review","volume":"11","author":"Degenhardt","journal-title":"Lancet Glob Health"},{"key":"R4","unstructured":"Findings from a formative assessment among people who inject drugs in selected towns in Zambia, 2020. ICAP at Columbia University; 2021."},{"key":"R5","unstructured":"Ministry of Legal Affairs, Government of the Republic of Zambia. Chapter 96. In: The Narcotic Drugs and Psychotropic Substances Act. Government of the Republic of Zambia; 1993. URL: https:\/\/www.zambialaws.com\/consolidated-statutes\/principal-legislation\/218-chapter-96narcotic-drugs-and-psychotropic-substances-act [Accessed 25-06-2025]"},{"key":"R6","unstructured":"Formative assessment of HIV risk and size estimation using census and enumeration methods among key populations most at risk of HIV in Zambia. Lusaka: Population Council, National HIV\/AIDS\/STI\/TB Council, Tropical Diseases Research Centre, and University of California, San Francisco; 2016."},{"key":"R7","unstructured":"Size estimation of people who inject drugs (PWID) and service mapping in Kabwe, Kitwe and Solwezi. MAINline; 2021."},{"issue":"1","key":"R8","doi-asserted-by":"publisher","DOI":"10.1186\/s12963-022-00286-3","article-title":"Estimating district HIV prevalence in Zambia using small-area estimation methods (SAE)","volume":"20","author":"Mweemba","journal-title":"Popul Health Metr"},{"key":"R9","unstructured":"Zambia country fact sheet 2023. UNAIDS. 2023. URL: https:\/\/www.unaids.org\/en\/regionscountries\/countries\/zambia [Accessed 28-05-2025]"},{"issue":"2","key":"R10","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1093\/oxfordjournals.epirev.a036192","article-title":"Capture-recapture methods in epidemiology: methods and limitations","volume":"17","author":"Hook","journal-title":"Epidemiol Rev"},{"issue":"10","key":"R11","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1016\/s0895-4356(99)00060-8","article-title":"Recommendations for presentation and evaluation of capture-recapture estimates in epidemiology","volume":"52","author":"Hook","journal-title":"J Clin Epidemiol"},{"issue":"4","key":"R12","first-page":"144","volume":"18","author":"Nanan","journal-title":"Chronic Dis Can"},{"key":"R13","unstructured":"WHOCDCUNAIDSFHI360. Biobehavioral survey guidelines for populations at risk for HIV. World Health Organization. 2017. URL: https:\/\/www.who.int\/publications\/i\/item\/978-92-4-151301-2 [Accessed 28-05-2025]"},{"issue":"2","key":"R14","doi-asserted-by":"publisher","first-page":"174","DOI":"10.2307\/3096941","article-title":"Respondent-driven sampling: a new approach to the study of hidden populations","volume":"44","author":"Heckathorn","journal-title":"Soc Probl"},{"issue":"1","key":"R15","doi-asserted-by":"publisher","first-page":"1491","DOI":"10.1214\/14-EJS923","article-title":"Estimating hidden population size using respondent-driven sampling data","volume":"8","author":"Handcock","journal-title":"Electron J Stat"},{"issue":"suppl_1","key":"R16","doi-asserted-by":"publisher","first-page":"i39","DOI":"10.1093\/ije\/dyv097.132","article-title":"If you are not counted, you don\u2019t count: estimating the number of African-American men who have sex with men in San Francisco","volume":"44","author":"Wesson","journal-title":"Int J Epidemiol"},{"key":"R17","unstructured":"McLaughlin KR Handcock MS Johnston LG et al. Inference for the visibility distribution for respondent-driven sampling. Presented at: Joint Statistical Meetings; Aug 8-13, 2015:2259-2267; Seattle, WA."},{"key":"R18","unstructured":"Fellows IE . Shinyrecap: shiny user interface for multiple source capture recapture models. GitHub. URL: https:\/\/fellstat.github.io\/shinyrecap\/ [Accessed 28-05-2025]"},{"key":"R19","unstructured":"Handcock MS Gile KJ Kim B McLaughlin KR . Package \u2018sspse\u2019: estimating hidden population size using respondent driven sampling data. The Comprehensive R Archive Network. URL: https:\/\/cran.r-project.org\/web\/packages\/sspse\/sspse.pdf [Accessed 28-05-2025]"},{"issue":"12","key":"R20","doi-asserted-by":"publisher","first-page":"e1192","DOI":"10.1016\/S2214-109X(17)30375-3","article-title":"Global prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review","volume":"5","author":"Degenhardt","journal-title":"Lancet Glob Health"},{"key":"R21","unstructured":"Handcock MS Gile KJ Fellows IEF Neely WW . RDS: respondent-driven sampling. 2012. URL: https:\/\/CRAN.R-project.org\/package=RDS [Accessed 28-05-2025]"},{"key":"R22","unstructured":"Fellows IE . Derive consensus estimates of a population quantity from multiple empirical estimates using a hierarchical bayesian model. GitHub. URL: https:\/\/github.com\/fellstat\/triangulator"},{"key":"R23","unstructured":"Adjusted population projections for HIV-related program planning based on 2010 Zambia Census. ZamStat; 2021."},{"issue":"3","key":"R24","doi-asserted-by":"publisher","DOI":"10.2196\/12118","article-title":"Estimating the size of key populations in Kampala, Uganda: 3-source capture-recapture study","volume":"5","author":"Doshi","journal-title":"JMIR Public Health Surveill"},{"issue":"9","key":"R25","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0256949","article-title":"National and subnational size estimation of female sex workers in Ghana 2020: comparing 3-source capture-recapture with other approaches","volume":"16","author":"Guure","journal-title":"PLoS One"},{"issue":"10","key":"R26","doi-asserted-by":"publisher","DOI":"10.2196\/34555","article-title":"Key population size estimation to guide HIV epidemic responses in Nigeria: bayesian analysis of 3-source capture-recapture data","volume":"8","author":"McIntyre","journal-title":"JMIR Public Health Surveill"},{"key":"R27","doi-asserted-by":"publisher","DOI":"10.1017\/S0950268821000595","article-title":"Female sex workers population size estimation in Rwanda using a three-source capture-recapture method","volume":"149","author":"Musengimana","journal-title":"Epidemiol Infect"},{"key":"R28","doi-asserted-by":"publisher","DOI":"10.2196\/43114","article-title":"Population size estimation of men who have sex with men in Rwanda: three-source capture-recapture method","volume":"9","author":"Tuyishime","journal-title":"JMIR Public Health Surveill"},{"issue":"2","key":"R29","doi-asserted-by":"publisher","first-page":"194","DOI":"10.2991\/jegh.k.210312.001","article-title":"Population size estimation of female sex workers in Hai Phong, Vietnam: use of three source capture-recapture method","volume":"11","author":"Nguyen","journal-title":"J Epidemiol Glob Health"},{"key":"R30","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2014.06.022","article-title":"Estimating the size of the population of persons who inject drugs in the island of Montr\u00e9al, Canada, using a six-source capture-recapture model","volume":"142","author":"Leclerc","journal-title":"Drug Alcohol Depend"}],"container-title":["JMIR Public Health and Surveillance"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/publichealth.jmir.org\/2025\/1\/e66551","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:28:42Z","timestamp":1785536922000},"score":1,"resource":{"primary":{"URL":"https:\/\/publichealth.jmir.org\/2025\/1\/e66551"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,30]]},"references-count":30,"URL":"https:\/\/doi.org\/10.2196\/66551","relation":{},"ISSN":["2369-2960"],"issn-type":[{"value":"2369-2960","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,30]]},"article-number":"v11i1Se66551"}}