Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa

Abiodun Adeola, Katlego Ncongwane, Gbenga Abiodun, Thabo Makgoale, Hannes Rautenbach, Joel Botai, Omolola Adisa and Christina Botai
Additional contact information
Abiodun Adeola: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
Katlego Ncongwane: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
Gbenga Abiodun: Department of Mathematics, Southern Methodist University, Dallas, TX 75275, USA
Thabo Makgoale: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
Hannes Rautenbach: UP Institute for Sustainable Malaria Control, School for Health Systems and Public Health, University of Pretoria, Pretoria 0002, South Africa
Joel Botai: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
Omolola Adisa: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
Christina Botai: South African Weather Service, Private Bag X097, Pretoria 0001, South Africa

IJERPH, 2019, vol. 16, issue 24, 1-15

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 effect 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 effect 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.

Keywords: malaria; rainfall; time series; trends; annual; seasonal (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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