A mathematical model capable of capturing age-specific patterns of malaria in areas of sub-Saharan Africa with different transmission intensities is reported this week in Nature Communications. The data obtained from this model may help improve estimates of the population at the highest risk from malaria, and better inform age-targeted disease control.
Jamie Griffin and colleagues created age-related disease burden estimates for sub-Saharan Africa by fitting a model of malaria transmission to data from clinical incidence studies reporting Plasmodium falciparum parasite prevalence and disease incidence across Africa. They showed that young children are mostly affected in highly endemic areas, while in areas of lower transmission many cases also occur in older children and adults, which is possibly due to slower acquisition of natural immunity. This may mean that age-targeted policies will progressively need to be refined.
The overall burden of disease due to malaria has fallen in many parts of Africa in recent years following introduction of more efficient treatment and preventive measures. This work has shown it to be correlated with incidence of the disease shifting towards older ages in regions of low transmission. Monitoring these age-burden changes is therefore important in order to properly adapt disease control measures following changing pattern of infection.