Martin Kuldorff | Spatiotemporal Models of Disease Outbreaks

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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