Literature DB >> 32188819

Analysis of COVID-19 infection spread in Japan based on stochastic transition model.

Kenji Karako1, Peipei Song2, Yu Chen1, Wei Tang3.   

Abstract

To assess the effectiveness of response strategies of avoiding large gatherings or crowded areas and to predict the spread of COVID-19 infections in Japan, we developed a stochastic transmission model by extending the Susceptible-Infected-Removed (SIR) epidemiological model with an additional modeling of the individual action on whether to stay away from the crowded areas. The population were divided into three compartments: Susceptible, Infected, Removed. Susceptible transitions to Infected every hour with a probability determined by the ratio of Infected and the congestion of area. The total area consists of three zones crowded zone, mid zone and uncrowded zone, with different infection probabilities characterized by the number of people gathered there. The time for each people to spend in the crowded zone is curtailed by 0, 2, 4, 6, 7, and 8 hours, and the time spent in mid zone is extended accordingly. This simulation showed that the number of Infected and Removed will increase rapidly if there is no reduction of the time spent in crowded zone. On the other hand, the stagnant growth of Infected can be observed when the time spent in the crowded zone is reduced to 4 hours, and the growth number of Infected will decrease and the spread of the infection will subside gradually if the time spent in the crowded zone is further cut to 2 hours. In conclusions The infection spread in Japan will be gradually contained by reducing the time spent in the crowded zone to less than 4 hours.

Entities:  

Keywords:  Japan; Susceptible-Infected-Removed (SIR); coronavirus disease 2019 (COVID-19); infection; modeling; transmission

Mesh:

Year:  2020        PMID: 32188819     DOI: 10.5582/bst.2020.01482

Source DB:  PubMed          Journal:  Biosci Trends        ISSN: 1881-7815            Impact factor:   2.400


  27 in total

1.  Common trends in the epidemic of Covid-19 disease.

Authors:  Milad Radiom; Jean-François Berret
Journal:  Eur Phys J Plus       Date:  2020-06-22       Impact factor: 3.911

Review 2.  Behavioral changes adopted to constrain COVID-19 in Japan: What are the implications for seasonal influenza prevention and control?

Authors:  Tatsuo Sawakami; Kenji Karako; Peipei Song
Journal:  Glob Health Med       Date:  2021-06-30

Review 3.  The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype.

Authors:  Musa Abdulkareem; Steffen E Petersen
Journal:  Front Artif Intell       Date:  2021-05-14

4.  Discrete and continuum models of COVID-19 virus, formal solutions, stability and comparison with real data.

Authors:  Hamdy I Abdel-Gawad; Ahmed H Abdel-Gawad
Journal:  Math Comput Simul       Date:  2021-05-14       Impact factor: 2.463

5.  Policy Implications of an Approximate Linear Infection Model for SARS-CoV-2.

Authors:  John E McCarthy; Bob A Dumas
Journal:  medRxiv       Date:  2020-06-08

6.  Controlling of pandemic COVID-19 using optimal control theory.

Authors:  Shahriar Seddighi Chaharborj; Sarkhosh Seddighi Chaharborj; Jalal Hassanzadeh Asl; Pei See Phang
Journal:  Results Phys       Date:  2021-05-19       Impact factor: 4.476

7.  Modelling Analysis of COVID-19 Transmission and the State of Emergency in Japan.

Authors:  Zhongxiang Chen; Zhiquan Shu; Xiuxiang Huang; Ke Peng; Jiaji Pan
Journal:  Int J Environ Res Public Health       Date:  2021-06-26       Impact factor: 3.390

8.  Precise Decision-Making and Adaptive Response Strategies Based on the Situations of Stress During the Coronavirus Disease 2019 (COVID-19) Pandemic.

Authors:  Weifeng Shen
Journal:  Front Public Health       Date:  2020-07-07

Review 9.  Considerations for an Individual-Level Population Notification System for Pandemic Response: A Review and Prototype.

Authors:  Mohammad Nazmus Sakib; Zahid A Butt; Plinio Pelegrini Morita; Mark Oremus; Geoffrey T Fong; Peter A Hall
Journal:  J Med Internet Res       Date:  2020-06-05       Impact factor: 5.428

Review 10.  Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.

Authors:  Agam Bansal; Rana Prathap Padappayil; Chandan Garg; Anjali Singal; Mohak Gupta; Allan Klein
Journal:  J Med Syst       Date:  2020-08-01       Impact factor: 4.460

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