Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa

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dc.contributor.authorSilal, Sheetal Prakashen_ZA
dc.contributor.authorBarnes, Karen Ien_ZA
dc.contributor.authorKok, Gerdalizeen_ZA
dc.contributor.authorMabuza, Aaronen_ZA
dc.contributor.authorLittle, Francescaen_ZA
dc.date.accessioned2015-11-10T14:49:14Z
dc.date.available2015-11-10T14:49:14Z
dc.date.issued2013en_ZA
dc.description.abstractSouth Africa, having met the World Health Organisation's pre-elimination criteria, has set a goal to achieve malaria elimination by 2018. Mpumalanga, one of three provinces where malaria transmission still occurs, has a malaria season subject to unstable transmission that is prone to sporadic outbreaks. As South Africa prepares to intensify efforts towards malaria elimination, there is a need to understand patterns in malaria transmission so that efforts may be targeted appropriately. This paper describes the seasonality of transmission by exploring the relationship between malaria cases and three potential drivers: rainfall, geography (physical location) and the source of infection (local/imported). Seasonal decomposition of the time series by Locally estimated scatterplot smoothing is applied to the case data for the geographical and source of infection sub-groups. The relationship between cases and rainfall is assessed using a cross-correlation analysis. The malaria season was found to have a short period of no/low level of reported cases and a triple peak in reported cases between September and May; the three peaks occurring in October, January and May. The seasonal pattern of locally-sourced infection mimics the triple-peak characteristic of the total series while imported infections contribute mostly to the second and third peak of the season (Christmas and Easter respectively). Geographically, Bushbuckridge municipality, which exhibits a different pattern of cases, contributed mostly to the first and second peaks in cases while Maputo province (Mozambique) experienced a similar pattern in transmission to the imported cases. Though rainfall lagged at 4 weeks was significantly correlated with malaria cases, this effect was dampened due to the growing proportion of imported cases since 2006. These findings may be useful as they enhance the understanding of the current incidence pattern and may inform mathematical models that enable one to predict the impact changes in these drivers will have on malaria transmission.en_ZA
dc.identifier.apacitationSilal, S. P., Barnes, K. I., Kok, G., Mabuza, A., & Little, F. (2013). Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa. <i>PLoS One</i>, http://hdl.handle.net/11427/14842en_ZA
dc.identifier.chicagocitationSilal, Sheetal Prakash, Karen I Barnes, Gerdalize Kok, Aaron Mabuza, and Francesca Little "Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa." <i>PLoS One</i> (2013) http://hdl.handle.net/11427/14842en_ZA
dc.identifier.citationSilal, S. P., Barnes, K. I., Kok, G., Mabuza, A., & Little, F. (2012). Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa. PloS One, 8(10), e76640. doi:10.1371/journal.pone.0076640en_ZA
dc.identifier.ris TY - Journal Article AU - Silal, Sheetal Prakash AU - Barnes, Karen I AU - Kok, Gerdalize AU - Mabuza, Aaron AU - Little, Francesca AB - South Africa, having met the World Health Organisation's pre-elimination criteria, has set a goal to achieve malaria elimination by 2018. Mpumalanga, one of three provinces where malaria transmission still occurs, has a malaria season subject to unstable transmission that is prone to sporadic outbreaks. As South Africa prepares to intensify efforts towards malaria elimination, there is a need to understand patterns in malaria transmission so that efforts may be targeted appropriately. This paper describes the seasonality of transmission by exploring the relationship between malaria cases and three potential drivers: rainfall, geography (physical location) and the source of infection (local/imported). Seasonal decomposition of the time series by Locally estimated scatterplot smoothing is applied to the case data for the geographical and source of infection sub-groups. The relationship between cases and rainfall is assessed using a cross-correlation analysis. The malaria season was found to have a short period of no/low level of reported cases and a triple peak in reported cases between September and May; the three peaks occurring in October, January and May. The seasonal pattern of locally-sourced infection mimics the triple-peak characteristic of the total series while imported infections contribute mostly to the second and third peak of the season (Christmas and Easter respectively). Geographically, Bushbuckridge municipality, which exhibits a different pattern of cases, contributed mostly to the first and second peaks in cases while Maputo province (Mozambique) experienced a similar pattern in transmission to the imported cases. Though rainfall lagged at 4 weeks was significantly correlated with malaria cases, this effect was dampened due to the growing proportion of imported cases since 2006. These findings may be useful as they enhance the understanding of the current incidence pattern and may inform mathematical models that enable one to predict the impact changes in these drivers will have on malaria transmission. DA - 2013 DB - OpenUCT DO - 10.1371/journal.pone.0076640 DP - University of Cape Town J1 - PLoS One LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa TI - Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa UR - http://hdl.handle.net/11427/14842 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/14842
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pone.0076640
dc.identifier.vancouvercitationSilal SP, Barnes KI, Kok G, Mabuza A, Little F. Exploring the seasonality of reported treated malaria cases in Mpumalanga, South Africa. PLoS One. 2013; http://hdl.handle.net/11427/14842.en_ZA
dc.language.isoengen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_ZA
dc.rights.holder© 2013 Silal et alen_ZA
dc.rights.urihttp://creativecommons.org/licenses/by/4.0en_ZA
dc.sourcePLoS Oneen_ZA
dc.source.urihttp://journals.plos.org/plosoneen_ZA
dc.subject.otherMalariaen_ZA
dc.subject.otherMathematical modelingen_ZA
dc.subject.otherInfectious disease controlen_ZA
dc.titleExploring the seasonality of reported treated malaria cases in Mpumalanga, South Africaen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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