Mathematical Modeling Predicts That Strict Social Distancing Measures Would Be Needed to Shorten the Duration of Waves of COVID-19 Infections in Vietnam
Overview
Affiliations
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.
Kante D, Jebrane A, Boukamel A, Hakim A PLoS One. 2024; 19(3):e0296740.
PMID: 38483954 PMC: 10939283. DOI: 10.1371/journal.pone.0296740.
Marin-Machuca O, Chacon R, Alvarez-Lovera N, Pesantes-Grados P, Perez-Timana L, Marin-Sanchez O Vaccines (Basel). 2023; 11(11).
PMID: 38005980 PMC: 10674587. DOI: 10.3390/vaccines11111648.
Response Strategies for Emerging Infectious Diseases: More Efforts Are Needed.
Lin Y, Chen T Trop Med Infect Dis. 2023; 8(8).
PMID: 37624342 PMC: 10459203. DOI: 10.3390/tropicalmed8080404.
Characterization of superspreaders movement in a bidirectional corridor using a social force model.
Kante D, Jebrane A, Hakim A, Boukamel A Front Public Health. 2023; 11:1188732.
PMID: 37575110 PMC: 10416642. DOI: 10.3389/fpubh.2023.1188732.
Zelenkov Y, Reshettsov I Expert Syst Appl. 2023; 224:120034.
PMID: 37033691 PMC: 10072952. DOI: 10.1016/j.eswa.2023.120034.