Mahmoud Khodadost, Hamid Sharifi, Ahmad Hajebi, Seyed Abbas Motevalian
{"title":"绘制和估计伊朗主要受影响人口的规模:方法问题。","authors":"Mahmoud Khodadost, Hamid Sharifi, Ahmad Hajebi, Seyed Abbas Motevalian","doi":"10.47176/mjiri.39.103","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Reliable estimates of key affected populations (KAPs), including people who inject drugs (PWID) and people who use drugs (PWUD), are essential for effective human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and harm reduction programming. This study compares how 3 methodological adjustments collectively modify PWID/PWUD size estimates across 4 Iranian cities.</p><p><strong>Methods: </strong>Using data from mapping exercises in 4 Iranian cities (Ahvaz, Sari, Yazd, and Tehran), we applied 3 methodological adjustments: (1) frequency adjustment (correcting for infrequent hotspot attendance); (2) duplication adjustment (accounting for multihotspot visitors); and (3) hidden population adjustment (incorporating KAPs avoiding mappable sites). Input parameters were derived from field surveys and national studies, including the Iranian Mental Health Survey.</p><p><strong>Results: </strong>Frequency adjustment increased initial PWID estimates (eg, Ahvaz: from 843 to 2104), while duplication adjustment reduced them by 29% to 37%. Hidden population adjustment (assuming 76% of PWID avoid hotspots) yielded final estimates of 1966 (Ahvaz), 854 (Sari), 663 (Yazd), and 28 (Tehran). PWUD estimates followed similar trends, although hidden population adjustments were limited by data gaps.</p><p><strong>Conclusion: </strong>Standard hotspot mapping significantly underestimates KAP sizes if methodological biases are unaddressed. Our 3-step adjustment framework enhances accuracy but highlights limitations, including reliance on mobility assumptions and accuracy of the available national survey data. These findings advocate for integrating correction factors into KAP surveillance systems to optimize resource allocation for harm reduction.</p>","PeriodicalId":18361,"journal":{"name":"Medical Journal of the Islamic Republic of Iran","volume":"39 ","pages":"103"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12516427/pdf/","citationCount":"0","resultStr":"{\"title\":\"Mapping and Estimating the Size of Key Affected Populations in Iran: Methodological Issues.\",\"authors\":\"Mahmoud Khodadost, Hamid Sharifi, Ahmad Hajebi, Seyed Abbas Motevalian\",\"doi\":\"10.47176/mjiri.39.103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Reliable estimates of key affected populations (KAPs), including people who inject drugs (PWID) and people who use drugs (PWUD), are essential for effective human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and harm reduction programming. This study compares how 3 methodological adjustments collectively modify PWID/PWUD size estimates across 4 Iranian cities.</p><p><strong>Methods: </strong>Using data from mapping exercises in 4 Iranian cities (Ahvaz, Sari, Yazd, and Tehran), we applied 3 methodological adjustments: (1) frequency adjustment (correcting for infrequent hotspot attendance); (2) duplication adjustment (accounting for multihotspot visitors); and (3) hidden population adjustment (incorporating KAPs avoiding mappable sites). Input parameters were derived from field surveys and national studies, including the Iranian Mental Health Survey.</p><p><strong>Results: </strong>Frequency adjustment increased initial PWID estimates (eg, Ahvaz: from 843 to 2104), while duplication adjustment reduced them by 29% to 37%. Hidden population adjustment (assuming 76% of PWID avoid hotspots) yielded final estimates of 1966 (Ahvaz), 854 (Sari), 663 (Yazd), and 28 (Tehran). PWUD estimates followed similar trends, although hidden population adjustments were limited by data gaps.</p><p><strong>Conclusion: </strong>Standard hotspot mapping significantly underestimates KAP sizes if methodological biases are unaddressed. Our 3-step adjustment framework enhances accuracy but highlights limitations, including reliance on mobility assumptions and accuracy of the available national survey data. These findings advocate for integrating correction factors into KAP surveillance systems to optimize resource allocation for harm reduction.</p>\",\"PeriodicalId\":18361,\"journal\":{\"name\":\"Medical Journal of the Islamic Republic of Iran\",\"volume\":\"39 \",\"pages\":\"103\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12516427/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical Journal of the Islamic Republic of Iran\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47176/mjiri.39.103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Journal of the Islamic Republic of Iran","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47176/mjiri.39.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Mapping and Estimating the Size of Key Affected Populations in Iran: Methodological Issues.
Background: Reliable estimates of key affected populations (KAPs), including people who inject drugs (PWID) and people who use drugs (PWUD), are essential for effective human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and harm reduction programming. This study compares how 3 methodological adjustments collectively modify PWID/PWUD size estimates across 4 Iranian cities.
Methods: Using data from mapping exercises in 4 Iranian cities (Ahvaz, Sari, Yazd, and Tehran), we applied 3 methodological adjustments: (1) frequency adjustment (correcting for infrequent hotspot attendance); (2) duplication adjustment (accounting for multihotspot visitors); and (3) hidden population adjustment (incorporating KAPs avoiding mappable sites). Input parameters were derived from field surveys and national studies, including the Iranian Mental Health Survey.
Results: Frequency adjustment increased initial PWID estimates (eg, Ahvaz: from 843 to 2104), while duplication adjustment reduced them by 29% to 37%. Hidden population adjustment (assuming 76% of PWID avoid hotspots) yielded final estimates of 1966 (Ahvaz), 854 (Sari), 663 (Yazd), and 28 (Tehran). PWUD estimates followed similar trends, although hidden population adjustments were limited by data gaps.
Conclusion: Standard hotspot mapping significantly underestimates KAP sizes if methodological biases are unaddressed. Our 3-step adjustment framework enhances accuracy but highlights limitations, including reliance on mobility assumptions and accuracy of the available national survey data. These findings advocate for integrating correction factors into KAP surveillance systems to optimize resource allocation for harm reduction.