Factors influencing SARS-CoV-2 infection rate in Belgian nursing home residents during the first wave of COVID-19 pandemic.

In April 2020, Belgium experienced high numbers of fatal COVID-19 cases among nursing home (NH) residents. In response, a mass testing campaign was organised testing all NH residents and staff. We analysed the data of Flemish NHs to identify institutional factors associated with increased SARS-CoV-2 infection rates among NH residents. Cross-sectional study was conducted between 8 April and 15 May 2020. Data collected included demographics, group category (i.e. staff or resident), symptom status and test result. We retrieved additional data: number of beds and staff, type of beds (level of dependency of residents) and ownership (public, private for profit/non-profit institutions). Risk factor analysis was performed using negative binomial regression. In total, 695 NHs were included, 282 (41%) had at least one resident tested positive. Higher infection rate among residents was associated with a higher fraction of RVT beds, generally occupied by more dependent residents (incidence rate ratio (IRR) 1.97; 95% CI 1.00-3.86) and higher staff infection rate (IRR 1.89; 95% CI 1.68-2.12). No relationship was found between other investigated NH characteristics and infection rate among residents. Staff-resident interactions are key in SARS-CoV-2 transmission dynamics. Vaccination, regular staff testing, assessment of infection prevention and control strategies in all NHs are needed to face future SARS-CoV-2 epidemics in these settings.

Annual, seasonal, and morning rush hour Land Use Regression models for black carbon in a school catchment area of Milan, Italy.

INTRODUCTION: The European Environment Agency has identified Northern Italy as one of the most polluted areas in Europe. Among air contaminants, black carbon (BC) has been identified as a sensitive marker of traffic related air pollution. This study aims to investigate the spatial distribution of BC in the catchment area of an elementary school of Milan, the biggest city in Northern Italy, using Land Use Regression (LUR) models and focusing especially on Morning Rush Hour (MRH). METHODS: Two recruitment campaigns were performed asking schoolchildren's parents and residents of the study area to host a monitoring site in their own dwellings. Finally, 34 monitoring sites and 1 reference site were sampled. BC was measured in two seasonal campaigns using eight micro-aethalometers. Six seasonal and annual LUR models were developed, 3 focused on MRH. RESULTS: Overall, median BC was 3247 and 1309 ng/m3 in the cold and warm season, respectively. In both seasons, there was a significant spatial variation between the monitoring sites. MRH values were higher than the daily values with median concentrations of 4227 and 2331 ng/m3, respectively. Developed LUR models showed that BC variability is well explained only by traffic variables; R2 ranged from 0.52 to 0.79 and from 0.65 to 0.81, for seasonal/annual and MRH LUR models respectively. DISCUSSION: LUR models based on traffic variables explain most of the measured BC distribution variability for both warm and cold season. MRH represents a critical moment for BC during all the year, with an increase of 1000 ng/m3 respective to the daily median value and differences in magnitude according to location. Our results highlight that the mobility issue is one of the most important challenges to reduce air pollution in the city of Milan and this is of particular concern for elementary schoolchildren that commute to school during MRH.

Dynamics of ultrafine particles inside a roadway tunnel.

Size-segregated ultrafine particles from motor vehicles were investigated in the Craeybeckx tunnel (E19 motorway, Antwerp, Belgium) at two measurement sites, at 100 and 300 m inside the tunnel, respectively, during March 2008. It was observed that out of the three size modes, nucleation, Aitken, and accumulation, Aitken mode was the most dominant size fraction inside the tunnel. The diurnal variation in ultrafine particle (UFP) levels closely follows the vehicular traffic inside the tunnel, which was maximum during office rush hours, both in the morning and evening and minimum during night-time around 3 am. The tunnel data showed very high growth rates in comparison with free atmosphere. The average condensation sink during the growth period was 14.1-17.3 × 10(-2) s(-1). The average growth rate (GR) of geometric mean diameter was found to be 18.6 ± 2.45 nm h(-1). It was observed that increase in Aitken mode was related to the numbers of heavy-duty vehicles (HDV), as they emit mainly in the Aitken mode. The higher Aitken mode during traffic jams correlated well with HDV numbers. At the end of the tunnel, sudden dilution leading to fast coagulation was responsible for the sudden drop in the UFP number concentration.

Perceived health status associated with transport choice for short distance trips.

BACKGROUND: This study examines the association between active transport and perceived general health, perceived psychological wellbeing and a healthy body weight in the Netherlands. METHODS: Data were collected by an online questionnaire (N = 3663) in the Netherlands. Data collection was conducted over a period of one calendar year starting July 2012. Logistic regression analyses were used to investigate the association between choice of transport mode (bicycling vs car use and walking vs car use) and perceived general health, perceived psychological wellbeing and having a healthy weight respectively. The presented OR's may be interpreted as the likelihood of an average person in our dataset to have a better perceived health or body weight when choosing active transport (either bicycling or walking) over using the car for trips up to 7.5 km. RESULTS: Cycling was found to be significantly associated with a better perceived general health (OR = 1.35, 95%CI:1.07-1.70) and having a healthy body weight (OR = 1.52, 95%CI:1.28-1.79), but not with a better perceived psychological wellbeing (OR = 1.12, 95%CI:0.93-1.34). Walking was found to be significantly associated with having a healthy body weight (OR = 1.35, 95%CI:1.09-1.69), but not with a better perceived general (OR = 1.12, 95%CI:0.84-1.51) or psychological wellbeing (OR = 0.85, 95%CI:0.67-1.08). CONCLUSION: Our results suggest that active transport use has been associated with a better perceived general health and a healthy body weight. However, more research is needed to be able to elucidate which factors cause this better health. No associations were observed between transport choice and perceived psychological wellbeing.

Negative effects of ultrafine particle exposure during forced exercise on the expression of Brain-Derived Neurotrophic Factor in the hippocampus of rats.

Exercise improves cognitive function, and Brain-Derived Neurotrophic Factor (BDNF) plays a key role in this process. We recently reported that particulate matter (PM) exposure negatively contributed to the exercise-induced increase in human serum BDNF concentration. Furthermore, PM exposure is associated with neuroinflammation and cognitive decline. The aim of this study was to investigate the effect of exposure to ultrafine particles (UFP) during a single bout of forced exercise on the expression of inflammatory (IL1α, IL1ß, TNF, IL6, NOS2, NOS3) and oxidative stress (NFE2L2)-related genes, as well as BDNF in the brain of rats. Four groups (n=6/group) of Wistar rats were exposed for 90 min to one of the following exposure regimes: UFP+exercise, UFP+rest, ambient air+exercise, ambient air+rest (control). Hippocampus, olfactory bulb and prefrontal cortex were collected 24h after exposure. Gene expression changes were analyzed with real-time PCR. In the condition ambient air+exercise, hippocampal expression of BDNF and NFE2L2 was up-regulated, while the expression of IL1α and NOS3 in the prefrontal cortex and IL1α in the olfactory bulb was down-regulated compared to the control. In contrast, gene expression in the condition UFP+exercise did not differ from the control. In the condition UFP+rest, hippocampal expression of NFE2L2 was down-regulated and there was a trend toward down-regulation of BDNF expression compared to the control. This study shows a negative effect of UFP exposure on the exercise-induced up-regulation of BDNF gene expression in the hippocampus of rats.

No exercise-induced increase in serum BDNF after cycling near a major traffic road.

Commuting by bike has a clear health enhancing effect. Moreover, regular exercise is known to improve brain plasticity, which results in enhanced cognition and memory performance. Animal research has clearly shown that exercise upregulates brain-derived neurotrophic factor (BDNF - a neurotrophine) enhancing brain plasticity. Studies in humans found an increase in serum BDNF concentration in response to an acute exercise bout. Recently, more evidence is emerging suggesting that exposure to air pollution (such as particulate matter (PM)) is higher in commuter cyclists compared to car drivers. Furthermore, exposure to PM is linked to negative neurological effects, such as neuroinflammation and cognitive decline. We carried-out a cross-over experiment to examine the acute effect of exercise on serum BDNF, and the potential effect-modification by exposure to traffic-related air pollution. Thirty eight physically fit, non-asthmatic volunteers (mean age: 43, 26% women) performed two cycling trials, one near a major traffic road (Antwerp Ring, R1, up to 260,000 vehicles per day) and one in an air-filtered room. The air-filtered room was created by reducing fine particles as well as ultrafine particles (UFP). PM10, PM2.5 and UFP were measured. The duration (∼20min) and intensity of cycling were kept the same for each volunteer for both cycling trials. Serum BDNF concentrations were measured before and 30min after each cycling trial. Average concentrations of PM10 and PM2.5 were 64.9µg/m(3) and 24.6µg/m(3) in cycling near a major ring way, in contrast to 7.7µg/m(3) and 2.0µg/m(3) in the air-filtered room. Average concentrations of UFP were 28,180 particles/cm(3) along the road in contrast to 496 particles/cm(3) in the air-filtered room. As expected, exercise significantly increased serum BDNF concentration after cycling in the air-filtered room (+14.4%; p=0.02). In contrast, serum BDNF concentrations did not increase after cycling near the major traffic route (+0.5%; p=0.42). Although active commuting is considered to be beneficial for health, this health enhancing effect could be negatively influenced by exercising in an environment with high concentrations of PM. Whether this effect is also present with chronic exercise and chronic exposure must be further elucidated.

Exposure assessment of a cyclist to PM10 and ultrafine particles.

Estimating personal exposure to air pollution is a crucial component in identifying high-risk populations and situations. It will enable policy makers to determine efficient control strategies. Cycling is again becoming a favorite mode of transport both in developing and in developed countries due to increasing traffic congestion and environmental concerns. In Europe, it is also seen as a healthy sports activity. However, due to high levels of hazardous pollutants in the present day road microenvironment the cyclist might be at a higher health risk due to higher breathing rate and proximity to the vehicular exhaust. In this paper we present estimates of the exposure of a cyclist to particles of various size fractions including ultrafine particles (UFP) in the town of Mol (Flanders, Belgium). The results indicate relatively higher UFP concentration exposure during morning office hours and moderate UFP levels during afternoon. The major sources of UFP and PM(10) were identified, which are vehicular emission and construction activities, respectively. We also present a dust mapping technique which can be a useful tool for town planners and local policy makers.

[The chromosomal polymorphism and divergence of populations in Chironomus nuditarsis Str. (Diptera, Chironomidae)].

The karyotype structure and chromosomal polymorphisms were investigated in 6 natural and 2 laboratory populations of Chironomus nuditarsis from Europe and Asia. The pool of rearranged polytene chromosome banding sequences of this species was determined that includes 16 inversion banding sequences and sequences with giant DNA-knobs (ndtG1k, ndtG2k). Obvious differences were demonstrated in the level of chromosomal polymorphism between European and Asian (Siberian) populations: the former were highly polymorphic, while the latter were practically monomorphic. It was suggested to consider the Siberian populations as marginal one. Cytogenetic distances between populations of C. nuditarsis as well between C. nuditarsis and the related species C. plumosus were estimated. The data obtained show that chromosomal rearrangements play a very important role in cytogenetic divergence of populations.

An uncertainty analysis of air pollution externalities from road transport in Belgium in 2010.

Although stricter standards for vehicles will reduce emissions to air significantly by 2010, a number of problems will remain, especially related to particulate concentrations in cities, ground-level ozone, and CO(2). To evaluate the impacts of new policy measures, tools need to be available that assess the potential benefits of these measures in terms of the vehicle fleet, fuel choice, modal choice, kilometers driven, emissions, and the impacts on public health and related external costs. The ExternE accounting framework offers the most up to date and comprehensive methodology to assess marginal external costs of energy-related pollutants. It combines emission models, air dispersion models at local and regional scales with dose-response functions and valuation rules. Vito has extended this accounting framework with data and models related to the future composition of the vehicle fleet and transportation demand to evaluate the impact of new policy proposals on air quality and aggregated (total) external costs by 2010. Special attention was given to uncertainty analysis. The uncertainty for more than 100 different parameters was combined in Monte Carlo simulations to assess the range of possible outcomes and the main drivers of these results. Although the impacts from emission standards and total fleet mileage look dominant at first, a number of other factors were found to be important as well. This includes the number of diesel vehicles, inspection and maintenance (high-emitter cars), use of air conditioning, and heavy duty transit traffic.