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| dc.contributor.supervisor | Lungu, Edward | |
| dc.contributor.supervisor | Szomolay, Barbara | |
| dc.contributor.author | Machingauta, Mandidayingeyi Hellen | |
| dc.date.accessioned | 2023-02-02T08:49:03Z | |
| dc.date.available | 2023-02-02T08:49:03Z | |
| dc.date.issued | 2022-02 | |
| dc.identifier.citation | Mandidayingeyi ,H. M. (2022) Mathematical modeling of infectious and non communicable diseases: exploring public health intervention strategies, PhD Dissertation, Botswana International University of Science and Technology: Palapye. | en_US |
| dc.identifier.uri | http://repository.biust.ac.bw/handle/123456789/528 | |
| dc.description.abstract | As new viruses and new pandemics emerge we face the question as to whether our global health systems are well prepared to deal with them. Non pharma ceutical measures are a key control measure in the battle against infectious diseases especially in the absence of vaccines or when available vaccine quantities are not sufficient. The 2014-2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We presented a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. We included the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlighted the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results showed that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management. Viral outbreaks differ in many ways, despite these differences policy responses used to tackle viral epidemics tend to be similar across time and countries. Substantial progress has been made since the 2014-2016 Ebola outbreak with lessons learnt from previous and ongoing outbreaks followed by significant investments into surveillance and preparedness and this has been of help in dealing with the COVID-19 pandemic. We formulated a mathematical model xiii for the spread of the coronavirus which incorporated adherence to disease prevention. The major results of this study were: first, we determined optimal infection coefficients such that high levels of coronavirus transmission were prevented. Secondly, we found that there existed several optimal pairs of removal rates, from the general population of asymptomatic and symptomatic infectives respectively that could protect hospital bed capacity and flatten the hospital admission curve. Of the many optimal strategies, this study recommended the pair that yielded the least number of coronavirus related deaths. The results for South Africa, which is better placed than the other sub-Sahara African countries, showed that failure to address hygiene and adherence issues will preclude the existence of an optimal strategy and could result in a more severe epidemic than the Italian COVID-19 epidemic. Relaxing lockdown measures to allow individuals to attend to vital needs such as food replenishment increases household and community infection rates and the severity of the overall infection. Although the tobacco epidemic is one of the biggest health threats, responsible for more than 8 million deaths annually with 15% of these caused by second hand smoke , only a few mathematical models have addressed smoking in the context of lung cancer. In our work we present two models, a stochastic model and a deterministic model both of which are fitted to actual smoking data. The expected solution of the stochastic model predicts a steady state solution in the long run for the moderate and heavy smokers with proportions of these popu lations remaining to sustain the habit contrary to the trend in the actual data which suggests extinction of these populations. The deterministic model, re vealed that the presence of highly quantifiable efficacious control measures can reduce the lung cancer load by 50% although the number of lung cancer deaths would remain the same for sometime. These results confirm the conclusions of the stochastic model and reveal further that these control measures can re duce the lung cancer load and lung cancer deaths by about 50% if there is a reduction of at least 20% in the population of susceptible individuals taking up smoking. Specifically, if the number of new potential (susceptible) smokers ex xiv ceeds a quantifiable threshold, Λ then even if R0 < 1 there is persistence of the epidemic. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Botswana International University of Science and Technology (BIUST) | en_US |
| dc.subject | Contact tracing | en_US |
| dc.subject | Hospital capacity | en_US |
| dc.subject | Lung cancer | en_US |
| dc.subject | Optimal control | en_US |
| dc.subject | Smoking | en_US |
| dc.subject | Bifurcation analys | en_US |
| dc.title | Mathematical modeling of infectious and non communicable diseases: exploring public health intervention strategies | en_US |
| dc.description.level | phd | en_US |
| dc.dc.description | Dissertation (Doctor of Philosophy in Pure and Applied Mathematics )---Botswana International University of Science and Technology, 2022 | |
| dc.description.accessibility | unrestricted | en_US |
| dc.description.department | mss | en_US |
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This collection is made up of electronic theses and dissertations produced by post graduate students from Faculty of Sciences