Background: The dichotomization or categorization of rural-urban codes, as nominal variables, is a prevailing paradigm in cancer disparity studies. The paradigm represents continuous rural-urban transition as discrete groups, which results in a loss of ordering information and landscape continuum, and thus may contribute to mixed findings in the literature. Few studies have examined the validity of using rural-urban codes as continuous variables in the same analysis. Methods: We geocoded cancer cases in north central Florida between 2005 and 2010 collected by Florida Cancer Data System. Using a linear hierarchical model, we regressed the occurrence of late stage cancer (including breast, colorectal, hematological, lung, and prostate cancer) on the rural-urban codes as continuous variables. To validate, the results were compared to those from using a truly continuous rurality data of the same study region. Results: In term of associations with late-stage cancer risk, the regression analysis showed that the use of rural-urban codes as continuous variables produces consistent outcomes with those from the truly continuous rurality for all types of cancer. Particularly, the rural-urban codes at the census tract level yield the closest estimation and are recommended to use when the continuous rurality data is not available. Conclusions: Methodologically, it is valid to treat rural-urban codes directly as continuous variables in cancer studies, in addition to converting them into categories. This proposed continuous-variable method offers researchers more flexibility in their choice of analytic methods and preserves the information in the ordering. It can better inform how cancer risk varies, degree by degree, over a finer spectrum of rural-urban landscape.

Extensive, severe wildfires, and wildfire‐induced smoke occurred across the western and central United States since August 2020. Wildfires resulting in the loss of habitats and emission of particulate matter and volatile organic compounds pose serious threatens to wildlife and human populations, especially for avian species, the respiratory system of which are sensitive to air pollutions. At the same time, the extreme weather (e.g., snowstorms) in late summer may also impact bird migration by cutting off their food supply and promoting their migration before they were physiologically ready. In this study, we investigated the environmental drivers of massive bird die‐offs by combining socioecological earth observations data sets with citizen science observations. We employed the geographically weighted regression models to quantitatively evaluate the effects of different environmental and climatic drivers, including wildfire, air quality, extreme weather, drought, and land cover types, on the spatial pattern of migratory bird mortality across the western and central US during August‐September 2020. We found that these drivers affected the death of migratory birds in different ways, among which air quality and distance to wildfire were two major drivers. Additionally, there were more bird mortality events found in urban areas and close to wildfire in early August. However, fewer bird deaths were detected closer to wildfires in California in late August and September. Our findings highlight the important impact of extreme weather and natural disasters on bird biology, survival, and migration, which can provide significant insights into bird biodiversity, conservation, and ecosystem sustainability.

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The year 2020 saw the confluence of two major crises, that is, the COVID-19 pandemic and the extensive, severe wildfires in August-September, impacting people's health and wellbeing in western and central United States. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), commonly known as COV-ID-19, was initially detected in Wuhan, China, and has widely spread across the globe (Zhu et al., 2020). On

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