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Several associations between the built environment and COVID-19 case distribution have been identified in previous studies. However, few studies have explored the non-linear associations between the built environment and COVID-19 at the community level. This study employed the March 2022 Shanghai COVID-19 pandemic as a case study to examine the association between built-environment characteristics and the incidence of COVID-19. A non-linear modeling approach, namely the boosted regression tree model, was used to investigate this relationship. A multi-scale study was conducted at the community level based on buffers of 5-minute, 10-minute, and 15-minute walking distances. The main findings are as follows: (1) Relationships between built environment variables and COVID-19 case distribution vary across scales of analysis at the neighborhood level. (2) Significant non-linear associations exist between built-environment characteristics and COVID-19 case distribution at different scales. Population, housing price, normalized difference vegetation index, Shannon's diversity index, number of bus stops, floor–area ratio, and distance from the city center played important roles at different scales. These non-linear results provide a more refined reference for pandemic responses at different scales from an urban planning perspective and offer useful recommendations for a sustainable COVID-19 post-pandemic response. [ABSTRACT FROM AUTHOR]

The year 2023 marks the 100th commemoration of the disastrous Kanto Earthquake in Japan, which shattered the urban fabric of Tokyo and other southern prefectures. In the years following 1923, much research into disaster risk reduction (especially fire prevention) was undertaken. This study evaluated research trends and the impact of the earthquake on the city using metropolitan population data. The following is reported: (1) This study summarized English and Japanese academic papers and reports on the Great Kanto Earthquake that have been published over the last 100 years. (2) The area of fire spread and number of damaged buildings in Tokyo due to the Great Kanto Earthquake were overwhelmingly larger than those in other areas. (3) The difference in the relative amount of damage caused by natural disasters with more than 1,000 death toll to the annual national budget in Japan became clear. (4) The Great Kanto Earthquake was the only natural disaster that caused a net worth of damage exceeding the Japanese national budget by 3.8 times. (5) The expansion of the Tokyo metropolitan area over the 100 years since the Great Kanto Earthquake was visually clarified based on demographics. (6) Today, many people live densely on soft ground, with an amplification factor of 1.8 or higher, which is 23.0% of the total population. [ABSTRACT FROM AUTHOR]

Open data is a practical source for identifying disaster risks. However, few studies have examined open data usage. This study employed CiteSpace to conduct a bibliometric analysis to determine the evolution of open data in the field of disaster risk based on the literature. The findings were as follows: first, the existing disaster-related research can be classified into four categories: introduction to risk management and its concepts, multi-hazard response, studies on the specific background or context, and analysis of the technology or methods used in disaster risk reduction. Second, the relevant literature first emerged in 1997 and has rapidly expanded in recent years. Top keywords were identified, such as "natural disaster," "risk," and "climate change." Third, the most productive country in terms of publications has been the People's Republic of China; however, the low centrality indicates a lack of international collaborations. Fourth, several bursts were found in the collected literature. The term "data analysis" appears to be one of the most pressing concerns. Finally, we identified the research frontiers. The topic "accessible global dataset" has been of primary interest to researchers recently. The results of this study can provide directional references for future research in the field. [ABSTRACT FROM AUTHOR]

In Yangon and the suburbs of Myanmar, timber-framed buildings are the popular choice of construction for residential purposes. Nearly 8% of the total population in Yangon live in the slums and slum-like areas where the dwellings are predominantly made of non-durable materials. Wood, jungle wood, and bamboo are used as the framework and corrugated galvanized iron sheets as walling and sheathing material. The seismic-resistance capacity of timber buildings in slum areas has never been approved based on experimental evidence. Therefore, this study aims to conduct a seismic fragility analysis for poorly built timber buildings by providing a suitable method through numerical and experimental approaches. Pull-over loading tests were conducted on selected buildings to assess their loading-displacement capacity. Further, numerical modeling was done using the Wallstat simulation tool, which is based on the discrete element method. The pushover curve was validated with the curve from the pull-over load test. Once the numerical model was confirmed, dynamic analysis was conducted for different peak ground acceleration (PGA) (g) values until the complete numerical collapse of the building. Three building configurations with three ranges of variable material properties were considered in this study. A primary damage state started at the low PGA value of 0.05 g, and it can be confirmed that the timber buildings that were studied, are vulnerable to earthquakes. The results based on qualitative analysis were accumulated to obtain the damage state matrix, which was then used to obtain the fragility curves. [ABSTRACT FROM AUTHOR]

Myanmar is a thriving country in Southeast Asia and is facing future earthquake risks caused by the Sagaing Fault. Under these circumstances, Yangon must implement earthquake risk reduction measures in future development. Applying the building collapse risk evaluation method proposed by the Tokyo Metropolitan Government, and analyzing current and future urban conditions of Yangon City based on available datasets, this study aimed to (1) evaluate present urban vulnerability focusing on building collapse risk, (2) clarify its future expansion tendency based on residential area development conditions from 2004 to 2018, and (3) estimate future building collapse risk in terms of future urban expansion limitation with urban function and building vulnerability in order to obtain useful information on earthquake risk reduction for future development in Yangon. Mainly, this research clarified as follows: (1) The inventory provided by YCDC (Yangon City Development Committee) showed that wooden buildings and RC accounted for 93.8% of all buildings in Yangon. (2) In order to understand the present urban vulnerability of Yangon based on the Tokyo Metropolitan Government's method, 567 objective wards were categorized into five ranks according to the building collapse risk value. It indicated that building collapse risk in the Dawpon and Tharkayta Townships, located on the west side of Pazundaung Creek, were the highest. Some newly developed outskirts areas, such as Hlaingtharyar or Dala, also appeared as vulnerable with Ranks 4 and 5. (3) Yangon's urban development conditions from 2004 to 2018 were visually clarified. Then, the relationships between the number of buildings, residential district area, and population according to townships were analyzed to estimate future development. (4) Finally, two types of urban development scenarios were set: Scenario A based on urban expansion limitation and urban function, and Scenario B based on building vulnerability. Then, the future building collapse risk trend from 2014 until 2040 was estimated. It was found that the Sub-center System would deter future urban sprawl in the future more than the Super CBD Single-core System, and the number of damaged buildings can be reduced by 43.5% at most in Dagon Seikkan. [ABSTRACT FROM AUTHOR]

The 2004 Indian Ocean tsunami damaged a number of buildings in many Asian countries. The research objective of this paper is to determine the significant predictor variables and the direction of their relationships regarding the building damage level. This quantitative study used data collected by Murao and Nakazato ['Recovery curves for housing reconstruction in Sri Lanka after the 2004 Indian Ocean tsunami,' J. Earthquake Tsunami 4(2), 51-60; 'Vulnerability functions for buildings based on damage survey data in Sri Lanka after the 2004 Indian Ocean Tsunami,' Proc. 1st Int. Conf. Sustainable Built Environment, Kandy, Sri Lanka, pp. 371-378] in Sri Lanka for analysis via the statistical approach. The tested explanatory parameters included the inundation depth, the structural materials, and the areas. This research is among the first pioneering efforts in applying the statistical analysis to investigate the influential parameters in tsunami damage areas. This work can contribute to the damage analysis research area in terms of providing the proved parameters as well as contributing to the practical understanding of urban planners, engineers, and related persons who are involved in building construction and disaster management. [ABSTRACT FROM AUTHOR]

On the 26th of December 2004, the Tsunami damaged to five provinces in Sri Lanka and more than 40,000 people were displaced, lost, or killed within a short time. After the tsunami, the Government provided three types of houses for the victims (temporary shelters, transitional houses, and permanent houses). The authors conducted several field surveys and interviews in the damaged area to investigate the recovery conditions, and obtained dataset, which had been collected for 13 months since December 2004 by Rebuilding and Development Agency. It shows the construction status of transitional house and permanent house in the damaged areas. This paper demonstrates recovery curves for the transitional houses and the permanent houses. With the aim of constructing post-earthquake recovery curves for Sri Lanka, the factors of time (months) and completion ratio of building construction are used. The obtained curves quantitatively clarify the regional differences in the completion dates and processes of construction. The proposed quantitative methodology will be used for other damaged countries due to the 2004 Indian Ocean Tsunami. It means that this kind of analysis is essential for investigating post-disaster recovery process because it enables comparative studies of urban/rural planning among different types of post-disaster recovery processes throughout the world. [ABSTRACT FROM AUTHOR]