OBJECTIVE: Seasonal migration may be an important driver of the HIV epidemic in India; however, migrant sexual behaviour data are limited. This study assessed the extent to which migration could explain heterogeneity in HIV prevalence in Bagalkot district, in Karnataka state, India, examining important migration-related risk factors for HIV transmission and implications for prevention. DESIGN: We used mathematical modelling to explore the potential impact of different seasonal migration patterns on HIV prevalence. METHODS: A deterministic compartmental mathematical model of heterosexually transmitted HIV infection was developed. Six migration scenarios were explored, depending on which population migrated (men/clients only/female sex workers; FSW), and which local population determined the demand for commercial sex while migrants were away. RESULTS: The impact of migration varied substantially across the six migration scenarios. Migration was unlikely to explain heterogeneity in HIV prevalence unless a fraction of all men migrated and local FSW drove the demand for commercial sex. Even with very high-risk migrant sexual behaviour in the migration destination, targeting interventions at 30%-100% of local core groups could prevent a maximum of 12%-40% of new infections (87% effective condoms), from 2004-2015. Targeting migrants locally and at their destination could have up to 1.6-times the impact of targeting migrants only at their destination. CONCLUSIONS: Results suggest that core group interventions introduced locally because of the difficulty of reaching migrant populations could still be beneficial. Understanding how local sexual networks change during migration is crucial for understanding the impact of migration on HIV transmission, and for designing HIV preventive interventions.
OBJECTIVE: Seasonal migration may be an important driver of the HIV epidemic in India; however, migrant sexual behaviour data are limited. This study assessed the extent to which migration could explain heterogeneity in HIV prevalence in Bagalkot district, in Karnataka state, India, examining important migration-related risk factors for HIV transmission and implications for prevention. DESIGN: We used mathematical modelling to explore the potential impact of different seasonal migration patterns on HIV prevalence. METHODS: A deterministic compartmental mathematical model of heterosexually transmitted HIV infection was developed. Six migration scenarios were explored, depending on which population migrated (men/clients only/female sex workers; FSW), and which local population determined the demand for commercial sex while migrants were away. RESULTS: The impact of migration varied substantially across the six migration scenarios. Migration was unlikely to explain heterogeneity in HIV prevalence unless a fraction of all men migrated and local FSW drove the demand for commercial sex. Even with very high-risk migrant sexual behaviour in the migration destination, targeting interventions at 30%-100% of local core groups could prevent a maximum of 12%-40% of new infections (87% effective condoms), from 2004-2015. Targeting migrants locally and at their destination could have up to 1.6-times the impact of targeting migrants only at their destination. CONCLUSIONS: Results suggest that core group interventions introduced locally because of the difficulty of reaching migrant populations could still be beneficial. Understanding how local sexual networks change during migration is crucial for understanding the impact of migration on HIV transmission, and for designing HIV preventive interventions.
Authors: Stevan Weine; Alexandra Golobof; Mahbat Bahromov; Adrianna Kashuba; Tohir Kalandarov; Jonbek Jonbekov; Sana Loue Journal: Women Health Date: 2013
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Authors: Sharmistha Mishra; Satyanarayana Ramanaik; James F Blanchard; Shiva Halli; Stephen Moses; T Raghavendra; Parinita Bhattacharjee; Rob Lorway; Marissa Becker Journal: BMC Public Health Date: 2012-09-28 Impact factor: 3.295
Authors: Souradet Y Shaw; Kathleen N Deering; Sushena Reza-Paul; Shajy Isac; Banadakoppa M Ramesh; Reynold Washington; Stephen Moses; James F Blanchard Journal: BMC Public Health Date: 2011-12-29 Impact factor: 3.295
Authors: Kathleen N Deering; Marie-Claude Boily; Catherine M Lowndes; Jean Shoveller; Mark W Tyndall; Peter Vickerman; Jan Bradley; Kaveri Gurav; Michael Pickles; Stephen Moses; Banadakoppa M Ramesh; Reynold Washington; S Rajaram; Michel Alary Journal: BMC Public Health Date: 2011-12-29 Impact factor: 3.295
Authors: Sangeeta S Dave; Andrew Copas; John Richens; Richard G White; Jayendrakumar K Kosambiya; Vikas K Desai; Judith M Stephenson Journal: PLoS One Date: 2012-08-27 Impact factor: 3.240