Pradeep Kumar, Chinmoyee Das, Bhawani Singh Khushwaha, Saiprasad P Bhavsar, Shantanu Kumar Purohit, Arvind Kumar, Subrata Biswas, Nidhi Priyam, Lalit Singh Kharayat, Shajan Mathew, Akhilesh Srivastava, Jyotsana Pal, Shreena Ramanathan, Abhina Aher, Deepika Srivastava Joshi, Rajatashuvra Adhikary, Shajy Isac, H Sanayaima Devi, P V M Lakshmi, Elangovan Arumugam, Sanjay K Rai, Sheela V Godbole, S K Singh, Himanshu K Chaturvedi, Shanta Dutta, Shashi Kant, Dandu Chandra Sekhar Reddy, Sanjay Mehendale, Shobini Rajan
{"title":"印度关键人口的规划制图和人口规模估计:方法和结果。","authors":"Pradeep Kumar, Chinmoyee Das, Bhawani Singh Khushwaha, Saiprasad P Bhavsar, Shantanu Kumar Purohit, Arvind Kumar, Subrata Biswas, Nidhi Priyam, Lalit Singh Kharayat, Shajan Mathew, Akhilesh Srivastava, Jyotsana Pal, Shreena Ramanathan, Abhina Aher, Deepika Srivastava Joshi, Rajatashuvra Adhikary, Shajy Isac, H Sanayaima Devi, P V M Lakshmi, Elangovan Arumugam, Sanjay K Rai, Sheela V Godbole, S K Singh, Himanshu K Chaturvedi, Shanta Dutta, Shashi Kant, Dandu Chandra Sekhar Reddy, Sanjay Mehendale, Shobini Rajan","doi":"10.1371/journal.pgph.0004475","DOIUrl":null,"url":null,"abstract":"<p><p>India has the world's second-largest HIV burden. Key populations of female sex workers (FSW), men who have sex with men (MSM), hijra/transgender (H/TG) people, and people who inject drugs (PWID), are disproportionately affected by the HIV epidemic. A community-led programmatic mapping and population size estimation (PMPSE) was carried out in 651 districts of 32 States and Union Territories of India. The goal was to identify the hotspots, network operators, and estimate the size of key population groups. This involved documenting the known hotspots, visiting them for rapid field assessment through key informants'/ network operators interviews, and identifying additional hotspots/ network operators through the snow-balling approach from the existing hotspots. For each identified hotspot, network operator, and village, size of each key population group was estimated after adjusting for the duplications and overlaps. These estimates were then aggregated to arrive at district, State, and ultimately national-level estimates. PMPSE estimated a total of 9,95,499 (9,02,277-10,88,712) FSWs, 3,51,020 (3,13,860-3,88,175) MSM, 2,88,717 (2,53,024-3,24,407) PWIDs, and 96,193 (85,206-1,07,174) H/TG individuals. The number of FSWs per 1000 adult women in different States/Union Territories (UT) varied from 0.34 to 17.25; MSM estimates ranged from 0.07 to 7.35 per 1000 adult men, H/TG persons ranged from 0.03 to 2.75 per 1000 adult men, and PWIDs ranged from 0.01 to 31.30 per 1000 adult men. Additionally, approximately 14% of FSWs, 7% of MSM, and 8% of H/TG individuals were estimated to operate exclusively through network operators. The community-led PMPSE has updated the size estimates for FSWs, MSM, PWIDs, and H/TG individuals at a granular level. This approach has emphatically quantified the presence of network operators. The methodological simplicity of the present round of PMPSE is likely to encourage and facilitate its periodic implementation for better tracking of population level changes in HIV burden based on more reliable denominators.</p>","PeriodicalId":74466,"journal":{"name":"PLOS global public health","volume":"5 5","pages":"e0004475"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12057993/pdf/","citationCount":"0","resultStr":"{\"title\":\"Programmatic mapping and population size estimation of key population in India: Method and findings.\",\"authors\":\"Pradeep Kumar, Chinmoyee Das, Bhawani Singh Khushwaha, Saiprasad P Bhavsar, Shantanu Kumar Purohit, Arvind Kumar, Subrata Biswas, Nidhi Priyam, Lalit Singh Kharayat, Shajan Mathew, Akhilesh Srivastava, Jyotsana Pal, Shreena Ramanathan, Abhina Aher, Deepika Srivastava Joshi, Rajatashuvra Adhikary, Shajy Isac, H Sanayaima Devi, P V M Lakshmi, Elangovan Arumugam, Sanjay K Rai, Sheela V Godbole, S K Singh, Himanshu K Chaturvedi, Shanta Dutta, Shashi Kant, Dandu Chandra Sekhar Reddy, Sanjay Mehendale, Shobini Rajan\",\"doi\":\"10.1371/journal.pgph.0004475\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>India has the world's second-largest HIV burden. Key populations of female sex workers (FSW), men who have sex with men (MSM), hijra/transgender (H/TG) people, and people who inject drugs (PWID), are disproportionately affected by the HIV epidemic. A community-led programmatic mapping and population size estimation (PMPSE) was carried out in 651 districts of 32 States and Union Territories of India. The goal was to identify the hotspots, network operators, and estimate the size of key population groups. This involved documenting the known hotspots, visiting them for rapid field assessment through key informants'/ network operators interviews, and identifying additional hotspots/ network operators through the snow-balling approach from the existing hotspots. For each identified hotspot, network operator, and village, size of each key population group was estimated after adjusting for the duplications and overlaps. These estimates were then aggregated to arrive at district, State, and ultimately national-level estimates. PMPSE estimated a total of 9,95,499 (9,02,277-10,88,712) FSWs, 3,51,020 (3,13,860-3,88,175) MSM, 2,88,717 (2,53,024-3,24,407) PWIDs, and 96,193 (85,206-1,07,174) H/TG individuals. The number of FSWs per 1000 adult women in different States/Union Territories (UT) varied from 0.34 to 17.25; MSM estimates ranged from 0.07 to 7.35 per 1000 adult men, H/TG persons ranged from 0.03 to 2.75 per 1000 adult men, and PWIDs ranged from 0.01 to 31.30 per 1000 adult men. Additionally, approximately 14% of FSWs, 7% of MSM, and 8% of H/TG individuals were estimated to operate exclusively through network operators. The community-led PMPSE has updated the size estimates for FSWs, MSM, PWIDs, and H/TG individuals at a granular level. This approach has emphatically quantified the presence of network operators. 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Programmatic mapping and population size estimation of key population in India: Method and findings.
India has the world's second-largest HIV burden. Key populations of female sex workers (FSW), men who have sex with men (MSM), hijra/transgender (H/TG) people, and people who inject drugs (PWID), are disproportionately affected by the HIV epidemic. A community-led programmatic mapping and population size estimation (PMPSE) was carried out in 651 districts of 32 States and Union Territories of India. The goal was to identify the hotspots, network operators, and estimate the size of key population groups. This involved documenting the known hotspots, visiting them for rapid field assessment through key informants'/ network operators interviews, and identifying additional hotspots/ network operators through the snow-balling approach from the existing hotspots. For each identified hotspot, network operator, and village, size of each key population group was estimated after adjusting for the duplications and overlaps. These estimates were then aggregated to arrive at district, State, and ultimately national-level estimates. PMPSE estimated a total of 9,95,499 (9,02,277-10,88,712) FSWs, 3,51,020 (3,13,860-3,88,175) MSM, 2,88,717 (2,53,024-3,24,407) PWIDs, and 96,193 (85,206-1,07,174) H/TG individuals. The number of FSWs per 1000 adult women in different States/Union Territories (UT) varied from 0.34 to 17.25; MSM estimates ranged from 0.07 to 7.35 per 1000 adult men, H/TG persons ranged from 0.03 to 2.75 per 1000 adult men, and PWIDs ranged from 0.01 to 31.30 per 1000 adult men. Additionally, approximately 14% of FSWs, 7% of MSM, and 8% of H/TG individuals were estimated to operate exclusively through network operators. The community-led PMPSE has updated the size estimates for FSWs, MSM, PWIDs, and H/TG individuals at a granular level. This approach has emphatically quantified the presence of network operators. The methodological simplicity of the present round of PMPSE is likely to encourage and facilitate its periodic implementation for better tracking of population level changes in HIV burden based on more reliable denominators.