Prevalence of asymptomatic malaria and associated factors in Ethiopia: Systematic review and meta-analysis

Active detection of asymptomatic malaria cases and resolution of associated factors are essential for malaria elimination. There are no nationwide estimates for asymptomatic malaria and associated factors in Ethiopia. Therefore, this study aims to generate comprehensive and conclusive evidence from various studies conducted in Ethiopia. Published articles from various electronic databases such as PubMed, Google Scholar, CINAHL, Scopes, Cochrane Library, the Web of Science, and African Journals Online were accessed. Also, unpublished studies from Addis Ababa digital library were identified. All observational study designs were included in the search. Data were extracted on the Microsoft Excel spreadsheet and analyzed using STATA version 14.1. A random-effects model was fitted to estimate the pooled prevalence of asymptomatic malaria. A meta-regression and subgroup analysis was computed to see heterogeneity. The publication bias was assessed by the funnel plots and Egger’s statistical tests. The analysis found that the pooled burden of asymptomatic malaria was 6.7 (95% confidence interval = 4.60, 8.79). The pooled prevalence of Plasmodium falciparum was 3.75 (95% confidence interval = 2.25, 5.18), and that of Plasmodium vivax was 2.22 (95% confidence interval = 1.46, 2.99). Factors such indoor residual spray service (odds ratio = 0.46; 95% confidence interval = 0.26, 0.81), never used insecticide-treated nets (odds ratio = 6.36; 95% confidence interval = 4.01, 10.09), and presence of stagnant water in the vicinity (odds ratio = 3.24; 95% confidence interval = 1.20, 8.71) were found to have a significant association with asymptomatic malaria. This study highlighted that pooled prevalence of asymptomatic malaria is high and varied by population groups. Prevalence of asymptomatic malaria was increased among those who never used insecticide-treated nets and were living near stagnant water by six and three times, respectively. The use of more sensitive diagnostic methods could yield a higher burden of the disease. Furthermore, active case detection is recommended for effective intervention toward elimination.