tetano
Editor, Senior Moderator
F1000Res
. 2020 Apr 23;9:283.
doi: 10.12688/f1000research.23401.1. eCollection 2020.
Predicting the evolution and control of the COVID-19 pandemic in Portugal
Ricardo J Pais[SUP] 1 [/SUP], Nuno Taveira[SUP] 1 2 [/SUP]
Affiliations
Abstract
Coronavirus disease 2019 (COVID-19) is a worldwide pandemic that has been affecting Portugal since 2 March 2020. The Portuguese government has been making efforts to contradict the exponential growth through social isolation measures. We have developed a mathematical model to predict the impact of such measures in the number of infected cases and peak of infection. We estimate the peak to be around 2 million infected cases by the beginning of May if no additional measures are taken. The model shows that current measures effectively isolated 25-30% of the population, contributing to some reduction on the infection peak. Importantly, our simulations show that the infection burden can be further reduced with higher isolation degree, providing information for a second intervention.
Keywords: COVID-19; Mathematical model; Pandemic Control; Predictive modeling; Simulation; Social Isolation.
. 2020 Apr 23;9:283.
doi: 10.12688/f1000research.23401.1. eCollection 2020.
Predicting the evolution and control of the COVID-19 pandemic in Portugal
Ricardo J Pais[SUP] 1 [/SUP], Nuno Taveira[SUP] 1 2 [/SUP]
Affiliations
- PMID: 32983416
- PMCID: PMC7503179
- DOI: 10.12688/f1000research.23401.1
Abstract
Coronavirus disease 2019 (COVID-19) is a worldwide pandemic that has been affecting Portugal since 2 March 2020. The Portuguese government has been making efforts to contradict the exponential growth through social isolation measures. We have developed a mathematical model to predict the impact of such measures in the number of infected cases and peak of infection. We estimate the peak to be around 2 million infected cases by the beginning of May if no additional measures are taken. The model shows that current measures effectively isolated 25-30% of the population, contributing to some reduction on the infection peak. Importantly, our simulations show that the infection burden can be further reduced with higher isolation degree, providing information for a second intervention.
Keywords: COVID-19; Mathematical model; Pandemic Control; Predictive modeling; Simulation; Social Isolation.