Author: Qihui Yang; Chunlin Yi; Aram Vajdi; Lee W Cohnstaedt; Hongyu Wu; Xiaolong Guo; Caterina M Scoglio
Title: Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China Document date: 2020_3_30
ID: kcb68hue_67
Snippet: From an epidemiological modeling perspective, we simulate the epidemic spreading in Wuhan city based on non-Markovian processes, and show that different distributions with the same mean infectious period can lead to inconsistency in terms of epidemic dynamics. Since most current network-based approaches are based on Markov processes, in which epidemiological parameters are assumed to follow exponential distributions, non-Markovian process-based m.....
Document: From an epidemiological modeling perspective, we simulate the epidemic spreading in Wuhan city based on non-Markovian processes, and show that different distributions with the same mean infectious period can lead to inconsistency in terms of epidemic dynamics. Since most current network-based approaches are based on Markov processes, in which epidemiological parameters are assumed to follow exponential distributions, non-Markovian process-based models need to be further explored to better predict the COVID-19 spreading. Our results show that reducing the infectious period via measures such as early case identification and isolation can reduce the epidemic size significantly.
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