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Comparative Study
. 2021 Nov:195:103-112.
doi: 10.1016/j.ymeth.2021.04.003. Epub 2021 Apr 8.

Eliciting Beliefs about COVID-19 Prevalence and Mortality: Epidemiological Models Compared with The Street

Glenn W Harrison  1 , Andre Hofmeyr  2 , Harold Kincaid  3 , Brian Monroe  4 , Don Ross  5 , Mark Schneider  6 , J Todd Swarthout  7
Affiliations
Comparative Study

Eliciting Beliefs about COVID-19 Prevalence and Mortality: Epidemiological Models Compared with The Street

Glenn W Harrison et al. Methods. 2021 Nov.

Abstract

Subjective belief elicitation about uncertain events has a long lineage in the economics and statistics literatures. Recent developments in the experimental elicitation and statistical estimation of subjective belief distributions allow inferences about whether these beliefs are biased relative to expert opinion, and the confidence with which they are held. Beliefs about COVID-19 prevalence and mortality interact with risk management efforts, so it is important to understand relationships between these beliefs and publicly disseminated statistics, particularly those based on evolving epidemiological models. The pandemic provides a unique setting over which to bracket the range of possible COVID-19 prevalence and mortality outcomes given the proliferation of estimates from epidemiological models. We rely on the epidemiological model produced by the Institute for Health Metrics and Evaluation together with the set of epidemiological models summarised by FiveThirtyEight to bound prevalence and mortality outcomes for one-month, and December 1, 2020 time horizons. We develop a new method to partition these bounds into intervals, and ask subjects to place bets on these intervals, thereby revealing their beliefs. The intervals are constructed such that if beliefs are consistent with epidemiological models, subjects are best off betting the same amount on every interval. We use an incentivised experiment to elicit beliefs about COVID-19 prevalence and mortality from 598 students at Georgia State University, using six temporally-spaced waves between May and November 2020. We find that beliefs differ markedly from epidemiological models, which has implications for public health communication about the risks posed by the virus.

Keywords: Beliefs; COVID-19 mortality; COVID-19 prevalence; Subjective beliefs.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported here.

Figures

Fig. 1
Fig. 1
Subjective Belief Task Interface and Bets of Subject #183 on May 29, 2020.
Fig. 2
Fig. 2
Bias and Confidence of Subjective Belief Distributions
Fig. 3
Fig. 3
Bets for Equiprobable Events.
Fig. 4
Fig. 4
Beliefs about COVID-19 infections in the U.S. by June 30, 2020.
Fig. 5
Fig. 5
Beliefs about COVID-19 deaths in the U.S. by June 30, 2020.
See this image and copyright information in PMC

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References

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