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Published on: February 3, 2023
Epidemiological Dynamics in Populations Structured by Neighbourhoods and Households
Abby Barlow1, Sarah Penington2, Ben Adams2
1Department of Mathematical Sciences, The University of Bath, Claverton Down, Bath, BA2 7AY, UK. ahb48@bath.ac.uk.
Understanding infectious disease spread requires considering both household and neighborhood structures. Spatial clustering of similar households can impact transmission dynamics, influencing outbreak probabilities and surveillance strategies.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- Infectious disease spread is influenced by host population structure, including households and neighborhoods.
- The interplay between household and neighborhood structures in disease epidemiology is not well understood.
Purpose of the Study:
- To develop a multi-scale epidemic model exploring the epidemiological implications of spatially clustered households with similar demographic structures.
- To analyze how household size, within-household vs. outside-household transmission, and neighborhood transmission localization affect disease dynamics.
Main Methods:
- Development of a multi-scale epidemic model incorporating neighborhoods of households.
- Construction of the household reproduction number across neighborhoods.
- Derivation of the analytic probability of an outbreak from a single infected individual.
Main Results:
- Reduced localization of transmission within neighborhoods decreases the household reproduction number when household sizes vary.
- This effect is amplified by greater household size differences and transmission rate divergence.
- The impact of large household sizes on infection risk is largely confined to residents of those neighborhoods.
Conclusions:
- Household size information is often more critical for surveillance than neighborhood data.
- Neighborhood localization and household size influence the spatial progression of outbreaks.
- The spatial and demographic structure of host populations significantly shapes epidemiological dynamics.
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