{"title":"Modeling time taken to HIV testing and uptake of test results: application of extended PWP model","authors":"M. Suranga, S. Samita","doi":"10.1080/24709360.2021.2017637","DOIUrl":null,"url":null,"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.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"97 - 112"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biostatistics and Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24709360.2021.2017637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
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.
改善最危险人群的艾滋病毒检测是实现到2030年消除艾滋病的可持续发展目标具体目标的首批步骤之一。影响艾滋病毒检测所需时间和随后到诊所接受检测结果的因素是制定艾滋病毒预防规划的重要投入。本研究旨在建立多元统计模型来描述MARP的HIV检测行为。使用单变量和多变量生存分析技术对2016年和2017年期间在斯里兰卡10个地区的国家艾滋病毒预防规划注册的5667名女性性工作者的艾滋病毒检测数据进行建模。结果表明,Prentice, Williams & Peterson间隙时间模型(PWPGTM)和所有单变量Cox比例风险模型共同产生了一致的结果。然而,与其他模型相比,PWPGTM中检测到的因素效应和相互作用效应的数量更多。此外,PWPGTM以更低的标准误差生成了更精确的估计。在所有模型中,大多数因素被确定为时间相关协变量。研究得出结论,扩展的PWPGTM是更合适的技术来模拟HIV检测和随后的诊所就诊时间,以吸收MARP的检测结果。