Seasonality of rotavirus disease in the tropics: a systematic review and meta-analysis

Abstract

Background: To date little conclusive evidence exists on the seasonality of rotavirus incidence in the tropics. We present a systematic review and meta-analysis on the seasonal epidemiology of rotavirus in the tropics, including 26 studies reporting continuous monthly rotavirus incidence for which corresponding climatological data was available.

Methods: Using linear regression models that account for serial correlation between months, monthly rotavirus incidence was significantly negatively correlated with temperature, rainfall and relative humidity in 65%, 55% and 60% of studies, respectively. We carried out pooled analyses using a generalized estimating equation (GEE) that accounts for correlation from between-study variation and serial correlation between months within a given study.

Results: For every 1 degrees C (1.8 degrees F) increase in mean temperature, 1 cm (0.39 in.) increase in mean monthly rainfall, and 1% increase in relative humidity (22%) this analysis showed reductions in rotavirus incidence of 10% (95% CI: 6-13%), 1% (95% CI: 0-1%), and 3% (95% CI:0-5%), respectively.

Conclusions: On the basis of the evidence, we conclude that rotavirus responds to changes in climate in the tropics, with the highest number of infections found at the colder and drier times of the year.

Figures

Figure 1

Heterogeneity plots of incidence rate ratios (IRR), showing 95% confidence intervals using Newey West standard errors, for regressions of rotavirus incidence vs: (A) monthly mean temperature (°C); (B) monthly rainfall (cm); and (C) relative humidity (%). The pooled effect from the generalized estimated equation (GEE) analysis is also shown