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Assessing the correlation between malaria case mortality rates and specific socioeconomic factors

Dissertation (MSc (Environmental Management))--University of Pretoria, 2019.

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Other Authors: Adeola, Abiodun M.
Format: Thesis
Language:English
Published: University of Pretoria 2024
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access_status_str Open Access
author2 Adeola, Abiodun M.
author_browse Adeola, Abiodun M.
author_facet Adeola, Abiodun M.
collection Thesis
dc_rights_str_mv © 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MSc (Environmental Management))--University of Pretoria, 2019.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:38:24.974Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/97756 Assessing the correlation between malaria case mortality rates and specific socioeconomic factors Adeola, Abiodun M. rynocoetzer11@gmail.com Coetzer, Ryno Harm UCTD Medical facilities Malaria mortality rate Socioeconomic factors Water bodies Dissertation (MSc (Environmental Management))--University of Pretoria, 2019. Background Various local villages in the Vhembe district of South Africa have experienced high malaria infection rates together with a high variability of malaria case mortality rates over the past 20 years. This research project sets out to determine if socioeconomic factors, (specifically the location of medical facilities and a geographical aspects) have a significant influence on the varying malaria case mortality rates. The data from this study could assist societies and authorities in mitigating the negative effects of malaria infections on human life expectancies through improved socioeconomic development. Methods The study used existing medical records of all reported malaria cases in the Vhembe district between 1998 and 2017. The data comprised malaria cases recorded at 263 medical facilities that reported 57 974 infections from 850 source locations across the villages and formal neighbourhoods. The data set was sampled using maximum variation sampling combined with a stratified sampling approach to select the 30 source locations with the highest reported variations in malaria case mortality. The number of medical facilities used, distances to the medical facilities, and proximity to significant water sources were subsequently spatially and statistically analysed for the sample source locations to determine potential correlations between these factors and the malaria case fatality rates of the source locations. Results The statistical analysis indicated a significant negative correlation between the case mortality rates and the number of medical facilities used by the sample source locations, the number of infections reported, and the maximum and mean distances travelled to the medical facilities used. This suggested that malaria patients from larger communities, those who had financial or other means to consult more advanced facilities or those with a larger variety of services had a significantly lower risk of mortality. In addition, the analysis indicated a positive correlation between the minimum distances travelled to the medical facilities used and the case mortality rates, indicating that, although maximum and average travelling distances had a negative correlation, medical facilities situated within the vicinities of communities could have a positive impact on reducing case mortality rates. The spatial analysis supported the majority of the findings from the statistical analysis, except for a small cluster of source locations that need further investigation. Proximity to significant water bodies was not found to have any significant impact on case mortality rates. Geography, Geoinformatics and Meteorology MSc (Environmental Management) Unrestricted Faculty of Natural and Agricultural Sciences 2024-08-20T13:46:05Z 2024-08-20T13:46:05Z 2020-05 2019-08 Dissertation * A2020 http://hdl.handle.net/2263/97756 en © 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Medical facilities
Malaria mortality rate
Socioeconomic factors
Water bodies
Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title_full Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title_fullStr Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title_full_unstemmed Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title_short Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
title_sort assessing the correlation between malaria case mortality rates and specific socioeconomic factors
topic UCTD
Medical facilities
Malaria mortality rate
Socioeconomic factors
Water bodies
url http://hdl.handle.net/2263/97756