A time series method to analyze incidence pattern and estimate reproduction number of COVID-19

The lack of treatment or vaccines for the COVID-19 disease has focused most attention on preventive public health measures. To understand which measures might be effective and why requires a strong explanatory model of how COVID-19 is transmitted. This paper proposes a model based on time-series data from China and 6 other countries, to identify trends of disease incidence as well as explanatory variables for disease prevalence.

Authored by Soudeep Deb and Manidipa Majumdar. Published by Cornell University.



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