ArticleInternational journal of environmental research and public health2022
Simulating and Forecasting the COVID-19 Spread in a U.S. Metropolitan Region with a Spatial SEIR Model.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Influence of spatial connectivity on the spread of Mpox in Maï-Ndombe province, Democratic Republic of the Congo, 2025.International journal of health geographics · 2026Article
- Spatial Interaction Analysis of Infectious Disease Import and Export between Regions.International journal of environmental research and public health · 2024Article
- Modeling the Impacts of Governmental and Human Responses on COVID-19 Spread Using Statistical Machine Learning.International journal of digital earth · 2024Article
- Forecasting the Endemic/Epidemic Transition in COVID-19 in Some Countries: Influence of the Vaccination.Diseases (Basel, Switzerland) · 2023Article
- Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission.International journal of environmental research and public health · 2023Article
- Modeling Consequences of COVID-19 and Assessing Its Epidemiological Parameters: A System Dynamics Approach.Healthcare (Basel, Switzerland) · 2023Article
- Multiple Concurrent Causal Relationships and Multiple Governance Pathways for Non-Pharmaceutical Intervention Policies in Pandemics: A Fuzzy Set Qualitative Comparative Analysis Based on 102 Countries and Regions.International journal of environmental research and public health · 2023Article
- Quantifying Social Interventions for Combating COVID-19 via a Symmetry-Based Model.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global COVID-19 pandemic has taken a heavy toll on health, social, and economic costs since the end of 2019. Predicting the spread of a pandemic is essential to developing effective intervention policies. Since the beginning of this pandemic, many models have been developed to predict its pathways. However, the majority of these models assume homogeneous dynamics over the geographic space, while the pandemic exhibits substantial spatial heterogeneity. In addition, spatial interaction among territorial entities and variations in their magnitude impact the pandemic dynamics. In this study, we used a spatial extension of the SEIR-type epidemiological model to simulate and predict the 4-week number of COVID-19 cases in the Charlotte-Concord-Gastonia Metropolitan Statistical Area (MSA), USA. We incorporated a variety of covariates, including mobility, pharmaceutical, and non-pharmaceutical interventions, demographics, and weather data to improve the model's predictive performance. We predicted the number of COVID-19 cases for up to four weeks in the 10 counties of the studied MSA simultaneously over the time period 29 March 2020 to 13 March 2021, and compared the results with the reported number of cases using the root-mean-squared error (RMSE) metric. Our results highlight the importance of spatial heterogeneity and spatial interactions among locations in COVID-19 pandemic modeling.
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