: Postprint online available 11/2021 as soon as is submitted to ZB.
COVID-19: Mathematical estimation of delay to deaths in relation to upsurges in positive rates.
Early Hum. Dev., DOI: 10.1016/j.earlhumdev.2020.105210 (2020)
Introduction: The world continues in the grip of the COVID-19 pandemic. Widespread public health measures and travel restrictions have dampened viral spread but outbreaks are expected as restrictions are raised. This study was carried out in order to devise an approach that may help to predict deaths based on upsurges (spikes or waves) of cases. Methods: Publically available data for daily new cases and deaths from December 2019 to August 2020 was obtained from the Our World In Data website. For the purposes of more detailed analysis, in addition to total global data, three countries were chosen for sub analysis: Italy, Germany and the United States. Results: Delay to death (days) were as follows: World: 20.6 (95% CI: 8.4–32.8); USA: 19.8 (95% CI: 9.3–30.4); Germany: 18.8 (95% CI: 6.1–31.6); Italy: 2.4 (95% CI −10.2–15.0). Discussion: Countries may be able to contain viral resurgence by adhering to WHO advice for reopening from restrictions/lockdowns. However, outbreaks are almost inevitable and deaths are to be expected approximately 20 days after rises in cases. This paper may therefore aid healthcare systems and hospitals for surges in cases as positive COVID-19 swabs increase in any given locality. Italy was an exception in these results as the initial surge and swabs taken represented symptomatic/admitted cases and not community surveillance tracking and tracing.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Coronavirus ; Pandemics ; Population Health ; Population Surveillance ; Prevention
ISSN (print) / ISBN 0378-3782
Journal Early Human Development
Publishing Place Amsterdam
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)