HABs Karenia brevis and Pseudo-nitzschia pre- and post-Hurricane Michael.

Increased occurrences of harmful algal blooms (HAB) in the Gulf of Mexico, and even worldwide, yield concern for increases in brevetoxin exposure leading to respiratory illness or even death, highlighting the need for extensive scientific research and human health monitoring. It is known that major events such as tropical storms and hurricanes are followed by periods of increased red tides caused by HABs; however, the nature by which phytoplankton blooms proliferate following major events remains a topic of great interest and research. The impact of Hurricane Michael on October 10, 2018 on HABs in the Florida panhandle was examined by analyzing data from the Florida Fish and Wildlife Conservation Commission in coordination with Normalized Fluorescence Line Height (nFLH) data from the University of South Florida College of Marine Science. Results presented here demonstrate four phases of HABs during storm events: 1. Pre-storm concentrations, 2. Decreased concentration during the storm, 3. Elevated concentrations following the storm and 4. Recovery period. This time frame can serve to be important in understanding the health dynamics of coastal systems following major storm events.

Classifying Building Roof Damage Using High Resolution Imagery for Disaster Recovery.

Post-hurricane damage assessments are often costly and time-consuming. Remotely sensed data provides a complementary method of data collection that can be completed comparatively quickly and at relatively low cost. This study focuses on 15 Florida counties impacted by Hurricane Michael (2018), which had category 5 strength winds at landfall. The present study evaluates the ability of aerial imagery collected to cost-effectively measure blue tarps on buildings for disaster impact and recovery. A support vector machine model classified blue tarp, and parcels received a damage indicator based on the model's prediction. The model had an overall accuracy of 85.3% with a sensitivity of 74% and a specificity of 96.7%. The model results indicated approximately 7% of all parcels (27 926 residential and 4431 commercial parcels) in the study area as having blue tarp present. The study results may benefit jurisdictions that lacked financial resources to conduct on-the-ground damage assessments.

The association of indoor heat exposure with diabetes and respiratory 9-1-1 calls through emergency medical dispatch and services documentation.

BACKGROUND: People with pre-existing medical conditions, who spend a large proportion of their time indoors, are at risk of emergent morbidities from elevated indoor heat exposures. In this study, indoor heat of structures wherein exposed people received Grady Emergency Services based care in Atlanta, GA, U.S., was measured from May to September 2016. METHOD: ology: In this case-control study, analyses were conducted to investigate the effect of indoor heat on the odds of 9-1-1 calls for diabetic (n = 90 cases) and separately, for respiratory (n = 126 cases), conditions versus heat-insensitive emergencies (n = 698 controls). Generalized Additive Models considered both linear and non-linear indoor heat and health outcome associations using thin-plate regression splines. RESULTS: Hotter and more humid indoor conditions were non-linearly associated with an increasing likelihood of receiving emergency care for complications of diabetes and severe respiratory distress. Higher heat indices were associated with increased odds of a diabetes (odds ratio for change from 30 to 31 °C: 1.12, 95% CI: 1.08-1.16) or respiratory 9-1-1 medical call versus control (odds ratio for change from 34 to 35 °C: 1.18, 95% CI: 1.09-1.28) call. Both diabetic and respiratory distress patients were more likely to be African-American and/or have comorbidities. CONCLUSIONS: In this study, the statistical association of indoor heat exposure with emergency morbidities (diabetic, respiratory) was demonstrated. The study also showcased the value and utility of data gathered by emergency medical dispatch and services from inaccessible private indoor sources (i.e., domiciles) for environmental health.

Remotely sensed measures of Hurricane Michael damage and adverse perinatal outcomes and access to prenatal care services in the Florida panhandle.

BACKGROUND: Studies of effects of hurricanes on perinatal outcomes often rely on approximate measures of exposure. This study aims to use observed damage from aerial imagery to refine residential building damage estimates, evaluate the population changes post landfall, and assess the associations between the extent of residential building damage and adverse perinatal outcomes and access to prenatal care (PNC) services.  METHODS: Vital statistics data from the Florida Department of Health's Office of Vital Statistics were used to align maternal geocoded address data to high-resolution imagery (0.5-foot resolution, true color with red, blue, and green bands) aerial photographs. Machine learning (support vector machines) classified residential roof damage across the study area. Perinatal outcomes were compared with the presence or absence of damage to the mother's home. Log-binomial regression models were used to compare the populations living in and outside of high-risk/damage areas, to assess the population changes after Hurricane Michael, and to estimate the associations between damage after Hurricane Michael and adverse perinatal outcomes/access to PNC services. A semi-parametric linear model was used to model time of first PNC visit and increase in damage. RESULTS: We included 8,965 women in analysis. Women with lower education and/or of Black or other non-White race/ethnicity were more likely to live in areas that would see high damage than other groups. Moreover, there was a greater proportion of births delivered by women living in the high-risk/damage area (> 25% damaged parcels after Michael) in the year before Michael than the year after Michael. Lastly, living in the area with relatively high damage increased the risk of having intermediate or inadequate PNC (adjusted Risk Ratio = 1.21, 95% CI: 1.03, 1.43), but not other adverse perinatal outcomes. CONCLUSIONS: Aerially observed damage data enable us to evaluate the impact of natural disasters on perinatal outcomes and access to PNC services based on residential building damage immediately surrounding a household. The association between the extent of damage and adverse perinatal outcomes should be further investigated in future studies.

Harmful algal bloom-related 311 calls, Cape Coral, Florida 2018-2019.

Harmful algal blooms (HABs) can adversely impact water quality and threaten human and animal health. People working or living along waterways with prolonged HAB contamination may face elevated toxin exposures and breathing complications. Monitoring HABs and potential adverse human health effects is notoriously difficult due to routes and levels of exposure that vary widely across time and space. This study examines the utility of 311 calls to enhance HAB surveillance and monitoring. The study focuses on Cape Coral, FL, USA, located along the banks of the Caloosahatchee River and Estuary and the Gulf of Mexico. The wider study area experienced a prolonged cyanobacteria bloom in 2018. The present study examines the relationship between weekly water quality characteristics (temperature, dissolved oxygen, pH, microcystin-LR) and municipal requests for information or services (algal 311 calls). Each 1 µg/L increase in waterborne microcystin-LR concentrations corresponded with 9% more algal 311 calls (95% confidence interval: 1.03-1.15, p = 0.002). The results suggest water quality monitoring and the 311 dispatch systems may be further integrated to improve public health surveillance.

Using social security number to identify sub-populations vulnerable to the health impacts from extreme heat in Florida, U.S.

BACKGROUND: Some socioeconomically vulnerable groups may experience disproportionately higher risk of extreme heat illness than other groups, but no study has utilized the presence/absence of a social security number (SSN) as a proxy for vulnerable sub-populations. METHODS: This study focused on the warm season from 2008 to 2012 in Florida, U.S. With a total number of 8,256,171 individual level health outcomes, we devised separate case-crossover models for five heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease), type of health care visit (emergency department (ED) and hospitalization), and patients reporting/not reporting an SSN. Each stratified model also considered potential effect modification by sex, age, or race/ethnicity. RESULTS: Mean temperature raised the odds of five heat-sensitive health outcomes with the highest odds ratios (ORs) for heat-related illness. Sex significantly modified heat exposure effects for dehydration ED visits (Males: 1.145, 95 % CI: 1.137-1.153; Females: 1.110, 95 % CI: 1.103-1.117) and hospitalization (Males: 1.116, 95 % CI: 1.110-1.121; Females: 1.100, 95 % CI: 1.095-1.105). Patients not reporting an SSN between 25 and 44 years (1.264, 95 % CI: 1.192-1.340) exhibited significantly higher dehydration ED ORs than those reporting an SSN (1.146, 95 % CI: 1.136-1.157). We also observed significantly higher ORs for cardiovascular disease hospitalization from the no SSN group (SSN: 1.089, 95 % CI: 1.088-1.090; no SSN: 1.100, 95 % CI: 1.091-1.110). CONCLUSIONS: This paper partially supports the idea that individuals without an SSN could experience higher risks of dehydration (for those 25-45 years), renal disease, and cardiovascular disease than those with an SSN.

Heat illness data strengthens vulnerability maps.

BACKGROUND: Previous extreme heat and human health studies have investigated associations either over time (e.g. case-crossover or time series analysis) or across geographic areas (e.g. spatial models), which may limit the study scope and regional variation. Our study combines a case-crossover design and spatial analysis to identify: 1) the most vulnerable counties to extreme heat; and 2) demographic and socioeconomic variables that are most strongly and consistently related to heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, acute renal disease, and respiratory disease) across 67 counties in the state of Florida, U. S over 2008-2012. METHODS: We first used a case-crossover design to examine the effects of air temperature on daily counts of health outcomes. We employed a time-stratified design with a 28-day comparison window. Referent periods were extracted from ±7, ±14, or ± 21 days to address seasonality. The results are expressed as odds ratios, or the change in the likelihood of each health outcome for a unit change in heat exposure. We then spatially examined the case-crossover extreme heat and health odds ratios and county level demographic and socioeconomic variables with multiple linear regression or spatial lag models. RESULTS: Results indicated that southwest Florida has the highest risks of cardiovascular disease, dehydration, acute renal disease, and respiratory disease. Results also suggested demographic and socioeconomic variables were significantly associated with the magnitude of heat-related health risk. The counties with larger populations working in farming, fishing, mining, forestry, construction, and extraction tended to have higher risks of dehydration and acute renal disease, whereas counties with larger populations working in installation, maintenance, and repair workers tended to have lower risks of cardiovascular, dehydration, acute renal disease, and respiratory disease. Finally, our results showed that high income counties consistently have lower health risks of dehydration, heat-related illness, acute renal disease, and respiratory disease. CONCLUSIONS: Our study identified different relationships with demographic/socioeconomic variables for each heat-sensitive health outcome. Results should be incorporated into vulnerability or risk indices for each health outcome.

Florida neighborhood analysis of social determinants and their relationship to life expectancy.

BACKGROUND: Social determinants of health (SDOH) contribute to unequal life expectancy (LE). Only a handful of papers have analyzed these relationships at the neighborhood level as opposed to the county level. This study draws on both the SDOH and social vulnerability literature to identify relevant factors affecting LE. METHODS: LE was calculated from mortality records for Florida from 2009 to 2013 for 3640 census tracts with reliable estimates. A spatial Durbin error model (SDEM) quantified the direction and magnitude of the factors to LE. The SDEM contains a spatial error term and jointly estimates both local and neighborhood associations. This methodology controls for non-independence between census tracts to provide unbiased statistical estimates. RESULTS: Factors significantly related to an increase in LE, include percentage (%) of the population who identify as Hispanic (beta coefficient [ß]: 0.06, p-value [P] < 0.001) and % of age dependent populations (% population < 5 years old and % population > 65) (ß: 0.13, P < 0.001). Conversely, the following factors exhibited significant negative LE associations, % of households with no automobile (ß: -0.05, P < 0.001), % of mobile homes (ß: -0.02, P < 0.001), and % of female headed households (ß: -0.11, P < 0.001). CONCLUSIONS: Results from the SDEM demonstrate social vulnerability indicators account for additional geographic LE variability beyond commonly studied SDOH. Empirical findings from this analysis can help local health departments identify drivers of spatial health disparities at the local level.

Using web data to improve surveillance for heat sensitive health outcomes.

BACKGROUND: Elevated and prolonged exposure to extreme heat is an important cause of excess summertime mortality and morbidity. To protect people from health threats, some governments are currently operating syndromic surveillance systems. However, A lack of resources to support time- and labor- intensive diagnostic and reporting processes make it difficult establishing region-specific surveillance systems. Big data created by social media and web search may improve upon the current syndromic surveillance systems by directly capturing people's individual and subjective thoughts and feelings during heat waves. This study aims to investigate the relationship between heat-related web searches, social media messages, and heat-related health outcomes. METHODS: We collected Twitter messages that mentioned "air conditioning (AC)" and "heat" and Google search data that included weather, medical, recreational, and adaptation information from May 7 to November 3, 2014, focusing on the state of Florida, U.S. We separately associated web data against two different sources of health outcomes (emergency department (ED) and hospital admissions) and five disease categories (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease). Seasonal and subseasonal temporal cycles were controlled using autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) and generalized linear model (GLM). RESULTS: The results show that the number of heat-related illness and dehydration cases exhibited a significant positive relationship with web data. Specifically, heat-related illness cases showed positive associations with messages (heat, AC) and web searches (drink, heat stroke, park, swim, and tired). In addition, terms such as park, pool, swim, and water tended to show a consistent positive relationship with dehydration cases. However, we found inconsistent relationships between renal illness and web data. Web data also did not improve the models for cardiovascular and respiratory illness cases. CONCLUSIONS: Our findings suggest web data created by social medias and search engines could improve the current syndromic surveillance systems. In particular, heat-related illness and dehydration cases were positively related with web data. This paper also shows that activity patterns for reducing heat stress are associated with several health outcomes. Based on the results, we believe web data could benefit both regions without the systems and persistently hot and humid climates where excess heat early warning systems may be less effective.

Minigrants to Local Health Departments: An Opportunity to Promote Climate Change Preparedness.

CONTEXT: Human health is threatened by climate change. While the public health workforce is concerned about climate change, local health department (LHD) administrators have reported insufficient knowledge and resources to address climate change. Minigrants from state to LHDs have been used to promote a variety of local public health initiatives. OBJECTIVE: To describe the minigrant approach used by state health departments implementing the Centers for Disease Control and Prevention's (CDC's) Building Resilience Against Climate Effects (BRACE) framework, to highlight successes of this approach in promoting climate change preparedness at LHDs, and to describe challenges encountered. DESIGN: Cross-sectional survey and discussion. INTERVENTION: State-level recipients of CDC funding issued minigrants to local public health entities to promote climate change preparedness, adaptation, and resilience. MAIN OUTCOME MEASURES: The amount of funding, number of LHDs funded per state, goals, selection process, evaluation process, outcomes, successes, and challenges of the minigrant programs. RESULTS: Six state-level recipients of CDC funding for BRACE framework implementation awarded minigrants ranging from $7700 to $28 500 per year to 44 unique local jurisdictions. Common goals of the minigrants included capacity building, forging partnerships with entities outside of health departments, incorporating climate change information into existing programs, and developing adaptation plans. Recipients of minigrants reported increases in knowledge, engagement with diverse stakeholders, and the incorporation of climate change content into existing programs. Challenges included addressing climate change in regions where the topic is politically sensitive, as well as the uncertainty about the long-term sustainability of local projects beyond the term of minigrant support. CONCLUSIONS: Minigrants can increase local public health capacity to address climate change. Jurisdictions that wish to utilize minigrant mechanisms to promote climate change adaptation and preparedness at the local level may benefit from the experience of the 6 states and 44 local health programs described.

Occupational heat exposure among municipal workers.

PURPOSE: Outdoor workers face elevated and prolonged heat exposures and have limited access to air-conditioned spaces. This study's overarching research aim is to increase knowledge of municipal worker heat exposure and adaptation practices. The study's sub-objectives are: (1) quantifying exposure misclassification from estimating personal heat exposure from the official weather station; (2) surveying worker's knowledge and practices to adapt to extreme heat; and (3) relating heat exposure and adaptation practices to self-reported thermal comfort. METHODS: Participants wore a personal heat exposure sensor over 7 days from June 1st to July 3rd, 2015 in Tallahassee, Florida US. Next, participants confirmed the days that they wore the sensor and reported their daily thermal comfort and heat adaptations. Finally, participants completed an extreme heat knowledge, attitudes, and practices survey. RESULTS: Some participants (37%) experienced hotter and more humid conditions (heat index > 2) than the weather station. The most common heat adaptations were staying hydrated (85%), wearing a hat (46%), and seeking shade (40%). During work hours, higher temperatures increased the odds (odds ratio: 1.21, 95% confidence interval: 1.03-1.41, p = 0.016) of a participant feeling too hot. Shifting work duty indoors made workers to feel more comfortable (odds ratio: 0.28, 95% confidence interval: 0.11-0.70, p = 0.005). CONCLUSION: In hot and humid climates, everyday, heat exposures continuously challenge the health of outdoor workers.

Social media responses to heat waves.

Social network services (SNSs) may benefit public health by augmenting surveillance and distributing information to the public. In this study, we collected Twitter data focusing on six different heat-related themes (air conditioning, cooling center, dehydration, electrical outage, energy assistance, and heat) for 182 days from May 7 to November 3, 2014. First, exploratory linear regression associated outdoor heat exposure to the theme-specific tweet counts for five study cities (Los Angeles, New York, Chicago, Houston, and Atlanta). Next, autoregressive integrated moving average (ARIMA) time series models formally associated heat exposure to the combined count of heat and air conditioning tweets while controlling for temporal autocorrelation. Finally, we examined the spatial and temporal distribution of energy assistance and cooling center tweets. The result indicates that the number of tweets in most themes exhibited a significant positive relationship with maximum temperature. The ARIMA model results suggest that each city shows a slightly different relationship between heat exposure and the tweet count. A one-degree change in the temperature correspondingly increased the Box-Cox transformed tweets by 0.09 for Atlanta, 0.07 for Los Angeles, and 0.01 for New York City. The energy assistance and cooling center theme tweets suggest that only a few municipalities used Twitter for public service announcements. The timing of the energy assistance tweets suggests that most jurisdictions provide heating instead of cooling energy assistance.

Influenza transmission during extreme indoor conditions in a low-resource tropical setting.

Influenza transmission occurs throughout the planet across wide-ranging environmental conditions. However, our understanding of the environmental factors mediating transmission is evaluated using outdoor environmental measurements, which may not be representative of the indoor conditions where influenza is transmitted. In this study, we examined the relationship between indoor environment and influenza transmission in a low-resource tropical population. We used a case-based ascertainment design to enroll 34 households with a suspected influenza case and then monitored households for influenza, while recording indoor temperature and humidity data in each household. We show that the indoor environment is not commensurate with outdoor conditions and that the relationship between indoor and outdoor conditions varies significantly across homes. We also show evidence of influenza transmission in extreme indoor environments. Specifically, our data suggests that indoor environments averaged 29 °C, 18 g/kg specific humidity, and 68 % relative humidity across 15 transmission events observed. These indoor settings also exhibited significant temporal variability with temperatures as high as 39 °C and specific and relative humidity increasing to 22 g/kg and 85 %, respectively, during some transmission events. However, we were unable to detect differences in the transmission efficiency by indoor temperature or humidity conditions. Overall, these results indicate that laboratory studies investigating influenza transmission and virus survival should increase the range of environmental conditions that they assess and that observational studies investigating the relationship between environment and influenza activity should use caution using outdoor environmental measurements since they can be imprecise estimates of the conditions that mediate transmission indoors.

Climatic Influences on Cryptococcus gattii [corrected] Populations, Vancouver Island, Canada, 2002-2004.

Vancouver Island, Canada, reports the world's highest incidence of Cryptococcus gattii infection among humans and animals. To identify key biophysical factors modulating environmental concentrations, we evaluated monthly concentrations of C. gatti in air, soil, and trees over a 3-year period. The 2 study datasets were repeatedly measured plots and newly sampled plots. We used hierarchical generalized linear and mixed effect models to determine associations. Climate systematically influenced C. gattii concentrations in all environmental media tested; in soil and on trees, concentrations decreased when temperatures were warmer. Wind may be a key process that transferred C. gattii from soil into air and onto trees. C. gattii results for tree and air samples were more likely to be positive during periods of higher solar radiation. These results improve the understanding of the places and periods with the greatest C. gattii colonization. Refined risk projections may help susceptible persons avoid activities that disturb the topsoil during relatively cool summer days.

Environmental predictors of seasonal influenza epidemics across temperate and tropical climates.

Human influenza infections exhibit a strong seasonal cycle in temperate regions. Recent laboratory and epidemiological evidence suggests that low specific humidity conditions facilitate the airborne survival and transmission of the influenza virus in temperate regions, resulting in annual winter epidemics. However, this relationship is unlikely to account for the epidemiology of influenza in tropical and subtropical regions where epidemics often occur during the rainy season or transmit year-round without a well-defined season. We assessed the role of specific humidity and other local climatic variables on influenza virus seasonality by modeling epidemiological and climatic information from 78 study sites sampled globally. We substantiated that there are two types of environmental conditions associated with seasonal influenza epidemics: "cold-dry" and "humid-rainy". For sites where monthly average specific humidity or temperature decreases below thresholds of approximately 11-12 g/kg and 18-21°C during the year, influenza activity peaks during the cold-dry season (i.e., winter) when specific humidity and temperature are at minimal levels. For sites where specific humidity and temperature do not decrease below these thresholds, seasonal influenza activity is more likely to peak in months when average precipitation totals are maximal and greater than 150 mm per month. These findings provide a simple climate-based model rooted in empirical data that accounts for the diversity of seasonal influenza patterns observed across temperate, subtropical and tropical climates.

Drinking water systems, hydrology, and childhood gastrointestinal illness in Central and Northern Wisconsin.

OBJECTIVES: This study investigated if the type of drinking water source (treated municipal, untreated municipal, and private well water) modifies the effect of hydrology on childhood (aged < 5 years) gastrointestinal illness. METHODS: We conducted a time series study to assess the relationship between hydrologic and weather conditions with childhood gastrointestinal illness from 1991 to 2010. The Central and Northern Wisconsin study area includes households using all 3 types of drinking water systems. Separate time series models were created for each system and half-year period (winter/spring, summer/fall). RESULTS: More precipitation (summer/fall) systematically increased childhood gastrointestinal illness in municipalities accessing untreated water. The relative risk of contracting gastrointestinal illness was 1.4 in weeks with 3 centimeters of precipitation and 2.4 in very wet weeks with 12 centimeters of precipitation. By contrast, gastrointestinal illness in private well and treated municipal areas was not influenced by hydrologic conditions, although warmer winter temperatures slightly increased incidence. CONCLUSIONS: Our study suggests that improved drinking water protection, treatment, and delivery infrastructure may improve public health by specifically identifying municipal water systems lacking water treatment that may transmit waterborne disease.

Biological control of mosquitoes in scrap tires in Brownsville, Texas, USA and Matamoros, Tamaulipas, Mexico.

Dengue periodically circulates in southern Texas and neighboring Tamaulipas, Mexico; thus, a closer examination of human and vector ecology at the northern limits of North American transmission may improve prevention activities. Scrap tires produce large mosquito populations and increase the risk of dengue transmission. Some households choose not to pay tire disposal fees, and many tires are illegally dumped in residential areas. Biological control may provide low-cost and environmentally friendly mosquito control. This pilot study evaluated the ability of Mesocyclops longisetus to reduce mosquito populations in existing residential scrap tire piles. Mosquito populations were measured by the number of all mosquito pupae within tires or adult Aedes aegypti and Ae. albopictus near piles. Mesocyclops longisetus treated piles did not significantly reduce total mosquito pupae (P = 0.07) in Matamoros, Mexico. The study also evaluated the efficacy of native Toxorhynchites moctezuma which preferentially colonized tire piles under vegetation cover in Brownsville, TX. Toxorhynchites moctezuma larvae significantly reduced total mosquito pupae, but the strength of control diminished over time.

Impact of the 2022 New Mexico, US wildfires on air quality and health.

The 2022 wildfires in New Mexico, United States, were unparalleled compared to past wildfires in the state in both their scale and intensity, resulting in poor air quality and a catastrophic loss of habitat and livelihood. Among all wildfires in New Mexico in 2022, six wildfires were selected for our study based on the size of the burn area and their proximity to populated areas. These fires accounted for approximately 90 % of the total burn area in New Mexico in 2022. We used a regional chemical transport model and data-fusion technique to quantify the contribution of these six wildfires (April 6 to August 22) on particulate matter (PM2.5: diameter ≤ 2.5 µm) and ozone (O3) concentrations, as well as the associated health impacts from short-term exposure. We estimated that these six wildfires emitted 152 thousand tons of PM2.5 and 287 thousand tons of volatile organic compounds to the atmosphere. We estimated that the average daily wildfire smoke PM2.5 across New Mexico was 0.3 µg/m3, though 1 h maximum exceeded 120 µg/m3 near Santa Fe. Average wildfire smoke maximum daily average 8-h O3 (MDA8-O3) contribution was 0.2 ppb during the study period over New Mexico. However, over the state 1 h maximum smoke O3 exceeded 60 ppb in some locations near Santa Fe. Estimated all-cause excess mortality attributable to short term exposure to wildfire PM2.5 and MDA8-O3 from these six wildfires were 18 (95 % Confidence Interval (CI), 15-21) and 4 (95 % CI: 3-6) deaths. Additionally, we estimate that wildfire PM2.5 was responsible for 171 (95 %: 124-217) excess cases of asthma emergency department visits. Our findings underscore the impact of wildfires on air quality and human health risks, which are anticipated to intensify with global warming, even as local anthropogenic emissions decline.

Aedes (Ochlerotatus) epactius along an elevation and climate gradient in Veracruz and Puebla States, México.

We report on the collection ofimmatures of Aedes (Ochlerotatus) epactius Dyar & Knab from artificial containers during July through September 2011 in 12 communities located along an elevation and climate gradient extending from sea level in Veracruz State to high elevations (>2,000 m) in Veracruz and Puebla States, México. Ae. epactius was collected from 11 of the 12 study communities; the lone exception was the highest elevation community along the transect (>2,400 m). This mosquito species was thus encountered at elevations ranging from near sea level in Veracruz City on the Gulf of México to above 2,100 m in Puebla City in the central highlands. Collection sites included the city of C6rdoba, located at approximately 850 m, from which some of the first described specimens of Ae. epactius were collected in 1908. Estimates for percentage of premises in each community with Ae. epactius pupae present, and abundance of Ae. epactius pupae on the study premises, suggest that along the transect in central México, the mosquito is present but rare at sea level, most abundant at mid-range elevations from 1,250-1,750 m and then decreases in abundance above 1,800 m. Statistically significant parabolic relationships were found between percentage of premises with Ae. epactius pupae present and average minimum daily temperature, cumulative growing degree-days, and rainfall. We recorded Ae. epactius immatures from a wide range of container types including cement water tanks, barrels/ drums, tires, large earthen jars, small discarded containers, buckets, cement water troughs, flower pots, cement water cisterns, and larger discarded containers. There were 45 documented instances of co-occurrence of Ae. epactius and Aedes aegypti (L.) immatures in individual containers.

Verifying Experimental Wet Bulb Globe Temperature Hindcasts Across the United States.

Hot and humid heat exposures challenge the health of outdoor workers engaged in occupations such as construction, agriculture, first response, manufacturing, military, or resource extraction. Therefore, government institutes developed guidelines to prevent heat-related illnesses and death during high heat exposures. The guidelines use Wet Bulb Globe Temperature (WBGT), which integrates temperature, humidity, solar radiation, and wind speed. However, occupational heat exposure guidelines cannot be readily applied to outdoor work places due to limited WBGT validation studies. In recent years, institutions have started providing experimental WBGT forecasts. These experimental products are continually being refined and have been minimally validated with ground-based observations. This study evaluated a modified WBGT hindcast using the historical National Digital Forecast Database and the European Centre for Medium-Range Weather Forecasts Reanalysis v5. We verified the hindcasts with hourly WBGT estimated from ground-based weather observations. After controlling for geographic attributes and temporal trends, the average difference between the hindcast and in situ data varied from -0.64°C to 1.46°C for different Köppen-Geiger climate regions, and the average differences are reliable for decision making. However, the results showed statistically significant variances according to geographical features such as aspect, coastal proximity, land use, topographic position index, and Köppen-Geiger climate categories. The largest absolute difference was observed in the arid desert climates (1.46: 95% CI: 1.45, 1.47), including some parts of Nevada, Arizona, Colorado, and New Mexico. This research investigates geographic factors associated with systematic WBGT differences and points toward ways future forecasts may be statistically adjusted to improve accuracy.