Author: Meher K Prakash
Title: Community Memory of COVID-19 Infections Post Lockdown as a Surrogate for Incubation Time Document date: 2020_4_20
ID: 4iwyjk8n_12
Snippet: In summary, we introduced a new way of estimating the incubation time by studying the new infection that arise after measures that restrict the interactions between the individuals in the community to a minimal or non-existent level. The advantages are that it is easy estimate. The estimates we made for three European countries suggest an incubation time with a median of 13.3 days. Models for public health should consider estimates for incubation.....
Document: In summary, we introduced a new way of estimating the incubation time by studying the new infection that arise after measures that restrict the interactions between the individuals in the community to a minimal or non-existent level. The advantages are that it is easy estimate. The estimates we made for three European countries suggest an incubation time with a median of 13.3 days. Models for public health should consider estimates for incubation time in the community, such as what we introduce here, for a better understanding of the differences between new cases arising after the incubation and the genuinely newer ones. Figure 1 . The daily infections observed after lockdown [11] and the predictions made using the infections before lockdown for: A. Austria (lockdown, 16 March 2020) B. Spain (lockdown, 14 March 2020) C. Germany (lockdown, 21 March 2020) are compared. The data until 13 April 2020 was used. The predictions were made as described with l=16, k=2. D. Similar graphs like A, B, C were generated for l between 5 to 20 to identify the value that best suits the data. l=16 optimizes the Weibull distribution for the data studied. k=2 was used in this analysis. It was independently optimized in the range k=1 to 3.
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