Are perceived prevalences of infection also biased and how? Lessons from large epidemics of mosquito-borne diseases in tropical regions
Objectives: Although people have been repeatedly found to underestimate the frequency of risks to health from common diseases, we still do not know much about reasons for this systematic bias, which is also referred to as “primary bias” in the literature. In this study, we take advantage of a series of large epidemics of mosquito-borne diseases to examine the accuracy of judgments of risk frequencies. In this aim, we assessed the perceived versus the observed prevalence of infection by zika, chikungunya or dengue fever during these outbreaks, as well as their variations among different subpopulations and epidemiological settings.Design: We used data drawn from 4 telephone surveys, conducted between 2006 and 2016, among representative samples of the adult population in tropical regions (Reunion, Martinique, and French Guiana). The participants were asked to estimate the prevalence of these infections by using a natural frequency scale.Results: The surveys showed that (1) most people greatly overestimated the prevalence of infection by arbovirus, (2) these risk overestimations fell considerably as the actual prevalence of these diseases increased, (3) the better-educated and male participants consistently yielded less inaccurate risk estimates across epidemics, and (4) that these biases in the perception of prevalence of these infectious diseases are relatively well predicted by probability weighting function.Conclusions: These findings suggest that the cognitive biases that affect perception of prevalence of acute infectious diseases are not fundamentally different from those that characterize other types of probabilistic judgments observed in the field of behavioral decision-making. They also indicate that numeracy may play a considerable role in people’s ability to transform epidemiological observations from their social environment to more accurate risk estimates.