Modeling the Impact of Social Distancing and Targeted Vaccination on the Spread of COVID-19 Through a Real City-Scale Contact Network [open html - 0B]
From the Introduction: "[T]argeted vaccination strategies that prioritize high-contact individuals far outperform a baseline strategy of vaccinating people at random for reducing cases, even when the targeted strategy is only imperfectly implemented. In this work, we expand on that approach by performing a comparative study of the effectiveness of both social distancing and a vaccination strategy that targets those with the most physical contacts (such as workers in high-contact public-facing professions). This analysis is motivated by the fact that both mitigation strategies have significant challenges and high costs, so it is important to quantify their respective marginal benefits. Social distancing suppresses economic activity, has deleterious effects on child education, and leads to increased levels of depression and anxiety. Prioritizing the most high-contact individuals for vaccination has both direct challenges toward identifying those individuals and the opportunity costs of not prioritizing other vulnerable groups, and it could slow overall distribution. (We stress that the vaccination policy choice we are considering is not whether to prioritize vaccination, but whether to accept the costs associated with a targeted vaccination strategy.) In this study, we only attempt to quantify the effectiveness of these two COVID-19 [coronavirus disease 2019] mitigation strategies for reducing the total number of cases; we do not model the number of hospitalizations or deaths, although these are also important factors for policy makers to consider. Nor do we consider other vaccination strategies, such as prioritizing the elderly, because our data source does not provide the necessary information to do so."
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