ArticleScientific reports2020
Forecasting the spread of COVID-19 under different reopening strategies.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global prevalence of COVID-19-induced acute respiratory distress syndrome: systematic review and meta-analysis.Systematic reviews · 2023Pooled it
- Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic.Scientific reports · 2025Article
- Global, regional, and national burden of acute glomerulonephritis from 1990 to 2021 and future trend predictions until 2036: a systematic analysis using the Global Burden of Disease Study 2021.Frontiers in public health · 2025Article
- Prediction of cross-border spread of the COVID-19 pandemic: A predictive model for imported cases outside China.PloS one · 2024Article
- A novel online multi-task learning for COVID-19 multi-output spatio-temporal prediction.Heliyon · 2023Article
- Novel model prediction time-to-event analysis: data validation and estimation of 200 million cases in the global COVID-19 epidemic.BMJ open · 2023Article
- Novel indicator for the spread of new coronavirus disease 2019 and its association with human mobility in Japan.Scientific reports · 2023Article
- Article
- Learning from the COVID-19 pandemic in Italy to advance multi-hazard disaster risk management.Progress in disaster science · 2022Article
- A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior.Scientific reports · 2022Article
- Chimeric forecasting: combining probabilistic predictions from computational models and human judgment.BMC infectious diseases · 2022Article
- Improving health across sectors: Best practices for the implementation of health in all policies approaches.Preventive medicine reports · 2022Article
- Usage of Compartmental Models in Predicting COVID-19 Outbreaks.The AAPS journal · 2022Review
- Listening to bluetooth beacons for epidemic risk mitigation.Scientific reports · 2022Article
- Human robot interaction as a service for combatting COVID-19: an experimental case study.Journal of ambient intelligence and humanized computing · 2022Article
- Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.Scientific reports · 2022Article
- The allometric propagation of COVID-19 is explained by human travel.Infectious Disease Modelling · 2022Article
- Impact of national culture on the severity of the COVID-19 pandemic.Current psychology (New Brunswick, N.J.) · 2022Article
- COVID-19 Surveillance Updates in US Metropolitan Areas: Dynamic Panel Data Modeling.JMIR public health and surveillance · 2022Article
- Microsimulation based quantitative analysis of COVID-19 management strategies.PLoS computational biology · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We combine COVID-19 case data with mobility data to estimate a modified susceptible-infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we find that the incidence of COVID-19 spread is concave in the number of infectious individuals, as would be expected if people have inter-related social networks. This concave shape has a significant impact on forecasted COVID-19 cases. In particular, our model forecasts that the number of COVID-19 cases would only have an exponential growth for a brief period at the beginning of the contagion event or right after a reopening, but would quickly settle into a prolonged period of time with stable, slightly declining levels of disease spread. This pattern is consistent with observed levels of COVID-19 cases in the US, but inconsistent with standard SIR modeling. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19.
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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.