Previous studies, performed between 2009-2019, in the Netherlands observed an until now still unexplained increased risk for pneumonia among residents living close to goat farms. Since data were ...collected in the provinces Noord-Brabant and Limburg (NB-L), an area with relatively high air pollution levels and proximity to large industrial areas in Europe, the question remains whether the results are generalizable to other regions. In this study, a different region, covering the provinces Utrecht, Gelderland, and Overijssel (UGO) with a similar density of goat farms, was included to assess whether the association between goat farm proximity and pneumonia is consistently observed across the Netherlands.
Data for this study were derived from the Electronic Health Records (EHR) of 21 rural general practices (GPs) in UGO, for 2014-2017. Multi-level analyses were used to compare annual pneumonia prevalence between UGO and data derived from rural reference practices ('control area'). Random-effects meta-analysis (per GP practice) and kernel analyses were performed to study associations of pneumonia with the distance between goat farms and patients' home addresses.
GP diagnoses of pneumonia occurred 40% more often in UGO compared to the control area. Meta-analysis showed an association at a distance of less than 500m (~70% more pneumonia compared to >500m) and 1000m (~20% more pneumonia compared to >1000m). The kernel-analysis for three of the four individual years showed an increased risk up to a distance of one or two kilometers (2-36% more pneumonia; 10-50 avoidable cases per 100,000 inhabitants per year).
The positive association between living in the proximity of goat farms and pneumonia in UGO is similar to the previously found association in NB-L. Therefore, we concluded that the observed associations are relevant for regions with goat farms in the entire country.
One of the largest Q fever outbreaks ever occurred in the Netherlands from 2007-2010, with 25 fatalities among 4,026 notified cases. Airborne dispersion of Coxiella burnetii was suspected but not ...studied extensively at the time. We investigated temporal and spatial variation of Coxiella burnetii in ambient air at residential locations in the most affected area in the Netherlands (the South-East), in the year immediately following the outbreak. One-week average ambient particulate matter < 10 μm samples were collected at eight locations from March till September 2011. Presence of Coxiella burnetii DNA was determined by quantitative polymerase chain reaction. Associations with various spatial and temporal characteristics were analyzed by mixed logistic regression. Coxiella burnetii DNA was detected in 56 out of 202 samples (28%). Airborne Coxiella burnetii presence showed a clear seasonal pattern coinciding with goat kidding. The spatial variation was significantly associated with number of goats on the nearest goat farm weighted by the distance to the farm (OR per IQR: 1.89, CI: 1.31-2.76). We conclude that in the year after a large Q fever outbreak, temporal variation of airborne Coxiella burnetii is suggestive to be associated with goat kidding, and spatial variation with distance to and size of goat farms. Aerosol measurements show to have potential for source identification and attribution of an airborne pathogen, which may also be applicable in early stages of an outbreak.
Respiratory disease and increased mortality occurred in minks on two farms in the Netherlands, with interstitial pneumonia and SARS-CoV-2 RNA in organ and swab samples. On both farms, at least one ...worker had coronavirus disease-associated symptoms before the outbreak. Variations in mink-derived viral genomes showed between-mink transmission and no infection link between the farms. Inhalable dust contained viral RNA, indicating possible exposure of workers. One worker is assumed to have attracted the virus from mink.
This longitudinal study aimed to assess the impact of COVID-19 containment measures on perceived health, health protective behavior and risk perception, and investigate whether chronic disease status ...and urbanicity of the residential area modify these effects. Participants (n = 5420) were followed for up to 14 months (September 2020-October 2021) by monthly questionnaires. Chronic disease status was obtained at baseline. Urbanicity of residential areas was assessed based on postal codes or neighborhoods. Exposure to containment measures was assessed using the Containment and Health Index (CHI). Bayesian multilevel-models were used to assess effect modification of chronic disease status and urbanicity by CHI. CHI was associated with higher odds for worse physical health in people with chronic disease (OR = 1.09, 95% credibility interval (CrI) = 1.01, 1.17), but not in those without (OR = 1.01, Crl = 0.95, 1.06). Similarly, the association of CHI with higher odds for worse mental health in urban dwellers (OR = 1.31, Crl = 1.23, 1.40) was less pronounced in rural residents (OR = 1.20, Crl = 1.13, 1.28). Associations with behavior and risk perception also differed between groups. Our study suggests that individuals with chronic disease and those living in urban areas are differentially affected by government measures put in place to manage the COVID-19 pandemic. This highlights the importance of considering vulnerable subgroups in decision making regarding containment measures.
Several domestic and wild animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. Reported (sero)prevalence in dogs and cats vary largely depending ...on the target population, test characteristics, geographical location and time period. This research assessed the prevalence of SARS‐CoV‐2‐positive cats and dogs (PCR‐ and/or antibody positive) in two different populations. Dogs and cats living in a household with at least one confirmed COVID‐19‐positive person (household (HH) study; 156 dogs and 152 cats) and dogs and cats visiting a veterinary clinic (VC) (VC study; 183 dogs and 140 cats) were sampled and tested for presence of virus (PCR) and antibodies. Potential risk factors were evaluated and follow‐up of PCR‐positive animals was performed to determine the duration of virus shedding and to detect potential transmission between pets in the same HH. In the HH study, 18.8% (27 dogs, 31 cats) tested SARS‐CoV‐2 positive (PCR‐ and/or antibody positive), whereas in the VC study, SARS‐CoV‐2 prevalence was much lower (4.6%; six dogs, nine cats). SARS‐CoV‐2 prevalence amongst dogs and cats was significantly higher in the multi‐person HHs with two or more COVID‐19‐positive persons compared with multi‐person HHs with only one COVID‐19‐positive person. In both study populations, no associations could be identified between SARS‐CoV‐2 status of the animal and health status, age or sex. During follow‐up of PCR‐positive animals, no transmission to other pets in the HH was observed despite long‐lasting virus shedding in cats (up to 35 days). SARS‐CoV‐2 infection in dogs and cats appeared to be clearly associated with reported COVID‐19‐positive status of the HH. Our study supports previous findings and suggests a very low risk of pet‐to‐human transmission within HHs, no severe clinical signs in pets and a negligible pet‐to‐pet transmission between HHs.
Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide ...information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance.
Abstract
Although there is scientific evidence for an increased prevalence of sleep disorders during the coronavirus disease 2019 (COVID-19) pandemic, there is still limited information on how ...lifestyle factors might have affected sleep patterns. Therefore, we followed a large cohort of participants in the Netherlands (n = 5,420) for up to 1 year (September 2020–2021) via monthly Web-based questionnaires to identify lifestyle changes (physical activity, cigarette smoking, alcohol consumption, electronic device use, and social media use) driven by anti–COVID-19 measures and their potential associations with self-reported sleep (latency, duration, and quality). We used the Containment and Health Index (CHI) to assess the stringency of anti–COVID-19 measures and analyzed associations through multilevel ordinal response models. We found that more stringent anti–COVID-19 measures were associated with higher use of electronic devices (per interquartile-range increase in CHI, odds ratio (OR) = 1.47, 95% confidence interval (CI): 1.40, 1.53), less physical activity (OR = 0.94, 95% CI: 0.90, 0.98), lower frequency of alcohol consumption (OR = 0.63, 95% CI: 0.60, 0.66), and longer sleep duration (OR = 1.11, 95% CI: 1.05, 1.16). Lower alcohol consumption frequency and higher use of electronic devices and social media were associated with longer sleep latency. Lower physical activity levels and higher social media and electronic device use were related to poorer sleep quality and shorter sleep duration.
Living in livestock-dense areas has been associated with health effects, suggesting airborne exposures to livestock farm emissions to be relevant for public health. Livestock farm emissions involve ...complex mixtures of various gases and particles. Endotoxin, a pro-inflammatory agent of microbial origin, is a constituent of livestock farm emitted particulate matter (PM) that is potentially related to the observed health effects. Quantification of livestock associated endotoxin exposure at residential addresses in relation to health outcomes has not been performed earlier.
We aimed to assess exposure-response relations for a range of respiratory endpoints and atopic sensitization in relation to livestock farm associated PM10 and endotoxin levels.
Self-reported respiratory symptoms of 12,117 persons participating in a population-based cross-sectional study were analyzed. For 2494 persons, data on lung function (spirometry) and serologically assessed atopic sensitization was additionally available. Annual-average PM10 and endotoxin concentrations at home addresses were predicted by dispersion modelling and land-use regression (LUR) modelling. Exposure-response relations were analyzed with generalized additive models.
Health outcomes were generally more strongly associated with exposure to livestock farm emitted endotoxin compared to PM10. An inverse association was observed for dispersion modelled exposure with atopic sensitization (endotoxin: p = .004, PM10: p = .07) and asthma (endotoxin: p = .029, PM10: p = .022). Prevalence of respiratory symptoms decreased with increasing endotoxin concentration at the lower range, while at the higher range prevalence increased with increasing concentration (p < .05). Associations between lung function parameters with exposure to PM10 and endotoxin were not statistically significant (p > .05).
Exposure to livestock farm emitted particulate matter is associated with respiratory health effects and atopic sensitization in non-farming residents. Results indicate endotoxin to be a potentially plausible etiologic agent, suggesting non-infectious aspects of microbial emissions from livestock farms to be important with respect to public health.
•Quantification of residential exposure to livestock farm emissions established•Land-use regression and dispersion modelling of particulate matter and endotoxin•Associations of exposure and health analyzed in a large population-based study•Respiratory health and atopic sensitization associated with endotoxin exposure•Highlights public health relevance of microbial air pollution from livestock farms
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