Time-to-Death approach in revealing Chronicity and Severity of COVID-19 across the World

PLoS One. 2020 May 12;15(5):e0233074. doi: 10.1371/journal.pone.0233074. eCollection 2020.

Abstract

Background: The outbreak of coronavirus disease, 2019 (COVID-19), which started from Wuhan, China, in late 2019, have spread worldwide. A total of 5,91,971 cases and 2,70,90 deaths were registered till 28th March, 2020. We aimed to predict the impact of duration of exposure to COVID-19 on the mortality rates increment.

Methods: In the present study, data on COVID-19 infected top seven countries viz., Germany, China, France, United Kingdom, Iran, Italy and Spain, and World as a whole, were used for modeling. The analytical procedure of generalized linear model followed by Gompertz link function was used to predict the impact lethal duration of exposure on the mortality rates.

Findings: Of the selected countries and World as whole, the projection based on 21st March, 2020 cases, suggest that a total (95% Cl) of 76 (65-151) days of exposure in Germany, mortality rate will increase by 5 times to 1%. In countries like France and United Kingdom, our projection suggests that additional exposure of 48 days and 7 days, respectively, will raise the mortality rates to10%. Regarding Iran, Italy and Spain, mortality rate will rise to 10% with an additional 3-10 days of exposure. World's mortality rates will continue increase by 1% in every three weeks. The predicted interval of lethal duration corresponding to each country has found to be consistent with the mortality rates observed on 28th March, 2020.

Conclusion: The prediction of lethal duration was found to have apparently effective in predicting mortality, and shows concordance with prevailing rates. In absence of any vaccine against COVID-19 infection, the present study adds information about the quantum of the severity and time elapsed to death will help the Government to take necessary and appropriate steps to control this pandemic.

MeSH terms

  • Betacoronavirus* / pathogenicity
  • COVID-19
  • Coronavirus Infections* / mortality
  • Global Health
  • Humans
  • Linear Models*
  • Pandemics*
  • Pneumonia, Viral* / mortality
  • Quarantine
  • SARS-CoV-2
  • Severity of Illness Index
  • Time Factors

Grant support

The author(s) received no specific funding for this work.