The aim of this rapid analysis was to investigate the spatial patterns of COVID-19 emergence across counties in Colorado. In the U.S. West, Colorado has the second highest number of cases and deaths, second only to California. Colorado is also reporting, like other states, that communities of color and low-income persons are disproportionately affected by COVID-19. Using GIS and correlation analysis, this study explored COVID-19 incidence and deaths from March 14 to April 8, 2020, with social determinants and chronic conditions. Preliminary results demonstrate that COVID-19 incidence intensified in mountain communities west of Denver and along the Urban Front Range, and evolved into new centers of risk in eastern Colorado. Overall, the greatest increase in COVID-19 incidence was in northern Colorado, i.e., Weld County, which reported the highest rates in the Urban Front Range. Social and health determinants associated with higher COVID-19-related deaths were population density and asthma, indicative of urban areas, and poverty and unemployment, suggestive of rural areas. Furthermore, a spatial overlap of high rates of chronic diseases with high rates of COVID-19 may suggest a broader syndemic health burden, where comorbidities intersect with inequality of social determinants of health.

Urban decentralisation in the USA during the past five decades has created an automobile-dependent landscape characterised by low-densities, largely single-use zoning and disconnected street networks. Longer distances between dispersing destinations, resulting from urban decentralisation, negatively affects the mobility of socially disadvantaged groups, including women, minorities and lower-income populations. Furthermore, the urban poor and minorities in communities experiencing severe disinvestment and decline, as evident in Detroit, suffer from greater transportation burdens in accessing basic necessities, such as employment and shopping. This study explores gendered travel patterns in six neighbourhoods within the Detroit region, including neighbourhoods experiencing severe disinvestment and decline. This analysis into the gendered dimensions of travel, with a particular focus placed on women, involves a full array of trips, including work and non-work. Ordinary Least Squares (OLS) regression analysis and ANCOVA (Analysis of Covariance) were used to further examine gender differences by childcare responsibility in an extensive array of disaggregated travel, including trips to work, shopping and personal services, restaurant visits and leisure destinations. This study reconfirms that the traditional gender role is reflected in women’s daily travel. It also reveals the burdens of travel placed on women living in racially segregated and socioeconomically disadvantaged neighbourhoods experiencing extreme disinvestment and decline. In addition, the research shows the importance of class and race in shaping travel behaviour.

Although rare, injury to the internal carotid artery (ICA) during pituitary surgery may result in serious morbidity such as stroke or death. This case series explores a single centre’s incidence an...

El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, descriptive and analytical methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the potential utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.

El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, two methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.