Wuhan City Lockdown and Nationwide Intensive Community Screening Are Effective in Controlling COVID-19 Epidemic: Analysis Based on a Modified SIR Model

2020 ◽  
Author(s):  
Tailai Peng ◽  
Xinhao Liu ◽  
Hefeng Ni ◽  
Zhe Cui ◽  
Lei Du
2020 ◽  
Author(s):  
Tailai Peng ◽  
Xinhao Liu ◽  
Hefeng Ni ◽  
Zhe Cui ◽  
Lei Du

Abstract In December 2019, an outbreak of COVID-19 epidemic occurred in Wuhan, China and this infection has spread rapidly into more than 109 countries around the world. To limit the rapid spread in community and nationwide, Wuhan city lockdown and nationwide intensive community screening were employed by Chinese government. To assess the effectiveness of city lockdown and intensive community screening, we built a modified SIR model by introducing an α value into the classic SIR model. The α value represents the proportion of the infected that is not effectively isolated from the susceptible at a given time point. The α value of China excluding Hubei province was largely reduced by Wuhan city lockdown. Although the α value of Wuhan city dropped a little with city lockdown, but dropped rapidly with intensive community screening. With the decrease of α value, the epidemic in China would be end at the beginning of June 2020. With current epidemiological data, the infection cases in South Korea and Italy are predicted to increase exponentially in the next days, if stringent mitigation measures were not adopted.Authors Tailai Peng and Xinhao Liu contributed equally to this work.


PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0238411 ◽  
Author(s):  
Tailai Peng ◽  
Xinhao Liu ◽  
Hefeng Ni ◽  
Zhe Cui ◽  
Lei Du

2020 ◽  
Author(s):  
Umamaheswari P

Coronavirus disease 2019 (COVID-19) emerged in Wuhan city, China, at the end of December 2019. As of July 26, 2020, 16258353 COVID-19 cases were confirmed worldwide, including  649848 deaths. The spread of COVID-19 is currently very high. Under the classical SIR (Susceptible-Infected-Recovered) model, epidemiological data for India up to 26th July 2020 were used to forecast the COVID-19 outbreak. For controlling the spreading of the virus, we have to prepare for precaution and futuristic calculation for infection spreading. We used the data from the COVID-2019 Outbreak of India on July 26th, 2020 in this report. In these results, for the initial level of experimental intent, we used 16291331 susceptible cases, 481248 infectious cases, and 910298 rewards / removed cases. Through the aid of the SIR model, data on a wide range of infectious diseases have been analyzed.  SIR model is one of the most effective models which can predict the spreading rate of the virus. We have validated the model with the current spreading rate with this SIR model. The findings of the SIR model can be used to forecast transmission and avoid the outbreak of COVID-2019 in India. The results of the study will shed light on understanding the outbreak patterns and indicate those regions' epidemiological points. Finally, from this study, we have found that the outbreak of the COVID-2019 epidemic in India will be at its peak on 09 August 2020 and after that, it will work slowly and on the verge of ending in the second or third week of November 2020.


2020 ◽  
pp. 276-289
Author(s):  
Mobina Fathi ◽  
Kimia Vakili ◽  
Niloofar Deravi

Around the end of December 2019, a new beta-coronavirus from Wuhan City, Hubei Province, China began to spread rapidly. The new virus, called SARS-CoV-2, which could be transmitted through respiratory droplets, had a range of mild to severe symptoms, from simple cold in some cases to death in others. The disease caused by SARS-CoV-2 was named COVID-19 by WHO and has so far killed more people than SARS and MERS. Following the widespread global outbreak of COVID-19, with more than 132758 confirmed cases and 4955 deaths worldwide, the World Health Organization declared COVID-19 a pandemic disease in January 2020. Earlier studies on viral pneumonia epidemics has shown that pregnant women are at greater risk than others. During pregnancy, the pregnant woman is more prone to infectious diseases. Research on both SARS-CoV and MERS-CoV, which are pathologically similar to SARS-CoV-2, has shown that being infected with these viruses during pregnancy increases the risk of maternal death, stillbirth, intrauterine growth retardation and, preterm delivery. With the exponential increase in cases of COVID-19 throughout the world, there is a need to understand the effects of SARS-CoV-2 on the health of pregnant women, through extrapolation of earlier studies that have been conducted on pregnant women infected with SARS-CoV, and MERS-CoV. There is an urgent need to understand the chance of vertical transmission of SARS-CoV-2 from mother to fetus and the possibility of the virus crossing the placental barrier. Additionally, since some viral diseases and antiviral drugs may have a negative impact on the mother and fetus, in which case, pregnant women need special attention for the prevention, diagnosis, and treatment of COVID-19.


Author(s):  
Zen Ahmad

Corona Virus Disease (Covid-19) is a contagious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which was discovered in December 2019 in China. This disease can cause clinical manifestations in the airway, lung and systemic. The World Health Organization (WHO) representative of China reported a pneumonia case with unknown etiology in Wuhan City, Hubei Province, China on December 31, 2019. The cause was identified as a new type of coronavirus on January 7, 2020 with an estimated source of the virus from traditional markets (seafood market). ) Wuhan city


Author(s):  
Lara Bittmann

On December 31, 2019, WHO was informed of cases of pneumonia of unknown cause in Wuhan City, China. A novel coronavirus was identified as the cause by Chinese authorities on January 7, 2020 and was provisionally named "2019-nCoV". This new Coronavirus causes a clinical picture which has received now the name COVID-19. The virus has spread subsequently worldwide and was explained on the 11th of March, 2020 by the World Health Organization to the pandemic.


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