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• W2887540147 abstract "Malaria is a life-threatening disease caused by parasites that are transmittedto humans through the bites of infected female mosquitoes. Almost half of theworld’s population is at risk of malaria. Schistosomiasis is considered second onlyto malaria as the most devastating parasitic disease, estimated to affect 237 millionpeople worldwide. The development, mortality and reproduction rates of themalaria and schistosomiasis parasites and their hosts are very sensitive to temperatureand the availability of water bodies. The distribution and prevalence ofthe diseases are most likely to be affected by climate change. The aim of thisthesis was to advance understanding of the potential effects of climate change onmalaria and schistosomiasis transmission, using non linear differential equations.In addition, the study also sought to assess the role of mathematical models inevaluating the impact of climate variability and change on malaria and schistosomiasistransmission. The work in this thesis focused on investigating the effectsof climate on malaria and schistosomiasis transmission in Africa and South America.Climate driven deterministic models were developed separately for malaria,schistosomiasis and malaria-schistosomiasis coinfection. Mathematical models ofhuman population dynamics and the vector population dynamics were developedfor both malaria and schistosomiasis. For both diseases, temperature-dependentstages of the parasites in their life cycles are considered. Temperature and rainfallwere incorporated in the models to explore the effects of climate variabilityand change on the diseases transmission dynamics. The equilibrium states for themodels were determined and analysed. The reproductive rates were computed foreach model and accordingly analysed. Mathematical packages (Mathematica, Matlaband C++) were used to perform sensitivity analyses and numerical simulations.Projections for future transmission dynamics were made from climate change projectionmodels in order to inform policy makers on how to deal with the diseases inthe future. Results from the malaria model suggest that temperature range 23oCto 38oC is ideal for malaria transmission. The reproduction number increases astemperature increases to attain a maximum at 31.5oC, beyond which the reproductionnumber starts declining. This result suggests the optimal temperaturefor malaria transmission is around 31oC. The analytic results are also supportedby numerical simulations which show an increase in malaria cases as temperatureincreases to about 38oC and a decrease thereafter. Furthermore, results frommodel analysis suggest daily rainfall in the range of 15 − 17mm is ideal for thespread of malaria. The models’ reproductive rates were simulated using climatemodels for Africa to determine the current transmission patterns and to aid predictionof future trends. The results of the simulated current transmission patternof malaria fall within the observed spatial distribution of falciparum limits on theAfrican continent. Results from future projections of malaria transmission suggestthat due to climate change, endemic malaria will die out on the southern fringeof the disease map in Africa by 2040, while malaria endemicity is going to becomea problem in the African highlands. A drying trend is the likely driving force forthe reduction in malaria transmission in the regions to the south of the continent,while a warming trend is the likely factor driving the projected increase in malariaendemicity in the highlands, although increases in malaria incidences in these areas can also be attributed to socioeconomic factors such as land use change anddrug resistance. The model has the following limitations: it did not consider therole of human migration, other climate variables, in particular relative humidityas the tropical anopheline mosquitoes prefer humidities above 60% and the role ofsocioeconomic factors inmalaria transmission dynamics. Despite these limitations,the model is reasonable enough to be able to give a realistic picture of malaria inthe African continent. Thus, results from the study will be useful at various levelsof decision making, for example, in setting up an early warning system andsustainable strategies for climate change adaptation for malaria vectors controlprogrammes in Africa. These results can be generalized to other tropical regionsoutside Africa. A mathematical model to explore the impact of temperature andrainfall (in the context of its effect on water bodies) on schistosomiasis transmissionis presented as a system of differential equations and analysed. The modelanalysis suggests that the optimal temperature for schistosomiasis transmissionis around 23OC. Geographical information systems (GIS) was used to map the reproductionnumber for Zimbabwe using temperature and rainfall data from 1950to 2000. It was noted that high reproduction numbers, which suggest high incidencesof schistosomiasis, are found in the Zambezi valley catchment area and thelowveld of the country. Amathematical model for schistosomiasis andmalaria coinfectionincorporating rainfall and temperature was developed and analysed. Thecoinfection reproduction number was computed and mapped on the continents ofAfrica and South America. Results from the mapping suggest that environmentalambient conditions in the equatorial regions of Africa and Latin America promotemalariaand schistosomiasis coinfection with a heavier burden of coinfection inSouth America, especially in Brazil. Within Africa, there are some countries whereit is beneficial to target both diseases, for example Angola, Democratic Republic ofCongo and Madagascar. However there are some areas where targeting Malariaonly is warranted. In the sub-tropical regions, including Namibia, South Africa,the greater part of Zimbabwe and the areas on the northern fringe of the Sahara,schistosomiasis is more dominant than malaria. Results also show that coinfectionis a greater problem in general in South America than in Africa. These findingssuggest that both schistosomiasis and malaria control programmes should be intensifiedin these regions of Africa and South America. The results of this studycan be used to identify areas which need special attention with regard to malariaand schistosomiasis control. This can be extended to incorporate other aspects likethe terrain of the region under study to capture the real transmission dynamics ofschistosomiasis and malaria." @default.
• W2887540147 created "2018-08-22" @default.
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• W2887540147 date "2016-09-01" @default.
• W2887540147 modified "2023-09-24" @default.
• W2887540147 title "Modelling the Impact of Climate Variability and Change on HumanHealth and Diseases" @default.
• W2887540147 hasPublicationYear "2016" @default.
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