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This study identifies determinants of the variation in depression resulting from COVID-19, specifies in detail the changes to daily life, and then compares the determinants' magnitude. The determinants were combined into three groups: first, the unpredictability of the disease and side effects by its response measures (specifically, restrictions on the freedom of movement and strain on social relationships); second, (mis)information through social media, public authorities, and mass media; and third, income reductions and other sociodemographic factors. Daily life changes were divided into four categories: travel/mobility, time at home (alone and with family), domestic activities (remote work, online shopping, food deliveries, reading, and online networking), and conflicts (with family and neighbors). We measured the total 29 predictors using data from the 2020 Seoul Survey, which is based on face-to-face interviews with a probability sample of adult residents. We made our estimations using partial least squares regression, which can analyze all original variables regardless of collinearity. The regression model found that major stressors include declines in out-of-home offline networking and the rise of domestic activities-and subsequent conflicts with family-restrictions on mobility (specifically, those of leisure travel), and income reductions. In contrast, changes to working and shopping (to remote work and online shopping) rather than leisure increased uses of private transportation modes. Moreover, we found influences of all forms of communications and media to be insignificant. We shall also provide a discussion on policy and academic implications of the findings.
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The social distancing policy is an effective way to prevent the spread of infectious diseases in the initial phase of their outbreak when medical evidence to support a particular course of treatment is deficient. While studies on the coronavirus disease 2019 (COVID-19) have mainly focused on the effects of specific measures (e.g., school and workplace closures and restrictions on movement), few investigated the characteristics of epidemic trends in response to the intensity of the policy and the amount of time required for policy measures to take effect. This study employs the SIRD (susceptible, infected, recovered, and deceased) model to analyze the COVID-19 epidemic trend according to the intensity of the social distancing policy in South Korea. The model reveals that the reproduction number began at 5.58 and fluctuated between 0.14 and 1.72 during the study period in accordance with different policy intensities. At the beginning of the social distancing policy, restrictions on public facility use were likely to have been effective in preventing the spread of COVID-19. When the intervention was relaxed, the transmission potential increased significantly. According to the reproduction number, social distancing policies prove to be effective after 13-19 days of implementation; however, as the pandemic progressed, this period extended from 13-14 to 18-19 days for the same effect. This suggests that governments need to consider not only the intensity of the social distancing policy, but also people's low responsiveness as the pandemic remains prevalent over time. It is also recommended they take preemptive action to ensure sufficient time for the policy to achieve its stated goal.
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With higher densities, urban agglomerations account for the fastest rates of COVID-19 transmission. In Indonesia, one of the most rapidly urbanizing regions in the world, the national government issues overall policy on the pandemic. However, implementation is often contingent on local governments. Many policies aim to stem the spread of infection by controlling people's mobility or regulating their daily activities. Urban agglomerations are a strategic site of investigation in this light, because they consist of interconnected communities governed by various levels and jurisdictions. This paper analyzes the effects of policy interventions relative to confirmed cases in the seven major urban agglomerations in Indonesia (totaling 30 municipal/district governments). Data were collected from confirmed and fatality trends from March to mid-October 2020, which were contrasted with corresponding policies for each jurisdiction. By sorting the indicators of the spread of the pandemic and its corresponding control measures, we reach conclusions about which dimensions served to curb or trigger the surge of COVID-19 clusters. The analysis unsurprisingly shows that within each agglomeration, the main cities continue to represent the highest number of confirmed cases despite variations between them. This study also highlights two key findings. First, the effectiveness of distancing measures depends considerably on the capacity of governments to implement restrictions. For example, budget limitations resulted in uneven implementation of national mandates by decentralized authority. Facilities and services at different locations also influence our understanding of disease transmission. Second, people's ability and willingness to engage with a policy regime is contingent upon personal values or economic constraints. The study shows that viewing the spatial distribution of COVID-19 at the scale of urban agglomerations helps to explain key aspects of transmission and policy, pointing to recommendations about pursuing certain protocols. Nevertheless, key challenges remain to meet the full potential of this analytical approach, due to relatively low levels of testing and inadequate data collection measures in Indonesia.
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Mini-solar photovoltaics, which are installed on apartment balconies, are rapidly spreading in Seoul, South Korea. Seoul has implemented a policy to diffuse mini-solar photovoltaics in apartments for energy transition since 2012. The policy considers compact land use and a large population of the city. This study examines a variety of variables in relation to the adoption of mini-solar photovoltaics. In particular, we focus on peer effects, namely, those of spatially adjacent, previously installed mini-solar photovoltaics. As apartment characteristics, four variables are selected to assess both within and between apartment complexes: one for the density of adopters as a within-complex variable and three for the number of adopters in the 500 m, 1 km, and 1.5 km radius of apartment complexes as between-complex variables. A major finding is that peer effects significantly contribute to the new adoption of mini-solar photovoltaics. Implications of this finding are discussed in an urban context.
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Seúl , Ciudades , República de CoreaRESUMEN
Due to the rapid ageing of the population, the number of traffic accidents involving elderly drivers has dramatically increased in Northeast Asia countries including South Korea. In order to ensure the mobility of elderly drivers and prevent the risk of accidents, it is necessary to consider various factors, which may affect elderly drivers while driving in urban areas. The primary goal of this study is to examine the characteristics of elderly drivers' traffic accidents in urban areas using spatial econometrics models. The study reveals that the highly populated areas (e.g. commercial areas, employment centres, and subway station catchment areas) have a higher risk of accidents involving elderly drivers. Also, due to an increase in cognitive response time and physical ageing of the elderly, the factors which represent complex driving condition for elderly drivers (e.g. traffic islands, intersections, and school zones) are found to be positively associated with the risk of accidents.