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.

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.

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.

Impacts of Sugarcane Fires on Air Quality and Public Health in South Florida.

BACKGROUND: Preharvest burning of sugarcane is a common agricultural practice in Florida, which produces fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5)] that is associated with higher mortality. OBJECTIVES: We estimated premature mortality associated with exposure to PM2.5 from sugarcane burning in people age 25 y and above for 20 counties in South Florida. METHODS: We combined information from an atmospheric dispersion model, satellites, and surface measurements to quantify PM2.5 concentrations in South Florida and the fraction of PM2.5 from sugarcane fires. From these concentrations, estimated mortalities attributable to PM2.5 from sugarcane fires were calculated by census tract using health impact functions derived from literature for six causes of death linked to PM2.5. Confidence intervals (CI) are provided based on Monte Carlo simulations that propagate uncertainty in the emissions, dispersion model, health impact functions, and demographic data. RESULTS: Sugarcane fires emitted an amount of primary PM2.5 similar to that of motor vehicles in Florida. PM2.5 from sugarcane fires is estimated to contribute to mortality rates within the Florida Sugarcane Growing Region (SGR) by 0.4 death per 100,000 people per year (95% CI: 0.3, 1.6 per 100,000). These estimates imply 2.5 deaths per year across South Florida were associated with PM2.5 from sugarcane fires (95% CI: 1.2, 6.1), with 0.16 in the SGR (95% CI: 0.09, 0.6) and 0.72 in Palm Beach County (95% CI: 0.17, 2.2). DISCUSSION: PM2.5 from sugarcane fires was estimated to contribute to mortality risk across South Florida, particularly in the SGR. This is consistent with prior studies that documented impacts of sugarcane fire on air quality but did not quantify mortality. Additional health impacts of sugarcane fires, which were not quantified here, include exacerbating nonfatal health conditions such as asthma and cardiovascular problems. Harvesting sugarcane without field burning would likely reduce PM2.5 and health burdens in this region. https://doi.org/10.1289/EHP9957.

Assessment of an evacuation shelter program for people with access and functional needs in Monroe County, Florida during Hurricane Irma.

This case study presents an evaluation framework to assess the facilitating and constraining factors that influenced the emergency response, operation, and management of a Special Needs Shelter Program in Monroe County, Florida during Hurricane Irma in 2017. A qualitative analysis of key documents and discussions with agencies directly involved in the Monroe County Special Needs Shelter Program was used to assess four major emergency response processes: notifications and communications, evacuation and transportation, sheltering, and interagency coordination. A critical cross-cutting theme emerged, which was a lack of a common definition for populations with "special needs" across different agencies resulting in uncertainties about who should be admitted to the Special Needs Shelter and have access to their services. We generate public health and emergency management lessons to inform future adaptation, preparedness, and response plans to extreme weather events for populations with access and functional needs in Monroe County and Florida's coastal communities more broadly.

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.

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.

Hurricane Michael and Adverse Birth Outcomes in the Florida Panhandle: Analysis of Vital Statistics Data.

OBJECTIVE: The aim of this study was to examine birth outcomes in areas affected by Hurricane Michael. METHODS: Vital statistics data of 2017-2019 were obtained from the state of Florida. Births occurring in the year before and after the date of Hurricane Michael (October 7, 2018) were used. Florida counties were divided into 3 categories reflecting extent of impact from Hurricane Michael. Birth outcomes including incidence of preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) were also compared before and after Hurricane Michael. Spontaneous and indicated PTBs were distinguished based on previously published algorithms. Multiple regression was used to control for potential confounders. RESULTS: Both LBW (aRR 1.19, 95% CI: 1.07, 1.32) and SGA (aRR 1.11, 95% CI: 1.01, 1.21) were higher in the year after Michael than the year before in the most-affected area; a similar effect was not seen in other areas. A stronger effect was seen for exposure in the first trimester or in the 2 months after Michael than in the second or third trimester. CONCLUSION: Consistent with many previous studies, this study of Hurricane Michael found an effect on fetal growth.

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.

Investigating city bike rental usage and wet-bulb globe temperature.

Extreme heat exacerbates human illness and constrains the intensity and/or duration of outdoor activities. Temperature is an incomplete metric of outdoor heat exposures. By contrast, Wet Bulb Globe Temperature (WBGT) is a heat exposure metric that considers air temperature, moisture, solar radiation, and wind speed. In the USA, bicycle activity increased by 60% from 2000 to 2010. Several studies examined weather conditions and bicycling activities. However, few studies examined how the public should conduct their daily physical activities per weather conditions.This study investigated the relationship between WBGT and shared city bicycle activity in New York City (NYC) and San Francisco (SF), USA. Generalized Additive Models examined nonlinear relationships between WBGT and bicycle activity while controlling for rider demographics and temporal trends. Next, bootstrapping estimated the "peak point", when the relationship between the bike rentals and WBGT notably changed.The analysis also examined whether the heat warning messages affected cycling activities. We found that the number of rented bikes declined at different peak points in each city. The peak point was in NYC at 34.3°C (95% CI 33°C-35°C) and 10.8°C (95% CI 10-12°C) in SF. Somewhat paradoxically, bike rentals increased when heat warnings were issued in both cities.

Knowledge, attitudes, and practices of Anopheles mosquito control through insecticide treated nets and community-based health programs to prevent malaria in East Sumba Island, Indonesia.

With an estimated 241 million human cases and 627,000 deaths in 2020, malaria remains a significant and ongoing global health challenge. This study employs a qualitative approach to investigate knowledge, attitudes, and practices surrounding mosquito control and prevention methods in East Sumba Regency, Indonesia. While malaria is under control in much of Indonesia, transmission in Sumba Island remains high, with incidence as high as 500 per 1000 population in some areas. A qualitative study was undertaken to explore use of insecticide treated nets, (ITNs), traditional Sumbanese mosquito control methods, and the role of women, integrated health service posts, (posyandu) and community-based health workers (kaders) in combatting malaria and controlling mosquitoes. Focus group discussions (n = 7) were conducted in East Sumba Island stratified by urban/rural location and level of malaria transmission. Key informant interviews (n = 14) were conducted with religious leaders, health workers, and women's group leaders. Results indicate that environmental conditions, such as high temperatures, were common deterrents to regular ITN use. Furthermore, our results suggest that community embedded health workers, kaders, and health service posts, posyandu, play an important role in information dissemination related to mosquitoes and mosquito-borne diseases as well as the distribution and use of ITNs in East Sumba Island. The role of the posyandu and kaders could be expanded to improve malaria prevention by integration with educational campaigns, aiding ITN distributions, and malaria diagnosis and treatment. This study is the first to examine mosquito-borne disease-related knowledge, attitudes, and practices in East Sumba Island, Indonesia. Results could improve mosquito control and malaria prevention by providing insights into local knowledge of Anopheles mosquitoes and malaria as well. Tailoring mosquito control and malaria prevention strategies around local knowledge and perceptions is likely to be more acceptable and sustainable.

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.

Assessing the effects of disasters and their aftermath on pregnancy and infant outcomes: A conceptual model.

Although many studies have examined broad patterns of effects on pregnancy and infant outcomes after disasters, the causes of adverse outcomes are not always clear. Disasters cause interrelated exposure to environmental pollutants, psychological stressors, and lack of health care, and interacts with other social determinants of health. This topical review examines the short- and long-term effects of disasters on pregnancy and how they are mediated by social, behavioral, and environmental effects. In the short term, disasters are associated with physical trauma, adverse environmental exposures, and unstable housing. In the longer term, disasters may lead to relocation, changes in family functioning, and negative economic effects. These aspects of disaster exposure, in turn, lead to lack of access to health care, increased stress and negative mental health outcomes, and negative behavioral changes, including smoking and substance use, poor nutrition, physical overexertion and limited activity, and reduction in breastfeeding. All of these factors interact with social determinants of health to worsen effects on the most vulnerable women, infants, and communities. Few interventions after disasters have been tested. With the increase in disasters due to climate change and the ongoing coronavirus pandemic, the models of effects of disasters and their human health consequences need increasing refinement, and, more importantly, should be applied to interventions that improve disaster prevention, mitigation, and response.

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.

Effects of Hurricane Michael on Access to Care for Pregnant Women and Associated Pregnancy Outcomes.

Background: Disasters are associated with worse perinatal outcomes, perhaps due to inadequate prenatal care (PNC). Methods: Using 2017-2019 Florida vital statistics, we compared PNC use before and after Hurricane Michael. We categorized counties as most affected (Area A) or less affected (Area B and C). We examined whether Michael's effects on perinatal outcomes varied by maternity care availability and used the Baron and Kenny method to assess whether delayed PNC initiation mediated perinatal outcomes. Log-binomial regression and semi-parametric linear regression were used, controlling for maternal and ZIP code tabulation area characteristics. Results: Compared to the one-year period pre-Michael, the week of the first PNC was later in all areas in the one-year period post-Michael, with the largest change in Area A (adjusted difference 0.112, 95% CI: 0.055-0.169), where women were less likely to receive PNC overall (aRR = 0.994, 95% CI = 0.990-0.998) and more likely to have inadequate PNC (aRR = 1.193, 95% CI = 1.127-1.264). Michael's effects on perinatal outcomes did not vary significantly by maternity care availability within Area A. Delayed PNC initiation appeared to mediate an increased risk in small for gestational age (SGA) births after Michael. Conclusion: Women in Area A initiated PNC later and had a higher likelihood of inadequate PNC. Delayed PNC initiation may partially explain increased risk of SGA.

Spatial Outcomes of Soft Tissue Sarcoma in Southern West Virginia.

Introduction Dioxins, polychlorinated biphenyls (PCBs), and 2,3,7,8-Tetrachlorodibenzodioxin (TCDDs) are persistent organic pollutants widely distributed in the food chain. For over 50 years, the Monsanto plant in Nitro, West Virginia, created dioxin waste while producing herbicides, Agent Orange (during the Vietnam War), and different forms of rubber. Recent and past literature has established a link between the Monsanto plant and increased cancer cases within the region. Soft tissue sarcoma is one of the few specific cancers that has been linked to dioxin exposure. This pilot study examined whether sarcoma cases were clustered or randomly distributed within Kanawha County, West Virginia over the years 2000 to 2013. We hypothesize that sarcoma cancer cases will be spatially clustered. Methods This study assessed the spatial distribution of cancer patients with addresses within the Nitro, West Virginia, and study area. The Charleston Area Medical Center shared soft tissue sarcoma (n = 97) cases from 2000 to 2013. An unweighted K function with confidence intervals (99 Monte Carlo permutations) and 10 distance at 2800 meters each band analyzed the distribution of cases. Results The results suggest that sarcoma cases are slightly clustered within the study area. The region also has a high concentration of chemical and industrial sites. The eighth distance band exhibited the greatest difference (11384), between the expected versus the observed K function. Conclusion The unweighted K function shows non-random clustering. Future studies could investigate possible associations to industrial, chemical, or other possible point source contamination within the study area.

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.

Seasonal characteristics of influenza vary regionally across US.

Given substantial regional differences in absolute humidity across the US and our understanding of the relationship between absolute humidity and influenza, we may expect important differences in regional seasonal influenza activity. Here, we assessed cross-seasonal influenza activity by comparing counts of positive influenza A and B rapid test results during the influenza season versus summer baseline periods for the 2016/2017 and 2017/2018 influenza years. Our analysis indicates significant regional patterns in cross-seasonal influenza activity, with relatively fewer influenza cases during the influenza season compared to summertime baseline periods in humid areas of the US, particularly in Florida and Hawaii. The cross-seasonal ratios vary from year-to-year and influenza type, but the geographic patterning of the ratios is relatively consistent. Mixed-effects regression models indicated absolute humidity during the influenza season was the strongest predictor of cross-seasonal influenza activity, suggesting a relationship between absolute humidity and cross-seasonal influenza activity. There was also evidence that absolute humidity during the summer plays a role, as well. This analysis suggests that spatial variation in seasonal absolute humidity levels may generate important regional differences in seasonal influenza activity and dynamics in the US.