Impact of COVID-19 containment measures on perceived health and health-protective behavior: a longitudinal study

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

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017–2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health

Potential environmental transmission routes of SARS-CoV-2 inside a large meat processing plant experiencing COVID-19 clusters

Worldwide exceptionally many COVID-19 clusters were observed in meat processing plants. Many contributing factors, promoting transmission, were suggested, including climate conditions in cooled production rooms favorable for environmental transmission but actual sampling studies are lacking. We aimed to assess SARS-CoV-2 contamination of air and surfaces to gain insight in potential environmental transmission in a large Dutch meat processing plant experiencing COVID-19 clusters. We performed SARS-CoV-2 screening of workers operating in cooled production rooms and intensive environmental sampling during a two-week study period in June 2020. Sampling of air (both stationary and personal), settling dust, ventilation systems, and sewage was performed. Swabs were collected from high-touch surfaces and workers’ hands. Screening of workers was done using oronasopharyngeal swabs. Samples were tested for presence of SARS-CoV-2 RNA by RT-qPCR. Of the 76 (predominantly asymptomatic) workers tested, 27 (35.5%) were SARS-CoV-2 RNA positive with modest to low viral loads (Ct≥29.7). In total, 6 out of 203 surface swabs were positive (Ct ≥38), being swabs taken from communal touchscreens/handles. One of the 12 personal air samples and one of the 4 sewage samples were positive, RNA levels were low (Ct≥38). All other environmental samples tested negative. Although one-third of workers tested SARS-CoV-2 RT-PCR positive, environmental contamination was limited. Hence widespread transmission of SARS-CoV-2 via air and surfaces was considered unlikely within this plant at the time of investigation in the context of strict COVID-19 control measures in place

Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and related humans in the Netherlands

In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and related humans on farms. High number of farm infections (68/126) in minks and farm related personnel (>50% of farms) were detected, with limited spread to the general human population. Three of five initial introductions of SARS-CoV-2 lead to subsequent spread between mink farms until November 2020. The largest cluster acquired a mutation in the receptor binding domain of the Spike protein (position 486), evolved faster and spread more widely and longer. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combing genetic information with epidemiological information at the animal-human interface

Farmers' knowledge and expectations of antimicrobial use and resistance are strongly related to usage in Dutch livestock sectors

Comprehensive strategies to improve on-farm antimicrobial use (AMU) are needed to contain antimicrobial resistance (AMR). Little is known about farmers' motivating and enabling factors, and about their influence on AMU. In a cross-sectional online survey, Dutch dairy, veal and pig farmers (n=457) reported their on-farm AMU as "Defined Daily Dose Animal" per year (DDDAF) and completed a detailed questionnaire on their view, knowledge and behavior towards AMU and AMR. Exploratory factor analysis (EFA) on the questionnaire items identified four psychological factors labeled as 'referent beliefs', 'perceived risk', 'knowledge', and 'undesired attitude to regulations'. Linear regression was done to explore the relationship between the obtained factors and on-farm AMU across the three animal sectors. Dairy farmers showed the highest factor scores for 'knowledge' and the lowest for 'perceived risk'. 'Knowledge' scores were significantly and inversely related to AMU (P=0.0004). Borderline significant associations with AMU were found for 'perceived risk' and 'undesired attitude to regulations' (negative and positive relationships respectively). There were no apparent differences for these relationships between the three livestock sectors. Behavioral interventions in farmers such as educational campaigns or increased support by veterinarians could empower farmers with more prudent and rational practices, eventually reducing AMU in food animals

Fecal Carriage of Extended-Spectrum-β-Lactamase/AmpC-Producing Escherichia coli in Horses

A nationwide study on the occurrence of extended-spectrum β-lactamase (ESBL)/AmpC in nonhospitalized horses in the Netherlands was performed. Molecular characterization was done, and questionnaires were analyzed to identify factors associated with carriage. In total, 796 horse owners were approached; 281 of these submitted a fecal sample from their horse(s), resulting in 362 samples. All samples were cultured qualitatively in Luria-Bertani (LB) broth and subsequently on MacConkey agar, both supplemented with 1 mg/liter cefotaxime (LB+ and MC+). Positive samples were subsequently cultured quantitatively on MC+. Initial extended-spectrum-β-lactamase (ESBL)/AmpC screening was performed by PCR, followed by whole-genome sequencing on selected strains. Associations between ESBL/AmpC carriage and questionnaire items were analyzed using a univariate generalized estimating equation (GEE) regression analysis, followed by a multiple GEE model for relevant factors. In total, 39 of 362 samples (11%) were determined to be positive for ESBL/AmpC. blaCTX-M-1-carrying isolates were obtained from 77% of positive samples (n = 30). Other ESBL/AmpC genes observed included blaCTX-M-2, blaCTX-M-14, blaCTX-M-15, blaCTX-M-32, blaSHV-12, blaCMY-2, and blaACT-10 A high association between the presence of blaCTX-M-1 and IncHI1 plasmids was observed (46% of samples; n = 18). Based on core genome analysis (n = 48 isolates), six Escherichia coli clusters were identified, three of which represented 80% of the isolates. A negative association between ESBL/AmpC carriage and horses being in contact with other horses at a different site was observed. The presence of a dog on the premises and housing in a more densely human-populated region were positively associated.IMPORTANCE Extended-spectrum β-lactamases (ESBLs) are widespread in human and animal populations and in the environment. Many different ESBL variants exist. The dissemination of ESBLs within and between populations and the environment is also largely influenced by genetic mobile elements (e.g., plasmids) that facilitate spread of these ESBLs. In order to identify potential attributable ESBL sources for, e.g., the human population, it is important to identify the different ESBL variants, the bacteria carrying them, and the potential risk factors for ESBL carriage from other potential sources. This nationwide study focuses on ESBL carriage in the open horse population and investigated the molecular characteristics, geographical distribution throughout the Netherlands, and potential risk factors for fecal ESBL carriage in horses. These data can be used for future attribution studies in order to reduce potential transmission of ESBL-producing bacteria between sources.</p

Risk of pneumonia in the vicinity of goat farms: a comparative assessment of temporal variation based on longitudinal health data

Abstract Background Although the association between living in the vicinity of a goat farm and the occurrence of pneumonia is well-documented, it is unclear whether the higher risk of pneumonia in livestock dense areas is season-specific or not. This study explored the temporal variation of the association between exposure to goat farms and the occurrence of pneumonia. Methods A large population-based study was conducted in the Netherlands, based on electronic health records from 49 general practices, collected for a period of six consecutive years (2014–2019). Monthly incidence rates of pneumonia in a livestock dense area were compared with those of a control group (areas with low livestock density) both per individual year and cumulatively for the entire six-year period. Using individual estimates of livestock exposure, it was also examined whether incidence of pneumonia differed per month if someone lived within a certain radius from a goat farm, compared to residents who lived further away. Results Pneumonia was consistently more common in the livestock dense area throughout the year, compared to the control area. Analyses on the association between the individual livestock exposure estimates and monthly pneumonia incidence for the whole six-year period, yielded a generally higher risk for pneumonia among people living within 500 m from a goat farm, compared to those living further away. Significant associations were observed for March (IRR 1.68, 95% CI 1.02–2.78), August (IRR 2.67, 95% CI 1.45–4.90) and September (IRR 2.52, 95% CI 1.47–4.32). Conclusions The increased occurrence of pneumonia in the vicinity of goat farms is not season-specific. Instead, pneumonia is more common in livestock dense areas throughout the year, including summer months

Associations between pneumonia and residential distance to livestock farms over a five-year period in a large population-based study

In a recent study of electronic health records (EHR) of general practitioners in a livestock-dense area in The Netherlands in 2009, associations were found between residential distance to poultry farms and the occurrence of community-acquired pneumonia (CAP). In addition, in a recent cross-sectional study in 2494 adults in 2014/2015 an association between CAP and proximity to goat farms was observed. Here, we extended the 2009 EHR analyses across a wider period of time (2009–2013), a wider set of health effects, and a wider set of farm types as potential risk sources. A spatial (transmission) kernel model was used to investigate associations between proximity to farms and CAP diagnosis for the period from 2009 to 2013, obtained from EHR of in total 140,059 GP patients. Also, associations between proximity to farms and upper respiratory infections, inflammatory bowel disease, and (as a control disease) lower back pain were analysed. Farm types included as potential risk sources in these analyses were cattle, (dairy) goats, mink, poultry, sheep, and swine. The previously found association between CAP occurrence and proximity to poultry farms was confirmed across the full 5-year study period. In addition, we found an association between increased risk for pneumonia and proximity to (dairy) goat farms, again consistently across all years from 2009 to 2013. No consistent associations were found for any of the other farm types (cattle, mink, sheep and swine), nor for the other health effects considered. On average, the proximity to poultry farms corresponds to approximately 119 extra patients with CAP each year per 100,000 people in the research area, which accounts for approximately 7.2% extra cases. The population attributable risk percentage of CAP cases in the research area attributable to proximity to goat farms is approximately 5.4% over the years 2009–2013. The most probable explanation for the association of CAP with proximity to poultry farms is thought to be that particulate matter and its components are making people more susceptible to respiratory infections. The causes of the association with proximity to goat farms is still unclear. Although the 2007–2010 Q-fever epidemic in the area probably contributed Q-fever related pneumonia cases to the observed additional cases in 2009 and 2010, it cannot explain the association found in later years 2011–2013.</p

Air pollution from livestock farms is associated with airway obstruction in neighboring residents

Rationale: Livestock farm emissions may not only affect respiratory health of farmers but also of neighboring residents. Objectives: To explore associations between spatial and temporal variation in pollutant emissions from livestock farms and lung function in a general, nonfarming, rural population in the Netherlands. Methods: We conducted a cross-sectional study in 2,308 adults (age, 20-72 yr). A pulmonary function test was performed measuring prebronchodilator and post-bronchodilator FEV1, FVC, FEV1/FVC, and maximum mid-expiratory flow (MMEF). Spatial exposure was assessed as (1) number of farms within 500 m and 1,000 m of the home, (2) distance to the nearest farm, and (3) modeled annual average fine dust emissions from farms within 500 m and 1,000 m of the home address. Temporal exposure was assessed as week-average ambient particulate matter,10 μm in diameter and ammonia (NH3) concentrations before lung function measurements. Data were analyzed with generalized additive models (smoothing). Measurements and Main Results: A negative association was found between the number of livestock farms within a 1,000-m buffer from the home address and MMEF, which was more pronounced in participants without atopy. No associations were found with other spatial exposure variables. Week-average particulate matter,10 μm in diameter and NH3 levels were negatively associated with FEV1, FEV1/FVC, and MMEF. In a two-pollutant model, only NH3 remained associated. A 25-mg/m3 increase in NH3 was associated with a 2.22% lower FEV1 (95% confidence interval, 23.69 to 20.74), FEV1/FVC of 21.12% (21.96 to 20.28), and MMEF of 25.67% (28.80 to 22.55). Conclusions: Spatial and temporal variation in livestock air pollution emissions are associated with lung function deficits in nonfarming residents