Author: Huazhen Lin; Wei Liu; Hong Gao; Jinyu Nie; Qiao Fan
Title: Trends in Transmissibility of 2019 Novel Coronavirus-infected Pneumonia in Wuhan and 29 Provinces in China Document date: 2020_2_25
ID: eedk54xf_2
Snippet: Wuhan [2, 3, 11, 12, 13, 14] . In practice, it becomes crucial to monitor quantitative changes in transmission rates and the effective reproduction number 23 R t over time to reveal the impacts of control measures [15, 16, 17, 18, 19] . The 24 transmissibility depends on the biological properties of the coronavirus, as 25 well as the contact patterns which can be intervened at the national or social 26 levels in populations. The dynamic changes i.....
Document: Wuhan [2, 3, 11, 12, 13, 14] . In practice, it becomes crucial to monitor quantitative changes in transmission rates and the effective reproduction number 23 R t over time to reveal the impacts of control measures [15, 16, 17, 18, 19] . The 24 transmissibility depends on the biological properties of the coronavirus, as 25 well as the contact patterns which can be intervened at the national or social 26 levels in populations. The dynamic changes in transmissibility of in Wuhan and across provinces in China remain unknown. We hypothe- 28 sized that there could be a significant reduction of transmissibility with time 29 which is in accordance with the public health interventions in Wuhan and 30 other provinces. 31 Here we provide a real-time model-based analysis to estimate trends in 32 transmissibility of COVID-19 from January 20 to February 13 in Wuhan, 33 Hubei and other 28 provinces in China and forecast the turning point to First, we build an index α k to represent the baseline infected cases in 102 province k on 20 January, 2020. Particularly, we will use T R k , F L k and M I k 103 to measure the relationship between provice k and Wuhan. We suppose
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