Background

As malaria transmission declines, continued improvements of prevention and control

interventions will increasingly rely on accurate knowledge of risk factors and an ability to

define high-risk areas and populations at risk for focal targeting of interventions. This paper

explores the independent association between living in a hotspot and prospective risk of

malaria infection.

Methods

Malaria infection status defined by nPCR and AMA-1 status in year 1 were used to define

geographic hotspots using two geospatial statistical methods (SaTScan and Kernel density

smoothing). Other malaria risk factors for malaria infection were explored by fitting a

multivariable model.

Results

This study demonstrated that residing in infection hotspot of malaria transmission is an

independent predictor of malaria infection in the future.

Conclusion

It is likely that targeting such hotspots with better coverage and improved malaria control

strategies will result in more cost-efficient uses of resources to move towards malaria

elimination.