34 results on '"de Rooij, Myrna M. T."'
Search Results
2. Establishing farm dust as a useful viral metagenomic surveillance matrix
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Kwok, Kirsty T. T., de Rooij, Myrna M. T., Messink, Aniek B., Wouters, Inge M., Smit, Lidwien A. M., Cotten, Matthew, Heederik, Dick J. J., Koopmans, Marion P. G., and Phan, My V. T.
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- 2022
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3. Anti-COVID-19 measures and lifestyle changes during theCOVID-19 pandemic and sleep patterns in the Netherlands: a longitudinal study
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Sandoval-Diez, Nekane, primary, Smit, Lidwien A M, additional, Boer, Jolanda M A, additional, de Rooij, Myrna M T, additional, Koppelman, Gerard H, additional, van Kersen, Warner, additional, Vonk, Judith M, additional, Vermeulen, Roel, additional, Gehring, Ulrike, additional, and Huss, Anke, additional
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- 2023
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4. Contribution of cats and dogs to SARS-CoV-2 transmission in households
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Fischer, Egil A. J., primary, Broens, Els M., additional, Kooistra, Hans S., additional, De Rooij, Myrna M. T., additional, Stegeman, Jan Arend, additional, and De Jong, Mart C. M., additional
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- 2023
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5. Increased risk of pneumonia amongst residents living near goat farms in different livestock-dense regions in the Netherlands
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Lotterman, Aniek, primary, Baliatsas, Christos, additional, de Rooij, Myrna M. T., additional, Huss, Anke, additional, Jacobs, José, additional, Dückers, Michel, additional, Boender, Gert Jan, additional, McCarthy, Catherine, additional, Heederik, Dick, additional, Hagenaars, Thomas J., additional, Yzermans, C. Joris, additional, and Smit, Lidwien A. M., additional
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- 2023
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6. Residential exposure to livestock farms and lung function in adolescence - The PIAMA birth cohort study
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Kiss, Pauline, de Rooij, Myrna M T, Koppelman, Gerard H, Boer, Jolanda, Vonk, Judith M, Vermeulen, Roel, Hogerwerf, Lenny, Sterk, Hendrika A M, Huss, Anke, Smit, Lidwien A M, Gehring, Ulrike, IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, LS Evidence Based Vet Medicine, IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, LS Evidence Based Vet Medicine, and Groningen Research Institute for Asthma and COPD (GRIAC)
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Livestock farming ,Adolescents ,Particulate matter ,Biochemistry ,Lung function ,General Environmental Science - Abstract
Background: There is a growing interest in the impact of air pollution from livestock farming on respiratory health. Studies in adults suggest adverse effects of livestock farm emissions on lung function, but so far, studies involving children and adolescents are lacking. Objectives: To study the association of residential proximity to livestock farms and modelled particulate matter ≤10 μm (PM10) from livestock farms with lung function in adolescence. Methods: We performed a cross-sectional study among 715 participants of the Dutch prospective PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort study. Relationships of different indicators of residential livestock farming exposure (distance to farms, distance-weighted number of farms, cattle, pigs, poultry, horses and goats within 3 km; modelled atmospheric PM10 concentrations from livestock farms) with forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) at age 16 were assessed by linear regression taking into account potential confounders. Associations were expressed per interquartile range increase in exposure. Results: Higher exposure to livestock farming was consistently associated with a lower FEV1, but not with FVC among participants living in less urbanized municipalities (2, N = 402). Shorter distances of homes to livestock farms were associated with a 1.4% (0.2%; 2.7%) lower FEV1. Larger numbers of farms within 3 km and higher concentrations of PM10 from livestock farming were associated with a 1.8% (0.8%, 2.9%) and 0.9% (0.4%,1.5%) lower FEV1, respectively. Conclusions: Our findings suggest that higher exposure to livestock farming is associated with a lower FEV1 in adolescents. Replication and more research on the etiologic agents involved in these associations and the underlying mechanisms is needed.
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- 2023
7. A comprehensive sampling study on SARS-CoV-2 contamination of air and surfaces in a large meat processing plant experiencing COVID-19 clusters in June 2020
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de Rooij, Myrna M T, Sikkema, Reina S, Bouwknegt, Martijn, de Geus, Yvette, Stanoeva, Kamelia R, Nieuwenweg, Sigrid, van Dam, Adriana S G, Raben, Ceder, Dohmen, Wietske, Heederik, Dick, Reusken, Chantal, Meijer, Adam, Koopmans, Marion P G, Franz, Eelco, and Smit, Lidwien A M
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- 2023
8. SARS‐CoV‐2 infection in dogs and cats is associated with contact to COVID‐19‐positive household members
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Kannekens‐Jager, Marleen M., primary, de Rooij, Myrna M. T., additional, de Groot, Yasmina, additional, Biesbroeck, Elena, additional, de Jong, Marja K., additional, Pijnacker, Tera, additional, Smit, Lidwien A. M., additional, Schuurman, Nancy, additional, Broekhuizen‐Stins, Marian J., additional, Zhao, Shan, additional, Duim, Birgitta, additional, Langelaar, Merel F. M., additional, Stegeman, Arjan, additional, Kooistra, Hans S., additional, Radstake, Carien, additional, Egberink, Herman F., additional, Wagenaar, Jaap A., additional, and Broens, Els M., additional
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- 2022
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9. Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms
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de Rooij, Myrna M T, Hakze-Van der Honing, Renate W, Hulst, Marcel M, Harders, Frank, Engelsma, Marc, van de Hoef, Wouter, Meliefste, Kees, Nieuwenweg, Sigrid, Oude Munnink, Bas B, van Schothorst, Isabella, Sikkema, Reina S, van der Spek, Arco N, Spierenburg, Marcel, Spithoven, Jack, Bouwstra, Ruth, Molenaar, Robert-Jan, Koopmans, Marion, Stegeman, Arjan, van der Poel, Wim H M, Smit, Lidwien A M, IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, dIRAS RA-I&I RA, FAH veterinaire epidemiologie, dFAH AVR, dFAH I&I, IRAS OH Epidemiology Microbial Agents, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, dIRAS RA-I&I RA, FAH veterinaire epidemiologie, dFAH AVR, dFAH I&I, and Virology
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0301 basic medicine ,Bio Process Engineering ,Veterinary medicine ,Exposure Assessment ,Range (biology) ,Epidemiology ,animal diseases ,Kwantitatieve Veterinaire Epidemiologie ,viruses ,air pollution ,Air pollution ,medicine.disease_cause ,law.invention ,0302 clinical medicine ,law ,030212 general & internal medicine ,Mink ,skin and connective tissue diseases ,Netherlands ,biology ,Bacteriologie ,Dust ,Bacteriology, Host Pathogen Interaction & Diagnostics ,Environmental exposure ,Virology & Molecular Biology ,Geography ,Transmission (mechanics) ,RNA, Viral ,Public Health ,Occupational exposure ,environment ,Animal Breeding & Genomics ,Air sampling ,Farms ,Bioinformatica & Diermodellen ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,farmers ,Respirable dust ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Occupational Exposure ,Environmental health ,biology.animal ,Bio-informatics & Animal models ,medicine ,Animals ,Humans ,Epidemiology, Bio-informatics & Animal models ,Fokkerij & Genomica ,Environmental risk assessment ,Host Pathogen Interaction & Diagnostics ,Epidemiologie ,business.industry ,SARS-CoV-2 ,Environmental and Occupational Health ,fungi ,Public Health, Environmental and Occupational Health ,Quantitative Veterinary Epidemiology ,COVID-19 ,RNA ,Bacteriology ,Environmental Exposure ,Virology ,Host Pathogen Interactie & Diagnostiek ,respiratory tract diseases ,Virologie & Moleculaire Biologie ,030104 developmental biology ,Epidemiologie, Bioinformatica & Diermodellen ,Bacteriologie, Host Pathogen Interactie & Diagnostiek ,WIAS ,business - Abstract
ObjectiveUnprecedented SARS-CoV-2 infections in farmed minks raised immediate concerns regarding transmission to humans and initiated intensive environmental investigations to assess occupational and environmental exposure.MethodsAir sampling was performed at infected Dutch mink farms, at farm premises and at nearby residential sites. A range of other environmental samples were collected from minks’ housing units, including bedding materials. SARS-CoV-2 RNA was analysed in all samples by quantitative PCR.ResultsInside the farms, considerable levels of SARS-CoV-2 RNA were found in airborne dust, especially in personal inhalable dust samples (approximately 1000–10 000 copies/m3). Most of the settling dust samples tested positive for SARS-CoV-2 RNA (82%, 75 of 92). SARS-CoV-2 RNA was not detected in outdoor air samples, except for those collected near the entrance of the most recently infected farm. Many samples of minks’ housing units and surfaces contained SARS-CoV-2 RNA.ConclusionsInfected mink farms can be highly contaminated with SARS-CoV-2 RNA. This warns of occupational exposure, which was substantiated by considerable SARS-CoV-2 RNA concentrations in personal air samples. Dispersion of SARS-CoV-2 to outdoor air was found to be limited and SARS-CoV-2 RNA was not detected in air samples collected beyond farm premises, implying a negligible risk of environmental exposure to nearby communities. Our occupational and environmental risk assessment is in line with whole genome sequencing analyses showing mink-to-human transmission among farm workers, but no indications of direct zoonotic transmission events to nearby communities.
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- 2021
10. Impact of the COVID-19 pandemic on physical and mental health over time in relation to chronic disease status and urbanicity
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Van Kersen, Warner, primary, De Rooij, Myrna M. T., additional, Diez, Nekane S., additional, Pieterson, Inka, additional, Tewis, Marjan, additional, Vermeulen, Roel, additional, Gehring, Ulrike, additional, Huss, Anke, additional, and Smit, Lidwien A.M., additional
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- 2022
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11. Manifestation of SARS-CoV-2 Infections in Mink Related to Host-, Virus- and Farm-Associated Factors, The Netherlands 2020
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Wolters, Wendy J., primary, de Rooij, Myrna M. T., additional, Molenaar, Robert Jan, additional, de Rond, Jan, additional, Vernooij, J. C. M., additional, Meijer, Paola A., additional, Oude Munnink, Bas B., additional, Sikkema, Reina S., additional, van der Spek, Arco N., additional, Spierenburg, Marcel A. H., additional, Hakze-van der Honing, Renate W., additional, van der Poel, Wim H. M., additional, Koopmans, Marion P. G., additional, Stegeman, J. Arjan, additional, Smit, Lidwien A. M., additional, Augustijn-Schretlen, Marieke, additional, and Velkers, Francisca C., additional
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- 2022
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12. SARS-CoV-2 infection in cats and dogs in infected mink farms
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van Aart, Anna E, Velkers, Francisca C, Fischer, Egil A J, Broens, Els M, Egberink, Herman, Zhao, Shan, Engelsma, Marc, Hakze-van der Honing, Renate W, Harders, Frank, de Rooij, Myrna M T, Radstake, Carien, Meijer, Paola A, Munnink, Bas B Oude, de Rond, Jan, Sikkema, Reina S, van der Spek, Arco N, Spierenburg, Marcel, Wolters, Wendy J, Molenaar, Robert-Jan, Koopmans, Marion P G, van der Poel, Wim H M, Stegeman, Arjan, Smit, Lidwien A M, FAH GZ pluimvee, dFAH I&I, FAH veterinaire epidemiologie, Klinische infectiologie en microb. lab., dI&I I&I-4, Virologie, dI&I I&I-1, IRAS OH Epidemiology Microbial Agents, dFAH AVR, dIRAS RA-I&I RA, Virology, FAH GZ pluimvee, dFAH I&I, FAH veterinaire epidemiologie, Klinische infectiologie en microb. lab., dI&I I&I-4, Virologie, dI&I I&I-1, IRAS OH Epidemiology Microbial Agents, dFAH AVR, and dIRAS RA-I&I RA
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Veterinary medicine ,dogs ,viruses ,animal diseases ,Kwantitatieve Veterinaire Epidemiologie ,Cat Diseases ,SARS‐CoV‐2 ,Serology ,0403 veterinary science ,Dog Diseases ,Mink ,Letter to the Editor ,0303 health sciences ,CATS ,biology ,Transmission (medicine) ,04 agricultural and veterinary sciences ,General Medicine ,Virology & Molecular Biology ,medicine.anatomical_structure ,epidemiology ,Farms ,Bioinformatica & Diermodellen ,040301 veterinary sciences ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Short Communication ,Animals, Wild ,Virus ,Interspecies transmission ,03 medical and health sciences ,one health ,Throat ,biology.animal ,Immunology and Microbiology(all) ,Bio-informatics & Animal models ,medicine ,Humans ,Animals ,Epidemiology, Bio-informatics & Animal models ,030304 developmental biology ,Epidemiologie ,General Veterinary ,General Immunology and Microbiology ,SARS-CoV-2 ,cats ,mink ,COVID-19 ,Quantitative Veterinary Epidemiology ,Serum samples ,veterinary(all) ,Virologie & Moleculaire Biologie ,Epidemiologie, Bioinformatica & Diermodellen ,WIAS - Abstract
Animals like mink, cats and dogs are susceptible to SARS-CoV-2 infection. In the Netherlands, 69 out of 127 mink farms were infected with SARS-CoV-2 between April and November 2020 and all mink on infected farms were culled after SARS-CoV-2 infection to prevent further spread of the virus. On some farms, (feral) cats and dogs were present. This study provides insight into the prevalence of SARS-CoV-2 positive cats and dogs in ten infected mink farms and their possible role in transmission of the virus. Throat and rectal swabs of 101 cats (12 domestic and 89 feral cats) and 13 dogs of ten farms were tested for SARS-CoV-2 using PCR. Serological assays were performed on serum samples from 62 adult cats and all 13 dogs. Whole Genome Sequencing was performed on one cat sample. Cat-to-mink transmission parameters were estimated using data from all ten farms. This study shows evidence of SARS-CoV-2 infection in twelve feral cats and two dogs. Eleven cats (19%) and two dogs (15%) tested serologically positive. Three feral cats (3%) and one dog (8%) tested PCR-positive. The sequence generated from the cat throat swab clustered with mink sequences from the same farm. The calculated rate of mink-to-cat transmission showed that cats on average had a chance of 12% (95%CI 10% to 18%) of becoming infected by mink, assuming no cat-to-cat transmission. As only feral cats were infected it is most likely that infections in cats were initiated by mink, not by humans. Whether both dogs were infected by mink or humans remains inconclusive. This study presents one of the first reports of interspecies transmission of SARS-CoV-2 that does not involve humans, namely mink-to-cat transmission, which should also be considered as a potential risk for spread of SARS-CoV-2.
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- 2022
13. A systematic knowledge synthesis on the spatial dimensions of Q fever epidemics
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De Rooij, Myrna M T, Van Leuken, Jeroen P G, Swart, Arno, Kretzschmar, Mirjam E E, Nielen, Mirjam, De Koeijer, Aline A, Janse, Ingmar, Wouters, Inge M, Heederik, Dick J J, One Health Microbieel, dIRAS RA-I&I RA, dFAH AVR, One Health Microbieel, dIRAS RA-I&I RA, and dFAH AVR
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Coxiella burnetii/physiology ,Epidemiology ,Review ,0403 veterinary science ,0302 clinical medicine ,Models ,Multidisciplinary approach ,Non-U.S. Gov't ,Review Articles ,Risk management ,biology ,airborne exposure ,Research Support, Non-U.S. Gov't ,risk assessment ,04 agricultural and veterinary sciences ,Q Fever/epidemiology ,Identification (information) ,Infectious Diseases ,Geography ,Coxiella burnetii ,epidemiology ,Public Health ,Risk assessment ,spatial analysis ,040301 veterinary sciences ,Bioinformatica & Diermodellen ,030231 tropical medicine ,Q fever ,Research Support ,Models, Biological ,Airborne transmission ,03 medical and health sciences ,Immunology and Microbiology(all) ,Bio-informatics & Animal models ,Journal Article ,medicine ,Animals ,Humans ,Epidemiology, Bio-informatics & Animal models ,Epidemics ,Exposure assessment ,Epidemiologie ,General Veterinary ,General Immunology and Microbiology ,business.industry ,Environmental and Occupational Health ,Public Health, Environmental and Occupational Health ,Biological ,biology.organism_classification ,medicine.disease ,veterinary(all) ,Data science ,Epidemiologie, Bioinformatica & Diermodellen ,WIAS ,business - Abstract
From 2007 through 2010, the Netherlands experienced the largest Q fever epidemic ever reported. This study integrates the outcomes of a multidisciplinary research programme on spatial airborne transmission of Coxiella burnetii and reflects these outcomes in relation to other scientific Q fever studies worldwide. We have identified lessons learned and remaining knowledge gaps. This synthesis was structured according to the four steps of quantitative microbial risk assessment (QMRA): (a) Rapid source identification was improved by newly developed techniques using mathematical disease modelling; (b) source characterization efforts improved knowledge but did not provide accurate C. burnetii emission patterns; (c) ambient air sampling, dispersion and spatial modelling promoted exposure assessment; and (d) risk characterization was enabled by applying refined dose–response analyses. The results may support proper and timely risk assessment and risk management during future outbreaks, provided that accurate and structured data are available and exchanged readily between responsible actors.
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- 2019
14. Genome Sequence of a Minacovirus Strain from a Farmed Mink in The Netherlands
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Kwok, Kirsty T T, de Rooij, Myrna M T, Sinartio, Felisita F, Smit, Lidwien A M, Koopmans, Marion P G, Phan, My V T, LS IRAS EEPI GRA (Gezh.risico-analyse), IRAS OH Epidemiology Microbial Agents, dIRAS RA-I&I RA, Virology, LS IRAS EEPI GRA (Gezh.risico-analyse), IRAS OH Epidemiology Microbial Agents, and dIRAS RA-I&I RA
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Whole genome sequencing ,Genetics ,0303 health sciences ,2019-20 coronavirus outbreak ,biology ,040301 veterinary sciences ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Strain (biology) ,viruses ,Genome Sequences ,04 agricultural and veterinary sciences ,biology.organism_classification ,Deep sequencing ,3. Good health ,Neovison ,0403 veterinary science ,03 medical and health sciences ,Immunology and Microbiology (miscellaneous) ,biology.animal ,Mink ,Molecular Biology ,Feces ,030304 developmental biology - Abstract
We report the genome sequence of a Minacovirus strain identified from a fecal sample from a farmed mink (Neovison vison) in The Netherlands that was tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using real-time PCR (RT-PCR). The viral genome sequence was obtained using agnostic deep sequencing.
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- 2021
15. Establishing farm dust as a useful viral metagenomic surveillance matrix
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Kwok, Kirsty T. T., primary, de Rooij, Myrna M. T., additional, Messink, Aniek B., additional, Wouters, Inge M., additional, Smit, Lidwien A. M., additional, Cotten, Matthew, additional, Heederik, Dick J.J., additional, Koopmans, Marion P. G., additional, and Phan, My V. T., additional
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- 2021
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16. Genome Sequences of Seven Megrivirus Strains from Chickens in The Netherlands
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Kwok, Kirsty T. T., primary, de Rooij, Myrna M. T., additional, Messink, Aniek B., additional, Wouters, Inge M., additional, Koopmans, Marion P. G., additional, and Phan, My V. T., additional
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- 2020
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17. Endotoxin and particulate matter emitted by livestock farms and respiratory health effects in neighboring residents
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de Rooij, Myrna M T, Smit, Lidwien A M, Erbrink, Hans J, Hagenaars, Thomas J, Hoek, Gerard, Ogink, Nico W M, Winkel, Albert, Heederik, Dick J J, Wouters, Inge M, One Health Microbieel, dIRAS RA-I&I RA, One Health Chemisch, One Health Microbieel, dIRAS RA-I&I RA, and One Health Chemisch
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Male ,spatial modelling ,endotoxin ,Livestock associated ,010504 meteorology & atmospheric sciences ,Epidemiology ,animal diseases ,air pollution ,Air pollution ,010501 environmental sciences ,medicine.disease_cause ,01 natural sciences ,Prevalence ,lcsh:Environmental sciences ,General Environmental Science ,lcsh:GE1-350 ,Air Pollutants ,education.field_of_study ,public health ,Particulates ,Emissions ,Female ,Livestock ,Emissions & Manure Valorisation ,livestock farming ,emmisions ,medicine.medical_specialty ,Farms ,Bioinformatica & Diermodellen ,Population ,Emissie & Mestverwaarding ,Health outcomes ,Environmental health ,Bio-informatics & Animal models ,medicine ,Animals ,Humans ,Epidemiology, Bio-informatics & Animal models ,education ,Respiratory health ,0105 earth and related environmental sciences ,Asthma ,Epidemiologie ,business.industry ,Public health ,Environmental Exposure ,Respiration Disorders ,medicine.disease ,Endotoxins ,Cross-Sectional Studies ,Epidemiologie, Bioinformatica & Diermodellen ,WIAS ,Particulate Matter ,business - Abstract
Background: 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. Objectives: 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. Methods: 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. Results: 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). Conclusions: 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. Keywords: Livestock farming, Emissions, Air pollution, Public health, Spatial modelling, Endotoxin
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- 2019
18. Spatial Variation of Endotoxin Concentrations Measured in Ambient PM10 in a Livestock-Dense Area: Implementation of a Land-Use Regression Approach
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de Rooij, Myrna M T, Heederik, Dick J J, van Nunen, Erik J H M, van Schothorst, Isabella J, Maassen, Catharina B M, Hoek, Gerard, Wouters, Inge M, One Health Microbieel, dIRAS RA-I&I RA, Dep IRAS, LS IRAS EEPI GRA (Gezh.risico-analyse), One Health Chemisch, dIRAS RA-2, One Health Microbieel, dIRAS RA-I&I RA, Dep IRAS, LS IRAS EEPI GRA (Gezh.risico-analyse), One Health Chemisch, and dIRAS RA-2
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Livestock ,Geographic information system ,animal diseases ,Health, Toxicology and Mutagenesis ,010501 environmental sciences ,Land use regression ,01 natural sciences ,03 medical and health sciences ,0302 clinical medicine ,Air Pollution ,parasitic diseases ,Animals ,Humans ,Netherlands ,0105 earth and related environmental sciences ,Air Pollutants ,business.industry ,Research ,Environmental resource management ,Public Health, Environmental and Occupational Health ,Models, Theoretical ,030210 environmental & occupational health ,Endotoxins ,Livestock farming ,Geographic Information Systems ,Environmental science ,Particulate Matter ,Spatial variability ,business ,Environmental Monitoring - Abstract
BACKGROUND: Results from studies on residential health effects of livestock farming are inconsistent, potentially due to simple exposure proxies used (e.g., livestock density). Accuracy of these proxies compared with measured exposure concentrations is unknown. OBJECTIVES: We aimed to assess spatial variation of endotoxin in PM10 (particulate matter ≤10μm) at residential level in a livestock-dense area, compare simple livestock exposure proxies to measured endotoxin concentrations, and evaluate whether land-use regression (LUR) can be used to explain spatial variation of endotoxin. METHODS: The study area (3,000 km2) was located in Netherlands. Ambient PM10 was collected at 61 residential sites representing a variety of surrounding livestock-related characteristics. Three to four 2-wk averaged samples were collected at each site. A local reference site was used for temporal variation adjustment. Samples were analyzed for PM10 mass by weighing and for endotoxin by using the limulus amebocyte lysate assay. Three LUR models were developed, first a model based on general livestock-related GIS predictors only, followed by models that also considered species-specific predictors and farm type-specific predictors. RESULTS: Variation in concentrations measured between sites was substantial for endotoxin and more limited for PM10 (coefficient of variation: 43%, 8%, respectively); spatial patterns differed considerably. Simple exposure proxies were associated with endotoxin concentrations although spatial variation explained was modest (R2
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- 2018
19. Insights into Livestock-Related Microbial Concentrations in Air at Residential Level in a Livestock Dense Area
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de Rooij, Myrna M. T., primary, Hoek, Gerard, additional, Schmitt, Heike, additional, Janse, Ingmar, additional, Swart, Arno, additional, Maassen, Catharina B. M., additional, Schalk, Marjolijn, additional, Heederik, Dick J. J., additional, and Wouters, Inge M., additional
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- 2019
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20. A systematic knowledge synthesis on the spatial dimensions of Q fever epidemics
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De Rooij, Myrna M. T., primary, Van Leuken, Jeroen P. G., additional, Swart, Arno, additional, Kretzschmar, Mirjam E. E., additional, Nielen, Mirjam, additional, De Koeijer, Aline A., additional, Janse, Ingmar, additional, Wouters, Inge M., additional, and Heederik, Dick J. J., additional
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- 2018
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21. SARS-CoV-2 infection in farmed minks, the Netherlands, April and May 2020.
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Oreshkova, Nadia, Molenaar, Robert Jan, Vreman, Sandra, Harders, Frank, Munnink, Bas B. Oude, Hakze-van der Honing, Renate W., Gerhards, Nora, Tolsma, Paulien, Bouwstra, Ruth, Sikkema, Reina S., Tacken, Mirriam G. J., de Rooij, Myrna M. T., Weesendorp, Eefke, Engelsma, Marc Y., Bruschke, Christianne J. M., Smit, Lidwien A. M., Koopmans, Marion, van der Poel, Wim H. M., and Stegeman, Arjan
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- 2020
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22. Detection of Coxiella burnetii in Ambient Air after a Large Q Fever Outbreak
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de Rooij, Myrna M. T., primary, Borlée, Floor, additional, Smit, Lidwien A. M., additional, de Bruin, Arnout, additional, Janse, Ingmar, additional, Heederik, Dick J. J., additional, and Wouters, Inge M., additional
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- 2016
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23. Spatial Variation of Endotoxin Concentrations Measured in Ambient PM10 in a Livestock-Dense Area: Implementation of a Land-Use Regression Approach.
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de Rooij, Myrna M. T., Heederik, Dick J. J., van Nunen, Erik J. H. M., van Schothorst, Isabella J., Maassen, Catharina B. M., Hoek, Gerard, and Wouters, Inge M.
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ENDOTOXINS , *LIVESTOCK farms , *TOXIC substance exposure , *LIMULUS test , *ECOLOGICAL carrying capacity , *AIR pollution , *ANIMALS , *RESIDENTIAL patterns , *ENDOTOXIN analysis , *BIOLOGICAL assay , *CATTLE , *STATISTICAL correlation , *ENVIRONMENTAL health , *HORSES , *POULTRY , *REGRESSION analysis , *SHEEP , *SWINE , *PARTICULATE matter , *STATISTICAL models , *DESCRIPTIVE statistics - Abstract
BACKGROUND: Results from studies on residential health effects of livestock farming are inconsistent, potentially due to simple exposure proxies used (e.g., livestock density). Accuracy of these proxies compared with measured exposure concentrations is unknown. OBJECTIVES: We aimed to assess spatial variation of endotoxin in PM10 (particulate matter ≤10 lm) at residential level in a livestock-dense area, compare simple livestock exposure proxies to measured endotoxin concentrations, and evaluate whether land-use regression (LUR) can be used to explain spatial variation of endotoxin. METHODS: The study area (3,000 km²) was located in Netherlands. Ambient PM10 was collected at 61 residential sites representing a variety of surrounding livestock-related characteristics. Three to four 2-wk averaged samples were collected at each site. A local reference site was used for temporal variation adjustment. Samples were analyzed for PM10 mass by weighing and for endotoxin by using the limulus amebocyte lysate assay. Three LUR models were developed, first a model based on general livestock-related GIS predictors only, followed by models that also considered speciesspecific predictors and farm type-specific predictors. RESULTS: Variation in concentrations measured between sites was substantial for endotoxin and more limited for PM10 (coefficient of variation: 43%, 8%, respectively); spatial patterns differed considerably. Simple exposure proxies were associated with endotoxin concentrations although spatial variation explained was modest (R² <26%). LUR models using a combination of animal-specific livestock-related characteristics performed markedly better, with up to 64% explained spatial variation. CONCLUSION: The considerable spatial variation of ambient endotoxin concentrations measured in a livestock-dense area can largely be explained by LUR modeling based on livestock-related characteristics. Application of endotoxin LUR models seems promising for residential exposure estimation within health studies. [ABSTRACT FROM AUTHOR]
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- 2018
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24. Risk Factors of Coxiella burnetii (Q Fever) Seropositivity in Veterinary Medicine Students
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de Rooij, Myrna M. T., primary, Schimmer, Barbara, additional, Versteeg, Bart, additional, Schneeberger, Peter, additional, Berends, Boyd R., additional, Heederik, Dick, additional, van der Hoek, Wim, additional, and Wouters, Inge M., additional
- Published
- 2012
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25. Associations of Anti-COVID-19 Measures and Lifestyle Changes During the COVID-19 Pandemic With Sleep Patterns in the Netherlands: A Longitudinal Study.
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Sandoval-Diez N, Smit LAM, Boer JMA, de Rooij MMT, Koppelman GH, van Kersen W, Vonk JM, Vermeulen R, Gehring U, and Huss A
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- Humans, Pandemics, SARS-CoV-2, Netherlands epidemiology, Longitudinal Studies, Life Style, Sleep, COVID-19 epidemiology
- 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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)
- Published
- 2024
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26. Residential exposure to microbial emissions from livestock farms: Implementation and evaluation of land use regression and random forest spatial models.
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Cornu Hewitt B, Smit LAM, van Kersen W, Wouters IM, Heederik DJJ, Kerckhoffs J, Hoek G, and de Rooij MMT
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- Animals, Swine, Farms, Escherichia coli, Random Forest, Poultry, Livestock, Air Pollutants analysis
- Abstract
Adverse health effects have been linked with exposure to livestock farms, likely due to airborne microbial agents. Accurate exposure assessment is crucial in epidemiological studies, however limited studies have modelled bioaerosols. This study used measured concentrations in air of livestock commensals (Escherichia coli (E. coli) and Staphylococcus species (spp.)), and antimicrobial resistance genes (tetW and mecA) at 61 residential sites in a livestock-dense region in the Netherlands. For each microbial agent, land use regression (LUR) and random forest (RF) models were developed using Geographic Information System (GIS)-derived livestock-related characteristics as predictors. The mean and standard deviation of annual average concentrations (gene copies/m
3 ) of E. coli, Staphylococcus spp., tetW and mecA were as follows: 38.9 (±1.98), 2574 (±3.29), 20991 (±2.11), and 15.9 (±2.58). Validated through 10-fold cross-validation (CV), the models moderately explained spatial variation of all microbial agents. The best performing model per agent explained respectively 38.4%, 20.9%, 33.3% and 27.4% of the spatial variation of E. coli, Staphylococcus spp., tetW and mecA. RF models had somewhat better performance than LUR models. Livestock predictors related to poultry and pig farms dominated all models. To conclude, the models developed enable enhanced estimates of airborne livestock-related microbial exposure in future epidemiological studies. Consequently, this will provide valuable insights into the public health implications of exposure to specific microbial agents., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)- Published
- 2024
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27. Short-term residential exposure to endotoxin emitted from livestock farms in relation to lung function in non-farming residents.
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de Rooij MMT, Erbrink HJ, Smit LAM, Wouters IM, Hoek G, and Heederik DJJ
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- Animals, Humans, Farms, Livestock, Endotoxins toxicity, Agriculture, Lung chemistry, Environmental Exposure analysis, Particulate Matter analysis, Air Pollution analysis, Environmental Pollutants analysis, Air Pollutants analysis
- Abstract
Background: Evidence on the public health relevance of exposure to livestock farm emissions is increasing. Research mostly focused on chemical air pollution, less on microbial exposure, while endotoxins are suggested relevant bacterial components in farm emissions. Acute respiratory health effects of short-term exposure to livestock-related air pollution has been shown for NH
3 and PM10 , but has not yet been studied for endotoxin. We aimed to assess associations between lung function and short-term exposure to livestock farming emitted endotoxin in co-pollutant models with NH3 and PM10 ., Methods: In 2014/2015, spirometry was conducted in 2308 non-farming residents living in a rural area in the Netherlands. Residential exposure to livestock farming emitted endotoxin during the week prior to spirometry was estimated by dispersion modelling. The model was applied to geo-located individual barns within 10 km of each home address using provincial farm data and local hourly meteorological conditions. Regional week-average measured concentrations of NH3 and PM10 were obtained through monitoring stations. Lung function parameters (FEV1 , FVC, FEV1 /FVC, MMEF) were expressed in %-predicted value based on GLI-2012. Exposure-response analyses were performed by linear regression modelling., Results: Week-average endotoxin exposure was negatively associated with FVC, independently from regional NH3 and PM10 exposure. A 1.1% decline in FVC was estimated for an increase of endotoxin exposure from 10th to 90th percentile. Stratified analyses showed a larger decline (3.2%) for participants with current asthma and/or COPD. FEV1 was negatively associated with week-average endotoxin exposure, but less consistent after co-pollutant adjustment. FEV1 /FVC and MMEF were not associated with week-average endotoxin exposure., Conclusions: Lower lung function in non-farming residents was observed in relation to short-term residential exposure to livestock farming emitted endotoxin. This study indicates the probable relevance of exposure to microbial emissions from livestock farms considering public health besides chemical air pollution, necessitating future research incorporating both., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: All authors reports financial support was provided by Netherlands Ministry of Infrastructure and Water Management. All authors reports financial support was provided by Province of Noord-Brabant. All authors reports financial support was provided by Netherlands Ministry of Health Welfare and Sport. All authors reports financial support was provided by Netherlands Ministry of Economic Affairs. All authors reports financial support was provided by Lung Foundation Netherlands. Co-author Gerard Hoek is associate editor at Environmental Research., (Copyright © 2023 Utrecht University. Published by Elsevier Inc. All rights reserved.)- Published
- 2024
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28. A Comprehensive Sampling Study on SARS-CoV-2 Contamination of Air and Surfaces in a Large Meat Processing Plant Experiencing COVID-19 Clusters in June 2020.
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de Rooij MMT, Sikkema RS, Bouwknegt M, de Geus Y, Stanoeva KR, Nieuwenweg S, van Dam ASG, Raben C, Dohmen W, Heederik D, Reusken C, Meijer A, Koopmans MPG, Franz E, and Smit LAM
- Subjects
- Humans, SARS-CoV-2, RNA, Viral, Sampling Studies, Sewage, COVID-19 epidemiology
- Abstract
Objective: We aimed to assess SARS-CoV-2 contamination of air and surfaces to gain insight into potential occupational exposure in a large meat processing plant experiencing COVID-19 clusters. Methods: Oro-nasopharyngeal SARS-CoV-2 screening was performed in 76 workers. Environmental samples ( n = 275) including air, ventilation systems, sewage, and swabs of high-touch surfaces and workers' hands were tested for SARS-CoV-2 RNA by real-time quantitative polymerase chain reaction. Results: Twenty-seven (35.5%) of the (predominantly asymptomatic) workers tested positive with modest to low viral loads (cycle threshold ≥ 29.7). Six of 203 surface swabs, 1 of 12 personal air samples, and one of four sewage samples tested positive; other samples tested negative. Conclusions: Although one third of workers tested positive, environmental contamination was limited. Widespread SARS-CoV-2 transmission via air and surfaces was considered unlikely within this plant at the time of investigation while strict COVID-19 control measures were already implemented., Competing Interests: Conflict of interest: The authors are employed by the respective affiliations mentioned. The authors declare no conflicts of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Occupational and Environmental Medicine.)
- Published
- 2023
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29. Residential exposure to livestock farms and lung function in adolescence - The PIAMA birth cohort study.
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Kiss P, de Rooij MMT, Koppelman GH, Boer J, Vonk JM, Vermeulen R, Hogerwerf L, Sterk HAM, Huss A, Smit LAM, and Gehring U
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- Animals, Swine, Cattle, Horses, Farms, Livestock, Cohort Studies, Prospective Studies, Cross-Sectional Studies, Environmental Exposure analysis, Particulate Matter analysis, Lung, Air Pollution adverse effects, Air Pollutants toxicity, Air Pollutants analysis
- Abstract
Background: There is a growing interest in the impact of air pollution from livestock farming on respiratory health. Studies in adults suggest adverse effects of livestock farm emissions on lung function, but so far, studies involving children and adolescents are lacking., Objectives: To study the association of residential proximity to livestock farms and modelled particulate matter ≤10 μm (PM
10 ) from livestock farms with lung function in adolescence., Methods: We performed a cross-sectional study among 715 participants of the Dutch prospective PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort study. Relationships of different indicators of residential livestock farming exposure (distance to farms, distance-weighted number of farms, cattle, pigs, poultry, horses and goats within 3 km; modelled atmospheric PM10 concentrations from livestock farms) with forced expiratory volume in 1 s (FEV1 ) and forced vital capacity (FVC) at age 16 were assessed by linear regression taking into account potential confounders. Associations were expressed per interquartile range increase in exposure., Results: Higher exposure to livestock farming was consistently associated with a lower FEV1 , but not with FVC among participants living in less urbanized municipalities (<1500 addresses/km2 , N = 402). Shorter distances of homes to livestock farms were associated with a 1.4% (0.2%; 2.7%) lower FEV1 . Larger numbers of farms within 3 km and higher concentrations of PM10 from livestock farming were associated with a 1.8% (0.8%, 2.9%) and 0.9% (0.4%,1.5%) lower FEV1 , respectively., Conclusions: Our findings suggest that higher exposure to livestock farming is associated with a lower FEV1 in adolescents. Replication and more research on the etiologic agents involved in these associations and the underlying mechanisms is needed., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Myrna MT de Rooij reports a relationship with NCOH (Netherlands Center for One Health) that includes: travel reimbursement. Gerard H. Koppelman reports a relationship with Netherlands Lung Foundation that includes: funding grants. Gerard H. Koppelman reports a relationship with ZonMw that includes: funding grants. Gerard H. Koppelman reports a relationship with Teva The Netherlands that includes: funding grants. Gerard H. Koppelman reports a relationship with GSK that includes: consulting or advisory and funding grants. Gerard H. Koppelman reports a relationship with Vertex that includes: funding grants. Gerard H. Koppelman reports a relationship with Ubbo Emmius foundation that includes: funding grants. Gerard H. Koppelman reports a relationship with European Union (H2020) that includes: funding grants. Gerard H. Koppelman reports a relationship with Pure IMS that includes: consulting or advisory. Gerard H. Koppelman reports a relationship with Sanofi that includes: consulting or advisory. Gerard H. Koppelman reports a relationship with Astra Zeneka that includes: consulting or advisory. Lidwien AM Smit reports a relationship with Ministry of Health, Welfare and Sport of the Netherlands that includes: funding grants. Lenny Hogerwerf reports a relationship with Ministry of Health, Welfare and Sport of the Netherlands that includes: funding grants. Lidwien AM Smit reports a relationship with Ministry of Agriculture, Nature and Food Quality of The Netherlands that includes: funding grants., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)- Published
- 2023
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30. Air pollution from livestock farms and the oropharyngeal microbiome of COPD patients and controls.
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van Kersen W, Bossers A, de Steenhuijsen Piters WAA, de Rooij MMT, Bonten M, Fluit AC, Heederik D, Paganelli FL, Rogers M, Viveen M, Bogaert D, Leavis HL, and Smit LAM
- Subjects
- Animals, Endotoxins analysis, Farms, Humans, Livestock, RNA, Ribosomal, 16S analysis, RNA, Ribosomal, 16S genetics, Air Pollutants analysis, Air Pollution adverse effects, Air Pollution analysis, Microbiota, Pulmonary Disease, Chronic Obstructive
- Abstract
Air pollution from livestock farms is known to affect respiratory health of patients with chronic obstructive pulmonary disease (COPD). The mechanisms behind this relationship, however, remain poorly understood. We hypothesise that air pollutants could influence respiratory health through modulation of the airway microbiome. Therefore, we studied associations between air pollution exposure and the oropharyngeal microbiota (OPM) composition of COPD patients and controls in a livestock-dense area. Oropharyngeal swabs were collected from 99 community-based (mostly mild) COPD cases and 184 controls (baseline), and after 6 and 12 weeks. Participants were non-smokers or former smokers. Annual average livestock-related outdoor air pollution at the home address was predicted using dispersion modelling. OPM composition was analysed using 16S rRNA-based sequencing in all baseline samples and 6-week and 12-week repeated samples of 20 randomly selected subjects (n = 323 samples). A random selection of negative control swabs, taken every sampling day, were also included in the downstream analysis. Both farm-emitted endotoxin and PM
10 levels were associated with increased OPM richness in COPD patients (p < 0.05) but not in controls. COPD case-control status was not associated with community structure, while correcting for known confounders (multivariate PERMANOVA p > 0.05). However, members of the genus Streptococcus were more abundant in COPD patients (Benjamini-Hochberg adjusted p < 0.01). Moderate correlation was found between ordinations of 20 subjects analysed at 0, 6, and 12 weeks (Procrustes r = 0.52 to 0.66; p < 0.05; Principal coordinate analysis of Bray-Curtis dissimilarity), indicating that the OPM is relatively stable over a 12 week period and that a single sample sufficiently represents the OPM. Air pollution from livestock farms is associated with OPM richness of COPD patients, suggesting that the OPM of COPD patients is susceptible to alterations induced by exposure to air pollutants., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)- Published
- 2022
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31. SARS-CoV-2 infection in cats and dogs in infected mink farms.
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van Aart AE, Velkers FC, Fischer EAJ, Broens EM, Egberink H, Zhao S, Engelsma M, Hakze-van der Honing RW, Harders F, de Rooij MMT, Radstake C, Meijer PA, Oude Munnink BB, de Rond J, Sikkema RS, van der Spek AN, Spierenburg M, Wolters WJ, Molenaar RJ, Koopmans MPG, van der Poel WHM, Stegeman A, and Smit LAM
- Subjects
- Animals, Animals, Wild, Cats, Dogs, Farms, Humans, Mink, SARS-CoV-2, COVID-19 epidemiology, COVID-19 veterinary, Cat Diseases epidemiology, Dog Diseases epidemiology
- Abstract
Animals like mink, cats and dogs are susceptible to SARS-CoV-2 infection. In the Netherlands, 69 out of 127 mink farms were infected with SARS-CoV-2 between April and November 2020 and all mink on infected farms were culled after SARS-CoV-2 infection to prevent further spread of the virus. On some farms, (feral) cats and dogs were present. This study provides insight into the prevalence of SARS-CoV-2-positive cats and dogs in 10 infected mink farms and their possible role in transmission of the virus. Throat and rectal swabs of 101 cats (12 domestic and 89 feral cats) and 13 dogs of 10 farms were tested for SARS-CoV-2 using PCR. Serological assays were performed on serum samples from 62 adult cats and all 13 dogs. Whole Genome Sequencing was performed on one cat sample. Cat-to-mink transmission parameters were estimated using data from all 10 farms. This study shows evidence of SARS-CoV-2 infection in 12 feral cats and 2 dogs. Eleven cats (18%) and two dogs (15%) tested serologically positive. Three feral cats (3%) and one dog (8%) tested PCR-positive. The sequence generated from the cat throat swab clustered with mink sequences from the same farm. The calculated rate of mink-to-cat transmission showed that cats on average had a chance of 12% (95%CI 10%-18%) of becoming infected by mink, assuming no cat-to-cat transmission. As only feral cats were infected it is most likely that infections in cats were initiated by mink, not by humans. Whether both dogs were infected by mink or humans remains inconclusive. This study presents one of the first reports of interspecies transmission of SARS-CoV-2 that does not involve humans, namely mink-to-cat transmission, which should also be considered as a potential risk for spread of SARS-CoV-2., (© 2021 The Authors. Transboundary and Emerging Diseases published by Wiley-VCH GmbH.)
- Published
- 2022
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32. Endotoxin and particulate matter emitted by livestock farms and respiratory health effects in neighboring residents.
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de Rooij MMT, Smit LAM, Erbrink HJ, Hagenaars TJ, Hoek G, Ogink NWM, Winkel A, Heederik DJJ, and Wouters IM
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- Air Pollutants toxicity, Animals, Asthma epidemiology, Asthma etiology, Cross-Sectional Studies, Endotoxins toxicity, Female, Humans, Livestock, Male, Particulate Matter toxicity, Prevalence, Respiration Disorders epidemiology, Air Pollutants analysis, Endotoxins analysis, Environmental Exposure analysis, Farms, Particulate Matter analysis, Respiration Disorders etiology
- Abstract
Background: 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., Objectives: We aimed to assess exposure-response relations for a range of respiratory endpoints and atopic sensitization in relation to livestock farm associated PM
10 and endotoxin levels., Methods: 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., Results: 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)., Conclusions: 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)- Published
- 2019
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33. Spatial Variation of Endotoxin Concentrations Measured in Ambient PM 10 in a Livestock-Dense Area: Implementation of a Land-Use Regression Approach.
- Author
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de Rooij MMT, Heederik DJJ, van Nunen EJHM, van Schothorst IJ, Maassen CBM, Hoek G, and Wouters IM
- Subjects
- Animals, Geographic Information Systems, Humans, Livestock, Models, Theoretical, Netherlands, Particulate Matter analysis, Air Pollutants analysis, Air Pollution analysis, Endotoxins analysis, Environmental Monitoring methods
- Abstract
Background: Results from studies on residential health effects of livestock farming are inconsistent, potentially due to simple exposure proxies used (e.g., livestock density). Accuracy of these proxies compared with measured exposure concentrations is unknown., Objectives: We aimed to assess spatial variation of endotoxin in PM
10 (particulate matter ≤10μm) at residential level in a livestock-dense area, compare simple livestock exposure proxies to measured endotoxin concentrations, and evaluate whether land-use regression (LUR) can be used to explain spatial variation of endotoxin., Methods: The study area (3,0002 ) was located in Netherlands. Ambient PM10 was collected at 61 residential sites representing a variety of surrounding livestock-related characteristics. Three to four 2-wk averaged samples were collected at each site. A local reference site was used for temporal variation adjustment. Samples were analyzed for PM10 mass by weighing and for endotoxin by using the limulus amebocyte lysate assay. Three LUR models were developed, first a model based on general livestock-related GIS predictors only, followed by models that also considered species-specific predictors and farm type-specific predictors., Results: Variation in concentrations measured between sites was substantial for endotoxin and more limited for PM10 (coefficient of variation: 43%, 8%, respectively); spatial patterns differed considerably. Simple exposure proxies were associated with endotoxin concentrations although spatial variation explained was modest (R2 <26%). LUR models using a combination of animal-specific livestock-related characteristics performed markedly better, with up to 64% explained spatial variation., Conclusion: The considerable spatial variation of ambient endotoxin concentrations measured in a livestock-dense area can largely be explained by LUR modeling based on livestock-related characteristics. Application of endotoxin LUR models seems promising for residential exposure estimation within health studies. https://doi.org/10.1289/EHP2252.- Published
- 2018
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34. Spatial and temporal variation in endotoxin and PM10 concentrations in ambient air in a livestock dense area.
- Author
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de Rooij MM, Heederik DJ, Borlée F, Hoek G, and Wouters IM
- Subjects
- Animals, Farms, Livestock, Models, Theoretical, Netherlands, Spatio-Temporal Analysis, Air Pollutants analysis, Endotoxins analysis, Particulate Matter analysis
- Abstract
Several studies have reported associations between farming and respiratory health in neighboring residents. Health effects are possibly linked to fine dust and endotoxin emissions from livestock farms. Little is known about levels of these air pollutants in ambient air in livestock dense areas. We aimed to explore temporal and spatial variation of PM10 and endotoxin concentrations, and the association with livestock-related spatial and meteorological temporal determinants. From March till September 2011, one week average PM10 samples were collected using Harvard Impactors at eight sites (residential gardens) representing a variety of nearby livestock-related characteristics. A background site was included in the study area, situated at least 500m away from the nearest farm. PM10 mass was determined by gravimetric analysis and endotoxin level by means of Limulus-Amebocyte-Lysate assay. Data were analyzed using mixed models. The range between sites of geometric mean concentrations was for PM10 19.8-22.3µg/m
3 and for endotoxin 0.46-0.66EU/m3 . PM10 concentrations and spatial variation were very similar for all sites, while endotoxin concentrations displayed a more variable pattern over time with larger differences between sites. Nonetheless, the temporal pattern at the background location was highly comparable to the sites mean temporal pattern both for PM10 and endotoxin (Pearson correlation: 0.92, 0.62). Spatial variation was larger for endotoxin than for PM10 (within/between site variance ratio: 0.63, 2.03). Spatial livestock-related characteristics of the surroundings were more strongly related to endotoxin concentrations, while temporal determinants were more strongly related to PM10 concentrations. The effect of local livestock-related sources on PM10 concentration was limited in this study carried out in a livestock dense area. The effect on endotoxin concentrations was more profound. To gain more insight in the effect of livestock-related sources on ambient levels of PM10 and endotoxin, measurements should be based on a broader set of locations., (Copyright © 2016. Published by Elsevier Inc.)- Published
- 2017
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