ArticleSustainable cities and society2021
Seesaw scenarios of lockdown for COVID-19 pandemic: Simulation and failure analysis.
Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Assessing the impacts of vaccination and viral evolution in contact networks.Scientific reports · 2024Article
- Measurement of economic resilience under the COVID-19 based on nighttime light remote sensing: Case of Hubei province.PloS one · 2024Article
- Article
- Exploring the Role of Industry 4.0 and Simulation as a Solution to the COVID-19 Outbreak: a Literature Review.Procedia computer science · 2023Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ongoing COVOD-19(SARS-CoV-2) outbreak has had a devastating impact on the economy, education and businesses. In this paper, the behavior of an epidemic is simulated on different contact networks. Herein, it is assumed that the infection may be transmitted at each contact from an infected person to a susceptible individual with a given probability. The probability of transmitting the disease may change due to the individuals' social behavior or interventions prescribed by the authorities. We utilized simulation on the contact networks to demonstrate how seesaw scenarios of lockdown can curb infection and level the pandemic without maximum pressure on the poor societies. Soft scenarios consist of closing businesses 2, 3, and 4 days in between with four levels of lockdown respected by 25%, 50%, 75%, and 100% of the population. The findings reveal that the outbreak can be flattened under softer alternatives instead of a doomsday scenario of complete lockdown. More specifically, it is turned out that proposed soft lockdown strategies can flatten up to 120% of the pandemic course. It is also revealed that transmission probability has a crucial role in the course of the infection, growth rate of the infection, and the number of infected individuals.
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