Impact of Travel on Spread of Infection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149965" target="_blank" >RIV/00216305:26220/23:PU149965 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-031-42689-6_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-42689-6_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-42689-6_8" target="_blank" >10.1007/978-3-031-42689-6_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Impact of Travel on Spread of Infection

Popis výsledku v původním jazyce

In this paper, we are concerned with a generalization of the classical SIR model describing the dynamics of an infectious disease. Two distinctive features of the proposed model are: (i) the split of the cohort of susceptible into two sub-cohorts, frequent travelers running higher risks of being infected and individuals who do not travel with a lower infection rate, and (ii) lack of immunity to disease with the possibility of re-infection after recovery. These modifications reflect recent experience from Covid-19 epidemics when countries were introducing quarantine measures or travel restrictions and multiple cases of repeated reinfection of individuals were reported. Numerical simulations demonstrate that the ratio between the infection rates of mobile and non-mobile susceptible significantly impacts the dynamics of the disease. Higher infection rates for a smaller sub-cohort of active travelers lead to earlier epidemics outbreaks and affect a larger proportion of individuals.

Název v anglickém jazyce

Impact of Travel on Spread of Infection

Popis výsledku anglicky

In this paper, we are concerned with a generalization of the classical SIR model describing the dynamics of an infectious disease. Two distinctive features of the proposed model are: (i) the split of the cohort of susceptible into two sub-cohorts, frequent travelers running higher risks of being infected and individuals who do not travel with a lower infection rate, and (ii) lack of immunity to disease with the possibility of re-infection after recovery. These modifications reflect recent experience from Covid-19 epidemics when countries were introducing quarantine measures or travel restrictions and multiple cases of repeated reinfection of individuals were reported. Numerical simulations demonstrate that the ratio between the infection rates of mobile and non-mobile susceptible significantly impacts the dynamics of the disease. Higher infection rates for a smaller sub-cohort of active travelers lead to earlier epidemics outbreaks and affect a larger proportion of individuals.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Computational and Mathematical Models in Biology

ISBN

978-3-031-42688-9

Počet stran výsledku

29

Strana od-do

183-211

Počet stran knihy

329

Název nakladatele

Springer Cham

Místo vydání

Cham, Switzerland

Kód UT WoS kapitoly

—