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doi: 10.3934/mbe.2020149
pmid: 32233563
The outbreak of COVID-19 caused by SARS-CoV-2 in Wuhan and other cities of China is a growing global concern. Delay in diagnosis and limited hospital resources lead to a rapid spread of COVID-19. In this study, we investigate the effect of delay in diagnosis on the disease transmission with a new formulated dynamic model. Sensitivity analyses and numerical simulations reveal that, improving the proportion of timely diagnosis and shortening the waiting time for diagnosis can not eliminate COVID-19 but can effectively decrease the basic reproduction number, significantly reduce the transmission risk, and effectively prevent the endemic of COVID-19, e.g., shorten the peak time and reduce the peak value of new confirmed cases and new infection, decrease the cumulative number of confirmed cases and total infection. More rigorous prevention measures and better treatment of patients are needed to control its further spread, e.g., increasing available hospital beds, shortening the period from symptom onset to isolation of patients, quarantining and isolating the suspected cases as well as all confirmed patients.
China, Delayed Diagnosis, SARS-CoV-2, Pneumonia, Viral, Basic Reproduction Number, COVID-19, Models, Theoretical, dynamic model, hospital resources, Betacoronavirus, covid-19, QA1-939, Humans, Computer Simulation, delay in diagnosis, Coronavirus Infections, Pandemics, TP248.13-248.65, Mathematics, Biotechnology
China, Delayed Diagnosis, SARS-CoV-2, Pneumonia, Viral, Basic Reproduction Number, COVID-19, Models, Theoretical, dynamic model, hospital resources, Betacoronavirus, covid-19, QA1-939, Humans, Computer Simulation, delay in diagnosis, Coronavirus Infections, Pandemics, TP248.13-248.65, Mathematics, Biotechnology
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 185 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |