Abstract
The outbreak of an infectious disease in a human population can lead to individuals responding with preventive measures in an attempt to avoid getting infected. This leads to changes in contact patterns. However, as we show in this paper, rational behaviour at the individual level, such as social distancing from infectious contacts, may not always be beneficial for the population as a whole. We use epidemic network models to demonstrate the potential negative consequences at the population level. We take into account the social structure of the population through several network models. As the epidemic evolves, susceptible individuals may distance themselves from their infectious contacts. Some individuals replace their lost social connections by seeking new ties. If social distancing occurs at a high rate at the beginning of an epidemic, then this can prevent an outbreak from occurring. However, we show that moderate social distancing can worsen the disease outcome, both in the initial phase of an outbreak and the final epidemic size. Moreover, the same negative effect can arise in real-world networks. Our results suggest that one needs to be careful when targeting behavioural changes as they could potentially worsen the epidemic outcome. Furthermore, network structure crucially influences the way that individual-level measures impact the epidemic at the population level. These findings highlight the importance of careful analysis of preventive measures in epidemic models.
Highlights
Mathematical models for the spread of infections have been used successfully to increase understanding of how epidemics may propagate: what are the most important features to determine the initial epidemic growth, final epidemic size or endemic level? Mathematical models are useful to evaluate the possible effects on epidemic dynamics of preventive measures
Social distancing in the configuration network is always beneficial at the beginning of an epidemic in the sense that it lowers R0
While preventive social distancing at moderate rates is always rational at the individual level, it may be harmful at the population level
Summary
Mathematical models for the spread of infections have been used successfully to increase understanding of how epidemics may propagate: what are the most important features to determine the initial epidemic growth, final epidemic size or endemic level? Mathematical models are useful to evaluate the possible effects on epidemic dynamics of preventive measures. Individuals may take their own measures to prevent themselves from getting infected, e.g. by wearing face masks, taking hygienic measures such as hand washing, or by socially distancing themselves from infectious contacts Such individual behaviour has been observed in, for example, the recent Ebola outbreak and the 2009 A/H1N1 epidemic [2,3,4,5,6]. It is often recognized that humans do take preventive measures in the course of an epidemic, models that incorporate behavioural dynamics are generally much harder to analyse. Such models have started to receive more attention, and important advances have been made to gain understanding of the effect of different behavioural changes on epidemic dynamics [7,8,9,10]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
