dc.contributor.advisor | De Necker, L | |
dc.contributor.advisor | Nkosi, NC | |
dc.contributor.advisor | Ayob, N | |
dc.contributor.author | Letlaila, Renamane Felleng | |
dc.date.accessioned | 2024-02-22T08:45:15Z | |
dc.date.available | 2024-02-22T08:45:15Z | |
dc.date.issued | 2023-10 | |
dc.identifier.uri | https://orcid.org 0000-0001-6334-6701 | |
dc.identifier.uri | http://hdl.handle.net/10394/42434 | |
dc.description | Master of Science in Geography and Environmental Management, North-West University, Mahikeng Campus | en_US |
dc.description.abstract | Schistosomiasis is a parasitic disease transmitted by freshwater host snails and is prevalent in tropical and subtropical regions. The spatial-temporal focal distribution and transmission of schistosomiasis are determined by the presence of these vectors in freshwater bodies. The disease has put approximately 40% of the South African population at risk of infection with people living in settings that have poor sanitary facilities having the highest infection rates. Children aged <15 years have the highest prevalence and transmission rates of schistosomiasis. The study aimed to understand the spatial and seasonal distribution of the schistosomiasis vectors, Biomphalaria pfeifferi and Bulinus globosus, in the Mpumalanga province over 40 years. The first objective was to determine the historical distribution of schistosomiasis transmitting snails using maximum entropy (MaxEnt) and a generalized linear model (GLM). The historical seasonal distribution of schistosomiasis was determined using an interpolation technique, kriging. The second objective was to assess the historic water quality of rivers within the Mbombela and Nkomazi local municipalities. The last objective was to identify rural areas that were vulnerable to schistosomiasis in Mbombela and Nkomazi local municipalities by creating a vulnerability index. ArcMap 10.8.1 was used to prepare the modelling and vulnerability index data which were converted to raster format. IBM SPSS statistics was used to conduct statistical analyses for the water quality assessment. The modelling results showed Mbombela local municipality and areas along the border of the local municipalities provided suitable conditions for the distribution of Biom. pfeifferi and Bul. globosus. The mapped seasonal distribution within Mbombela local municipality shows that post-rainy followed the trend of the modelled historical distribution, along the Crocodile River and Komati River. There were notable changes in salt, pH and nutrient levels within the Mbombela river systems and this likely affected the water quality in turn negatively affecting the biotic ecosystem where the schistosomiasis vectors are found. The overall vulnerability was observed along areas where models had shown the host snails to be abundant, especially the high and very high vulnerability areas. Vulnerability percentage showed the difference between the vulnerability zones for each snail species. These findings suggest that interventions should consider the dynamic nature of social and environmental factors that contribute to vulnerability in addressing schistosomiasis transmissions. Knowing the historical distribution of schistosomiasis and historically vulnerable areas will aid in predicting areas that may be vulnerable to exposure currently and in the future as it provides a guide for health officials on which areas need fast interventions. | en_US |
dc.language.iso | en | en_US |
dc.publisher | North-West University (South Africa) | en_US |
dc.subject | Schistosomiasis | en_US |
dc.subject | Species distribution modelling | en_US |
dc.subject | Bulinus globosus | en_US |
dc.subject | Biomphalaria pfeifferi | en_US |
dc.subject | Local municipalities | en_US |
dc.subject | Vulnerability index | en_US |
dc.subject | Water quality | en_US |
dc.title | The historical and seasonal distribution of schistosomiasis transmitting vectors in the Mpumalanga province, South Africa | en_US |
dc.type | Thesis | en_US |
dc.description.thesistype | Masters | en_US |
dc.contributor.researchID | 28509633 - De Necker, Lizaan (Supervisor) | |
dc.contributor.researchID | 23676442 - Nkosi, Ncobile Charity (Co- supervisor) | |
dc.contributor.researchID | 23799110 - Ayob, Nisa (Co- supervisor) | |