Health Sciences and Technology

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Browsing Health Sciences and Technology by Author "Daudi, Salamida"

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    Modeling the implications of seasonality and heterogeneous mean worm burden in Guinea-worm disease dynamics in dog population
    (Elsevier, 2025-05-26) Lusekelo, Eva; Daudi, Salamida; Helikumi, Mlyashimbi; Mushayabasa, Steady
    Prior to 2012, it was believed that only humans could host Guinea-worm disease. Recent findings show that dogs also act as hosts. With the 2030 goal for eradicating Guinea-worm approaching, understanding dogs’ roles is crucial. We develop a mathematical model to study seasonal Guinea-worm disease, focusing on dogs as primary hosts, given the low human cases. Our model includes seasonal variations, as previous studies indicate that disease prevalence is linked to seasonal fisheries. We also categorize infectious dogs based on their average worm burden. Our analysis examines how dog screening and tethering influence disease dynamics. Results indicate that both strategies can lower disease transmission. However, they may not be enough for total eradication on their own. Therefore, we suggest combining these methods with additional actions, like dog culling, to improve disease control.
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    Optimal Control Applied to a Dengue Model Incorporating Symptomatic, Asymptomatic, and Severe Cases With Limited Healthcare Resource
    (Elsevier, 2025-10-14) Daudi, Salamida; Lusekelo, Eva; Helikumi, Mlyashimbi; Mushayabasa, Steady
    dengue clinical manifestations and the insufficiency of public health infrastructure are not well understood. Accounting for these factors provides valuable insights for the effective management of the disease. This study develops a novel mathematical model for dengue fever that incorporates various clinical manifestations, constraints imposed by limited medical resources, and preventive control strategies. We computed the basic reproduction number and examined its correlation with model parameters. Dynamical analysis revealed that the model exhibits a backward bifurcation. Using numerical techniques, we investigated the influence of varying control strategies, modeled as both time-dependent and non-time-dependent functions, on epidemic dynamics. In both scenarios, we identified threshold levels of intervention and the timelines required for disease extinction. These findings underscore the complexity of dengue dynamics and highlight the necessity of tailored intervention approaches for effective disease management.