Modelling Malaria Transmission in Ndumo and Shemula, KwaZulu-Natal
Master Thesis
2022
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The KwaZulu Natal (KZN) province is the front runner for malaria elimination in South Africa. It accounts for a small proportion of the total number of malaria cases diagnosed in the whole country in recent times. This study focused on the key localities in the province, Ndumo, and Shemula which reported the highest number of local malaria cases between the years, 2014 and 2018. The study aimed at investigating and assessing the most influential factors that drive malaria in the localities and to represent the malaria key features such as treatment, imported cases, vector spraying, and vector/human relationships. The model used in the study examines the malaria behaviour at a smaller scale as other models mainly look at larger population sizes such as district level and provinces to find the most effective strategies as we move closer to elimination. The purpose of this was to understand how malaria will change in the future if the existing strategies change. It also aimed at studying impact these changes would have on the existing cases, as to whether there will be a rise or a drop with the existing intervention coverages. This was achieved by formulating an 11 compartmental population-based, nonlinear stochastic ordinary differential equation model that will be used to simulate malaria transmission in the two localities to assess the potential impact of various policy interventions that may be used to achieve malaria elimination. It was also developed to assess the impact of policy interventions on imported infections, seasonal spraying, the effectiveness of reducing the current coverages over time, and to reach the goal of malaria elimination. Based on our analysis, we deduced that to maintain a low number of malaria cases, it would be sufficient to employ the current coverages but to reduce the number of cases, we need to consider finding ways to increase the IRS efficacy. Thus, for IRS, we conclude that, to reduce the malaria cases to its minimum (even further to 0), we need to consider increasing both the IRS coverage and its efficacy closer to 100%. With imported cases having a big impact on local cases, we concluded that we could reduce the number of local cases if we can control imported cases from other areas. Strategies such as the border clinics, screening at the border etc, would result in significant impact in the local malaria cases as we would eliminate one of the major contributors to existing malaria cases. In conclusion, we believe that increasing our efforts on the existing interventions, would result in a further decrease in the number of cases. Although one would argue that the investment is not worthwhile and that the decrease is redundant, and because of this, it is worth considering moving all those efforts towards the prevention of the more concerning variable; imported cases. In terms of local cases, we would then consider maintaining the current coverages. In that case, we should only treat those who require the treatment and spray the areas that still report cases.
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Moya, M. 2022. Modelling Malaria Transmission in Ndumo and Shemula, KwaZulu-Natal. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/37668