Emerging and Chronic Diseases: Application of Geospatial Approach

Emerging public health crises (e.g., the coronavirus disease 2019 (COVID-19) pandemic) disproportionately impact certain populations, such as racial/ethnic minority groups and individuals having comorbidities (e.g., obesity, diabetes, and heart diseases). Recent studies emphasize that neighborhood social environment plays a key role shaping disparities in emerging and chronic diseases in the US and around the globe. Specifically, neighborhood research focusing on neighborhood characteristics include built or physical environment, neighborhood socioeconomic status (SES), neighborhood segregation, poverty, and violence. There is a small but growing interest in applying geospatial methods, such as geographic information systems (GIS) and global positioning systems (GPS) to quantify exposure to neighborhood characteristics, and their links to emerging and chronic diseases. Analyses using geospatial methods (e.g., geographically weighted regression (GWR) and spatial scan statistics) allow researchers to identify certain geographic areas where emerging and chronic diseases originate and cluster. Thus, research applying geospatial methods can also be beneficial for public health policy makers and practitioners to take advantage of these methods. Findings of such analyses can help to facilitate and develop more geospatially oriented screenings and prevention activities.  

 

This Special Issue emphasizes specific research topics including the application of geospatial methods, such as GIS/GPS technologies and GWR analyses, as well as traditional objective and subjective (perceived) exposure assessment on neighborhood social contexts, such as neighborhood SES, poverty, neighborhood racial composition, built or physical environment, and social cohesion. This issue focuses on both emerging (COVID-19) and chronic diseases (e.g., obesity, diabetes, cardiovascular disease, cancers). Especially, COVID-19 can serve as an outcome in relation to neighborhood social environment, or a confounder to investigate how exposure to neighborhood social environment impacts chronic diseases. We encourage longitudinal studies examining cause–effect; however, we also accept studies with cross-sectional design as well as mediation analyses with rigorous statistical methods.