2020/02/07 by Jun Li, Li, Jun · 9 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #A priori and a posteriori #Applications (stat.AP) #Artificial intelligence #Biology #COVID-19 epidemiological studies #Computer science #Coronavirus #Coronavirus disease 2019 (COVID-19) #Data mining #Disease #Econometrics #Economics #Estimation #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Infectious disease (medical specialty) #Influenza Virus Research Studies #Mathematics #Medicine #Methodology (stat.ME) #Outbreak #Outlier #Physics and Society (physics.soc-ph) #Populations and Evolution (q-bio.PE) #Robustness (evolution) #SARS-CoV-2 and COVID-19 Research #Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) #Statistics #Telecommunications #Transmission (telecommunications) #Virology #physics.soc-ph #q-bio.PE #stat.AP #stat.ME
paper · pdf · doi:10.48550/arxiv.2002.03828
published in arXiv (Cornell University) (Cornell University) · Short paper, 4 page text, total 10 pages
arxiv created 2020/02/07 · openalex publication_date 2020/02/07 · arxiv updated 2020/02/11 · openalex created_date 2020/02/14 · openalex updated_date 2026/08/06
The recent outbreak of a novel coronavirus (2019-nCoV) has quickly evolved into a global health crisis. The transmission potential of 2019-nCoV has been modelled and studied in several recent research works. The key factors such as the basic reproductive number, R0, of the virus have been identified by fitting contagious disease spreading models to aggregated data. The data include the reported cases both within China and in closely connected cities over the world. In this paper, we study the transmission potential of 2019-nCoV from the perspective of the robustness of the statistical estimation, in light of varying data quality and timeliness in the initial stage of the outbreak. Sample consensus algorithm has been adopted to improve model fitting when outliers are present. The robust estimation enables us to identify two clusters of transmission models, both are of substantial concern, one with R0:8∼14, comparable to that of measles and the other dictates a large initial infected group.