Abstract
Spatial dynamics and human mobility significantly influence the transmission dynamics of vector-borne diseases like Zika virus. This paper reviews advancements in mathematical modeling that integrate spatial factors and human movement to enhance our understanding of disease transmission dynamics. Traditional SEIR (Susceptible-Exposed-Infectious-Recovered) models have been foundational but lack spatial heterogeneity and human mobility considerations. Recent studies have addressed these limitations by developing spatially explicit models that incorporate local interactions, environmental conditions, and human mobility patterns. By synthesizing findings from these studies, we identify strengths, limitations, and future research directions for improving predictive modeling of Zika virus transmission. Key insights include the amplifying effect of local interactions on disease spread and the critical role of human mobility networks in shaping transmission pathways. Addressing remaining challenges, such as refining spatial modeling techniques and integrating real-time data sources, will enhance the accuracy and applicability of spatial disease models in informing public health strategies.
Published Version
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