Estimates of the collective immunity to COVID-19 derived from a stochastic cellular automaton based framework

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dc.contributor.authorLima I.
dc.contributor.authorBalbi P.P.
dc.date.accessioned2024-03-12T19:14:08Z
dc.date.available2024-03-12T19:14:08Z
dc.date.issued2022
dc.description.abstract© 2022, The Author(s), under exclusive licence to Springer Nature B.V.In the context of the propagation of infectious diseases, when a sufficient degree of immunisation is achieved within a population, the spread of the disease is ended or significantly decreased, leading to collective immunity, meaning the indirect protection given by immune individuals to susceptible individuals. Here we describe the estimates of the collective immunity to COVID-19 from a stochastic cellular automaton based model designed to emulate the spread of SARS-CoV-2 in a population of static individuals interacting only via a Moore neighbourhood of radius one, with a view to analyze the impact of initially immune individuals on the dynamics of COVID-19. This impact was measured by comparing a progression of initial immunity ratio—the percentage of immunised individuals before patient zero starts infecting its neighbourhood—from 0 to 95% of the initial population, with the number of susceptible individuals not contaminated, the peak value of active cases, the total number of deaths and the emulated pandemic duration in days. The influence of this range of immunities over the model was tested with different parameterisations regarding the uncertainties involved in the model such as the durations of the cellular automaton states, the contamination contributions of each state and the state transition probabilities. A collective immunity threshold of 55 % ± 2.5 % on average was obtained from this procedure, under four distinct parameterisations, which is in tune with the estimates of the currently available medical literature, even increasing the uncertainty of the input parameters.
dc.description.firstpage449
dc.description.issuenumber3
dc.description.lastpage461
dc.description.volume21
dc.identifier.doi10.1007/s11047-022-09893-3
dc.identifier.issn1572-9796
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/34318
dc.relation.ispartofNatural Computing
dc.rightsAcesso Aberto
dc.subject.otherlanguagecollective immunity
dc.subject.otherlanguageContagious disease dynamic
dc.subject.otherlanguageCOVID-19
dc.subject.otherlanguageSARS-CoV-2
dc.subject.otherlanguageStochastic cellular automaton
dc.titleEstimates of the collective immunity to COVID-19 derived from a stochastic cellular automaton based framework
dc.typeArtigo
local.scopus.citations3
local.scopus.eid2-s2.0-85132178559
local.scopus.subjectAutomata-based model
local.scopus.subjectCollective immunity
local.scopus.subjectContagious disease
local.scopus.subjectContagious disease dynamic
local.scopus.subjectDisease dynamics
local.scopus.subjectInfectious disease
local.scopus.subjectInitial population
local.scopus.subjectNeighbourhood
local.scopus.subjectStochastic cellular automaton
local.scopus.subjectUncertainty
local.scopus.updated2024-12-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85132178559&origin=inward
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