In less‐developed countries, the lack of granular data limits the researcher's ability to study the spatial interaction of different factors on the COVID‐19 pandemic. This study designs a novel database to examine the spatial effects of demographic and population health factors on COVID‐19 prevalence across 640 districts in India. The goal is to provide a robust understanding of how spatial associations and the interconnections between places influence disease spread. In addition to the linear Ordinary Least Square regression model, three spatial regression models—Spatial Lag Model, Spatial Error Model, and Geographically Weighted Regression are employed to study and compare the variables explanatory power in shaping geographic variations in the COVID‐19 prevalence. We found that the local GWR model is more robust and effective at predicting spatial relationships. The findings indicate that among the demographic factors, a high share of the population living in slums is positively associated with a higher incidence of COVID‐19 across districts. The spatial variations in COVID‐19 deaths were explained by obesity and high blood sugar, indicating a strong association between pre‐existing health conditions and COVID‐19 fatalities. The study brings forth the critical factors that expose the poor and vulnerable populations to severe public health risks and highlight the application of geographical analysis vis‐a‐vis spatial regression models to help explain those associations.
This paper evaluates the efficiency of existing pedestrian facilities in Ludhiana, Punjab (India) using the Pedestrian Level of Service (PLOS) model. Assessment of the PLOS is essential in analysing the factors that lead to pedestrian congestion in the city. The study focuses on the major junctions and the city’s core and is limited to Ludhiana considering the population projection and the proposed Land use. The paper is an exploratory study that collects and analyses data from primary and secondary sources. Primary studies included on-site observations and surveys such as user evaluation survey and pedestrian volume count, interviews, and discussions with domain experts and residents on pedestrian facilities’ problems. The approach is intended to assist Urban Planners and Transportation Engineers in making informed decisions when designing road cross-sections that satisfy pedestrians’ basic need and assess and prioritise the needs of existing roadways for sidewalk retrofit development. Further, this study can be used as a benchmark for pedestrianizing the other congested streets and intersections.
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