The (In)Visible Health Risks of Climate Change

This paper scrutinizes the assertion that knowledge gaps concerning health risks from climate change are unjust, and must be addressed, because they hinder evidence-led interventions to protect vulnerable populations. First, we construct a taxonomy of six inter-related forms of invisibility (social marginalization, forced invisibility by migrants, spatial marginalization, neglected diseases, mental health, uneven climatic monitoring and forecasting) which underlie systematic biases in current understanding of these risks in Latin America, and advocate an approach to climate-health research that draws on intersectionality theory to address these inter-relations. We propose that these invisibilities should be understood as outcomes of structural imbalances in power and resources rather than as haphazard blindspots in scientific and state knowledge. Our thesis, drawing on theories of governmentality, is that context-dependent tensions condition whether or not benefits of making vulnerable populations legible to the state outweigh costs. To be seen is to be politically counted and eligible for rights, yet evidence demonstrates the perils of visibility to disempowered people. For example, flood-relief efforts in remote Amazonia expose marginalized urban river-dwellers to the traumatic prospect of forced relocation and social and economic upheaval. Finally, drawing on research on citizenship in post-colonial settings, we conceptualize climate change as an ‘open moment’ of political rupture, and propose strategies of social accountability, empowerment and trans-disciplinary research which encourage the marginalized to reach out for greater power. These achievements could reduce drawbacks of state legibility and facilitate socially-just governmental action on climate change adaptation that promotes health for all

Association of Exposure to Wildfire Air Pollution With Exacerbations of Atopic Dermatitis and Itch Among Older Adults.

This cross-sectional study evaluates the association of exposure to wildfire air pollution with exacerbations of atopic dermatitis and itch among adults aged 65 years or older

A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires

Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8–20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke. Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health

Association of Wildfire Air Pollution With Clinic Visits for Psoriasis

This cross-sectional study examines whether clinic visits and online search interest for psoriasis were associated with wildfire air pollution after a delayed lag period

Association of Wildfire Air Pollution and Health Care Use for Atopic Dermatitis and Itch.

IMPORTANCE: Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. OBJECTIVE: To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. EXPOSURES: Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 μm in diameter (PM2.5), and satellite-based smoke plume density scores. MAIN OUTCOMES AND MEASURES: Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. RESULTS: Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-μg/m3 increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). CONCLUSIONS AND RELEVANCE: This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals' counseling of patients with skin disease and public health practice

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Planning for the new urban climate: interactions of local environmental planning and regional extreme heat

The Earth's climate is changing and cities are facing a warmer future. As the locus of economic activity and concentrated populations on the planet, cities are both a primary driver of greenhouse gas emissions and places where the human health impacts of climate change are directly felt. Cities increase local temperatures through the conversion of natural land covers to urban uses, and exposures to elevated temperatures represent a serious and growing health threat for urban residents. This work is concerned with understanding the interactions of global trends in climate with local influences tied to urban land covers. First, it examines temperatures during an extended period of extreme heat and asks whether changes in land surface temperatures during a heat wave are consistent in space and time across all land cover types. Second, the influences of land covers on temperatures are considered for normal and extreme summer weather to find out which characteristics of the built environment most influence temperatures during periods of extreme heat. Finally, the distribution of health vulnerabilities related to extreme heat in cities are described and examined for spatial patterns. These topics are investigated using meteorology from the summer of 2006 to identify extremely hot days in the cities of Atlanta, Chicago, Philadelphia, and Phoenix and their surrounding metropolitan regions. Remotely sensed temperature data were examined with physical and social characteristics of the urban environment to answer the questions posed above. The findings confirm that urban land covers consistently exhibit higher temperatures than surrounding rural areas and are much more likely to be among the hottest in the region, during a heat wave specifically. In some cities urban thermal anomalies grew between the beginning and end of a heat wave. The importance of previously recognized built environment thermal influences (impervious cover and tree canopy) were present, and in some cases, emphasized during extreme summer weather. Extreme heat health health vulnerability related to environmental factors coincided spatially with risks related to social status. This finding suggests that populations with fewer resources for coping with extreme heat tend to reside in built environments that increase temperatures, and thus they may be experiencing increased thermal exposures. Physical interventions and policies related to the built environment can help to reduce urban temperatures, especially during periods of extremely hot weather which are predicted to become more frequent with global climate change. In portions of the city where populations with limited adaptive capacity are concentrated, modification of the urban landscape to decrease near surface longwave radiation can reduce the chances of adverse health effects related to extreme heat. The specific programs, policies, and design strategies pursued by cities and regions must be tailored with respect to scale, location, and cultural context. This work concludes with suggestions for such strategies.PhDCommittee Member: Elliott, Michael ; Committee Member: Liu, Yang; Committee Member: Luber, George; Committee Member: Russell, Armistead; Committee Member: Stone, Bria

The Performance of the National Weather Service Heat Warning System against Ground Observations and Satellite Imagery

Deadly heat waves are increasing with climate change. Public forecasts and warnings are a primary public health strategy for dealing with such extreme weather events; however, temperatures can vary widely within the administrative units used to issue warnings, particularly across urban landscapes. The emergence of more frequent and widely distributed sources of urban temperature data provide the opportunity to investigate the specificity of the current National Weather Service (NWS) warnings and to improve their accuracy and precision. In this work, temperatures from distributed public weather stations, NWS heat advisories and warnings, and land surface temperature imagery throughout two large metropolitan areas, Atlanta and Chicago, during the 2006–2012 summers are considered. We investigate the spatial variability of hazardous temperatures and their agreement against NWS advisories. Second, we examine the potential for thermal imagery to replicate National Weather Service heat warnings. Observations from weather stations exhibit varying degrees of agreement with NWS advisories. The level of agreement varied by station and was not found to be associated with the station’s proximate land cover. Air temperatures estimated from satellite imagery correspond with NWS Advisory status regionally and may enable creating more refined public warnings regarding hazardous temperatures and protective action

Trends in bicycle-related injuries, hospital admissions, and deaths in the USA 1997-2013.

Objective: Cycling is associated with numerous health benefits but also the risk of traumatic injury. Recent data demonstrate an increase in overall cycling injuries as well as hospital admissions from 1997 to 2013 in the United States. We seek to better understand the causes of the increase in cycling injuries and hospital admissions. Methods: Data regarding cycling-related injuries and hospital admissions were obtained from the National Electronic Injury Surveillance System (NEISS). Participation data were derived from the National Sporting Goods Association Sports Participation Survey, and fatality data were collected from the Fatality Analysis Reporting System (FARS). Population estimates were obtained using a complex survey design. Linear regression was used to evaluate univariate relationships between cycling injuries, hospital admissions, deaths, and participation. To evaluate factors associated with hospital admission, we developed a multivariable logistic regression model that included year, age, gender, body part injured, and injury type (i.e., contusion, fracture, or laceration). Results: The number of individuals who cycle did not change significantly over time, but there was a substantial increase in cycling-related injuries, leading to an increase in per participant injuries from 701/100,000 in 1997 to 1,164/100,000 in 2013. When the injuries were evaluated by age group, younger cyclists have an increased risk for injury, whereas the rise in injuries among older cyclists stemmed from an increase in ridership rather than a unique susceptibility to injury. Trends in hospital admissions and fatalities appeared to be driven by increases in the older age groups. In the multivariable model evaluating factors related to hospital admission, the odds of hospital admission increased for each decade after age 25, as well as male gender and body part injured. Conclusion: On a per participant basis, the rate of cycling-related injuries and hospital admissions increased between 1997 and 2013. This trend likely reflects a combination of shifting demographics among cyclists with an increase in older cyclists who are at increased risk of severe injury