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. 2022 Nov 27;19(23):15771.
doi: 10.3390/ijerph192315771.

Simulating and Forecasting the COVID-19 Spread in a U.S. Metropolitan Region with a Spatial SEIR Model

Faizeh Hatami  1 , Shi Chen  2   3 , Rajib Paul  2   3 , Jean-Claude Thill  1   3
Affiliations

Simulating and Forecasting the COVID-19 Spread in a U.S. Metropolitan Region with a Spatial SEIR Model

Faizeh Hatami et al. Int J Environ Res Public Health. .

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.

Keywords: SEIR model; approximate Bayesian computation; epidemic model; mobility; spatial SEIR model; spatial dependence; temporal variability.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Map of the Charlotte–Concord–Gastonia MSA.
Figure 2
Figure 2
Reported historical (blue dots) COVID-19 cases and cases simulated with model 2 (black line) in 10 counties of the study area, including the last 4 weeks not used for model fitting. The 5% confidence interval is shown with dashed lines. The last 4 weeks to the right of the gray vertical lines show the forecasted number of cases.
See this image and copyright information in PMC

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