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Sources of data/modeling
Published in Edward M. Rafalski, Ross M. Mullner, Healthcare Analytics, 2022
Edward M. Rafalski, Robert Marksthaler
Epidemic doubling time, the rate in days at which the size of an infected population doubles, proved to be another valuable predictive metric as it led to the identification of hot spots that needed to be monitored more closely. This was of particular use when modeling the spread of the virus in the SNF population which was disproportionately leading to hospital admissions in the first wave/peak.9
Estimation of the doubling time and reproduction number for COVID-19
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Shamim Ahmed, Mohammad Shemanto, Hasin Azhari, Golam Zakaria
The doubling time (Td) is the time required to double the total cumulative number of cases in an epidemic. Td is an unrefined estimation of the current rate of spread of the virus. For uncontrolled exponential growth, we expect Td to remain constant. A higher Td implies that it is taking more time for the cases to double and shows that the contamination is spreading at a slower rate. On the other hand, a lower Td recommends a quicker spread of contamination. For an infection growing at a constant exponential rate, the Td is constant. For example, Td is 1 means, if there is 100 cases to start with on day 0, there would be 200 cases on day 1, 400 on day 2, and so on. However, if the Td is 3, 100 cases on day 0 would increase to 200 cases on day 3.
Transmissibility and mortality trends of COVID-19 epidemic in Egypt
Published in Alexandria Journal of Medicine, 2020
Mohamed Masoud, Gihan Gewaifel, Nahla Gamaleldin
During the early phase of the epidemics, calculation of doubling time and R0 could be obtained from the growth rate of the cases. The assumption of this method is that at the beginning of the epidemic, and before implementation of any PHSMs, the cumulative number of the cases grows at an exponential rate. During this exponential phase of the epidemic, doubling time can be estimated based on the exponential growth rate and furthermore R0 is computed as a function of the growth rate and the duration of the infectivity period [6,7].