The geography of COVID-19 spread in Italy and implications for the relaxation of confinement measures.

Nat Commun

Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, CH, Switzerland.

Published: August 2020

AI Article Synopsis

  • - The text discusses the need to safely resume socioeconomic activities in Italy while managing COVID-19 spread, using a model that accounts for hidden infections to guide decision-making.
  • - It highlights that even a small increase in transmission (like 40%) can lead to a surge in cases, emphasizing the importance of targeted isolation efforts, specifically isolating about 5.5% of highly infectious individuals daily to keep infections under control.
  • - Finally, the text includes an evaluation of actual disease transmission data that emerged after lockdown measures were relaxed, assessing how these changes affected the outbreak's trajectory.

Article Abstract

The pressing need to restart socioeconomic activities locked-down to control the spread of SARS-CoV-2 in Italy must be coupled with effective methodologies to selectively relax containment measures. Here we employ a spatially explicit model, properly attentive to the role of inapparent infections, capable of: estimating the expected unfolding of the outbreak under continuous lockdown (baseline trajectory); assessing deviations from the baseline, should lockdown relaxations result in increased disease transmission; calculating the isolation effort required to prevent a resurgence of the outbreak. A 40% increase in effective transmission would yield a rebound of infections. A control effort capable of isolating daily  ~5.5% of the exposed and highly infectious individuals proves necessary to maintain the epidemic curve onto the decreasing baseline trajectory. We finally provide an ex-post assessment based on the epidemiological data that became available after the initial analysis and estimate the actual disease transmission that occurred after weakening the lockdown.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449964PMC
http://dx.doi.org/10.1038/s41467-020-18050-2DOI Listing

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