The impact of threshold decision mechanisms of collective behaviour on disease spread

Abstract

Humans are a hyper social species, which greatly impacts the spread of infectious diseases. How do social dynamics impact epidemiology? How does public health policy best take into account these impacts? Here we develop a model of disease transmission that incorporates human behaviour and social dynamics. We use a "tipping-point" dynamic, previously used in the sociological literature, where individuals adopt a behaviour given a sufficient frequency of the behaviour in the population. The thresholds at which individuals adopt behaviours is modulated by the perceived risks of infection, i.e.\ the disease prevalence and transmission rate, and the behaviour of others. Social conformity creates a type of "stickiness" whereby individuals are resistant to changing their behaviour due to the population's inertia. In this model, the epidemic attack rate is sensitive to the timing of the behavioural response. Near the optimal response, small errors can result in large increases in the total number infected during the epidemic. And, more surprisingly, we observe a non-monotinicity in the attack rate as a function of various biological and social parameters such as the transmission rate, efficacy of social distancing, the costs to social distancing, the weight of social consequences of shirking the norm, and the degree of heterogeneity in the population.

Vaccination and collective action under social norms

“…The change in v ( t ) is determined by the Granovetter-Schelling social dynamic, Equation 1d. This dynamic was originally developed in the social science literature to model collective action [23–26, 30, 40, 41], and has recently been employed to model the uptake of non-pharmaceutical interventions during an epidemic [32]. f (Δ π ( I ( t ), v ( t ))) ∈ [0, 1] is a smoothed best response function of the difference between the payoffs to choosing to be vaccinated and choosing not be vaccinated, Δ π ( I ( t ), v ( t )) (which in turn is a function of the prevalence of infection and vaccination rate as discussed below).…”

“… is the social cost, which is positive if . The payoff difference is therefore A similar type of payoff difference has been previously used to model the adoption of non-pharmaceutical interventions, which change the transmission rate [32].…”

“…And, during the COVID-19 pandemic, this literature has grown immensely. These models include individuals’ awareness of the the death rate or infection rates [32, 48] as well as individual decision making about uptake of non-pharmaceutical interventions [32, 37, 39]. Such models have shown that public policy makers face difficult decisions in light of the role of social dynamics.…”

“…Such models have shown that public policy makers face difficult decisions in light of the role of social dynamics. One example is that optimal social distancing levels can be highly sensitive to the R 0 of the disease [32], and another is that misinformation can undermine the efficacy of public policy [43]. More generally, public policy makers cannot assume that individuals are purely rational decision makers.…”

“…a social cost) is generated from deviating from others’ behaviour, since individuals are assumed to be conformists. It has been found that such conformity can result in non-monotonicity of the attack rate with respect to key epidemiological parameters such as the transmission rate the and the efficacy of non-pharmaceutical interventions [32]. Together, these factors determine individual’s vaccine decision making, and thus the course of the disease.…”