A RETROSPECTIVE EVALUATION OF MORBIDITY AND MORTALITY IN ASSOCIATION WITH INFESTATION BY THE MITE STERNOSTOMA TRACHEACOLUM IN AN AVIARY-HOUSED POPULATION OF GOULDIAN FINCHES (CHLOEBIA GOULDIAE).

The Rhynonyssid mesostigmatic mite, Sternostoma tracheacolum, is a well-documented endoparasitic hematophagous arthropod of the respiratory tracts of multiple avian species, particularly Estrildid finches and canaries. In this retrospective study, 175 medical and 278 pathology records for the Gouldian finch (Chloebia gouldiae) population (N = 377) at the San Diego Zoo between 2013 and 2021 were analyzed to evaluate the effectiveness of ivermectin-based prophylaxis. A multivariable negative binomial regression model was constructed to evaluate the population effects of monthly treatments on morbidity or mortality associated with respiratory mites. While controlling for other factors in the model, the prophylactic treatment did not significantly reduce the monthly rate of mite-associated morbidity or mortality (IRR = 1.017, 95% CI: 0.997-1.036, P = 0.0759); however, low proportions of the population were prophylactically treated over time. Different factors were significant when separately evaluating adjusted associations with respiratory morbidity and mortality. The findings suggest increased rates of respiratory morbidity for each successive year of the study period (IRR = 1.180, 95% CI: 1.046-1.342, P = 0.0090) and increased rates of mite-associated mortality occurring annually between May and October (IRR = 1.697, 95% CI: 1.034-2.855, P = 0.0404) compared to the wet winter season. Our findings highlight the need to continually evaluate and optimize treatment regimens in zoological collections. Further investigations into this host-parasite relationship and potential treatments and preventive therapies are warranted.

Health and equity implications of individual adaptation to air pollution in a changing climate.

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyone's need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.

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).

Estimating the Burden of Heat-Related Illness Morbidity Attributable to Anthropogenic Climate Change in North Carolina.

Climate change is known to increase the frequency and intensity of hot days (daily maximum temperature ≥30°C), both globally and locally. Exposure to extreme heat is associated with numerous adverse human health outcomes. This study estimated the burden of heat-related illness (HRI) attributable to anthropogenic climate change in North Carolina physiographic divisions (Coastal and Piedmont) during the summer months from 2011 to 2016. Additionally, assuming intermediate and high greenhouse gas emission scenarios, future HRI morbidity burden attributable to climate change was estimated. The association between daily maximum temperature and the rate of HRI was evaluated using the Generalized Additive Model. The rate of HRI assuming natural simulations (i.e., absence of greenhouse gas emissions) and future greenhouse gas emission scenarios were predicted to estimate the HRI attributable to climate change. Over 4 years (2011, 2012, 2014, and 2015), we observed a significant decrease in the rate of HRI assuming natural simulations compared to the observed. About 3 out of 20 HRI visits are attributable to anthropogenic climate change in Coastal (13.40% [IQR: -34.90,95.52]) and Piedmont (16.39% [IQR: -35.18,148.26]) regions. During the future periods, the median rate of HRI was significantly higher (78.65%: Coastal and 65.85%: Piedmont), assuming a higher emission scenario than the intermediate emission scenario. We observed significant associations between anthropogenic climate change and adverse human health outcomes. Our findings indicate the need for evidence-based public health interventions to protect human health from climate-related exposures, like extreme heat, while minimizing greenhouse gas emissions.

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions.

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Climate Change and Infections on the Move in North America.

Climate change is increasingly recognized for its impacts on human health, including how biotic and abiotic factors are driving shifts in infectious disease. Changes in ecological conditions and processes due to temperature and precipitation fluctuations and intensified disturbance regimes are affecting infectious pathogen transmission, habitat, hosts, and the characteristics of pathogens themselves. Understanding the relationships between climate change and infectious diseases can help clinicians broaden the scope of differential diagnoses when interviewing, diagnosing, and treating patients presenting with infections lacking obvious agents or transmission pathways. Here, we highlight key examples of how the mechanisms of climate change affect infectious diseases associated with water, fire, land, insects, and human transmission pathways in the hope of expanding the analytical framework for infectious disease diagnoses. Increased awareness of these relationships can help prepare both clinical physicians and epidemiologists for continued impacts of climate change on infectious disease in the future.

Mapping Human Vulnerability to Extreme Heat: A Critical Assessment of Heat Vulnerability Indices Created Using Principal Components Analysis.

BACKGROUND: Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping. OBJECTIVE: We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA. METHODS: We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) "unsupervised"-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) "supervised"-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles). RESULTS: Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups. DISCUSSION: HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.

Time series analysis of total and direct associations between high temperatures and preterm births in Detroit, Michigan.

OBJECTIVES: Preterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care. DESIGN AND SETTING: We obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects. RESULTS: At 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked. CONCLUSION: This additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.

Changes in extreme events and the potential impacts on human health.

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future. IMPLICATIONS: Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.

Assessment of Vulnerability to Coccidioidomycosis in Arizona and California.

Coccidioidomycosis is a fungal infection endemic to the southwestern United States, particularly Arizona and California. Its incidence has increased, potentially due in part to the effects of changing climatic variables on fungal growth and spore dissemination. This study aims to quantify the county-level vulnerability to coccidioidomycosis in Arizona and California and to assess the relationships between population vulnerability and climate variability. The variables representing exposure, sensitivity, and adaptive capacity were combined to calculate county level vulnerability indices. Three methods were used: (1) principal components analysis; (2) quartile weighting; and (3) percentile weighting. Two sets of indices, "unsupervised" and "supervised", were created. Each index was correlated with coccidioidomycosis incidence data from 2000-2014. The supervised percentile index had the highest correlation; it was then correlated with variability measures for temperature, precipitation, and drought. The supervised percentile index was significantly correlated (p < 0.05) with coccidioidomycosis incidence in both states. Moderate, positive significant associations (p < 0.05) were found between index scores and climate variability when both states were concurrently analyzed and when California was analyzed separately. This research adds to the body of knowledge that could be used to target interventions to vulnerable counties and provides support for the hypothesis that population vulnerability to coccidioidomycosis is associated with climate variability.

Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health.

There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.

Potential Impacts of Future Warming and Land Use Changes on Intra-Urban Heat Exposure in Houston, Texas.

Extreme heat events in the United States are projected to become more frequent and intense as a result of climate change. We investigated the individual and combined effects of land use and warming on the spatial and temporal distribution of daily minimum temperature (Tmin) and daily maximum heat index (HImax) during summer in Houston, Texas. Present-day (2010) and near-future (2040) parcel-level land use scenarios were embedded within 1-km resolution land surface model (LSM) simulations. For each land use scenario, LSM simulations were conducted for climatic scenarios representative of both the present-day and near-future periods. LSM simulations assuming present-day climate but 2040 land use patterns led to spatially heterogeneous temperature changes characterized by warmer conditions over most areas, with summer average increases of up to 1.5°C (Tmin) and 7.3°C (HImax) in some newly developed suburban areas compared to simulations using 2010 land use patterns. LSM simulations assuming present-day land use but a 1°C temperature increase above the urban canopy (consistent with warming projections for 2040) yielded more spatially homogeneous metropolitan-wide average increases of about 1°C (Tmin) and 2.5°C (HImax), respectively. LSM simulations assuming both land use and warming for 2040 led to summer average increases of up to 2.5°C (Tmin) and 8.3°C (HImax), with the largest increases in areas projected to be converted to residential, industrial and mixed-use types. Our results suggest that urbanization and climate change may significantly increase the average number of summer days that exceed current threshold temperatures for initiating a heat advisory for metropolitan Houston, potentially increasing population exposure to extreme heat.

Vulnerability to extreme heat by socio-demographic characteristics and area green space among the elderly in Michigan, 1990-2007.

OBJECTIVES: We examined how individual and area socio-demographic characteristics independently modified the extreme heat (EH)-mortality association among elderly residents of 8 Michigan cities, May-September, 1990-2007. METHODS: In a time-stratified case-crossover design, we regressed cause-specific mortality against EH (indicator for 4-day mean, minimum, maximum or apparent temperature above 97th or 99 th percentiles). We examined effect modification with interactions between EH and personal marital status, age, race, sex and education and ZIP-code percent "non-green space" (National Land Cover Dataset), age, race, income, education, living alone, and housing age (U.S. Census). RESULTS: In models including multiple effect modifiers, the odds of cardiovascular mortality during EH (99 th percentile threshold) vs. non-EH were higher among non-married individuals (1.21, 95% CI=1.14-1.28 vs. 0.98, 95% CI=0.90-1.07 among married individuals) and individuals in ZIP codes with high (91%) non-green space (1.17, 95% CI=1.06-1.29 vs. 0.98, 95% CI=0.89-1.07 among individuals in ZIP codes with low (39%) non-green space). Results suggested that housing age may also be an effect modifier. For the EH-respiratory mortality association, the results were inconsistent between temperature metrics and percentile thresholds of EH but largely insignificant. CONCLUSIONS: Green space, housing and social isolation may independently enhance elderly peoples' heat-related cardiovascular mortality vulnerability. Local adaptation efforts should target areas and populations at greater risk.

Strategies to reduce the harmful effects of extreme heat events: a four-city study.

Extreme heat events (EHEs) are becoming more intense, more frequent and longer lasting in the 21st century. These events can disproportionately impact the health of low-income, minority, and urban populations. To better understand heat-related intervention strategies used by four U.S. cities, we conducted 73 semi-structured interviews with government and non-governmental organization leaders representing public health, general social services, emergency management, meteorology, and the environmental planning sectors in Detroit, MI; New York City, NY; Philadelphia, PA and Phoenix, AZ-cities selected for their diverse demographics, climates, and climate adaptation strategies. We identified activities these leaders used to reduce the harmful effects of heat for residents in their city, as well as the obstacles they faced and the approaches they used to evaluate these efforts. Local leaders provided a description of how local context (e.g., climate, governance and city structure) impacted heat preparedness. Despite the differences among study cities, political will and resource access were critical to driving heat-health related programming. Upon completion of our interviews, we convened leaders in each city to discuss these findings and their ongoing efforts through day-long workshops. Our findings and the recommendations that emerged from these workshops could inform other local or national efforts towards preventing heat-related morbidity and mortality.

Staying cool in a changing climate: Reaching vulnerable populations during heat events.

The frequency and intensity of hot weather events are expected to increase globally, threatening human health, especially among the elderly, poor, and chronically ill. Current literature indicates that emergency preparedness plans, heat health warning systems, and related interventions may not be reaching or supporting behavior change among those most vulnerable in heat events. Using a qualitative multiple case study design, we comprehensively examined practices of these populations to stay cool during hot weather ("cooling behaviors") in four U.S. cities with documented racial/ethnic and socio-economic disparities and diverse heat preparedness strategies: Phoenix, Arizona; Detroit, Michigan; New York City, New York; and Philadelphia, Pennsylvania. Based on semi-structured in-depth interviews we conducted with 173 community members and organizational leaders during 2009-2010, we assessed why vulnerable populations do or do not participate in health-promoting behaviors at home or in their community during heat events, inquiring about perceptions of heat-related threats and vulnerability and the role of social support. While vulnerable populations often recognize heat's potential health threats, many overlook or disassociate from risk factors or rely on experiences living in or visiting warmer climates as a protective factor. Many adopt basic cooling behaviors, but unknowingly harmful behaviors such as improper use of fans and heating and cooling systems are also adopted. Decision-making related to commonly promoted behaviors such as air conditioner use and cooling center attendance is complex, and these resources are often inaccessible financially, physically, or culturally. Interviewees expressed how interpersonal, intergenerational relationships are generally but not always protective, where peer relationships are a valuable mechanism for facilitating cooling behaviors among the elderly during heat events. To prevent disparities in heat morbidity and mortality in an increasingly changing climate, we note the implications of local context, and we broadly inform heat preparedness plans, interventions, and messages by sharing the perspectives and words of community members representing vulnerable populations and leaders who work most closely with them.

Preventing cold-related morbidity and mortality in a changing climate.

Winter weather patterns are anticipated to become more variable with increasing average global temperatures. Research shows that excess morbidity and mortality occurs during cold weather periods. We critically reviewed evidence relating temperature variability, health outcomes, and adaptation strategies to cold weather. Health outcomes included cardiovascular-, respiratory-, cerebrovascular-, and all-cause morbidity and mortality. Individual and contextual risk factors were assessed to highlight associations between individual- and neighborhood-level characteristics that contribute to a person's vulnerability to variability in cold weather events. Epidemiologic studies indicate that the populations most vulnerable to variations in cold winter weather are the elderly, rural and, generally, populations living in moderate winter climates. Fortunately, cold-related morbidity and mortality are preventable and strategies exist for protecting populations from these adverse health outcomes. We present a range of adaptation strategies that can be implemented at the individual, building, and neighborhood level to protect vulnerable populations from cold-related morbidity and mortality. The existing research justifies the need for increased outreach to individuals and communities for education on protective adaptations in cold weather. We propose that future climate change adaptation research couple building energy and thermal comfort models with epidemiological data to evaluate and quantify the impacts of adaptation strategies.

Assessment and application of national environmental databases and mapping tools at the local level to two community case studies.

Communities are concerned over pollution levels and seek methods to systematically identify and prioritize the environmental stressors in their communities. Geographic information system (GIS) maps of environmental information can be useful tools for communities in their assessment of environmental-pollution-related risks. Databases and mapping tools that supply community-level estimates of ambient concentrations of hazardous pollutants, risk, and potential health impacts can provide relevant information for communities to understand, identify, and prioritize potential exposures and risk from multiple sources. An assessment of existing databases and mapping tools was conducted as part of this study to explore the utility of publicly available databases, and three of these databases were selected for use in a community-level GIS mapping application. Queried data from the U.S. EPA's National-Scale Air Toxics Assessment, Air Quality System, and National Emissions Inventory were mapped at the appropriate spatial and temporal resolutions for identifying risks of exposure to air pollutants in two communities. The maps combine monitored and model-simulated pollutant and health risk estimates, along with local survey results, to assist communities with the identification of potential exposure sources and pollution hot spots. Findings from this case study analysis will provide information to advance the development of new tools to assist communities with environmental risk assessments and hazard prioritization.

Tools available to communities for conducting cumulative exposure and risk assessments.

This paper summarizes and assesses over 70 tools that could aid with gathering information and taking action on environmental issues related to community-based cumulative risk assessments (CBCRA). Information on tool use, development and research needs, was gathered from websites, documents, and CBCRA program participants and researchers, including 25 project officers who work directly with community groups. The tools were assessed on the basis of information provided by project officers, community members, CBCRA researchers, and by case study applications. Tables summarize key environmental issues and tool features: (1) a listing of CBCRA-related environmental issues of concern to communities; (2) web-based tools that map environmental information; (3) step-by-step guidance documents; (4) databases of environmental information; and (5) computer models that simulate human exposure to chemical stressors. All tools described here are publicly available, with the focus being on tools developed by the US Environmental Protection Agency. These tables provide sources of information to promote risk identification and prioritization beyond risk perception approaches, and could be used by CBCRA participants and researchers. The purpose of this overview is twofold: (1) To present a comprehensive, though not exhaustive, summary of numerous tools that could aid with performing CBCRAs; and (2) To use this toolset as a sample of the current state of CBCRA tools to critically examine their utility and guide research for the development of new and improved tools.