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An expert judgment model to predict early stages of the COVID-19 outbreak in the United States.

ABSTRACT: During early stages of the COVID-19 pandemic, forecasts provided actionable information about disease transmission to public health decision-makers. Between February and May 2020, experts in infectious disease modeling made weekly predictions about the impact of the pandemic in the U.S. We aggregated these predictions into consensus predictions. In March and April 2020, experts predicted that the number of COVID-19 related deaths in the U.S. by the end of 2020 would be in the range of 150,000 to 250,000, with scenarios of near 1m deaths considered plausible. The wide range of possible future outcomes underscored the uncertainty surrounding the outbreak's trajectory. Experts' predictions of measurable short-term outcomes had varying levels of accuracy over the surveys but showed appropriate levels of uncertainty when aggregated. An expert consensus model can provide important insight early on in an emerging global catastrophe.

SUBMITTER: McAndrew T

PROVIDER: S-EPMC7523166 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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An expert judgment model to predict early stages of the COVID-19 outbreak in the United States.

McAndrew Thomas T Reich Nicholas G NG

medRxiv : the preprint server for health sciences 20200923

During early stages of the COVID-19 pandemic, forecasts provided actionable information about disease transmission to public health decision-makers. Between February and May 2020, experts in infectious disease modeling made weekly predictions about the impact of the pandemic in the U.S. We aggregated these predictions into consensus predictions. In March and April 2020, experts predicted that the number of COVID-19 related deaths in the U.S. by the end of 2020 would be in the range of 150,000 to ...[more]

PMID: 32995825

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Project description:Commercial fisheries globally experienced numerous and significant perturbations during the early months of the COVID-19 pandemic, affecting the livelihoods of millions of fishers worldwide. In the Northeast United States, fishers grappled with low prices and disruptions to export and domestic markets, leaving many tied to the dock, while others found ways to adapt to the changing circumstances brought about by the pandemic. This paper investigates the short-term impacts of the early months of the COVID-19 pandemic (March-June 2020) on commercial fishers in the Northeast U.S. to understand the effects of the pandemic on participation in the fishery and fishers' economic outcomes, using data collected from an online survey of 258 Northeast U.S. commercial fishers. This research also assesses characteristics of those fishers who continued fishing and their adaptive strategies to the changing circumstances. Analysis of survey responses found the majority of fishers continued fishing during the early months of the pandemic, while a significant number had stopped fishing. Nearly all reported a loss of income, largely driven by disruptions of export markets, the loss of restaurant sales, and a resulting decline in seafood prices. Landings data demonstrate that while fishing pressure in 2020 was reduced for some species, it remained on track with previous years for others. Fishers reported engaging in a number of adaptation strategies, including direct sales of seafood, switching species, and supplementing their income with government payments or other sources of income. Many fishers who had stopped fishing indicated plans to return, suggesting refraining from fishing as a short-term adaptation strategy, rather than a plan to permanently stop fishing. Despite economic losses, fishers in the Northeast U.S. demonstrated resilience in the face of the pandemic by continuing to fish and implementing other adaptation strategies rather than switching to other livelihoods.

Dataset Information

An expert judgment model to predict early stages of the COVID-19 outbreak in the United States.

Publications

An expert judgment model to predict early stages of the COVID-19 outbreak in the United States.

Similar Datasets

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