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Assessing the Spread of the Novel Coronavirus in the Absence of Mass Testing
21 Pages Posted: 27 Jul 2020
More...Abstract
Background: Assessing how many people have already been infected by the COVID 19 virus is important for predicting virus dynamics. This paper outlines a simple method for estimating the spread of the COVID 19 virus in the absence of data on test results for a large, random sample of the population.
Method: We estimate a version of the SIR model applied to data on the number who have tested positive in several countries. Up to the end of April 2020 such data came from non-random samples of populations who were overwhelmingly those who displayed symptoms. We use this data to assess two things: how large might be the group of those infected with few (or no) symptoms; how effective have lockdown measures been.
Findings: We find that to match data on daily new cases of the virus, the estimated model favours high values for the number of people infected but asymptomatic. That result is very sensitive to whether the transmission rate of the virus is different for symptomatic and asymptomatic cases, something about which there is significant uncertainty.
Interpretation: Our findings illustrate how difficult it is to estimate the spread of the virus until very large samples of the population can be tested. But there is some indirect evidence that the infection may have spread far enough to mean that the trajectory of falling new cases could be maintained with some easing of restrictions.
Funding Statement: We did not have funding for this research.
Declaration of Interests: There are no competing interest or conflicts of interest.
Keywords: COVID 19; SIR model; reproduction number
Suggested Citation: Suggested Citation
CESifo (Center for Economic Studies and Ifo Institute)
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