Your browser doesn't support javascript.
A chain binomial epidemic with asymptomatics motivated by COVID-19 modelling.
Lefèvre, Claude; Picard, Philippe; Simon, Matthieu; Utev, Sergey.
  • Lefèvre C; Département de Mathématique, Université Libre de Bruxelles, Campus Plaine C.P. 210, 1050, Brussels, Belgium. claude.lefevre@ulb.be.
  • Picard P; ISFA, LSAF EA2429, Univ Lyon, Université Lyon 1, 50 Avenue Tony Garnier, 69007, Lyon, France.
  • Simon M; Departament de Matemàtica Econòmica, Financera i Actuarial, Universitat de Barcelona, 690 Avinguda Diagonal, 08034, Barcelona, Spain.
  • Utev S; Département de Mathématique, Université de Mons, 20 Place du Parc, 7000, Mons, Belgium.
J Math Biol ; 83(5): 54, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1491092
ABSTRACT
Motivated by modelling epidemics like COVID-19, this paper proposes a generalized chain binomial process which integrates two types of infectives, those with symptoms and those without. Testing of infectives and vaccination of susceptibles are then incorporated as preventive protective measures. Our interest relates to the distribution of the state of the population at the end of infection and to the reproduction number [Formula see text] with the associated extinction condition. The method uses the construction of a family of martingales and a branching approximation for large populations, respectively. A more general branching process for epidemics is also constructed and studied. Finally, some results obtained are illustrated by numerical examples.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Topics: Vaccines Limits: Humans Language: English Journal: J Math Biol Year: 2021 Document Type: Article Affiliation country: S00285-021-01680-5

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Topics: Vaccines Limits: Humans Language: English Journal: J Math Biol Year: 2021 Document Type: Article Affiliation country: S00285-021-01680-5