Spatiotemporal disease mapping and analysis (II)
Type: Virtual Paper
Day: 2/28/2022
Start Time: 9:40 AM
End Time: 11:00 AM
Theme:
Sponsor Group(s):
Health and Medical Geography Specialty Group
, Spatial Analysis and Modeling Specialty Group
, Geographic Information Science and Systems Specialty Group
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Organizer(s):
Eric Delmelle
, Michael Desjardins
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Chairs(s):
Hui Luan, University of Oregon
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Description:
Mapping disease incidence/prevalence and identifying risk factors have been longstanding areas of interest in public health and spatial epidemiology. The emergence of the COVID-19 pandemic has stimulated extensive research in spatiotemporal disease mapping and analysis, including a flood of dashboard visualizing disease spread over space and time via Web and mobile applications. With innovations in data acquisition and dissemination, and with methodological advances in analyzing complex longitudinal data, contemporary disease mapping research has been increasingly focused on understanding how health varies across space, time, socioeconomic, and demographic groups. There are, however, a number of unresolved and challenging methodological issues in mapping and analyzing spatiotemporal health outcomes and behaviours, including but not limited to:
• Sparse data and noise (e.g., zero-inflation)
• Spatiotemporally misaligned data analysis
• Multiscale modeling
• Spatially and temporally varying regression modeling
• Multivariate modeling of more than one health outcome
• Missing data and imputation
• Spatiotemporal cluster detection
• Disease surveillance
• Uncertainty modelling and quantification
• Human mobility and social distancing in disease spreading
• Geoprivacy
• Geovisual analytics of disease patterns
Presentation(s), if applicable
Jian Lange, Esri; Apply GIS and Machine Learning to Examine the Interplay of Factors Affecting COVID-19 Vaccine Rates |
Hui Luan, University of Texas Southwestern Medical Center; A Bayesian spatiotemporal approach to analyze publicly available, censored HIV datasets in Mississippi, 2014-2018 |
Kyunghee Rhyu, ; Spatio-temporal Disparities in the Acceptance of COVID-19 Vaccinations in Texas counties |
Varun Goel, University of South Carolina; Evidence of Rebound Malaria: Estimating the Impact of Malaria Transmission Intensity on Reduced Malaria Vaccine Efficacy in Sub-Saharan Africa |
Non-Presenting Participants Agenda
| Role | Participant |
| Discussant | Xun Shi |
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Spatiotemporal disease mapping and analysis (II)
Description
Virtual Paper
Contact the Primary Organizer
Hui Luan - hui.luan@utsouthwestern.edu
Session Sponsored By
