Article ; Online: Mathematical Modeling Predicts That Strict Social Distancing Measures Would Be Needed to Shorten the Duration of Waves of COVID-19 Infections in Vietnam.
2021 Volume 8, Page(s) 559693
Abstract: ... measures reduces the number of infected cases but does not shorten the duration of the epidemic waves ... of COVID-19 in urban areas of Vietnam. Both models show that the adoption of relaxed social distancing ... Whereas, more strict measures would lead to the containment of each epidemic wave in one and a half months. ...
| Abstract | Coronavirus disease 2019 (COVID-19) emerged in Wuhan, China in 2019, has spread throughout the world and has since then been declared a pandemic. As a result, COVID-19 has caused a major threat to global public health. In this paper, we use mathematical modeling to analyze the reported data of COVID-19 cases in Vietnam and study the impact of non-pharmaceutical interventions. To achieve this, two models are used to describe the transmission dynamics of COVID-19. The first model belongs to the susceptible-exposed-infectious-recovered (SEIR) type and is used to compute the basic reproduction number. The second model adopts a multi-scale approach which explicitly integrates the movement of each individual. Numerical simulations are conducted to quantify the effects of social distancing measures on the spread of COVID-19 in urban areas of Vietnam. Both models show that the adoption of relaxed social distancing measures reduces the number of infected cases but does not shorten the duration of the epidemic waves. Whereas, more strict measures would lead to the containment of each epidemic wave in one and a half months. |
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| MeSH term(s) | COVID-19/prevention & control ; China/epidemiology ; Communicable Disease Control/methods ; Forecasting ; Humans ; Models, Theoretical ; Pandemics/prevention & control ; Physical Distancing ; Quarantine/methods ; SARS-CoV-2 ; Vietnam/epidemiology |
| Language | English |
| Publishing date | 2021-01-12 |
| Publishing country | Switzerland |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2711781-9 |
| ISSN | 2296-2565 ; 2296-2565 |
| ISSN (online) | 2296-2565 |
| ISSN | 2296-2565 |
| DOI | 10.3389/fpubh.2020.559693 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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