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This article is part of the supplement: Learning from large scale prevention efforts: findings from Avahan

Open Access Research

Heterogeneity of the HIV epidemic in the general population of Karnataka state, south India

Pradeep Banandur12*, Subramanian Potty Rajaram134, Sangameshwar B Mahagaonkar3, Janet Bradley3, Banadakoppa M Ramesh4, Reynold G Washington45, James F Blanchard6, Stephen Moses6, Catherine M Lowndes7 and Michel Alary1389

Author Affiliations

1 CHARME II Project, Bangalore 560044, India

2 Department of Community Medicine, Rajarajeswari Medical College and Hospital, Bangalore 560074, India

3 CHARME I Project, Bangalore 560044, India

4 Karnataka Health Promotion Trust, Bangalore 560044, India

5 Infectious Diseases Unit, St John’s Research Institute, Bangalore 560034, India

6 University of Manitoba, Winnipeg, Canada

7 Health Protection Agency, London, UK

8 URESP, Centre de recherche du CHA universitaire de Québec, Québec, Canada

9 Département de médecine sociale et préventive, Université Laval, Québec, Canada

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BMC Public Health 2011, 11(Suppl 6):S13  doi:10.1186/1471-2458-11-S6-S13

Published: 29 December 2011

Abstract

Background

In the context of AVAHAN, the India AIDS Initiative of the Bill & Melinda Gates Foundation, general population surveys (GPS) were carried out between 2006 and 2008 in Belgaum (northern), Bellary (mid-state) and Mysore (southern) districts of Karnataka state, south India. Data from these three surveys were analysed to understand heterogeneity in HIV risk.

Methods

Outcome variables were the prevalence of HIV and sexually transmitted infections (STIs). Independent variables included age, district, place of residence, along with socio-demographic, medical and behavioural characteristics. Multivariate logistic regression was undertaken to identify characteristics associated with HIV and differences between districts, incorporating survey statistics to consider weights and cluster effects.

Results

The participation rate was 79.0% for the interview and 72.5% for providing a blood or urine sample that was tested for HIV. Belgaum had the highest overall HIV (1.43%) and Herpes simplex type-2 (HSV-2) (16.93%) prevalence, and the lowest prevalence of curable STIs. In Belgaum, the HIV epidemic is predominantly rural, and among women. In Bellary, the epidemic is predominantly in urban areas and among men, and HIV prevalence was 1.18%. Mysore had the lowest prevalence of HIV (0.80%) and HSV-2 (10.89%) and the highest prevalence of curable STIs. Higher HIV prevalence among men was associated with increasing age (p<0.001), and with history of STIs (AOR=2.44,95%CI:1.15-5.17). Male circumcision was associated with lower HIV prevalence (AOR=0.33,95%CI:0.13-0.81). Higher HIV prevalence among women was associated with age (AOR25-29years=11.22,95%CI:1.42-88.74, AOR30-34years=13.13,95%CI:1.67-103.19 and AOR35-39years=11.33,95%CI:1.32-96.83), having more than one lifetime sexual partner (AOR=4.61,95%CI:1.26-16.91) and having ever used a condom (AOR=3.32,95%CI:1.38-7.99). Having a dissolved marriage (being widowed/divorced/separated) was the strongest predictor (AOR=10.98,95%CI: 5.35-22.57) of HIV among women. Being a muslim woman was associated with lower HIV prevalence (AOR=0.27,95%CI:0.08-0.87).

Conclusion

The HIV epidemic in Karnataka shows considerable heterogeneity, and there appears to be an increasing gradient in HIV prevalence from south to north. The sex work structure in the northern districts may explain the higher prevalence of HIV in northern Karnataka. The higher prevalence of HIV and HSV-2 and lower prevalence of curable STIs in Belgaum suggests a later epidemic phase. Similarly, higher prevalence of curable STIs and lower HIV and HSV-2 prevalence in Mysore suggests an early phase epidemic.