COVID-19 in regions with low prevalence and low density of population. An uncertainty dynamic modeling approach

Abstract

AbstractThe coronavirus disease 2019 (COVID-19) that emerged in China at the end of 2019 has spread worldwide. In this article, we present a mathematical SEIR model focused on analysing the transmission dynamics of COVID-19, the patients circulating in the hospitals and evaluating the effects of health policies and vaccination on the control of the pandemic. We tested the model using registered cases and population data from the province of Granada (Spain), that represents a population size near 1 million citizens with low density of population and low prevalence. After calibrating the model with the data obtained from 15 March to 22 September 2020, we simulate different vaccination scenarios - including effectiveness and availability date - in order to study the possible evolution of the disease. The results show that: 1) infected will increase until 5.6% - 7.4% of the total population over next 3-4 months (2nd wave); 2) vaccination seems not to be enough to face the pandemic and other strategies should be used; 3) we also support the claim of the WHO about the effectiveness of the vaccine, that should be, at least, of 50% to represent a substantial progress against the COVID-19; 4) after the 2nd wave, the return to normal life should be controlled and gradual to avoid a 3rd wave. The proposed study may be a useful tool for giving insight into the transmission dynamics of SARS-CoV-2 and to design vaccination and health policies.