Simple Simulation for COVID-19 in Wuhan, Hubei, China to Predict Outbreak in Wuhan, the Initial Case in Wuhan, and the Epidemic in Japan as of 11 February, 2020

Object: Prediction of the COVID-19 epidemic represents a matter of concern not only for public health or medicine but also for Earth’s general population. This study predicts outbreaks in Wuhan and in Japan as of 11 February, 2020.Method: We applied a simple SIR model to data published by Hubei public health authorities. Moreover, into the model, we incorporate mild and asymptomatic cases from experiences of Japanese residents of Wuhan up to the outbreak. Finally, we predict an outbreak in Japan based on 10,000 iterations of a simulation conducted under the assumption of infected people including mild cases visiting Japan according to the estimated distribution of patients in Wuhan since the date on which the initial case occurred to the date when travel from Wuhan to Japan was suspended. Results: Results suggest the basic reproduction number, R0, as 2.84;its 95% confidence interval (CI) was [2.35, 3.33]. The peak is estimated to be reached on March 11. Its 95% CI peak date is 29 February to 27 March. The 95% CI peak date in Japan is 26 April to 2 May. The greatest number of patients at the peak with severe symptoms was estimated as 858.3 thousand. Discussion and Conclusion: Our obtained R0 of 2.84 approximates an earlier estimate. We predicted the greatest number of patients at the peak with severe symptoms as 858.3 thousand in Japan. This number is 63% greater than the highest daily peak of influenza.

Clinical characteristics of 290 foreign-imported cases infected with SARS-CoV-2 in Chengdu, China

Objective:To analyze the epidemiological and clinical characteristics of foreign-imported patients infected with SARS-CoV-2 in Chengdu City.Methods:A total of 290 foreign-imported patients infected with SARS-CoV-2 and discharged from Public Health Clinical Center of Chengdu were included in our study,they were divided into asymptomatic infection group(131 cases)and confirmed cases group(159 cases)in order to compare the epidemiology,clinical characteristics and laboratory tests between two groups.Multi-factor logistic regression analysis was used to investigate the influence factors of becoming a dominant infection after infected with SARS-CoV-2.Results:Among the 290 cases aged from 2 months to 68 years old,83.4%were males,62.1%came from Asia,and 43.8%were complicated with fatty liver disease,the age group of 14-49 years old had the largest number(247 cases).80.5%confirmed case group cases were general type,there was only 1 severe patient.Hospital stays in asymptomatic infection group was shorter than that in confirmed cases group,lymphocyte count,CD4+T count,CD8+T count,CD4+T/CD8+T creatine kinase in two groups half a month after discharge were relatively lower than those on admission,and alanine aminotransferase,aspartate aminotransferase,albumin,lactate dehydrogenase,creatine kinase isoenzyme were relatively higher than those on admission(P<0.05).Logistic regression analysis showed that increased age,decreased lymphocyte count on admission and increased lactate dehydrogenase on admission were associated with dominant infection.Chest CT of 13 general type cases indicated an increase in lesions compared with that at discharge and 3 of them had re-detectable positive RNA test.Conclusion:The majority of foreign-imported cases in Chengdu are mainly from Asia,fewer of them are severe patients.In the early stage of recovery,some SARS-CoV-2 infected patients still have intermittent viral replication.Early isolation and early treatment of imported patients is not only conducive to epidemic prevention and control,but also may change the natural course of the disease.

Modelling SARS-CoV-2 unreported cases in Italy: Analysis of serological survey and vaccination scenarios

Objectives:Aim of the present paper is the study of the large unreported component,characterizing the SARS-CoV-2 epidemic event in Italy,taking advantage of the Istat survey.Particular attention is devoted to the sensitivity and specificity of the serological test and their effects.Methods:The model satisfactory reproduces the data of the Italian survey showing a relevant predictive power and relegating in a secondary position models which do not include,in the simulation,the presence of asymptomatic groups.The corrections due to the serological test sensitivity(in particular those ones depending on the symptoms onset)are crucial for a realistic analysis of the unreported(and asymptomatic)components.Results:The relevant presence of an unreported component during the second pandemic wave in Italy is confirmed and the ratio of reported to unreported cases is predicted to be roughly 1:4 in the last months of year 2020.A method to correct the serological data on the basis of the antibody sensitivity is suggested and systematically applied.The asymptomatic component is also studied in some detail and its amount quantified.A model analyses of the vaccination scenarios is performed confirming the relevance of a massive campaign(at least 80000 immunized per day)during the first six months of the year 2021,to obtain important immunization effects within August/September 2021.