Challenges of COVID-19 Case Forecasting in the US, 2020–2021
Baseline (sea)
Pandemic
DOI:
10.1371/journal.pcbi.1011200
Publication Date:
2024-05-06T17:58:34Z
AUTHORS (109)
ABSTRACT
During the COVID-19 pandemic, forecasting trends to support planning and response was a priority for scientists decision makers alike. In United States, coordinated by large group of universities, companies, government entities led Centers Disease Control Prevention US Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts weekly state-level cases predictions 1–4 weeks into future submitted 24 teams from August 2020 December 2021. assessed coverage central prediction intervals weighted interval scores (WIS), adjusting missing relative baseline forecast, used Gaussian generalized estimating equation (GEE) model evaluate differences in skill across epidemic phases that were defined effective reproduction number. Overall, we found high variation individual models, with ensemble-based outperforming other approaches. generally higher larger jurisdictions (e.g., states compared counties). Over time, performed worst periods rapid changes reported (either increasing or decreasing phases) 95% dropping below 50% during growth winter 2020, Delta, Omicron waves. Ideally, case could serve as leading indicator transmission dynamics. However, while most outperformed naïve model, even accurate unreliable key phases. Further research improve indicators, like cases, leveraging additional real-time data, addressing performance phases, improving characterization forecast confidence, ensuring coherent spatial scales. meantime, it is critical users appreciate current limitations use broad set indicators inform pandemic-related making.
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