Malaria remains one of the most devastating vector-borne parasitic diseases in tropical and subtropical regions. Approximately 40% of the world’s population lives in malaria endemic areas mostly in developing countries. The estimated global incidence is about 225 million cases and 80% of these cases occur in sub-Saharan Africa. The approximated global deaths due to malaria every year is about 700,000 people and 90% occur in Africa. In South Africa, parts of Mpumalanga, Limpopo and KwaZulu-Natal have endemic malaria. The incidence of malaria in South Africa by province is 56, 2 cases per 100,000 population at risk; 31,1 cases per 100,000 population at risk and 3,3 cases per 100,000 population at risk for Mpumalanga; Limpopo and KwaZulu-Natal, respectively. Approximately 80% of the cases are imported from malaria endemic countries and diagnosed in the South African health facilities. It is therefore important that these cases are disentangled from local cases using environmental or climatic conditions as proxy measures especially in light of South Africa eradication goal.
Methodology
Secondary data used in this study were obtained from Mpumalanga Department of Health, South African Weather Services, Statistics South Africa and Global Climatic Research Units. These data were analysed from 2001 to 2010 to determine the correlation between surrounding climatic or environmental conditions and malaria incidence in Mpumalanga Province. The Pearson correlation was used to assess for significant correlations between malaria incidence and environmental or climatic conditions. A negative binomial regression model was used to identify and quantify factors significantly association with
malaria risk. The Kulldorff spatial and space-time scan statistic was used to detect significant clustering of malaria cases in space and space-time.
Results
The incidence of malaria has decreased significantly since 2001 to 2010 in Mpumalanga Province. The decline has been observed from 1,304 cases per 100,000 population at risk in 2001 to less than 200 cases per 100,000 population at risk in 2010. About 96% of malaria cases were reported from Ehlanzeni District and less than 4% were reported from Gert Sibande and Nkangala Districts. The temperature, rainfall and humidity were statistically significant in all months from all years (p<0.05). The temperature, rainfall and humidity had a significant positive correlation with malaria cases. An excess of 1,752 and 104 malaria cases were detected in May and June over time when using weather stations data. When using remote sensed data, an excess of 1,131; 3,036; 4,009; 994 and 235 cases were observed from March, April, May, June and July, respectively.
Discussion and conclusion
The significant positive correlations between malaria cases and temperature, rainfall and humidity suggested that for an increase in each unit factor, malaria cases also increases. The excess number of cases observed especially during the winter season, suggested the likelihood of the importation of those cases. These results were in accordance with results from previous studies.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/15518 |
Date | 11 September 2014 |
Creators | Khumalo, Mbhekiseni Phikelamangwe |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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