ArticleInternational journal of health geographics2015
Improved correlation of human Q fever incidence to modelled C. burnetii concentrations by means of an atmospheric dispersion model.
Article in International journal of health geographics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic knowledge synthesis on the spatial dimensions of Q fever epidemics.Zoonoses and public health · 2019Pooled it
- Airborne geographical dispersal of Q fever from livestock holdings to human communities: a systematic review and critical appraisal of evidence.BMC infectious diseases · 2018Pooled it
- Environmental risk factors of human Q fever in Spain.One health (Amsterdam, Netherlands) · 2025Article
- Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission.Scientific reports · 2023Article
- Performance Evaluation and Validation of Air Samplers To Detect Aerosolized Coxiella burnetii.Microbiology spectrum · 2022Article
- Regional Relative Risk, a Physics-Based Metric for Characterizing Airborne Infectious Disease Transmission.Applied and environmental microbiology · 2021Article
- Multi-Scale Airborne Infectious Disease Transmission.Applied and environmental microbiology · 2021Review
- Farming, Q fever and public health: agricultural practices and beyond.Archives of public health = Archives belges de sante publique · 2018Review
- Coxiella burnetii Circulation in a Naturally Infected Flock of Sheep: Individual Follow-Up of Antibodies in Serum and Milk.Applied and environmental microbiology · 2017Article
- Human Q fever incidence is associated to spatiotemporal environmental conditions.One health (Amsterdam, Netherlands) · 2016Article
- Spread of Coxiella burnetii between dairy cattle herds in an enzootic region: modelling contributions of airborne transmission and trade.Veterinary research · 2016Article
- Climate change effects on airborne pathogenic bioaerosol concentrations: a scenario analysis.Aerobiologia · 2016Article
- Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock - A review to inform risk assessment studies.Microbial risk analysis · 2016Review
- Article
- Circulation of Coxiella burnetii in a Naturally Infected Flock of Dairy Sheep: Shedding Dynamics, Environmental Contamination, and Genotype Diversity.Applied and environmental microbiology · 2015Article
- Integrating interdisciplinary methodologies for One Health: goat farm re-implicated as the probable source of an urban Q fever outbreak, the Netherlands, 2009.BMC infectious diseases · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtmospheric dispersion models (ADMs) may help to assess human exposure to airborne pathogens. However, there is as yet limited quantified evidence that modelled concentrations are indeed associated to observed human incidence.
methodsWe correlated human Q fever (caused by the bacterium Coxiella burnetii) incidence data in the Netherlands to modelled concentrations from three spatial exposure models: 1) a NULL model with a uniform concentration distribution, 2) a DISTANCE model with concentrations proportional to the distance between the source and residential addresses of patients, and 3) concentrations modelled by an ADM using three simple emission profiles. We used a generalized linear model to correlate the observed incidences to modelled concentrations and validated it using cross-validation.
resultsADM concentrations generally correlated the best to the incidence data. The DISTANCE model always performed significantly better than the NULL model. ADM concentrations based on wind speeds exceeding threshold values of 0 and 2 m/s performed better than those based on 4 or 6 m/s. This might indicate additional exposure to bacteria originating from a contaminated environment.
conclusionsBy adding meteorological information the correlation between modelled concentration and observed incidence improved, despite using three simple emission profiles. Although additional information is needed - especially regarding emission data - these results provide a basis for the use of ADMs to predict and to visualize the spread of airborne pathogens during livestock, industry and even bio-terroristic related outbreaks or releases to a surrounding human population.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.