Linking a dose-response model to observed infection to describe spatial-temporal patterns in a Q fever outbreak

Ann Arbor MI 01-22-2019 01-22-2019

Abstract: We explore a Netherlands outbreak of Q fever in 2009 by combining a human dose–response model with geostatistics to predict local probability of infection, associated 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 (established via historical experiments) to convert the observed risk map into an estimated smooth spatial field of local dose. Based on the observed symptomatic cases, the dose–response model predicts a median of 611 asymptomatic infections (95% range 410 to 1,084), i.e., 2.78 (95% range 1.86 to 4.93) asymptomatic infections for each reported case. The estimated peak levels of exposure extend to the north–east from the point source with an increasing 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 interventions during an outbreak, estimating future disease burden, and planning public health response.

Joint work with R. John Brooke, St. Jude Children’s Research Hospital, Memphis TN; Peter FM Teunis, Centre for Infectious Disease Control, RIVM, Bilthoven, the Netherlands; Mirjam EE Kretzschmar, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands.

Environmental Statistics Day Lecture featuring Lance Waller, PhD (Emory Univ)

icon to add this event to your google calendarJanuary 22, 2019
1:00 pm - 2:00 pm
1690 SPH I (Lane Auditorium)
1415 Washington Heights
Ann Arbor, MI 48109-2029

Sponsored by: Integrated Health Sciences Core of M-LEEaD (Michigan Center on Lifestage Environmental Exposures and Disease)
Contact Information: Meredith McGehee (mcgehee@umich.edu | 647-0819)

Abstract: We explore a Netherlands outbreak of Q fever in 2009 by combining a human dose–response model with geostatistics to predict local probability of infection, associated 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 (established via historical experiments) to convert the observed risk map into an estimated smooth spatial field of local dose. Based on the observed symptomatic cases, the dose–response model predicts a median of 611 asymptomatic infections (95% range 410 to 1,084), i.e., 2.78 (95% range 1.86 to 4.93) asymptomatic infections for each reported case. The estimated peak levels of exposure extend to the north–east from the point source with an increasing 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 interventions during an outbreak, estimating future disease burden, and planning public health response.

Joint work with R. John Brooke, St. Jude Children’s Research Hospital, Memphis TN; Peter FM Teunis, Centre for Infectious Disease Control, RIVM, Bilthoven, the Netherlands; Mirjam EE Kretzschmar, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands.

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