Urban densification in the Netherlands and its impact on mental health: An expert-based causal loop diagram.

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals' mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all.

Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing.

During the COVID-19 pandemic, contact tracing was used to identify individuals who had been in contact with a confirmed case so that these contacted individuals could be tested and quarantined to prevent further spread of the SARS-CoV-2 virus. Many countries developed mobile apps to find these contacted individuals faster. We evaluate the epidemiological effectiveness of the Dutch app CoronaMelder, where we measure effectiveness as the reduction of the reproduction number R. To this end, we use a simulation model of SARS-CoV-2 spread and contact tracing, informed by data collected during the study period (December 2020 - March 2021) in the Netherlands. We show that the tracing app caused a clear but small reduction of the reproduction number, and the magnitude of the effect was found to be robust in sensitivity analyses. The app could have been more effective if more people had used it, and if notification of contacts could have been done directly by the user and thus reducing the time intervals between symptom onset and reporting of contacts. The model has two innovative aspects: i) it accounts for the clustered nature of social networks and ii) cases can alert their contacts informally without involvement of health authorities or the tracing app.

Cohort profile: The Corona Behavioral Unit cohort, a longitudinal mixed-methods study on COVID-19-related behavior, well-being and policy support in the Netherlands.

This 'cohort profile' aims to provide a description of the study design, methodology, and baseline characteristics of the participants in the Corona Behavioral Unit cohort. This cohort was established in response to the COVID-19 pandemic by the Dutch National Institute for Public Health and the Environment (RIVM) and the regional public health services. The aim was to investigate adherence of and support for COVID-19 prevention measures, psychosocial determinants of COVID-19 behaviors, well-being, COVID-19 vaccination, and media use. The cohort also examined specific motivations and beliefs, such as for vaccination, which were collected through either closed-ended items or open text responses. In April 2020, 89,943 participants aged 16 years and older were recruited from existing nation-wide panels. Between May 2020 and September 2022, 99,676 additional participants were recruited through online social media platforms and mailing lists of higher education organizations. Participants who consented were initially invited every three weeks (5 rounds), then every six weeks (13 rounds), and since the summer of 2022 every 12 weeks (3 rounds). To date, 66% of participants were female, 30% were 39 years and younger, and 54% completed two or more questionnaires, with an average of 9.2 (SD = 5.7) questionnaires. The Corona Behavioral Unit COVID-19 cohort has published detailed insights into longitudinal patterns of COVID-19 related behaviors, support of COVID-19 preventive measures, as well as peoples' mental wellbeing in relation to the stringency of these measures. The results have informed COVID-19 policy making and pandemic communication in the Netherlands throughout the COVID-19 pandemic. The cohort data will continuously be used to examine COVID-19 related outcomes for scientific analyses, as well as to inform future pandemic preparedness plans.