CSTE Spatial Analysis Workgroup Webinar: Detecting Emerging COVID-19 Community Outbreaks
Please join the Council of State and Territorial Epidemiologists (CSTE) on Wednesday, July 22, 2020 at 2:00 PM EDT for a webinar entitled, “Detecting Emerging COVID-19 Community Outbreaks,” hosted by the Spatial Analysis Workgroup.
Spatiotemporal analysis of COVID-19 data can support state and local health officials to monitor disease spread and target interventions. However, detecting newly emerging or re-emerging COVID-19 hotspots during an epidemic is considerably more challenging than detecting a newly emerging outbreak, such as for Legionnaires’ disease. During this webinar, Dr. Martin Kulldorff will present the use of space-time scan statistics and purely spatial and purely temporal adjustments. Dr. Sharon Greene will present the system for detecting community-based COVID-19 hotspots in near-real time at census tract resolution in New York City, accounting for testing variability.
By the end of the presentation, participants will be able to:
Spatiotemporal analysis of COVID-19 data can support state and local health officials to monitor disease spread and target interventions. However, detecting newly emerging or re-emerging COVID-19 hotspots during an epidemic is considerably more challenging than detecting a newly emerging outbreak, such as for Legionnaires’ disease. During this webinar, Dr. Martin Kulldorff will present the use of space-time scan statistics and purely spatial and purely temporal adjustments. Dr. Sharon Greene will present the system for detecting community-based COVID-19 hotspots in near-real time at census tract resolution in New York City, accounting for testing variability.
By the end of the presentation, participants will be able to:
- Articulate methodological challenges pertinent to prospective cluster detection for COVID-19.
- Differentiate the three probability models in SaTScan for count data: discrete Poisson, Bernoulli and space-time permutation.
- Parameterize analyses using the free SaTScan software to quickly detect emerging COVID-19 hotspots in their own jurisdiction.
Sharon K. Greene, PhD, MPH is the director of the Data Analysis Unit in the Bureau of Communicable Disease of the New York City Department of Health and Mental Hygiene. She oversees spatiotemporal cluster detection for COVID-19 and other reportable diseases. For her work applying SaTScan, she received the 2018 CSTE Presidential Priorities award for advancing the use of informatics to improve health outcomes.
Martin Kulldorff, PhD, is a biostatistician in the Division of Pharmacoepidemiology and Pharmacoeconomics at the Brigham and Women’s Hospital. One of his major areas of methodological research is spatial and spatio-temporal disease surveillance, for which Dr. Kulldorff has developed various scan statistics for disease cluster detection and investigation and for the early detection of infectious disease outbreaks.
Registration is required for attendance. Once the host approves your registration, you will receive a confirmation email with instructions for joining the session.
For questions, or more information, please contact Maria Patselikos at mpatselikos@cste.org. The webinar slides and recording will be archived in the CSTE Webinar Library.
Martin Kulldorff, PhD, is a biostatistician in the Division of Pharmacoepidemiology and Pharmacoeconomics at the Brigham and Women’s Hospital. One of his major areas of methodological research is spatial and spatio-temporal disease surveillance, for which Dr. Kulldorff has developed various scan statistics for disease cluster detection and investigation and for the early detection of infectious disease outbreaks.
Registration is required for attendance. Once the host approves your registration, you will receive a confirmation email with instructions for joining the session.
For questions, or more information, please contact Maria Patselikos at mpatselikos@cste.org. The webinar slides and recording will be archived in the CSTE Webinar Library.