HIV incidence from the first population-based cohort study in India

BMC Infectious Diseases

Rakhi Dandona²  Michel Alary¹  Talasila Sudha³  Sri P Ramgopal²  Mohammed Akbar²  G Md Mushtaq Ahmed²  Vemu Lakshmi³  G Anil Kumar²  Lalit Dandona⁴ 

[1] URESP, Centre de recherche FQRS du CHA universitaire de Québec, Québec, Canada;Public Health Foundation of India, New Delhi, India;Department of Microbiology, Nizam’s Institute of Medical Sciences, Hyderabad, India;Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA

关键词: Spouse;    Rural;    Population-based cohort;    India;    HIV incidence;   

Others  :  1146932
DOI  :  10.1186/1471-2334-13-327

 received in 2012-10-23, accepted in 2013-06-27,  发布年份 2013

【 摘 要 】

Background

Understanding about who acquires new HIV infection and the determinants of why some persons get infected and others do not is fundamental to controlling HIV in the population. We assess HIV incidence and its associations in the population of a high HIV burden district in Andhra Pradesh state in southern India by a population-based longitudinal cohort study.

Methods

We re-surveyed a population-based cohort of 12,617 adults in Guntur district of Andhra Pradesh for which we had reported a baseline HIV prevalence of 1.72% (rural 1.64%, urban 1.89%) among the 15–49 years age group in 2004–2005. We conducted interviews to assess risk behaviour and performed HIV testing again in 2010–2011. We assessed the rate of new HIV infection and its associations using multiple logistic regression.

Results

The participation rate in the follow-up was 74.9% and 63.9% of the baseline rural and urban samples, respectively. Over a mean follow-up of 5.63 years, the incidence of HIV was 1.26 per 1000 person-years (95% CI 0.83-1.69), after adjusting for slight compositional bias in the follow-up sample. The incidence per 1000 person-years was higher among rural men (1.68) than urban men (0.85), and among rural women (1.28) than urban women (0.54). The strongest association with incidence was a HIV positive spouse in the baseline for both men (odds ratio 266, 95% CI 62–1137) and women (odds ratio 28, 95% CI 9–88). Among men the other significant associations with HIV incidence were frequent use of condom for sex over the past 6 months, non-circumcision, more than one lifetime woman sex partner or ever visited sex worker, and transport-related occupation; for women the other significant associations were having had HIV testing other than antenatal check-up, previously married but currently not, and tobacco use.

Conclusion

These first population-based cohort incidence data from India suggest that rural areas of high HIV burden states would need more attention to prevent new HIV infections, and that spouses of HIV positive persons and some other risk groups need to be targeted more effectively by HIV prevention programmes.

【 授权许可】

   
2013 Dandona et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Ahmed S, Lutalo T, Wawer M, Serwadda D, Sewankambo NK, Nalugoda F, Makumbi F, Wabwire-Mangen F, Kiwanuka N, Kigozi G, et al.: HIV incidence and sexually transmitted disease prevalence associated with condom use: a population study in Rakai, Uganda. AIDS 2001, 15(16):2171-2179.
• [2]Aulagnier M, Wendy J, Beer ID, Rooy G, Gaeb E, Hesp C, Gaag J, Wit TFR: Incidence of HIV in Windhoek, Namibia: Demographic and Socio-Economic Associations. PLoS One 2011, 6(10):e25860.
• [3]Barnighausen T, Tanser F, Gqwede Z, Mbizana C, Herbst K, Newell ML: High HIV incidence in a community with high HIV prevalence in rural South Africa: findings from a prospective population-based study. AIDS 2008, 22(1):139-144.
• [4]Feldblum PJ, Latka MH, Lombaard J, Chetty C, LChen P, Sexton C, Fischer S: HIV incidence and prevalence among cohorts of women with higher risk behaviour in Bloemfontein and Rustenburg, South Africa: a prospective study. BMJ Open 2012, 2(1):e000626.
• [5]Geis S, Maboko L, Saathoff E, Hoffmann O, Geldmacher C, Mmbando D, Samky E, LMichael N, Birx DL, Robb ML, et al.: Risk factors for HIV-1 infection in a longitudinal, prospective cohort of adults from the Mbeya Region, Tanzania. J Acquir Immune Defic Syndr 2011, 56(5):453-459.
• [6]Kamali A, Carpenter LM, Whitworth JA, Pool R, Ruberantwari A, Ojwiya A: Seven-year trends in HIV-1 infection rates, and changes in sexual behaviour, among adults in rural Uganda. AIDS 2000, 14(4):427-434.
• [7]Kumwenda N, Hoffman I, Chirenje M, Kelly C, Coletti A, Ristow A, Martinson F, Brown J, Chilongozi D, Richardson B, et al.: HIV incidence among women of reproductive age in Malawi and Zimbabwe. Sex Transm Dis 2006, 33(11):646-651.
• [8]Lopman B, Nyamukapa C, Mushati P, Mupambireyi Z, Mason P, Garnett GP, Gregson S: HIV incidence in 3 years of follow-up of a Zimbabwe cohort–1998–2000 to 2001–03: contributions of proximate and underlying determinants to transmission. Int J Epidemiol 2008, 37(1):88-105.
• [9]Mmbaga EJ, Hussain A, Leyna GH, Klouman E, Masenga E, Sam N, Mnyika KS, Klepp K: Incidence of HIV-1 infection and changes in prevalence of reproductive tract infections and sexual risk behaviours: a population-based longitudinal study in rural Tanzania. Afr J AIDS Res 2006, 5(3):281-288.
• [10]Ruzagira E, Wandiembe S, Abaasa A, Levin J, Bwanika A, Bahemuka U, Price MA, Kamali A: Prevalence and Incidence of HIV in a Rural Community-Based HIV Vaccine Preparedness Cohort in Masaka, Uganda. PLoS One 2011, 6(6):e20684.
• [11]Shafer LA, Biraro S, Nakivingi-Miro J, Kamali A, Ssematimba D, Ouma J, Ojwiva A, Hughes P, Paal L, Whitworth J, et al.: HIV prevalence and incidence are no longer falling in southwest Uganda: evidence from a rural population cohort 1989–2005. AIDS 2008, 22(13):1641-1649.
• [12]Wambura M, Urassa M, Isingo R, Ndege M, Marston M, Slaymaker E, Mngara J, Changalucha J, Boerma TJ, Zaba B: HIV prevalence and incidence in rural Tanzania: results from 10 years of follow-up in an open-cohort study. J Acquir Immune Defic Syndr 2007, 46(5):616-623.
• [13]Center for Disease Control and Prevention: Interim recommendations for the use of the BED capture enzyme immunoassay for incidence estimation and surveillance. Atlanta, GA: Center for Disease Control and Prevention, Office of the Global AIDS Coordinator; 2006.
• [14]Williams B, Gouws E, Wilkinson D, Karim SA: Estimating HIV incidence rates from age prevalence data in epidemic situations. Stat Med 2001, 20:2003-2016.
• [15]Dandona L, Dandona R: Drop of HIV estimate for India to less than half. Lancet 2007, 370:1811-1813.
• [16]UNAIDS: Global report: UNAIDS report on the global AIDS epidemic 2010. Geneva: UNAIDS; 2010.
• [17]National AIDS Control Organization (NACO): Technical report India HIV estimates. New Delhi: Ministry of Health & Family Welfare Government of India; 2010.
• [18]Dandona L, Lakshmi V, Sudha T, Kumar GA, Dandona R: A population-based study of human immunodeficiency virus in south India reveals major differences from sentinel surveillance-based estimates. BMC Med 2006, 4:31. BioMed Central Full Text
• [19]Becker ML, Ramesh BM, Washington RG, Halli S, Blanchard JF, Moses S: Prevalence and determinants of HIV infection in South India: a heterogeneous, rural epidemic. AIDS 2007, 21(6):739-747.
• [20]Pandey A, Reddy DC, Ghys PD, Thomas M, Sahu D, Bhattacharya M, Maiti KD, Arnold F, Kant S, Khera A, et al.: Improved estimates of India’s HIV burden in 2006. Indian J Med Res 2009, 129(1):50-58.
• [21]Banandur P, Rajaram SP, Mahagaonkar SB, Bradley J, Ramesh BM, Washington RG, Blanchard JF, Moses S, Lowndes CM, Alary M: Heterogeneity of the HIV epidemic in the general population of Karnataka state, south India. BMC Publ Health 2011, 11(Suppl 6):S13. BioMed Central Full Text
• [22]Registrar General of India: Census of India 2001: Primary Census Abstract: Andhra Pradesh. New Delhi: Office of the Registrar General of India; 2001.
• [23]Registrar General of India: Census of India 2011: Provisional Population Totals Paper 2 of 2011: Andhra Pradesh. New Delhi: Office of the Registrar General of India; 2011.
• [24]Abrahams M, Ram D, Das S, Britt RP: Use of the WHO hemoglobin color scale in family welfare clinics in India. Southeast Asian J Trop Med Public Health 2005, 36(4):976-978.
• [25]Bennett S, Woods T, Liyanage WM, Smith DL: A simplified general method for cluster-sample surveys of health in developing countries. World Health Stat Quart 1991, 44:98-106.
• [26]Dandona L, Dandona R, Kumar GA, Reddy GB, Ameer MA, Ahmed GM, Ramgopal SP, Akbar M, Sudha T, Lakshmi V: Risk factors associated with HIV in a population-based study in Andhra Pradesh state of India. Int J Epidemiol 2008, 37:1274-1286.
• [27]International Institute for Population Sciences (IIPS) and ORC Macro: National Family Health Survey (NFHS-2), 1998–99: India. Mumbai: IIPS; 2000.