MATHEMATICAL MODELING OF THE SPATIAL DYNAMICS OF ZIKA TRANSMISSION IN MOMBASA COUNTY, KENYA

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dc.contributor.authorKASYOKI BRANDON MUSILI
dc.date.accessioned2026-04-21T13:15:09Z
dc.date.available2026-04-21T13:15:09Z
dc.date.issued2025-09
dc.descriptionTHESIS
dc.description.abstractZika virus continues to present a pressing health concern due to its neurological complications and its ability to spread rapidly in tropical urban environments. This study formulates a deterministic spatial SEIR–SEI model to examine the dynamics of Zika transmission in Mombasa, Kenya,a coastal city with dense informal settlements, uneven infrastructure, and climate-sensitive mosquito breeding environments, using a spatial resolution of 1 km2. In practice, this means the study area was divided into 1 km × 1 km grid cells, with each cell treated as a spatial patch for simulating human–vector dynamics, environmental factors, and mobility. This resolution balances neighborhood-level detail with computational feasibility.”. The framework couples human and mosquito populations while accounting for temperature, precipitation, mobility between neighborhoods, and the limited dispersal of vectors. The system was solved numerically in MATLAB R2023a through operator splitting, applying finite differences for spatial diffusion and Runge–Kutta methods for nonlinear infection terms. A sensitivity analysis combining Latin Hypercube Sampling with Partial Rank Correlation Coefficients highlighted adult mosquito mortality and the probability of transmission from vectors to humans as the most influential factors. Simulation results indicate that infection waves advance at an average speed of 2.3 km per day, with basic reproduction numbers ranging from 2.07 in peri-urban settings to 3.14 in densely populated areas. Attack rates were nearly three times higher in poorly drained neighborhoods than in planned residential zones. Climate-driven scenarios suggest that mid-century warming could lengthen the transmission season by about 15%, increasing the number of days with sustained transmission potential. Control experiments reveal that early, spatially targeted larval reduction and habitat modification can lower infections by over 70%, whereas delayed interventions achieve much less impact. The findings emphasize the importance of climate-sensitive early warning systems, mobility-aware surveillance, and geographically focused interventions to reduce the public health threat posed by Zika in coastal urban environments.
dc.identifier.urihttps://repository.cuea.edu/handle/123456789/687
dc.language.isoen_US
dc.publisherTHE CATHOLIC UNIVERSITY OF EASTERN AFRICA
dc.subjectMathematical modeling
dc.subjectspatial dynamics
dc.subjectZika virus transmission
dc.subjectinfectious disease modeling
dc.subjectvector-borne diseases
dc.subjectepidemiological modeling
dc.subjectMombasa County
dc.subjectKenya
dc.titleMATHEMATICAL MODELING OF THE SPATIAL DYNAMICS OF ZIKA TRANSMISSION IN MOMBASA COUNTY, KENYA
dc.typeThesis

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