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Abstract

<jats:p>The recent pandemics remind us that the speed and extent of infectious disease spread heavily depend on human mobility patterns. Despite their long history, mobility restrictions have not always been successful in controlling disease spread. Understanding the implications of mobility restrictions on the geographic distribution of secondary infections, in relation to healthcare availability and quality, is critical for effective disease management. In this study, we explore the impact of short-term travel between two economically distinct communities on the transmission and containment of epidemics. We implemented a two-community mathematical model, where socio-economic conditions influence transmission rates and healthcare access. The model tracks individuals' place of residency by incorporating the proportion of time each resident spends traveling. We found that, in scenarios that amplify populations' disparities, the final epidemic size shows non-monotonic behavior with respect to mobility. Differences in population sizes amplify these effects, the larger population dominates disease dynamics, making mobility restrictions less effective in certain scenarios. Moreover, travel times that reduce the final epidemic size (relative to the isolation scenario) depend on the population's relative sizes and infection rates. Moreover, we found that treatment interventions mitigate infection peaks across both groups but fail to fully overcome disparities. Our results suggest that investing in treatment access for low-income communities is more effective in reducing the total final epidemic size than equivalent investments in high-income communities, especially when low-income populations are larger.</jats:p>

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Keywords

mobility disease restrictions effective communities

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