Result for
Topic: Modeling and Prediction
February 25, 2020
Effectiveness of intervention strategies for Coronavirus Disease 2019 and an estimation of its 1 peak time
Pan et al. developed two mathematical SEIR models to simulate the current COVID-10 outbreak. The models predicted decline of the basic reproductive number R0 from 5.75 to 1.69 in Wuhan and 6.22 to 1.67 elsewhere in China from 19 January to 16 February 2020. The results also predict the peak of new asymptomatic cases per…
Early phylogenetic estimate of the effective reproduction number of 2019-nCoV
Lai et al used 15 2019-nCoV genomes to reconstruct the evolutionary dynamics of the COVID-19 outbreak, demonstrating the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. Lai et al (Feb 23, 2020): Early phylogenetic estimate of the effective reproduction number of 2019-nCoV. Pre-print downloaded Feb 25…
February 21, 2020
Estimating the cure rate and case fatality rate of the ongoing epidemic COVID-19
Diao et al. estimate the cure rate and case fatality for COVID-19 patients in Wuhan and the rest of mainland China using data on hospital discharges to support more precise modelling. They estimate that in mainland China, 93% of patients recover compared to 87% in Wuhan. These numbers suggest a case fatality among known patients…
February 19, 2020
Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China
Liu et al. estimate the temporal trends of the outbreak, focusing on peak windows in Hubei Province and other parts of China. Unlike Peng et al., this paper suggests that peak case counts will not be reached until March. Liu et al. (Feb 18, 2020). Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China. Pre-print…
Epidemic analysis of COVID-19 in China by dynamical modeling
Using public national data out of China, researchers attempted to predict the trajectory of the outbreak, estimating optimistically that the outbreak would be over by the end of February in Beijing and Shanghai and in the rest of mainland China by mid-march. The outbreak in Wuhan was estimated to end in early April. As always,…
February 18, 2020
Understanding the present status and forecasting of COVID―19 in Wuhan
Tomie modelled COVID-19 incidence data for Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. The model suggests that the number of new cases outside of Wuhan will be negligible by the end of February if the current trends do not change. Daily fluctuation in Wuhan makes predicting the end of the outbreak there…
The role of absolute humidity on transmission rates of the COVID-19 outbreak
Researchers evaluated absolute humidity and transmission of COVID-19. They found that high humidity will not necessarily limit the survival and transmission of the virus. Sustained and exponential disease transmission can occur across a range of humidity conditions. Thus, changes in weather will likely not lead to reduced case counts without extensive public health interventions. Luo…
Impact of seasonal forcing on a potential SARS-CoV-2 pandemic
Researchers use data on the seasonal variation of four endemic coronaviruses to model the effect of seasonal variation on a potential COVID-19 pandemic. They conclude that seasonality may, in combination with infection control processes, contribute to a slowing of the outbreak but that it seems likely this virus will shift into a seasonal endemic pattern…
February 12, 2020
Assessing the plausibility of subcritical transmission of 2019-nCoV in the United States
The upper bound for basic reproduction number, R, in the current US context is estimated based on the number of imported primary cases and secondary cases, and using a maximum likelihood technique. R is found to be less than 1 (subcritical) at this time. Depending on the value of a dispersion parameter reflecting heterogeneity of…
Beyond R0: the importance of contact tracing when predicting epidemics
Hebert-Dufrense, et al. apply network theory to improve basic estimates of R0, using added information from the numeric heterogeneity of secondary infections – that is, the fact that some individuals create more secondary infections then others. A range of predictions for the final size of the Wuhan 2019-nCoV epidemic is provided, using R0 estimates from…
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