An Exploratory Analysis of Housing and the Distribution of COVID-19 in Sweden

The impact of COVID-19 on various aspects of our life is evident. Proximity and close contact with individuals infected with the virus, and the extent of such contact, contribute to the intensity of the spread of the virus. Healthy and infected household members who both require sanctuary and quarantine space come into close and extended contact in housing. In other words, housing and living conditions can impact the health of occupants and the spread of COVID-19. This study investigates the relationship between housing characteristics and variations in the spread of COVID-19 per capita across Sweden’s 290 municipalities. For this purpose, we have used the number of infected COVID-19 cases per capita during the pandemic period—February 2020 through April 2021—per municipality. The focus is on variables that measure housing and housing conditions in the municipalities. We use exploratory analysis and Principal Components Analysis to reduce highly correlated variables into a set of linearly uncorrelated variables. We then use the generated variables to estimate direct and indirect effects in a spatial regression analysis. The results indicate that housing and housing availability are important explanatory factors for the geographical spread of COVID-19. Overcrowding, availability, and quality are all critical explanatory factors.

Determinants of Development Achievements on District/City of Central Java in 2019

In 2019, Badan Perencanaan Pembangunan Nasional (Bappenas) awarded Central Java as the province with the best Perencanaan dan Pembangunan Daerah (PPD). However, if it is reviewed at the district/city level, it shows that there are still many areas that have low development achievements. In accordance with the United Nations Development Programme (UNDP) proposal, the Human Development Index (HDI) is used as an indicator of the achievement of district/city development whose calculations are good enough to describe development from both a social and economic perspective. The large difference in HDI between districts/cities in Central Java and the distribution of development achievements are still centered around the provincial capital, namely Semarang City, this indicates the occurrence of inequality in development achievements at the district/city level in Central Java. Because the observations in this study are districts/cities in Central Java, the linkage between district/city causes spatial autocorrelation. Therefore, spatial regression model is used to determine the model that has spatial autocorrelation. This study aims to determine the achievements of development and its determinants in the districts/cities of Central Java in 2019 using the spatial regression analysis method. From the results of the study, it is known that there is a dependence on development achievements between districts/cities in Central Java which is influenced by the regional capacity factor is characterized by PAD and economic growth; operational resource factors characterized by DAU, DAK and technology; and the level of poverty.

The Effect of Urban Form on PM2.5 Concentration: Evidence from China’s 340 Prefecture-Level Cities

Exploring how urban form affects the Particulate Matter 2.5 (PM2.5) concentration could help to find environmentally friendly urbanization. According to the definition of geography, this paper constructs a comprehensive urban form evaluation index system applicable to many aspects. Four urban form metrics, as well as road density and five control variables are selected. Based on 2015 data on China’s 340 prefecture-level cities, the spatial regression model and geographically weighted regression model were used to explore the relationship between the urban form evaluation index system and PM2.5 pollution. The main results show that the spatial distribution of PM2.5 in China follows an increasing trend from northwest to southeast. Urban form indicators such as AI, LPI, PLAND, LSI and road density were all significantly related to PM2.5 concentrations. More compact urban construction, lower fragmentation of urban land, and lower density of the road network are conducive factors for improving air quality conditions. In addition, affected by seasonal changes, the correlation between urban form and PM2.5 concentration in spring and winter is higher than that in summer and winter. This study confirmed that a reasonable urban planning strategies are very important for improving air quality.