ArticleProceedings of the National Academy of Sciences of the United States of America2021
Intracounty modeling of COVID-19 infection with human mobility: Assessing spatial heterogeneity with business traffic, age, and race.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed, 144 citations in OpenAlex.
- Risk and Spatial Spread of a Measles Outbreak in Texas.Viruses · 2026Article
- A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.Bulletin of mathematical biology · 2026Article
- Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City.PLoS computational biology · 2025Article
- Global urban activity changes from COVID-19 physical distancing restrictions.Scientific data · 2025Article
- Geographic Realities of Abortion Access in Texas: Exploring the Heterogeneous Effects of Texas Senate Bill 8 with Mobile Phone Data.Population research and policy review · 2025Article
- Interacting particle models on the impact of spatially heterogeneous human behavioral factors on dynamics of infectious diseases.PLoS computational biology · 2024Article
- Nonrepresentativeness of Human Mobility Data and its Impact on Modeling Dynamics of the COVID-19 Pandemic: Systematic Evaluation.JMIR formative research · 2024Article
- Building Environmental and Sociological Predictive Intelligence to Understand the Seasonal Threat of SARS-CoV-2 in Human Populations.The American journal of tropical medicine and hygiene · 2024Article
- Road networks and socio-demographic factors to explore COVID-19 infection during its different waves.Scientific reports · 2024Article
- First application of data assimilation-based control to fusion plasma.Scientific reports · 2024Article
- Modeling the Impacts of Governmental and Human Responses on COVID-19 Spread Using Statistical Machine Learning.International journal of digital earth · 2024Article
- Development of an Early-Phase Local Model for Pandemics Using Public Health Data: Application to the COVID-19 Pandemic.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Open-source data pipeline for street-view images: A case study on community mobility during COVID-19 pandemic.PloS one · 2024Article
- Revealing associations between spatial time series trends of COVID-19 incidence and human mobility: an analysis of bidirectionality and spatiotemporal heterogeneity.International journal of health geographics · 2023Article
- Change of urban park usage as a response to the COVID-19 global pandemic.Scientific reports · 2023Article
- Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data.PLoS computational biology · 2023Article
- COVID-19 is linked to changes in the time-space dimension of human mobility.Nature human behaviour · 2023Article
- Evaluating the strategies to control SARS-CoV-2 Delta variant spread in New Caledonia, a zero-COVID country until September 2021.IJID regions · 2023Article
- Using call detail records to determine mobility patterns of different socio-demographic groups in the western area of Sierra Leone during early COVID-19 crisis.Environment and planning. B, urban analytics and city science · 2023Article
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Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic is a global threat presenting health, economic, and social challenges that continue to escalate. Metapopulation epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic, and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What's more, variation of intracounty environments creates spatial heterogeneity of transmission in different regions. To address this issue, we develop a human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behaviors. This modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and business foot traffic, race and ethnicity, and age structure are then investigated. The results reveal that, in a college town (Dane County), the most important heterogeneity is age structure, while, in a large city area (Milwaukee County), racial and ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate to various reopening policies, which suggests that policy makers may need to take these heterogeneities into account very carefully when designing policies for mitigating the ongoing spread of COVID-19 and reopening.
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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.