Epidemiological dynamics are affected by the spatial and demographic structure of the host population. Households and neighbourhoods are known to be important groupings but little is known about the epidemiological interplay between them. In order to explore the implications for infectious disease epidemiology of households with similar demographic structures clustered in space we develop a multi-scale epidemic model consisting of neighbourhoods of households. In our analysis we focus on key parameters which control household size, the importance of transmission within households relative to outside of them, and the degree to which the non-household transmission is localised within neighbourhoods. We construct the household reproduction number R & lowast;\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_*$$\end{document} over all neighbourhoods and derive the analytic probability of an outbreak occurring from a single infected individual in a specific neighbourhood. We find that reduced localisation of transmission within neighbourhoods reduces R & lowast;\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_*$$\end{document} when household size differs between neighbourhoods. This effect is amplified by larger differences between household sizes and larger divergence between transmission rates within households and outside of them. However, the impact of neighbourhoods with larger household sizes on an individual's risk of infection is mainly limited to the individuals that reside in those neighbourhoods. We consider various surveillance scenarios and show that household size information from the initial infectious cases is often more important than neighbourhood information while household size and neighbourhood localisation influences the sequence of neighbourhoods in which an outbreak is observed.
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Harvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USAHarvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USA
Tarnita, Corina E.
Antal, Tibor
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Harvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USAHarvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USA
Antal, Tibor
Ohtsuki, Hisashi
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Tokyo Inst Technol, Dept Value & Decis Sci, Tokyo 1528552, JapanHarvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USA
Ohtsuki, Hisashi
Nowak, Martin A.
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Harvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USAHarvard Univ, Dept Organism & Evolutionary Biol, Dept Math, Program Evolutionary Dynam, Cambridge, MA 02138 USA