Spatial Spread of Dengue Virus: Appropriate Spatial Scales for Transmission

          @misc{ scivideos_22878,
            doi = {},
            url = {https://old.simons.berkeley.edu/talks/spatial-spread-dengue-virus-appropriate-spatial-scales-transmission},
            author = {},
            keywords = {},
            language = {en},
            title = {Spatial Spread of Dengue Virus: Appropriate Spatial Scales for Transmission},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {oct},
            note = {22878 see, \url{https://scivideos.org/simons-institute/22878}}
          }
          

Abstract

Abstract Dengue virus is the most significant viral mosquito-borne infection in terms of its human impact. Mathematical modeling has contributed to our understanding of its transmission and control strategies aimed at halting its spread. We consider the spread of dengue at the level of a city. Because the Aedes aegypti mosquito that transmits dengue has relatively low dispersal over its lifetime, human movement plays a major role in its spread and the household is a key spatial scale on which transmission occurs. Simple multi-patch deterministic models---metapopulation models, which consider the population to be described as a network of well-mixed patches---have been used to model city-level spatial spread and can provide expressions for key epidemiological quantities such as the basic reproduction number, $R_0$. We compare dynamics predicted by such models with results from individual-based network models and illustrate several discrepancies. We argue that the small size of households and local depletion of susceptibles are key features of the dynamics that are not captured in the standard $R_0$ analysis of the ODE model. In order to gain analytic understanding, we propose the use of household-level models, which can be analyzed using branching process theory. Our work, which echoes results previously found for directly-transmitted infections, highlights the importance of correctly accounting for the relevant spatial scales on which transmission occurs