Population behavioural dynamics can mediate the persistence of emerging infectious diseases

Abstract

The critical community size (CCS) is the minimum closed population size in which a pathogen can persist indefinitely. Below this threshold, stochastic extinction eventually causes pathogen extinction. Here we use a simulation model to explore behaviour-mediated persistence: a novel mechanism by which the population response to the pathogen determines the CCS. We model severe coronavirus 2 (SARS-CoV-2) transmission and non-pharmaceutical interventions (NPIs) in a population where both individuals and government authorities restrict transmission more strongly when SARS-CoV-2 case numbers are higher. This results in a coupled human-environment feedback between disease dynamics and population behaviour. In a parameter regime corresponding to a moderate population response, this feedback allows SARS-CoV-2 to avoid extinction in the trough of pandemic waves. The result is a very low CCS that allows long term pathogen persistence. Hence, an incomplete pandemic response represents a “sour spot” that not only ensures relatively high case incidence and unnecessarily long lockdown, but also promotes long-term persistence of the pathogen by reducing the CCS. Given the worldwide prevalence of small, isolated populations in which a pathogen with low CCS can persist, these results emphasize the need for a global approach to coronavirus disease 2019 (COVID-19) vaccination.

The effect of delayed awareness and fatigue on the efficacy of self-isolation in epidemic control

“…Finally, adherence to self-isolation may be the result of an individual component, explored here, along with a population component defined by a level of awareness and of risk perception that may evolve over time [41], depending on the evolving epidemic context. This may be an important component contributing to the observed relaxation effects after COVID-19 pandemic wave, possibly resulting in case resurgences [42][43][44].…”

Coupling the socio-economic and ecological dynamics of cyanobacteria: single lake and network dynamics

“…For example, the importance of linking human and social dynamics to climate models to understand climate trajectories has been addressed [4,5]. Other researchers have used social processes to better understand disease outbreaks [6,7]. Ecologically, social dynamics have been coupled to forestry, fishery and other common-pool resource models to gain insight towards the balance between sustainable resource use and profit seekers [8][9][10][11].…”