BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250712T081410EDT-8132fkuBIZ@132.216.98.100 DTSTAMP:20250712T121410Z DESCRIPTION:Title:Linking a Dose-Response Model to Observed Infection to De scribe Spatial-Temporal Patterns in a Q Fever Outbreak\n\nAbstract: Lance A. Waller\, Ph.D. is a Professor in the Department of Biostatistics and Bi oinformatics\, Rollins School of Public Health\, Emory University. He is a member of the National Academy of Science Board on Mathematical Sciences and Analytics and has served on National Academies Committees on applied a nd theoretical statistics\, cancer near nuclear facilities\, geographic as sessments of exposures to Agent Orange\, and standoff explosive technologi es.  His research involves the development of statistical methods for geog raphic data including applications in environmental justice\, epidemiology \, disease surveillance\, spatial cluster detection\, conservation biology \, and disease ecology.  His research appears in biostatistical\, statisti cal\, environmental health\, and ecology journals and in the textbook Appl ied Spatial Statistics for Public Health Data (2004\, Wiley). We explore a Netherlands outbreak of Q fever in 2009 by combining a human dose–respons e model with geostatistics to predict local probability of infection\, ass ociated probability of illness\, and local effective exposures to Coxiella burnetii. We begin with the spatial distribution of 220 notified cases in the at–risk population.  Next\, we use the dose-response relationship (es tablished via historical experiments) to convert the observed risk map int o an estimated smooth spatial field of local dose. The estimated peak leve ls of exposure extend to the north–east from the point source with an incr easing proportion of asymptomatic infections further from the source.  Our work combines established methodology from model-based geostatistics and dose–response modeling providing a novel approach to study outbreaks. Such predictions (and associated uncertainties) are important for targeting in terventions during an outbreak\, estimating future disease burden\, and pl anning public health response.\n DTSTART:20190128T210000Z DTEND:20190128T220000Z LOCATION:Room 521\, McIntyre Medical Building\, CA\, QC\, Montreal\, H3G 1Y 6\, 3655 promenade Sir William Osler SUMMARY:LANCE A. WALLER\, PhD\, Rollins School of Public Health-Emory Unive rsity URL:/mathstat/channels/event/lance-waller-phd-rollins- school-public-health-emory-university-293714 END:VEVENT END:VCALENDAR