Estimation of HIV Prevalence among the Female Population in South India: A Bayesian Approach
A Bayesian Approach
Abstract
Introduction: The HIV Sentinel Surveillance (HSS) conducted by National AIDS Control Organization (NACO) is the predominant data source for HIV estimations in India. While the HSS targets the key populations at risk of HIV infection, the National Family Health Survey (NFHS) measures the community- based HIV prevalence. Improvised HIV estimates in India were attributed to the HIV prevalence data obtained from the NACO-HSS and NFHS.
Methods: Bayesian analysis was performed to determine the state-level prevalence of HIV among females in seven South Indian States. The analysis involved plotting the prior, likelihood, and posterior distributions, facilitating a visual assessment of the data. The HIV prevalence among females calculated from the NFHS (2015-16) survey data was used for prior distributions. HIV prevalence among pregnant women obtained from the HIV Sentinel Surveillance 2019 was used for likelihood. Bayesian analysis was performed using the R programming (RStudio 2022.02.0). A posterior probability distribution was obtained using the prior distribution and the likelihood by applying the Bayes theorem. Graphical representation was achieved through R's plotting functions. Kerala and Pondicherry were not included in the analysis due to zero or very low prevalence reported in both NFHS and HSS.
Results: The Bayesian estimates of HIV prevalence among females were 0.38 % [95% CI:0.29 - 0.47] in Andhra Pradesh, 0.28 [95% CI:0.23 - 0.35] in Karnataka, 0.27 [95% CI:0.20 - 0.34] Odisha, 0.27 % [95% CI:0.19 - 0.36] in Telangana and 0.19 [95% CI:0.15 - 0.24] in Tamil Nadu.
Conclusion: Bayesian techniques present a versatile and robust strategy for modelling and analysing HIV- related data, offering a flexible and powerful approach to data analysis.
2. NACO, ICMR-NIMS. National AIDS Control Organization & ICMR- National Institute of Medical Statistics. India HIV Estimates 2021:Fact Sheet. [Internet]. New Delhi: NACO, Ministry of Health and Family Welfare, Government of India; 2022. Available from: http://naco.gov.in/sites/ default/files/India%20HIV%20Estimates%20 2021%20_Fact%20Sheets__Final_ Shared_24_08_2022_0.pdf
3. Pandey A, Reddy DCS, Ghys PD, Thomas M, Sahu D, Bhattacharya M, et al. Improved estimates of India's HIV burden in 2006. Indian J Med Res [Internet]. 2009;129(1). Available from: https://journals.lww.com/ijmr/ Fulltext/2009/29010/Improved_estimates_of_ India_s_HIV_burden_in_2006.8.aspx .
4. National AIDS Control Organization. ANC HSS 2019: Technical Report. New Delhi: NACO, Ministry of Health and Family Welfare, Government of India; 2020.
5. International Institute for Population Sciences (IIPS) and ICF. 2017. National Family Health Survey (NFHS-4), 2015-16: India. Mumbai: IIPS.
6. Onovo AA, Adeyemi A, Onime D, Kalnoky M, Kagniniwa B, Dessie M, et al. Estimation of HIV prevalence and burden in Nigeria: a Bayesian predictive modelling study. eClinicalMedicine. 2023 Aug;62:102098.
7. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Andhra Pradesh State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
8. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Karnataka State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
9. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Kerala State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
10. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Odisha State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
11. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Puducherry State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
12. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Tamil Nadu State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
13. ICMR - National Institute of Epidemiology (2020). HIV Sentinel Surveillance 2018-19, Telangana State Report : Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
14. Elangovan A, K David J, Aridoss S, Jaganathasamy N, Mathiyazhakan M, Ganesh B, et al. An Analysis of Levels and Trends in HIV Prevalence Among Pregnant Women Attending Antenatal Clinics in Karnataka, South India, 2003-2019. Int J Matern Child Health AIDS IJMA. 2021;10(2):198–209.
15. Elangovan A, Santhakumar A, Mathiyazhakan M, Nagaraj J, David JK, Ganesh B, et al. Sub-regional Trend of HIV Infection Among Antenatal Clinic Attendees in Andhra Pradesh (2003-2019). Curr HIV Res. 202220(4):327–36.
16. Santhakumar A, Mathiyazhakan M, Jaganathasamy N, Ganesh B, Manikandan N, Padmapriya V, et al. Prevalence and Risk Factors Associated with HIV Infection among Pregnant Women in Odisha State, India. Int J Matern Child Health AIDS IJMA. 2020;9(3):411–20.
17. Santhakumar A, Nagaraj J, David JK, Malathi M, Ganesh B, Manikandan N, et al. Levels and trend of HIV prevalence among pregnant women in Tamil Nadu: Analysis of data from HIV sentinel surveillance (2003–2019). Clin Epidemiol Glob Health. 2021;9:280–8.
18. National Institute of Health and Family Welfare (NIHFW) National AIDS Control Organisation (NACO) Annual HIV Sentinel Surveillance, Country Report, 2008-09. New Delhi: NACO, Ministry of Health and Family Welfare Government of India; 2009 [Internet]. Available from: https://www.naco. gov.in/sites/default/files/HIV%20Sentinel%20 Surveillance%20India%20Country%20 Report%2C%202008-09.pdf .
19. Pandey A, Reddy D, Thomas M. What Lies behind the Fall in the HIV Population in India? Econ Polit Wkly. 2008;157.
20. Joseph L, Gyorkos TW, Coupal L. Bayesian Estimation of Disease Prevalence and the Parameters of Diagnostic Tests in the Absence of a Gold Standard. Am J Epidemiol. 1995;141(3):263–72.
21. Wesson PD, Mirzazadeh A, McFarland W. A Bayesian approach to synthesise estimates of the size of hidden populations: the Anchored Multiplier. Int J Epidemiol. 2018;47(5):1636– 44.
22. Aridoss S, Jaganathasamy N, Kumar A, Natesan M, Adhikary R, Arumugam E. Socio-demographic factors associated with HIV prevalence among pregnant women attending antenatal clinics in six Southern States of India: Evidences from the latest round of HIV sentinel surveillance. Indian J Public Health. 2020;64(5):26.
23. Boily MC, Pickles M, Lowndes CM, Ramesh BM, Washington R, Moses S, et al. Positive impact of a large-scale HIV prevention programme among female sex workers and clients in South India. AIDS. 2013;27(9):1449–60.
24. Arjun BY, Unnikrishnan B, Ramapuram JT, Thapar R, Mithra P, Kumar N, et al. Factors Influencing Quality of Life among People Living with HIV in Coastal South India. J Int Assoc Provid AIDS Care JIAPAC. 2017 May;16(3):247–53.
25. Bhatnagar T, Dutta T, Stover J, Godbole S, Sahu D, Boopathi K, et al. Fitting HIV Prevalence 1981 Onwards for Three Indian States Using the Goals Model and the Estimation and Projection Package. Nishiura H, editor. PLOS ONE. 2016;11(10):e0164001.
26. Dunson DB. Commentary: Practical Advantages of Bayesian Analysis of Epidemiologic Data. Am J Epidemiol. 2001;153(12):1222–6.
Files | ||
Issue | Vol 9 No 2 (2023) | |
Section | Original Article(s) | |
DOI | https://doi.org/10.18502/jbe.v9i2.14624 | |
Keywords | ||
HIV Prevalence Sentinel Surveillance Bayesian Analysis India Data Modeling |
Rights and permissions | |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |