ArticlePLoS computational biology2022
Enhancing long-term forecasting: Learning from COVID-19 models.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Multivariable Behavioral Change Modeling of Epidemics in the Presence of Undetected Infections.Statistics in medicine · 2026Article
- Evaluation of respiratory disease hospitalisation forecasts using synthetic outbreak data.Communications medicine · 2026Article
- Population-level behavioral and structural drivers of COVID-19 vaccine uptake in the US.PLoS computational biology · 2026Article
- Faster Uptake, Slower Let-Down: Asymmetric Community Responses to Changing Risks During a Pandemic.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Emerging and re-emerging vector-borne and other zoonotic RNA viruses: pathogenesis, climate-driven dynamics, and strategies for global control.Frontiers in microbiology · 2026Review
- A hybrid STL-LightGBM framework with probabilistic forecasting for Influenza A incidence in the post-pandemic Saudi Arabia.Frontiers in public health · 2026Article
- Simulating nationwide coupled disease and fear spread in an agent-based model.Scientific reports · 2025Article
- Identifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic.BMC medical research methodology · 2025Article
- Machine Learning-Driven COVID-19 Hospitalization Forecasting: From Theory to Practice in a Major Northeastern Academic Medical Center.Open forum infectious diseases · 2025Article
- Incorporating endogenous human behavior in models of COVID-19 transmission: A systematic scoping review.Dialogues in health · 2024Article
- Parameter estimation in behavioral epidemic models with endogenous societal risk-response.PLoS computational biology · 2024Article
- Validation framework for epidemiological models with application to COVID-19 models.PLoS computational biology · 2023Article
- Coupling an individual adaptive-decision model with a SIRV model of influenza vaccination reveals new insights for epidemic control.Statistics in medicine · 2023Article
- Implicit feedback policies for COVID-19: why "zero-COVID" policies remain elusive.Scientific reports · 2023Article
- A missing behavioural feedback in COVID-19 models is the key to several puzzles.BMJ global health · 2022Article
- Effect of mandating vaccination on COVID-19 cases in colleges and universities.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
- Quantifying the COVID-19 endgame: Is a new normal within reach?System dynamics review · 2022Article
- Behavioral responses to risk promote vaccinating high-contact individuals first.System dynamics reviewArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While much effort has gone into building predictive models of the COVID-19 pandemic, some have argued that early exponential growth combined with the stochastic nature of epidemics make the long-term prediction of contagion trajectories impossible. We conduct two complementary studies to assess model features supporting better long-term predictions. First, we leverage the diverse models contributing to the CDC repository of COVID-19 USA death projections to identify factors associated with prediction accuracy across different projection horizons. We find that better long-term predictions correlate with: (1) capturing the physics of transmission (instead of using black-box models); (2) projecting human behavioral reactions to an evolving pandemic; and (3) resetting state variables to account for randomness not captured in the model before starting projection. Second, we introduce a very simple model, SEIRb, that incorporates these features, and few other nuances, offers informative predictions for as far as 20-weeks ahead, with accuracy comparable with the best models in the CDC set. Key to the long-term predictive power of multi-wave COVID-19 trajectories is capturing behavioral responses endogenously: balancing feedbacks where the perceived risk of death continuously changes transmission rates through the adoption and relaxation of various Non-Pharmaceutical Interventions (NPIs).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.