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Large-scale installation of broad-spectrum (white) road lighting has been claimed to bring about a substantial reduction in road traffic collisions (RTCs). This confirmatory study estimates the effect on personal injury RTCs of a relighting programme that installed nearly 80,000 new white lamps, between the years 2005 and 2013, throughout the large UK city of Leeds. Time series of weekly RTC personal injury counts in 107 areas, within the city over nearly 9 years when its road lighting was almost completely relit, were analysed, using multilevel modelling. The background change in each area when and where no lighting was being changed was separated from that associated with when and where new replacement white lamps were installed by including a polynomial for the underlying time-trend. The key interest is how the installation of the new lamps affects the ratio of the rate of collisions occurring in darkness to those occurring in daylight. The measure sought is given by the daylight adjusted darkness collision rate ratio (CRR) for the specified amount of relighting, that is the factor by which the daylight adjusted collision rate changes by the specified change in lighting. The daylight adjusted darkness collision rate ratio (CRR) has a point estimate of 0.990 and a 95% confidence interval, CI (0.971, 1.010) for 100 replaced lamps; representing a range between a 3% reduction in the collision rate to a 1% increase. Using the series truncated at the end of 2011 that seems more trustworthy, gives a revised point estimate of 0.993 and a CI (0.971, 1.015). Both CIs include one, therefore no effect on road safety was detected. The CIs for any other number of lamps installed will also include one. Typically, the plausible range of road safety impact brought by the new white lamps for a typical area with 700 lamps, roughly spans 20% reduction to a 10% increase for the daylight adjusted darkness collision rate. No convincing evidence was found for an improvement (or detriment) in road safety by relighting with white lamps, despite the extensive, city-wide installation efforts and associated costs. [ABSTRACT FROM AUTHOR]

During the first year of the COVID-19 pandemic in Jakarta, Indonesia, the government designated some hospitals as specific COVID-19 healthcare centers to meet demand and ensure accessibility. However, the policy demand evaluation was based on a purely spatial approach. Studies on accessibility to healthcare are widely available, but those that consider temporal as well as spatial dynamics are lacking. This study aims to analyze the spatiotemporal dynamics of healthcare accessibility against COVID-19 cases within the first year of the COVID-19 pandemic, and the overall pattern of spatiotemporal accessibility. A two-step floating catchment area (2SFCA) was used to analyze the accessibility of COVID-19 healthcare against the monthly data of the COVID-19 infected population, as the demand. Such a spatiotemporal approach to 2SFCA has never been used in previous studies. Furthermore, rather than the traditional buffer commonly used to define catchments, the 2SFCA in this study was improved with automated delineation based on the road network using ArcGIS Service Areas Analysis tools. The accessibility tends to follow the distance decay principle, which is relatively high in the city's center and low in the outskirts. This contrasts with the city's population distribution, which is higher on the outskirts and lower in the center. This research is a step toward optimizing the spatial distribution of hospital locations to correspond with the severity of the pandemic condition. One method to stop the transmission of disease during a pandemic that requires localizing the infected patient is to designate specific healthcare facilities to manage the sick individuals. 'What-if' scenarios may be used to experiment with the locations of these healthcare facilities, which are then assessed using the methodology described in this work to obtain the distribution that is most optimal. [ABSTRACT FROM AUTHOR]

In this study, we examined temporal changes in the incidence of primary biliary cirrhosis (PBC) and investigated associations between PBC incidence and sociodemographic factors and spatial clustering. We included 982 patients aged ≥40 years from North East England with incident PBC diagnosed during 1987–2003. Age-standardized incidence rates with 95% confidence intervals were calculated. Negative binomial regression was used to analyze incidence and socioeconomic deprivation. Clustering analysis was performed using point process methods, testing the null hypothesis that disease risk does not vary spatially and that PBC cases occur independently. The age-standardized incidence rate was 53.50 per million persons per year (95% confidence interval: 48.65, 58.35) in 1987–1994 and 45.09 per million persons per year (95% confidence interval: 41.10, 49.07) in 1995–2003. Risk of PBC increased in areas with higher levels of socioeconomic deprivation (P = 0.035). More specifically, risk increased in areas with higher levels of overcrowded homes (P = 0.040), higher levels of households without cars (P < 0.001), and higher levels of non-owner-occupied homes (P < 0.001). Overall, there was evidence of spatial clustering (P = 0.001). The findings confirm that overall incidence of PBC did not rise over time, but sociodemographic variations suggest that certain aspects of deprivation are involved in its etiology. [ABSTRACT FROM PUBLISHER]