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_61
Snippet: In Fig. 6 (c-d), simulated results incorporating non-Markovian processes deviate from the results obtained from Markov processes. More specifically, the epidemic curve with non-Markovian processes is flattened with a smaller epidemic peak compared with that from Markov processes. This is because the infectious period used in the Markovian model has an exponential distribution (mean =3.9 days) similar to the shape of the exponential distribution (.....
Document: In Fig. 6 (c-d), simulated results incorporating non-Markovian processes deviate from the results obtained from Markov processes. More specifically, the epidemic curve with non-Markovian processes is flattened with a smaller epidemic peak compared with that from Markov processes. This is because the infectious period used in the Markovian model has an exponential distribution (mean =3.9 days) similar to the shape of the exponential distribution (mean=4.0 days) in Fig. 6 (a) , but shorter than the lognormal distribution (mean=3.9 days, median=1.5 days) used after January 18 th . The reasons above indicate that control measures to reduce the infectious period can effectively mitigate the outbreak.
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