A key policy measure introduced by governments worldwide at the beginning of the coronavirus disease 2019 (COVID-19) pandemic was to restrict travel, highlighting the importance of people's mobility as one of the key contributors to spreading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there was little consistency regarding the geographical scale or the severity of these measures. Little use was made of commuting and travel data to inform decisions on when, where and at what level restrictions should be applied. We aim to contribute to regional policy by providing evidence that could be used to inform future policy debates on the most effective travel restrictions to impose during a pandemic. We present an analysis of the impact of mobility between municipalities on COVID-19 incidence in the Netherlands. We used multiple linear regression models and geographical information systems to gain insight into the association between mobility-related factors and demographic, socio-economic and geographical factors with COVID-19 incidence in municipalities. Our results indicate that spatial mobility patterns, when combined with COVID-19 incidence in municipalities of origin, were associated with increased COVID-19 incidence in municipalities of destination. In addition, various regional characteristics were associated with municipal incidence. By conducting our analyses over three different periods, we highlight the importance of time for COVID-19 incidence. In the light of ongoing mitigation measures (and possible future events), spatial mobility patterns should be a key factor in exploring regional mobility restrictions as an alternative for national lockdowns.
DOCUMENT
Background: Development of more effective interventions for nonspecific chronic low back pain (LBP), requires a robust theoretical framework regarding mechanisms underlying the persistence of LBP. Altered movement patterns, possibly driven by pain-related cognitions, are assumed to drive pain persistence, but cogent evidence is missing. Aim: To assess variability and stability of lumbar movement patterns, during repetitive seated reaching, in people with and without LBP, and to investigate whether these movement characteristics are associated with painrelated cognitions. Methods: 60 participants were recruited, matched by age and sex (30 back-healthy and 30 with LBP). Mean age was 32.1 years (SD13.4). Mean Oswestry Disability Index-score in LBP-group was 15.7 (SD12.7). Pain-related cognitions were assessed by the ‘Pain Catastrophizing Scale’ (PCS), ‘Pain Anxiety Symptoms Scale’ (PASS) and the task-specific ‘Expected Back Strain’ scale(EBS). Participants performed a seated repetitive reaching movement (45 times), at self-selected speed. Lumbar movement patterns were assessed by an optical motion capture system recording positions of cluster markers, located on the spinous processes of S1 and T8. Movement patterns were characterized by the spatial variability (meanSD) of the lumbar Euler angles: flexion-extension, lateralbending, axial-rotation, temporal variability (CyclSD) and local dynamic stability (LDE). Differences in movement patterns, between people with and without LBP and with high and low levels of pain-related cognitions, were assessed with factorial MANOVA. Results: We found no main effect of LBP on variability and stability, but there was a significant interaction effect of group and EBS. In the LBP-group, participants with high levels of EBS, showed increased MeanSDlateral-bending (p = 0.004, η2 = 0.14), indicating a large effect. MeanSDaxial-rotation approached significance (p = 0.06). Significance: In people with LBP, spatial variability was predicted by the task-specific EBS, but not by the general measures of pain-related cognitions. These results suggest that a high level of EBS is a driver of increased spatial variability, in participants with LBP.
DOCUMENT
Literature highlights the need for research on changes in lumbar movement patterns, as potential mechanisms underlying the persistence of low-back pain. Variability and local dynamic stability are frequently used to characterize movement patterns. In view of a lack of information on reliability of these measures, we determined their within- and between-session reliability in repeated seated reaching. Thirty-six participants (21 healthy, 15 LBP) executed three trials of repeated seated reaching on two days. An optical motion capture system recorded positions of cluster markers, located on the spinous processes of S1 and T8. Movement patterns were characterized by the spatial variability (meanSD) of the lumbar Euler angles: flexion–extension, lateral bending, axial rotation, temporal variability (CyclSD) and local dynamic stability (LDE). Reliability was evaluated using intraclass correlation coefficients (ICC), coefficients of variation (CV) and Bland-Altman plots. Sufficient reliability was defined as an ICC ≥ 0.5 and a CV < 20%. To determine the effect of number of repetitions on reliability, analyses were performed for the first 10, 20, 30, and 40 repetitions of each time series. MeanSD, CyclSD, and the LDE had moderate within-session reliability; meanSD: ICC = 0.60–0.73 (CV = 14–17%); CyclSD: ICC = 0.68 (CV = 17%); LDE: ICC = 0.62 (CV = 5%). Between-session reliability was somewhat lower; meanSD: ICC = 0.44–0.73 (CV = 17–19%); CyclSD: ICC = 0.45–0.56 (CV = 19–22%); LDE: ICC = 0.25–0.54 (CV = 5–6%). MeanSD, CyclSD and the LDE are sufficiently reliable to assess lumbar movement patterns in single-session experiments, and at best sufficiently reliable in multi-session experiments. Within-session, a plateau in reliability appears to be reached at 40 repetitions for meanSD (flexion–extension), meanSD (axial-rotation) and CyclSD.
MULTIFILE
Supermarkets are essential urban household amenities, providing daily products, and for their social role in communities. Contrary to many other countries, including nearby ones, the Netherlands have a balanced distribution of supermarkets across villages and urban neighbourhoods. However, spatial supermarket patterns, are subject to influential developments. First, due to economies of scale, there is a tendency for supermarkets to increase their catchment areas and to disappear from peripheral villages. Second, supermarkets are now mainly located in residential areas, although the urban periphery appears to be attractive for the retail sector, perhaps including the rise of hypermarkets. Third, today, online grocery shopping is still lagging far behind on other online shopping products, but a breaks through will dilute population support for in-store supermarkets and can lead to dramatic ‘game changer’ shifts with major spatial and social effects. These three important trends will reinforce each other. Consequences are of natural community meeting places at the expense of social cohesion; reduced accessibility for daily products, leading to more travel, often by car; increasing delivery flows; real estate vacancies, and increasing suburban demand increase for retail and logistics. Expected changes in supermarket patterns require understanding, but academic literature on OGS is still scarce, and does hardly address household behaviour in changing spatial constellations. We develop likely spatial supermarket patterns, and model the consequences for travel demand, social cohesion and real estate demand, as well as the distribution between online and in-store grocery shopping, by developing a stated preference experiment, among Dutch households.
The reclaiming of street spaces for pedestrians during the COVID-19 pandemic, such as on Witte de Withstraat in Rotterdam, appears to have multiple benefits: It allows people to escape the potentially infected indoor air, limits accessibility for cars and reduces emissions. Before ordering their coffee or food, people may want to check one of the many wind and weather apps, such as windy.com: These apps display the air quality at any given time, including, for example, the amount of nitrogen dioxide (NO2), a gas responsible for an increasing number of health issues, particularly respiratory and cardiovascular diseases. Ships and heavy industry in the nearby Port of Rotterdam, Europe’s largest seaport, exacerbate air pollution in the region. Not surprisingly, in 2020 Rotterdam was ranked as one of the unhealthiest cities in the Netherlands, according to research on the health of cities conducted by Arcadis. Reducing air pollution is a key target for the Port Authority and the City of Rotterdam. Missing, however, is widespread awareness among citizens about how air pollution links to socio-spatial development, and thus to the future of the port city cluster of Rotterdam. To encourage awareness and counter the problem of "out of sight - out of mind," filmmaker Entrop&DeZwartFIlms together with ONSTV/NostalgieNet, and Rotterdam Veldakademie, are collaborating with historians of the built environment and computer science and public health from TU Delft and Erasmus University working on a spatial data platform to visualize air pollution dynamics and socio-economic datasets in the Rotterdam region. Following discussion of findings with key stakeholders, we will make a pilot TV-documentary. The documentary, discussed first with Rotterdam citizens, will set the stage for more documentaries on European and international cities, focusing on the health effects—positive and negative—of living and working near ports in the past, present, and future.
