期刊名称：International Journal of Statistics and Applications
印刷版ISSN：2168-5193
电子版ISSN：2168-5215
出版年度：2019
卷号：9
期号：6
页码：171-179
DOI：10.5923/j.statistics.20190906.01
语种：English
出版社：Scientific & Academic Publishing Co.
摘要：In Kenya, approximately 1.5 Million people are living with HIV and 28,000 deaths are recorded annually as a result of AIDS related illnesses. The country was considered a priority country by UNAIDS when it launched a 90-90-90 strategy in 2014. The strategy aimed to diagnose 90 per cent of all HIV-positive persons, provide antiretroviral therapy (ART) for 90 percent of those diagnosed, and achieve viral suppression for 90 per cent of those treated by 2020. This study is motivated by the need to assess the 3rd 90; viral suppression for 90 per cent of those ART treated and seeks to evaluate the two statistical paradigms (Frequentist and Bayesian) that have conventionally been used for geo-spatial trends analysis. The use of Frequentist approach or Bayesian approach has been used previously to assess the prevalence and incidence of diseases; this study however, seeks to compare the two approaches when analyzing spatial trends of HIV viral load suppression in Kenya. In revisiting the theoretical framework of the two approaches and application of real data from the Kenyan setting spanning from 2012 to 2017, results show the Bayesian approach as more robust and in depth and entailing more information when modeling spatial trends of viral load suppression. Further, first line ART regimen, HIV-TB co-infection and retention rates are significant predictors of viral load suppression.
