Mapping disease incidence/prevalence and identifying risk/protective factors have been longstanding areas of interest in public health and spatial epidemiology. 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 over both space and time.
There are, however, a number of unresolved issues in the mapping and analysis of spatiotemporal health outcomes and behaviors, including:
• Sparse data and noise
• Spatiotemporally misaligned data and/or multiscale data
• Spatiotemporal risk factor exposure (through the life course, activity spaces)
• Missing data and imputation
• Spatiotemporal cluster detection and disease surveillance
• Policy evaluation
• Communicating spatiotemporal analyses to health practitioners
This session welcomes submissions that address one of these topics (or a related topic). If interested, please email your name, organization, talk title, abstract of 250 words or less to, and PIN to Henry Hui Luan (firstname.lastname@example.org) and/or Matthew Quick (email@example.com) by Nov 8, 2018.
The session organized via this CFP will be part of the AAG 2019 Special Theme on Geography, GIScience, and Health: Building an International Geospatial Health Research Network (IGHRN).
|Presenter||Daniel Yonto*, University of North Carolina - Charlotte, Hongwei Jiang, Research Institute for Humanity and Nature, Kyoto, Japan, Lin Lin, Xi’an Jiaotong – Liverpool University, Preventing human liver fluke transmission in Southeast Asia: A spatiotemporal analyses from a rural community in the Lao People's Democratic Republic||20||2:35 PM|
|Presenter||Nuria Font-Casaseca*, Universitat de Barcelona, Facultat Geografia i Historia, The effects of socioeconomic deprivation on the spatial distribution of new VIH diagnoses in Catalonia (Spain): some geographical challenges and limitations using Ring maps||20||2:55 PM|
|Presenter||Henry Hui Luan*, University of Oregon, Imputing censored health data at small-area levels: A Bayesian spatiotemporal modelling approach||20||3:15 PM|
|Presenter||Matthew Quick*, University of Waterloo, Multilevel modeling of cognitive function at individual- and area-levels: A profile of middle-aged and older adults in Canada||20||3:35 PM|
|Presenter||Eric Delmelle*, University of North Carolina at Charlotte, Claudio Owusu, University of North Carolina at Charlotte, Michael Desjardins, University of North Carolina at Charlotte, Alexander Hohl, Uttica College, Paul Jung, University of North Carolina at Charlotte, Yu Lan, University of North Carolina at Charlotte, Coline Dony, American Association of Geographers, Uncertainty in Geographical Analysis: Current Challenges and Future Opportunities||20||3:55 PM|
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