Data will be analysed using the
‘meta’ packages of the statistical software R (version 3.5.1, The R Foundation for statistical computing, Vienna, Austria). Unadjusted prevalence will be recalculated based on the information of crude numerators and denominators provided by individual studies. Prevalence will be reported with their 95% confidence interval and prediction interval. To keep the effect of studies with extremely small or extremely large prevalence estimates on the overall estimate to a minimum, the variance of the study -specific prevalence will be stabilised with the Freeman-Tukey double arcsine transformation before pooling the data with the random-effects meta-analysis model [
8]. Egger’s test will serve to assess the presence of publication bias [
9]. A
p value < 0.10 on Egger test will be considered indicative of statistically significant publication bias. Heterogeneity will be evaluated by the
χ2 test on Cochrane’s
Q statistic [
10], which will be quantified by
H and
I2 values. The
I2 statistic estimates the percentage of total variation across studies due to true between-study differences rather than chance. In general,
I2 values greater than 60–70% indicate the presence of substantial heterogeneity [
11]. Subgroup analyses will be performed for the following subgroups: age groups (0–5 years versus > 5 years), population (children [≤ 15 years] versus adults), clinical presentation (severe versus benign forms), and UNSD African Regions. Univariable meta-regression will be used to test for an effect of study and participants’ characteristics (year of publication, seasonality, number of screened viruses, clinical presentation, age groups, population, UNSD of regions, absolute latitude [distance to equator], latitude, longitude, and altitude). Following crude overall prevalence, we will conduct two sensitivity analyses to assess the robustness of our findings. The first one will include only studies with low risk of bias and the second only studies reporting data of a full year(s) period (complete season(s)).