Abstract:
This contribution aims to investigate the influence of monthly total rainfall variations
on malaria transmission in the Limpopo Province. For this purpose, monthly total rainfall was
interpolated from daily rainfall data from weather stations. Annual and seasonal trends, as well as
cross-correlation analyses, were performed on time series of monthly total rainfall and monthly
malaria cases in five districts of Limpopo Province for the period of 1998 to 2017. The time series
analysis indicated that an average of 629.5 mm of rainfall was received over the period of study.
The rainfall has an annual variation of about 0.46%. Rainfall amount varied within the five districts,
with the northeastern part receiving more rainfall. Spearman’s correlation analysis indicated that
the total monthly rainfall with one to two months lagged e ect is significant in malaria transmission
across all the districts. The strongest correlation was noticed in Vhembe (r = 0.54; p-value = <0.001),
Mopani (r = 0.53; p-value = <0.001), Waterberg (r = 0.40; p-value =< 0.001), Capricorn (r = 0.37;
p-value = <0.001) and lowest in Sekhukhune (r = 0.36; p-value = <0.001). Seasonally, the results
indicated that about 68% variation in malaria cases in summer—December, January, and February
(DJF)—can be explained by spring—September, October, and November (SON)—rainfall in Vhembe
district. Both annual and seasonal analyses indicated that there is variation in the e ect of rainfall on
malaria across the districts and it is seasonally dependent. Understanding the dynamics of climatic
variables annually and seasonally is essential in providing answers to malaria transmission among
other factors, particularly with respect to the abrupt spikes of the disease in the province.
