Martin Kuldorff | Spatiotemporal Models of Disease Outbreaks
About this episode
Note: This conversation was recorded June 25, 2021.
Martin Kuldorff | Spatiotemporal Models of Outbreaks Martin Kuldorff (Harvard Medical School) talks about the integration of biological & demographic information (and general reality) in the spatiotemporal models used to detect disease outbreaks. He also discusses how these methods can be applied to non-infectious diseases like cancer.
0:00 - Spatio-temporal modeling of outbreaks 6:02 - Important features of spatio-temporal outbreak models 12:20 - Which diseases wouldn't you track for modeling? 19:02 - Multiple comparison adjustments of alarms 25:15 - Domain knowledge of outbreak features 29:30 Competing hazards & risks 34:30 Comparing hemispheres 37:00 - Bridging the gap for infectious diseases to cancer 45:10 - Retrospective data correction / changing monitoring 57:00 - Competing risks & statistics 1:01:30 - Deducing risks & affects through knowledge of immunological mechanisms 1:09:00 - Future scientific convos
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