title: Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.
abstract: We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). 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 allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.
authors: From the aJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; bCentre for Infectious, Disease Control, RIVM, Bilthoven, The Netherlands; cDepartment of Sexual Health, Infectious Diseases, and Environmental Health, South Limburg Public Health Service, Heerlen, The Netherlands; dDepartment of Medical Microbiology, School of Public Health and Primary Care, Maastricht University Medical Center, Maastricht, The Netherlands; eHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA; and fDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
authors: Russell J
authors: RJ
authors: Brooke
authors: Mirjam E E
authors: ME
authors: Kretzschmar
authors: Volker
authors: V
authors: Hackert
authors: Christian J P A
authors: CJ
authors: Hoebe
authors: Peter F M
authors: PF
authors: Teunis
authors: Lance A
authors: LA
authors: Waller
mesh_terms: D058345:Asymptomatic Infections / Q000453:epidemiology*; D016997:Coxiella burnetii; D018563:Disease Notification; D004196:Disease Outbreaks; D006801:Humans; D015994:Incidence; D009426:Netherlands / Q000453:epidemiology; D011778:Q Fever / Q000453:epidemiology*; D012307:Risk Factors