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.
| Original language | English |
|---|---|
| Article number | 105615 |
| Journal | BioSystems |
| Volume | 258 |
| Early online date | 16 Oct 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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