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dc.contributor.authorSilva, Thiago Christiano
dc.contributor.authorAnghinoni, Leandro
dc.contributor.authorZhao, Liang
dc.description.abstractAlthough COVID-19 has spread almost all over the world, social isolation is still a controversial public health policy and governments of many countries still doubt its level of effectiveness. This situation can create deadlocks in places where there is a discrepancy among municipal, state and federal policies. The exponential increase of the number of infectious people and deaths in the last days shows that the COVID-19 epidemics is still at its early stage in Brazil and such political disarray can lead to very serious results. In this work, we study the COVID-19 epidemics in Brazilian cities using early-time approximations of the SIR model in networks. Different from other works, the underlying network is constructed by feeding real-world data on local COVID-19 cases reported by Brazilian cities to a regularized vector autoregressive model, which estimates directional COVID-19 transmission channels (links) of every pair of cities (vertices) using spectral network analysis. Our results reveal that social isolation and, especially, the use of masks can effectively reduce the transmission rate of COVID-19 in Brazil. We also build counterfactual scenarios to measure the human impact of these public health measures in terms of reducing the number of COVID-19 cases at the epidemics peak. We find that the efficiency of social isolation and of using of masks differs significantly across cities. For instance, we find that they would potentially decrease the COVID-19 epidemics peak in Sao Paulo (SP) and Brasilia (DF) by 15% and 25%, respectively. We hope our study can support the design of further public health measures.en_US
dc.subjectEvaluation Studies as Topicen_US
dc.subjectDisease Transmission, Infectiousen_US
dc.subjectSocial Isolationen_US
dc.titleQuantitative Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmissionen_US
eihealth.countryGlobal (WHO/OMS)en_US
eihealth.categoryPublic Health Interventionsen_US
eihealth.typePublished Articleen_US
eihealth.maincategorySlow Spread / Reducir la Dispersiónen_US

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