Changes in risk perception and self-reported protective behaviour during the first week of the COVID-19 pandemic in the United States

Abstract

Efforts to change behaviour are critical in minimizing the spread of highly transmissible pandemics such as COVID-19. However, it is unclear whether individuals are aware of disease risk and alter their behaviour early in the pandemic. We investigated risk perception and self-reported engagement in protective behaviours in 1591 United States-based individuals cross-sectionally and longitudinally over the first week of the pandemic. Subjects demonstrated growing awareness of risk and reported engaging in protective behaviours with increasing frequency but underestimated their risk of infection relative to the average person in the country. Social distancing and hand washing were most strongly predicted by the perceived probability of personally being infected. However, a subgroup of individuals perceived low risk and did not engage in these behaviours. Our results highlight the importance of risk perception in early interventions during large-scale pandemics.

Estimating and explaining the spread of COVID-19 at the county level in the USA

“…The first factor is the timing of the onset of county-level epidemic: 35% of the local outbreaks started after the declaration of COVID-19 as a pandemic by the WHO on 11 March, 2020 22 . Therefore, we anticipated estimates of r 0 to decrease with the Julian date of outbreak onset due to changes in human behaviors caused by public awareness about COVID-19 7 . Because our goal was to estimate disease spread under “normal” conditions, we wanted to factor out the effect of timing.…”

“…Using R 0 estimates to design public health policies is predicated on the assumption that the R 0 values at the start of the epidemic reflect properties of the infective agent and population, and therefore predict the potential rate of spread of the disease. Estimates of R 0 , however, might not predict future risks if (i) they are measured after perceived risks have generated government actions or pre-emptive personal measures to reduce the spread rate 5 – 7 , (ii) they are driven by stochastic events, such as super-spreading 8 , 9 , or (iii) they are driven by social or environmental conditions that are likely to change between the time of initial epidemic and the future time for which public health interventions are designed 10 , 11 . To address these potential limitations for using R 0 to design public health policies and future risks of spread, we investigated possible underlying causes for variation in estimates of R 0 among counties: if the causes are unlikely to change in the future, then so too are values of R 0 unlikely to change.…”

Causal Modeling of Twitter Activity during COVID-19

“…As it is important to observe the countries that are ahead in terms of pandemic timeline and learn the behaviour of the pandemic, it is equally important to understand also the public attention and sentiment characteristics from those countries. Wise et al show that risk perception of people and their frequency of engagement in protective behaviour change during the early stages of the pandemic [90]. Inference of such patterns in a causal manner from social media can aid us in the pursuit of timely decisions and suitable policy-making, and consequently, high public engagement.…”

Risk Perception of COVID−19 Community Transmission among the Spanish Population

“…Risk perception belongs to the psychology category, which refers to an individual's perception and understanding of the presence of objective danger to the individual or to the individual's environment [27,28] Risk perception is an important factor that influences risk behaviours, such as whether or not to accept vaccination [29]. People with a lower risk perception tend to assume risky behaviours or reduce preventive behaviours, as shown by the Ding study, to the Chinese university population [21].…”