| Autor: |
Abiodun GJ; Research Unit, Foundation for Professional Development, Pretoria, South Africa.; Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa., Njabo KY; Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, California, USA., Witbooi PJ; Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa., Adeola AM; South African Weather Service, Private Bag X097, Pretoria 0001, South Africa.; School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa., Fuller TL; Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, California, USA., Okosun KO; Department of Mathematics, Vaal University of Technology, X021, Vanderbijlpark 1900, South Africa., Makinde OS; Department of Statistics, Federal University of Technology, P.M.B 704, Akure, Nigeria., Botai JO; South African Weather Service, Private Bag X097, Pretoria 0001, South Africa.; Department of Geography, Geoinformation and Meteorology, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa. |
| Abstrakt: |
The recent resurgence of malaria incidence across epidemic regions in South Africa has been linked to climatic and environmental factors. An in-depth investigation of the impact of climate variability and mosquito abundance on malaria parasite incidence may therefore offer useful insight towards the control of this life-threatening disease. In this study, we investigate the influence of climatic factors on malaria transmission over Nkomazi Municipality. The variability and interconnectedness between the variables were analyzed using wavelet coherence analysis. Time-series analyses revealed that malaria cases significantly declined after the outbreak in early 2000, but with a slight increase from 2015. Furthermore, the wavelet coherence and time-lagged correlation analyses identified rainfall and abundance of Anopheles arabiensis as the major variables responsible for malaria transmission over the study region. The analysis further highlights a high malaria intensity with the variables from 1998-2002, 2004-2006, and 2010-2013 and a noticeable periodicity value of 256-512 days. Also, malaria transmission shows a time lag between one month and three months with respect to mosquito abundance and the different climatic variables. The findings from this study offer a better understanding of the importance of climatic factors on the transmission of malaria. The study further highlights the significant roles of An. arabiensis on malaria occurrence over Nkomazi. Implementing the mosquito model to predict mosquito abundance could provide more insight into malaria elimination or control in Africa. |
