ArticleComputers, environment and urban systems2010
Spatial-temporal transmission of influenza and its health risks in an urbanized area.
Article in Computers, environment and urban systems, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 58 citations in OpenAlex.
- Estimation of transmission distance between cases of (re-)emerging respiratory infectious diseases and its potential application in outbreak response.Infectious Disease Modelling · 2026Article
- Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.Progress in planning · 2023Article
- A mathematical model for simulating the spread of a disease through a country divided into geographical regions with different population densities.Journal of mathematical biology · 2022Article
- Respiratory pandemics, urban planning and design: A multidisciplinary rapid review of the literature.Cities (London, England) · 2022Article
- Borough-level COVID-19 forecasting in London using deep learning techniques and a novel MSE-Moran's I loss function.Results in physics · 2022Article
- Combinational Recommendation of Vaccinations, Mask-Wearing, and Home-Quarantine to Control Influenza in Megacities: An Agent-Based Modeling Study With Large-Scale Trajectory Data.Frontiers in public health · 2022Article
- Computational simulation of the COVID-19 epidemic with the SEIR stochastic model.Computational and mathematical organization theory · 2021Article
- Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico's Megacity North Periphery.Healthcare (Basel, Switzerland) · 2020Article
- A cyberGIS approach to spatiotemporally explicit uncertainty and global sensitivity analysis for agent-based modeling of vector-borne disease transmission.Annals of the American Association of Geographers · 2020Article
- Using Multiple Scale Spatio-Temporal Patterns for Validating Spatially Explicit Agent-Based Models.International journal of geographical information science : IJGIS · 2019Article
- Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.JMIR research protocols · 2017Article
- Visual analytics of geo-social interaction patterns for epidemic control.International journal of health geographics · 2016Article
- Per capita incidence of sexually transmitted infections increases systematically with urban population size: a cross-sectional study.Sexually transmitted infections · 2015Article
- Synthesis of a high resolution social contact network for Delhi with application to pandemic planning.Artificial intelligence in medicine · 2015Article
- Modeling triple-diffusions of infectious diseases, information, and preventive behaviors through a metropolitan social network-An agent-based simulation.Applied geography (Sevenoaks, England) · 2014Article
- The spatial resolution of epidemic peaks.PLoS computational biology · 2014Article
- A geovisual analytic approach to understanding geo-social relationships in the international trade network.PloS one · 2014Article
- Predictive validation of an influenza spread model.PloS one · 2013Article
- Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks.BMC public health · 2011Article
- Leveraging social networks for understanding the evolution of epidemics.BMC systems biology · 2011Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cities and urban areas play an important role in fostering influenza transmission, often leading to epidemics and even pandemics. Although there is growing literature on influenza transmission at national and international scales, little attention has been paid to a city scale. This article aims to understand the spatial-temporal transmission of influenza and identify its health risks in the urbanized area of Buffalo, New York. An individual-based spatially explicit model is established to replicate an urban contact network, and simulate influenza epidemics. The resulting epidemic curves and infection intensity maps are used to analyze the transmission dynamics, possible contributing factors, and high-risk places and times. The results indicate that the city-wide transmission of influenza can be described by five stages: local growth, expansion, fast city-wide growth, slow city-wide growth, and fade-out. The places and times associated with higher risk are closely related to spatial heterogeneity in the population, and travel behaviors of individuals. Interestingly, these high-risk places and times are insensitive to where infection sources are introduced. This research suggests that high-risk places can be pre-identified as control targets using census and land use data. In addition, a better understanding on the city-wide travel of individuals is critical for designing proper timelines for influenza control. These suggestions will be valuable for local health agencies as they prepare to combat new waves of H1N1 influenza.
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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.