In opdracht van het ministerie van Binnenlandse Zaken en Koninkrijksrelaties heeft het lectoraat Changing Role of Europe van De Haagse Hogeschool de rol van de Dutch Urban Envoy geëvalueerd. De betekenis, de inzet, het vervolg en de toekomstige invulling van de rol van de Dutch Urban Envoy komen aan bod. Op basis van de inzichten van 37 interviews met 39 betrokken partijen (van het Ministerie van BZK, Nederlandse steden, Europese steden, koepelorganisaties, Europese instellingen en andere ministeries binnen de Rijksoverheid) en deskresearch zijn de volgende conclusies en aanbevelingen geformuleerd.
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The crossroads of living in cities on the one hand and ageing of the population on the other is studied in an interdisciplinary field of research called urban ageing (van Hoof and Kazak 2018, van Hoof et al. 2018). People live longer and in better health than ever before in Europe. Despite all the positive aspects of population ageing, it poses many challenges. The interaction of population ageing and urbanisation raises issues in various domains of urban living (Phillipson and Buffel 2016). According to the Organisation for Economic Co-operation and Development (OECD 2015), the population share of those of 65 years old is expected to climb to 25.1% in 2050 in its member states. Cities in particular have large numbers of older inhabitants and are home to 43.2% of this older population. The need to develop supportive urban communities are major issues for public policy to understand the relationship between population ageing and urban change (Buffel and Phillipson 2016). Plouffe and Kalache (2010) see older citizens as a precious resource, but in order to tap the full potential these people represent for continued human development (Zaidi et al. 2013), the world’s cities must ensure their inclusion and full access to urban spaces, structures, and services. Therefore, cities are called upon to complement the efforts of national governments to address the consequences of the unprecedented demographic shift (OECD 2015). Additionally, at the city level there is a belief to understand the requirements and preferences of local communities (OECD 2015). An important question in relation to urban ageing is what exactly makes a city age-friendly (Alley et al. 2007, Lui et al. 2009, Plouffe and Kalache 2010, Steels 2015, Moulaert and Garon 2016, Age Platform Europe 2018)? Another relevant question is which factors allow some older people in cities to thrive, while others find it hard to cope with the struggles of daily life? This chapter explores and describes which elements and factors make cities age-friendly, for instance, on the neighbourhood level and in relation to technology for older people.
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Abstract Background: COVID-19 was first identified in December 2019 in the city of Wuhan, China. The virus quickly spread and was declared a pandemic on March 11, 2020. After infection, symptoms such as fever, a (dry) cough, nasal congestion, and fatigue can develop. In some cases, the virus causes severe complications such as pneumonia and dyspnea and could result in death. The virus also spread rapidly in the Netherlands, a small and densely populated country with an aging population. Health care in the Netherlands is of a high standard, but there were nevertheless problems with hospital capacity, such as the number of available beds and staff. There were also regions and municipalities that were hit harder than others. In the Netherlands, there are important data sources available for daily COVID-19 numbers and information about municipalities. Objective: We aimed to predict the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants per municipality in the Netherlands, using a data set with the properties of 355 municipalities in the Netherlands and advanced modeling techniques. Methods: We collected relevant static data per municipality from data sources that were available in the Dutch public domain and merged these data with the dynamic daily number of infections from January 1, 2020, to May 9, 2021, resulting in a data set with 355 municipalities in the Netherlands and variables grouped into 20 topics. The modeling techniques random forest and multiple fractional polynomials were used to construct a prediction model for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants per municipality in the Netherlands. Results: The final prediction model had an R2 of 0.63. Important properties for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants in a municipality in the Netherlands were exposure to particulate matter with diameters <10 μm (PM10) in the air, the percentage of Labour party voters, and the number of children in a household. Conclusions: Data about municipality properties in relation to the cumulative number of confirmed infections in a municipality in the Netherlands can give insight into the most important properties of a municipality for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants in a municipality. This insight can provide policy makers with tools to cope with COVID-19 and may also be of value in the event of a future pandemic, so that municipalities are better prepared.
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