Magnitude and predictors of HIV-Drug resistance in Africa: A protocol for systematic review and meta-analysis

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Abstract

Human Immunodeficiency Virus (HIV) is continued to be a major public health problem in low-income countries and more importantly in Africa. For the last decade, access to Antiretroviral Therapy (ART) and its impact in improving quality of life and reducing HIV-related morbidity and mortality has significantly been improved in Africa. Nevertheless, the emergency of HIV drug resistance (HIVDR) has posed challenges in achieving optimal ART treatment outcomes and is alarmingly increasing globally in general and in Africa in particular. Comprehensive epidemiological data on the magnitude of HIVDR and HIVDR mutations, and predictors of HIVDR are, however, limited in Africa. Objective The main objective of this systematic review will be to estimate the pooled proportion of HIVDR and HIVDR mutations, and identify factors associated with HIVDR among people living with HIV/AIDS (PLWH) in Africa. Method Published Literature from 2000 until 30 October 2021 will be searched in PubMed/Medline Ovid, HINARI, SCOPUS, EMBASE, CINAHL, Web of Sciences, and Cochrane electronic databases. Initially, the literature will be screened based on title/abstract and followed by full-text appraisal for methodological quality using JBI critical appraisal tools. Data will be extracted from eligible articles after the full-text appraisal. Heterogeneity will be qualitatively assessed by a visual Funnel plot and quantitatively measured by an index of heterogeneity (I2 statistics). Random-effects model will be fitted to estimate the proportion of HIVDR and each HIVDR mutations. Sub-group and sensitivity analyses will be conducted to reduce heterogeneity. Meta-regression will be done by median year of sampling per study to observe the pattern of changes over time. Publication bias will be assessed by egger’s statistics. In case of publication bias, Trim and Fill analysis will be conducted to overcome small-study effect. Data analysis will be performed using Stata version 14.

Original languageEnglish
Article numbere0267159
JournalPLoS ONE
Volume17
Issue number4 April
DOIs
Publication statusPublished - Apr 2022

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