Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible? (Preprint)

semanticscholar(2020)

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摘要
UNSTRUCTURED Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.
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