A systematic review of changing malaria disease burden in sub-Saharan Africa since 2000: comparing model predictions and empirical observations.

ABSTRACT: BACKGROUND:The most widely used measures of declining burden of malaria across sub-Saharan Africa are predictions from geospatial models. These models apply spatiotemporal autocorrelations and covariates to parasite prevalence data and then use a function of parasite prevalence to predict clinical malaria incidence. We attempted to assess whether trends in malaria cases, based on local surveillance, were similar to those captured by Malaria Atlas Project (MAP) incidence surfaces. METHODS:We undertook a systematic review (PROSPERO International Prospective Register of Systematic Reviews; ID?=?CRD42019116834) to identify empirical data on clinical malaria in Africa since 2000, where reports covered at least 5 continuous years. The trends in empirical data were then compared with the trends of time-space matched clinical malaria incidence from MAP using the Spearman rank correlation. The correlations (rho) between changes in empirically observed and modelled estimates of clinical malaria were displayed by forest plots and examined by meta-regression. RESULTS:Sixty-seven articles met our inclusion criteria representing 124 sites from 24 African countries. The single most important factor explaining the correlation between empirical observations and modelled predictions was the slope of empirically observed data over time (rho?=?-?0.989; 95% CI -?0.998, -?0.939; p?

SUBMITTER: Kamau A 

PROVIDER: S-EPMC7189714 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature