{"title":"The threat of asymptomatic carriers and the benefits of testing","authors":"Luca Zamboni","doi":"10.1016/j.biosystems.2025.105615","DOIUrl":null,"url":null,"abstract":"<div><div>I present a model of infectious disease transmission with asymptomatic carriers, social distancing, and diagnostic testing. First, I study the impact of asymptomatic carriers on the spread of an infectious disease in the absence of testing, to determine when their presence increases the overall prevalence of symptomatic infection and hence unhealthy agents. Then, I consider mass testing and isolation policies to identify and isolate asymptomatic carriers, and incorporate them into my model. I establish that diagnostic testing successfully reduces steady state disease prevalence. I then explore the implications of testing accuracy, explicitly studying the impact of false positive and false negative test results. I find that reducing the rate of false negatives is unambiguously beneficial, since it improves the identification and isolation of asymptomatic carriers. In contrast, reducing the rate of false positives can be detrimental: by limiting the unintended isolation of susceptible individuals, lower rates of false positives reduce the overall level of social distancing in the population and increase disease spread. Hence, I demonstrate how, under certain conditions, false positive results can improve social welfare.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"258 ","pages":"Article 105615"},"PeriodicalIF":1.9000,"publicationDate":"2025-10-13","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/S0303264725002254","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
I present a model of infectious disease transmission with asymptomatic carriers, social distancing, and diagnostic testing. First, I study the impact of asymptomatic carriers on the spread of an infectious disease in the absence of testing, to determine when their presence increases the overall prevalence of symptomatic infection and hence unhealthy agents. Then, I consider mass testing and isolation policies to identify and isolate asymptomatic carriers, and incorporate them into my model. I establish that diagnostic testing successfully reduces steady state disease prevalence. I then explore the implications of testing accuracy, explicitly studying the impact of false positive and false negative test results. I find that reducing the rate of false negatives is unambiguously beneficial, since it improves the identification and isolation of asymptomatic carriers. In contrast, reducing the rate of false positives can be detrimental: by limiting the unintended isolation of susceptible individuals, lower rates of false positives reduce the overall level of social distancing in the population and increase disease spread. Hence, I demonstrate how, under certain conditions, false positive results can improve social welfare.
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.