Modeling time taken to HIV testing and uptake of test results: application of extended PWP model

Abstract

Improving HIV testing among the most at risk populations (MARP) is one of the first steps to achieve the Sustainable Development Goal target of ending AIDS by 2030. Factors affecting time taken to HIV testing and subsequent clinic visits to uptake the test result are important inputs for development of HIV prevention programmes. This study aims to develop multivariate statistical models to describe HIV testing behavior of MARP. HIV testing data of 5667 Female Sex Workers registered with the National HIV Prevention Programme in 10 districts of Sri Lanka during 2016 and 2017 were modelled using univariate and multivariate survival analysis techniques. Results showed that the Prentice, Williams & Peterson gap time model (PWPGTM), and all univariate Cox Proportional Hazard Models together generated consistent results. However, higher number of effects of the factors and interaction effects were detected in the PWPGTM compared to other models. Further, PWPGTM generated more precise estimates with lower standard errors. In all the models, most of the factors were identified as time dependent covariates. Study concludes that the extended PWPGTM is the more appropriate technique to model time taken to HIV testing and subsequent clinic visit to uptake of test results among MARP.

KEYWORDS:

• HIV testing
• multiple ordered events
• PWP model
• time-dependent covariates
• multivariate survival model

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No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

M. Suchira Suranga

M. Suchira Suranga is a Monitoring & Evaluation and Programme Management Specialist with 15 years of experience in 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), South Asian Regional Office, and International Planned Parenthood Federation (IPPF). Also, he worked in Helpage, World vison 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. Mr. Suranga is a member of Sri Lanka Institute of Applied Statistics and the joint secretory of the Sri Lanka Evaluation Association. Mr. Suranga serves as a visiting lecturer and an examiner for the Post Graduate Diploma in Evaluation, University of Sri Jayewardenepura.

S. Samita

Prof. 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. Prof. Samita 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. Prof. Samita 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. Prof. Samita 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.