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Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa

Bibliographic Data

ID15495997
AuthorsAbiodun M Adeola (0000-0002-6105-7110, South African Weather Service, corresponding author), Katlego P Ncongwane (0000-0002-3923-1530, South African Weather Service), Katlego Ncongwane (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa), Gbenga J Abiodun (0000-0002-6805-2128, Southern Methodist University), Gbenga Abiodun (Southern Methodist University), Thabo Makgoale (0000-0002-5197-4353, South African Weather Service), Hannes Rautenbach (0000-0002-3292-5396, Education Labour Relations Council), Joel O Botai (0000-0003-4355-0662, South African Weather Service), Omolola M Adisa (0000-0002-5733-4664, Central University of Technology), Christina M Botai (0000-0003-3498-539X, South African Weather Service), Christina Botai (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)
Year2019
Volume16
Issue24
Pages5156-5156
Publication date2019-12-17
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph16245156
PMID31861127
OpenAlexW2995657342
LanguageEN
Citations received6
References cited31

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 = p -value = p -value = p -value = 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

Environmental health · Environmental protection · Geography · Malaria · Socioeconomics · Global Health and Epidemiology · Medicine

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Citations per year1.2
Citation span2021 - 2026 (6)
Highly citedNo

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