Social Vulnerability in US Communities Affected by Wildfire Smoke, 2011 to 2021.

Objectives. To describe demographic and social characteristics of US communities exposed to wildfire smoke. Methods. Using satellite-collected data on wildfire smoke with the locations of population centers in the coterminous United States, we identified communities potentially exposed to light-, medium-, and heavy-density smoke plumes for each day from 2011 to 2021. We linked days of exposure to smoke in each category of smoke plume density with 2010 US Census data and community characteristics from the Centers for Disease Control and Prevention's Social Vulnerability Index to describe the co-occurrence of smoke exposure and social disadvantage. Results. During the 2011-to-2021 study period, increases in the number of days of heavy smoke were observed in communities representing 87.3% of the US population, with notably large increases in communities characterized by racial or ethnic minority status, limited English proficiency, lower educational attainment, and crowded housing conditions. Conclusions. From 2011 to 2021, wildfire smoke exposures in the United States increased. As smoke exposure becomes more frequent and intense, interventions that address communities with social disadvantages might maximize their public health impact. (Am J Public Health. 2023;113(7):759-767. https://doi.org/10.2105/AJPH.2023.307286).

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 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.

Overcoming Barriers to Successful Climate and Health Adaptation Practice: Notes from the Field.

State and local public health agencies are at the forefront of planning and responding to the health challenges of climate hazards but face substantial barriers to effective climate and health adaptation amidst concurrent environmental and public health crises. To ensure successful adaptation, it is necessary to understand and overcome these barriers. The U.S. Centers for Disease Control and Prevention Climate-Ready States and Cities Initiative (CRSCI) provides funding to state and local health departments to anticipate and respond to health impacts from climate change using the Building Resilience Against Climate Effects (BRACE) framework. This paper explores the barriers to and enablers of successful adaptation projects among BRACE West CRSCI grantees, including Arizona, California, Oregon, and the city and county of San Francisco. The barriers included competing demands such as the COVID-19 pandemic, dependence on partners with similar challenges, staff and leadership turnover, uncertain and complex impacts on at-risk populations, and inadequate resources. The enablers included effective partnerships, leadership support, dedicated and skilled internal staff, and policy windows enabling institutional change and reprioritization. These findings highlight effective strategies in the field that state and local health departments may use to anticipate potential barriers and establish their work in an environment conducive to successful adaptation.

COVIDNearTerm: A simple method to forecast COVID-19 hospitalizations.

Introduction: COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy. Methods: Here we present a method called COVIDNearTerm to "forecast" hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. It is easy to use as it requires only previous hospitalization data, and there is an open-source R package that implements the algorithm. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT). Results: We found that COVIDNearTerm predictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16 to 36%. For those same comparisons, the CalCAT ensemble errors were between 30 and 59%. Conclusion: COVIDNearTerm is a simple and useful tool for predicting near-term COVID-19 hospitalizations.

Nonpharmaceutical Interventions Remain Essential to Reducing Coronavirus Disease 2019 Burden Even in a Well-Vaccinated Society: A Modeling Study.

Vaccination and nonpharmaceutical interventions (NPIs) reduce transmission of severe acute respiratory syndrome coronavirus 2 infection, but their effectiveness depends on coverage and adherence levels. We used scenario modeling to evaluate their effects on cases and deaths averted and herd immunity. NPIs and vaccines worked synergistically in different parts of the pandemic to reduce disease burden.

Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California.

With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021-the most of any state. We analyzed California's racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through October 2020, combining data from 15.4 million SARS-CoV-2 tests with subcounty exposure risk estimates from the American Community Survey. We defined "high-exposure-risk" households as those with one or more essential workers and fewer rooms than inhabitants. Latino people in California are 8.1 times more likely to live in high-exposure-risk households than White people (23.6 percent versus 2.9 percent), are overrepresented in cumulative cases (3,784 versus 1,112 per 100,000 people), and are underrepresented in cumulative testing (35,635 versus 48,930 per 100,000 people). These risks and outcomes were worse for Latino people than for members of other racial/ethnic minority groups. Subcounty disparity analyses can inform targeting of interventions and resources, including community-based testing and vaccine access measures. Tracking COVID-19 disparities and developing equity-focused public health programming that mitigates the effects of systemic racism can help improve health outcomes among California's populations of color.

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.

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.

Out-of-Hospital Cardiac Arrests and Wildfire-Related Particulate Matter During 2015-2017 California Wildfires.

Background The natural cycle of large-scale wildfires is accelerating, increasingly exposing both rural and populous urban areas to wildfire emissions. While respiratory health effects associated with wildfire smoke are well established, cardiovascular effects have been less clear. Methods and Results We examined the association between out-of-hospital cardiac arrest and wildfire smoke density (light, medium, heavy smoke) from the National Oceanic Atmospheric Association's Hazard Mapping System. Out-of-hospital cardiac arrest data were provided by the Cardiac Arrest Registry to Enhance Survival for 14 California counties, 2015-2017 (N=5336). We applied conditional logistic regression in a case-crossover design using control days from 1, 2, 3, and 4 weeks before case date, at lag days 0 to 3. We stratified by pathogenesis, sex, age (19-34, 35-64, and ≥65 years), and socioeconomic status (census tract percent below poverty). Out-of-hospital cardiac arrest risk increased in association with heavy smoke across multiple lag days, strongest on lag day 2 (odds ratio, 1.70; 95% CI, 1.18-2.13). Risk in the lower socioeconomic status strata was elevated on medium and heavy days, although not statistically significant. Higher socioeconomic status strata had elevated odds ratios with heavy smoke but null results with light and medium smoke. Both sexes and age groups 35 years and older were impacted on days with heavy smoke. Conclusions Out-of-hospital cardiac arrests increased with wildfire smoke exposure, and lower socioeconomic status appeared to increase the risk. The future trajectory of wildfire, along with increasing vulnerability of the aging population, underscores the importance of formulating public health and clinical strategies to protect those most vulnerable.

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.

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.

Climate Change and Heat-Related Excess Mortality in the Eastern USA.

Climate change will increase extreme heat-related health risks. To quantify the health impacts of mid-century climate change, we assess heat-related excess mortality across the eastern USA. Health risks are estimated using the US Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program (BenMAP). Mid-century temperature estimates, downscaled using the Weather Research and Forecasting model, are compared to 2007 temperatures at 36 km and 12 km resolutions. Models indicate the average apparent and actual summer temperatures rise by 4.5° and 3.3° C, respectively. Warmer average apparent temperatures could cause 11,562 additional annual deaths (95% confidence interval, CI: 2641-20,095) due to cardiovascular stress in the population aged 65 years and above, while higher minimum temperatures could cause 8767 (95% CI: 5030-12,475) additional deaths each year. Modeled future climate data available at both coarse (36 km) and fine (12 km) resolutions predict significant human health impacts from warmer climates. The findings suggest that currently available information on future climates is sufficient to guide regional planning for the protection of public health. Higher resolution climate and demographic data are still needed to inform more targeted interventions.

The San Diego 2007 wildfires and Medi-Cal emergency department presentations, inpatient hospitalizations, and outpatient visits: An observational study of smoke exposure periods and a bidirectional case-crossover analysis.

BACKGROUND: The frequency and intensity of wildfires is anticipated to increase as climate change creates longer, warmer, and drier seasons. Particulate matter (PM) from wildfire smoke has been linked to adverse respiratory and possibly cardiovascular outcomes. Children, older adults, and persons with underlying respiratory and cardiovascular conditions are thought to be particularly vulnerable. This study examines the healthcare utilization of Medi-Cal recipients during the fall 2007 San Diego wildfires, which exposed millions of persons to wildfire smoke. METHODS AND FINDINGS: Respiratory and cardiovascular International Classification of Diseases (ICD)-9 codes were identified from Medi-Cal fee-for-service claims for emergency department presentations, inpatient hospitalizations, and outpatient visits. For a respiratory index and a cardiovascular index of key diagnoses and individual diagnoses, we calculated rate ratios (RRs) for the study population and different age groups for 3 consecutive 5-day exposure periods (P1 [October 22-26], P2 [October 27-31], and P3 [November 1-5]) versus pre-fire comparison periods matched on day of week (5-day periods starting 3, 4, 5, 6, 8, and 9 weeks before each exposed period). We used a bidirectional symmetric case-crossover design to examine emergency department presentations with any respiratory diagnosis and asthma specifically, with exposure based on modeled wildfire-derived fine inhalable particles that are 2.5 micrometers and smaller (PM2.5). We used conditional logistic regression to estimate odds ratios (ORs), adjusting for temperature and relative humidity, to assess same-day and moving averages. We also evaluated the United States Environmental Protection Agency (EPA)'s Air Quality Index (AQI) with this conditional logistic regression method. We identified 21,353 inpatient hospitalizations, 25,922 emergency department presentations, and 297,698 outpatient visits between August 16 and December 15, 2007. During P1, total emergency department presentations were no different than the reference periods (1,071 versus 1,062.2; RR 1.01; 95% confidence interval [CI] 0.95-1.08), those for respiratory diagnoses increased by 34% (288 versus 215.3; RR 1.34; 95% CI 1.18-1.52), and those for asthma increased by 112% (58 versus 27.3; RR 2.12; 95% CI 1.57-2.86). Some visit types continued to be elevated in later time frames, e.g., a 72% increase in outpatient visits for acute bronchitis in P2. Among children aged 0-4, emergency department presentations for respiratory diagnoses increased by 70% in P1, and very young children (0-1) experienced a 243% increase for asthma diagnoses. Associated with a 10 µg/m3 increase in PM2.5 (72-hour moving average), we found 1.08 (95% CI 1.04-1.13) times greater odds of an emergency department presentation for asthma. The AQI level "unhealthy for sensitive groups" was associated with significantly elevated odds of an emergency department presentation for respiratory conditions the day following exposure, compared to the AQI level "good" (OR 1.73; 95% CI 1.18-2.53). Study limitations include the use of patient home address to estimate exposures and demographic differences between Medi-Cal beneficiaries and the general population. CONCLUSIONS: Respiratory diagnoses, especially asthma, were elevated during the wildfires in the vulnerable population of Medi-Cal beneficiaries. Wildfire-related healthcare utilization appeared to persist beyond the initial high-exposure period. Increased adverse health events were apparent even at mildly degraded AQI levels. Significant increases in health events, especially for respiratory conditions and among young children, are expected based on projected climate scenarios of wildfire frequency in California and globally.

Comparison of US metropolitan region pedestrian and bicyclist fatality rates.

Annual US pedestrian and bicyclist fatalities involving motor vehicles have each increased by 30% in just six years, reaching their highest levels in two decades. To provide information to reverse this trend, we quantified pedestrian and bicyclist fatality rates in 46 of the largest US metropolitan statistical areas (MSAs) during two five-year time periods: 1999-2003 and 2007-2011. We divided the annual average number of pedestrian and bicyclist fatalities during 1999-2003 from the Fatality Analysis Reporting System by the annual estimates of pedestrian and bicycle trips, kilometers traveled, and minutes traveled from the 2001 National Household Travel Survey (NHTS) and the annual average number of fatalities from 2007 to 2011 by similar estimates from the 2009 NHTS. The five most dangerous regions for walking during 2007-2011 averaged 262 pedestrian fatalities per billion trips while the five safest averaged 49 pedestrian fatalities per billion trips. The five most dangerous regions for bicycling averaged 458 bicyclist fatalities per billion trips while the five safest averaged 75 bicyclist fatalities per billion trips. Random-effects meta-analysis identified eight metropolitan regions as outliers with low pedestrian fatality rates, six with high pedestrian fatality rates, one with a low bicyclist fatality rate, and five with high bicyclist fatality rates. MSAs with low pedestrian and bicycle fatality rates tended to have central cities recognized as Walk Friendly Communities and Bicycle Friendly Communities for investing in pedestrian and bicycle projects and programs. Random-effects meta-regression showed that certain socioeconomic characteristics and high pedestrian and bicyclist mode shares were associated with lower MSA fatality rates. Results suggest that pedestrian and bicycle infrastructure and safety programs should be complemented with strategies to increase walking and bicycling. In particular, safety initiatives should be honed to reduce pedestrian and bicyclist fatality risk in immigrant communities and to make pedestrian travel safer for the growing senior-age population.

Climate Change and Public Health Policy.

Climate change poses real and immediate impacts to the public health of populations around the globe. Adverse impacts are expected to continue throughout the century. Emphasizing co-benefits of climate action for health, combining adaptation and mitigation efforts, and increasing interagency coordination can effectively address both public health and climate change challenges.

Bicyclist Deaths Associated with Motor Vehicle Traffic - United States, 1975-2012.

Physical activity, including bicycling, is linked with multiple health benefits. However, although bicycles account for only about 1% of trips across all modes of transportation, on a per trip basis, bicyclists die on U.S. roads at a rate double that of vehicle occupants. In 2009, an estimated 392 billion trips (across all modes) were taken in the United States, including 4.1 billion bicycle trips, and 33,808 deaths occurred on U.S roadways (across all modes), including 630 bicyclist deaths. This report examines mortality trends among cyclists using national collision data from the Fatality Analysis Reporting System (FARS) for the period 1975-2012. Annual rates for cyclist mortality decreased 44%, from 0.41 to 0.23 deaths per 100,000 during this period, with the steepest decline among children aged <15 years. In recent years, reductions in cyclist deaths have slowed. However, age-specific cyclist mortality rates for adults aged 35-74 years have increased since 1975. Multifaceted approaches to bicyclist safety have been shown to be effective in increasing bicycling while decreasing traffic injuries and fatalities. With U.S. adults choosing to walk and cycle more, implementation of these approaches might help counter recent increases in adult cyclist deaths.

Avoided heat-related mortality through climate adaptation strategies in three US cities.

Heat-related mortality in US cities is expected to more than double by the mid-to-late 21st century. Rising heat exposure in cities is projected to result from: 1) climate forcings from changing global atmospheric composition; and 2) local land surface characteristics responsible for the urban heat island effect. The extent to which heat management strategies designed to lessen the urban heat island effect could offset future heat-related mortality remains unexplored in the literature. Using coupled global and regional climate models with a human health effects model, we estimate changes in the number of heat-related deaths in 2050 resulting from modifications to vegetative cover and surface albedo across three climatically and demographically diverse US metropolitan areas: Atlanta, Georgia, Philadelphia, Pennsylvania, and Phoenix, Arizona. Employing separate health impact functions for average warm season and heat wave conditions in 2050, we find combinations of vegetation and albedo enhancement to offset projected increases in heat-related mortality by 40 to 99% across the three metropolitan regions. These results demonstrate the potential for extensive land surface changes in cities to provide adaptive benefits to urban populations at risk for rising heat exposure with climate change.