01913nam 2200349 450 991051041780332120230825150812.0(CKB)4930000000238646(NjHacI)994930000000238646(EXLCZ)99493000000023864620230825d2021 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierProceedings of the 2nd ACM SIGSPATIAL international workshop on spatial computing for epidemiology (SpatialEpi 2021) /Taylor Anderson [and five others], editorsNew York, New York :Association for Computing Machinery,2021.1 online resource (23 pages)1-4503-9119-2 The spatial behavior of humans, plants, and animals as well as changing geographical and ecological environments play a role in the spread of diseases. In light of the COVID-19 pandemic, recent scientific efforts focus on the development of real time monitoring and response systems, modeling and simulation to predict disease outcomes under existing or hypothetical scenarios, and the analysis of spatiotemporal data to describe or explain behaviors that affect disease trajectories. In general, these efforts seek to generate or leverage spatiotemporal data to improve our understanding, prediction, and response to infectious disease outbreaks.Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology Computer scienceCongressesComputer science004Anderson TaylorNjHacINjHaclBOOK9910510417803321Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology (SpatialEpi 2021)2550083UNINA