Dengue Virus Infection in Sub-Saharan Africa Between 2010 and 2020: A Systematic Review and Meta-Analysis

Abstract

Dengue virus (DENV) infection has garnered a global interest in the past few decades. Nevertheless, its epidemiology in certain developing and low-income regions remains poorly understood, due to the absence of comprehensive surveillance and reporting systems. This systematic review and meta-analysis aimed to determine the prevalence of DENV infection in the population of Sub-Saharan Africa using DENV infection markers, and to track any changes in its prevalence during the past ten years. It was conducted in accordance with the PRISMA guidelines, targeting the literature available at MEDLINE/PubMed, ScienceDirect, Cochrane library and Google Scholar. All articles published in English language between January 2010 and June 2020 were screened for eligibility. Random effects model was used to calculate the pooled prevalence of all infection markers. The Inconsistency Index (I 2) was used to assess the level of heterogeneity between studies. Subgroup analysis according to country and time-frame of studies was conducted to provide possible explanations to substantial heterogeneity. The critical appraisal tool for prevalence studies designed by the Joanna Briggs Institute (JBI) was used to assess the risk of bias in all included studies. A total of 84 articles, covering 21 countries, were included in this review. Quantitative meta-analysis estimated a pooled IgG prevalence of 25% (95% CI: 21-29%, I 2 = 99%), a pooled IgM prevalence of 10% (95% CI: 9-11%, I 2 = 98%) and a pooled DENV RNA prevalence of 14% (95% CI: 12-16%, I 2 = 99%). Evidence for possible publication bias was also found in all three meta-analyses. Subgroup analysis according to the time of sample collection was performed to closely track the changing prevalence of DENV infection markers between 2010 and 2019. This meta-analysis estimates a high prevalence of DENV infection in Sub-Saharan Africa. More cost-efficient vector control strategies should be designed and implemented in order to adapt to the low-resource nature of this region.