On Linear Growth in COVID-19 Cases
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We present an elementary model of COVID-19 propagation that makes explicit the connection between testing strategies and rates of transmission and the linear growth in new cases observed in many parts of the world. An essential feature of the model is that it captures the population-level response to the infection statistics information provided by governments and other organisations. The conclusions from this model have important implications regarding benefits of wide-spread testing for the presence of the virus, something that deserves greater attention.
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