Actions
  • shareshare
  • link
  • cite
  • add
add
Other research product . 2020

Matematisk modellering af COVID-19: En undersøgelse af skyggebæreres betydning for spredning af COVID-19

Wissing, Alberte Lund; Møller-Sørensen, Jon; Mølgaard, Antonie Lauritzen;
Open Access
Danish
Published: 01 Jan 2020
Country: Denmark
Abstract

Severe Acute Respiratory Syndrome Coronavirus-2 is a coronavirus that causes the disease COVID-19. The virus is transmitted mainly through small respiratory droplets from coughing or sneezing, where these droplets are then inhaled. The symptoms of COVID-19 vary in severity from being asymptomatic and in the more severe cases there is a risk of acute respiratory distress syndrome and pneumonia, which can poteintially lead to death. The asymptomatic cases is a problem, because they are as infectious as the servere cases, but they are not put in quarantine, which means they can still infect others. In this study we try to estimate the asymptomatic cases or non-registered cases, with an extended SEIR-model, using data from Iceland. In our extended SEIR-model we added two new I compartments, such that it consisted of both infected with no symptoms and infected with severe symptoms. The infected with severe symptoms will subsequently be placed in quarantine. We extended the SEIR-model, because in the classic SEIR-model it was not possible to differentiate the infected, since SEIR only gave an estimate on the total number of infections. In our SEIIIR-model we estimated different parameters to the associated compartments, to get the most optimal model. Since COVID-19 is an ongoing global pandemic, there is a lack of knowledge of the virus and the effective reproduction number is constantly changing. It is difficult to make any extensive conclutions. However, from this study we can conclude, that the non-registered cases have a big impact on the epidemic duration, R value and mortality, but to estimate the exact quantity requires a lot of testing, even on people who are feeling well.

Related Organizations
Related to Research communities
COVID-19
moresidebar