Your browser doesn't support javascript.
loading
Human mobility and COVID-19 transmission: a systematic review and future directions
Mengxi Zhang; Siqin Wang; Tao Hu; Xiaokang Fu; Xiaoyue Wang; Yaxin Hu; Briana Halloran; Yunhe Cui; Haokun Liu; Zhimin Liu; Shuming Bao.
Afiliação
  • Mengxi Zhang; Ball State University
  • Siqin Wang; The University of Queensland
  • Tao Hu; Harvard University
  • Xiaokang Fu; Wuhan University
  • Xiaoyue Wang; Wuhan University
  • Yaxin Hu; Wuhan University
  • Briana Halloran; Ball State University
  • Yunhe Cui; University of Connecticut
  • Haokun Liu; University of Bern
  • Zhimin Liu; East China Normal University
  • Shuming Bao; China Data Center
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21250889
ABSTRACT
Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, statistical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19 spatially, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve statistical models used in analyzing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico / Review / Revisão sistemática Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico / Review / Revisão sistemática Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
...