Abstract
Improving HIV testing among the populations at high risk is one of the first steps to achieving the Sustainable Development Goal target of ending AIDS by 2030. This study aims to develop multivariate statistical models to describe the HIV testing behavior of most at-risk populations. HIV testing data of 5667 Female Sex Workers (FSWs) registered with the National HIV Prevention Programme in 10 districts of Sri Lanka during 2016 and 2017 were modeled using univariate and multivariate survival analysis techniques. As the proportional hazard assumption was violated, the Prentice Williams & Peterson (PWP) model was extended to include time-dependent covariates. The results show that the PWP gap time model and all univariate Cox Proportional Hazard Models generated consistent results. However, a higher number of effects of factors and their interactions were detected in the gap time model than in univariate models. The gap time model generated more precise estimates with lower standard errors compared to the total time model. The study concludes that the PWP model can be extended to handle time-dependent covariates. The PWP gap model is the more appropriate technique to model the time taken for HIV testing and subsequent clinic visit to uptake test results among Most at-risk Populations.
Acknowledgements
Dr. Ariyaratne Manatunga, Ms. Thushara Agus, Mr. Amal Bandara, Mr. Duminda Rajakaruna, Mr. Janaranga Dewasurendra, Ms. Nilanthi Weerasinghe, Ms. Natasha De Rosyro, All the Community-Based Organizations, All the STD clinic staff, and All the participants in the study
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability
The data that support the findings of this study are available from the corresponding author on reasonable request.
Ethical approval
The research protocol and other related documents were submitted to the ethical review committee (ERC) of the Sri Lanka Medical Association (SLMA) for ethical approval and exemption for ethical review was received on 20th April 2018 (ERC – 18-007) as the study is based on the secondary data and there is no direct involvement of human participants.
Informed consent from the respondents
Not Applicable
Additional information
Funding
Notes on contributors
M. Suchira Suranga
M. Suchira Suranga is a Monitoring & Evaluation Specialist with 15 years of experience in the national and international development projects and organizations. He is currently working as the Director (Organizational Learning and Evaluation) at FPA Sri Lanka. He worked in the capacity of Senior Technical Adviser (Organizational Learning and Evaluation) at the South Asian Regional Office of the International Planned Parenthood Federation (IPPF). Also, he worked in Helpage, World Vision and RDC and held various responsibilities. He completed B.Sc. degree in Agricultural Economics, M.Sc. degree in Bio-statistics, M.Sc. degree in Organizational Management and M.Phil degree in Reproductive Health at the University of Peradeniya. He is a member of Institute of Applied Statistics of Sri Lanka (IASSL) and the joint secretory of the Sri Lanka Evaluation Association (SLEvA). He serves as a visiting lecturer, evaluation supervisor, and as an examiner for the Post Graduate Diploma in Evaluation, University of Sri Jayewardenepura.
S. Samita
S. Samita is Professor of Bio-Statistics attached to University of Peradeniya, Sri Lanka. He completed his Ph.D in Bio-Statistics at University of Edinburgh, United Kingdom, M.Phil. In Biometry and B.Sc. in Agriculture at University of Peradeniya, Sri Lanka. He has over 30 years of experience in teaching, research supervision and conducting research at various national and international academic institutions in the field of Bio-Statistics. He served as the Director of Postgraduate Institute of Agriculture during 2014–2017 and the Chairperson of the Board of Study Bio-Statistics, University of Peradeniya during 2002–2007. He served as the President of Institute of Applied Statistics Sri Lanka (IASSL) during 2002–2005 and the Secretary of IASSL during 1999–2002. He is an author of several textbooks, book chapters and journal articles and has presented key research findings at national and international conferences. His research interests include Categorical Data Analysis, Epidemiological Statistics and Multivariate Statistics.