Spatio-Temporal Modeling and Tropical Disease
A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366). This special issue belongs to the section "Neglected and Emerging Tropical Diseases".
Deadline for manuscript submissions: closed (10 October 2021) | Viewed by 7118
Special Issue Editors
Interests: spatio-temporal modeling; tropical disease; health informatics; geographic information systems; infectious disease epidemiology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With rapid urbanization and intensive international traffic, infectious diseases are spreading more quickly and widely than before. Immediate detection of aberrations in disease patterns and precise public health intervention can help mitigate large epidemics and reduce the disease burden. How to identify hotspots and quantify risks in a timely manner and geographically by spatio-temporal modeling based on disease surveillance data and epidemiological investigation data is a critical and challenging question. The dynamics of hosts, agents and environments interact and evolve in time and space. Traditional spatio-temporal statistical models, Bayesian models, and machine-learning or deep-learning algorithms are applied to predict disease occurrence or explain the risk factors involved in diseases’ spatio-temporal distribution. Different levels of spatio-temporal resolution of data nowadays also increase the complexity of model computation.
This Special Issue entitled “Spatio-Temporal Modeling and Tropical Disease” welcomes different approaches to spatio-temporal modelling of tropical diseases. Success stories on how to apply models for disease control or prevention are especially welcome. We also encourage data scientists and statisticians to share information on their innovative models or tools which can be applied to first-line public health usage.
Dr. Ta-Chien Chan
Prof. Dr. Mathuros Tipayamongkholgul
Guest Editors
Manuscript Submission Information
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Keywords
- clusters
- hotspots
- spatio-temporal analysis
- GIS
- spatial epidemiology
- surveillance
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