{"title":"Antagonistic coinfection in rock–paper–scissors models during concurrent epidemics","authors":"J. Menezes , R. Menezes , S. Batista , E. Rangel","doi":"10.1016/j.biosystems.2025.105616","DOIUrl":null,"url":null,"abstract":"<div><div>We investigate the dynamics of dual disease epidemics within the spatial rock–paper–scissors model. In this framework, individuals from all species are equally susceptible to infection by two distinct pathogens transmitted via person-to-person contact. We assume antagonistic mortality, where the simultaneous occurrence of coinfection reduces the probability of host mortality due to complications arising from either coexisting disease. Specifically, we explore two scenarios: global antagonism, where the presence of one pathogen inhibits the progression of the other in coinfected hosts, and uneven antagonism, where only one pathogen affects the development of the other. Using stochastic simulations, we show that the characteristic length scale of the spatial patterns emerging from random initial conditions diminishes as antagonism becomes more significant. We find that antagonism enhances species population growth and reduces the average probability of healthy organisms becoming infected. Additionally, introducing individuals’ mobility restrictions significantly decreases both organisms’ infection risk and selection pressures. Our results demonstrate that combining mobility restrictions with antagonistic coinfection can increase organisms’ life expectancy by up to 54%. Our findings show that integrating antagonistic coinfection and mobility restriction strategies into ecological models may provide insights into designing interventions for managing concurrent epidemics in complex systems.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"258 ","pages":"Article 105616"},"PeriodicalIF":1.9000,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0303264725002266","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
We investigate the dynamics of dual disease epidemics within the spatial rock–paper–scissors model. In this framework, individuals from all species are equally susceptible to infection by two distinct pathogens transmitted via person-to-person contact. We assume antagonistic mortality, where the simultaneous occurrence of coinfection reduces the probability of host mortality due to complications arising from either coexisting disease. Specifically, we explore two scenarios: global antagonism, where the presence of one pathogen inhibits the progression of the other in coinfected hosts, and uneven antagonism, where only one pathogen affects the development of the other. Using stochastic simulations, we show that the characteristic length scale of the spatial patterns emerging from random initial conditions diminishes as antagonism becomes more significant. We find that antagonism enhances species population growth and reduces the average probability of healthy organisms becoming infected. Additionally, introducing individuals’ mobility restrictions significantly decreases both organisms’ infection risk and selection pressures. Our results demonstrate that combining mobility restrictions with antagonistic coinfection can increase organisms’ life expectancy by up to 54%. Our findings show that integrating antagonistic coinfection and mobility restriction strategies into ecological models may provide insights into designing interventions for managing concurrent epidemics in complex systems.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.