OBJECTIVE : Nkomazi local municipality of South Africa is a high-risk malaria region with an
incidence rate of about 500 cases per 100 000. We examined the influence of environmental factors
on population (age group) at risk of malaria.
methods R software was used to statistically analyse data. Using remote sensing technology, a Landsat
8 image of 4th October 2015 was classified using object-based classification and a 5-m resolution. Spot
height data were used to generate a digital elevation model of the area. RESULTS : A total of 60 718 malaria cases were notified across 48 health facilities in Nkomazi municipality between January 1997 and August 2015. Malaria incidence was highly associated with
irrigated land (P = 0.001), water body (P = 0.011) and altitude ≤400 m (P = 0.001). The multivariate
model showed that with 10% increase in the extent of irrigated areas, malaria risk increased by almost
39% in the entire study area and by almost 44% in the 2-km buffer zone of selected villages. Malaria
incidence is more pronounced in the economically active population aged 15–64 and in males. Both
incidence and case fatality rate drastically declined over the study period. CONCLUSION : A predictive model based on environmental factors would be useful in the effort towards malaria elimination by fostering appropriate targeting of control measures and allocating of resources.