This study was conducted to examine, at the county level, the relationship between pediatric cancers incidence rate and atrazine and nitrate mean concentrations in surface and groundwater. A negative binomial regression analysis was performed to investigate the association between central nervous system (CNS) tumors, leukemia, lymphoma, and atrazine and nitrate mean concentrations in surface and groundwater. The age-adjusted brain and other CNS cancers incidence was higher than the national average in 63% of the Nebraska counties. After controlling for nitrate concentrations in surface and groundwater, counties with atrazine concentrations between 0.95 - 2.82 µg/L in both surface and groundwater had a higher incidence rate for pediatric cancers (brain and other CNS, leukemia, and lymphoma) compared to counties with surface and groundwater atrazine concentrations in the reference group (0.00 - 0.13 µg/L). Additionally, compared to counties with groundwater nitrate concentrations between 0 and 2 mg/L (reference group), counties with groundwater nitrate concentrations between 2.1 and 5 mg/L (group 2) had a higher incidence rate for pediatric brain and other CNS cancers (IRR=13.25; 95% CI: 13.00-13.50), leukemia (IRR=6.13; 95% CI: 6.02-6.26), and lymphoma (IRR=11.53; 95% CI: 11.32-11.75) after adjusting for all covariates in the model. While these findings do not indicate a causal relationship, they suggest that atrazine and nitrate may pose a significant risk relative to the genesis of pediatric brain and CNS cancers, leukemia, and lymphoma.

The scale and extent of the effects of COVID-19 on our lives is unmatched by any other recent natural disaster. Effective management of the spread and consequences of this pandemic can reduce the burden on health and help in managing the different costs by relaxing restrictions. Understanding this need, our interdisciplinary team of geo and health scientists at the University of Nebraska Medical Center (UNMC) developed a multi-layered interactive dashboard in March 2020. The dashboard provides an automatically updating map of COVID case numbers and their time series in Nebraska counties. Also, Nebraska’s pandemic response leaders can see each hospital and its number of beds and contact information, the location of dialysis centers, long term care facilities, and pharmacies; the name of the emergency response coordinator; and the number of electricity-dependent Medicare beneficiaries in each county. The UNMC Dashboard, has helped the emergency response and health departments of Nebraska. It has received attention from local to international level. In addition to garnering public recognition, the Dashboard established connections between our team and stakeholders in our original climate tracking projects, as well as with other groups with whom we had not previously collaborated. We have established a close connection with Nebraska Medicine, one of the top medical facilities in the region, and their demand forecasting team. Also, we have developed new connections with out of state contacts in health department, resulting into an expanded version of the dashboard. Additionally, the dashboard demonstrated our capabilities and strengthened our relationships with local health departments in Nebraska. One of our primary projects relates to public health emergency preparedness for extreme weather and climate events in Nebraska. The success of that project depends on collaboration with different health officials in the state, who are now more aware of our team and our capability to provide practical solutions and tools. We suggest that this system can adapt to different frameworks, such as the Emergency Risk Framework (ERF) by World Health Organization (WHO). Our system provides the foundation for the information sharing required by such systems -therefore helping with communication and decision making.

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 2011-2016. 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. During 2011-2016, we observed a significant decrease in the rate of HRI assuming natural simulations compared to the observed. About 15% of HRI is 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.

Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternative analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resulted Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combination of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized section. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings.

Drought is probably the most complex among natural hazards to assess its effects. While most drought indicators and risk assessments are developed around agricultural or water shortages effects of drought, its effect on human health is highly understudied because of its unclear and complicated path towards physical and mental health effects. This study assesses the health risk of the latest decadal drought over the US counties by spatially superimposing several proxy variables of counties’ health vulnerabilities over their drought levels. We have used different variations of Local Moran’s I statistics to assess the spatial distribution of drought-vulnerability in two five-year study periods (2010-2014 and 2015-2019) and their differences. Our results show large clusters of significant risk increase in the west due to increases in both vulnerability and hazard indicators in the second study period. Since the used vulnerability variables include indicators of agriculture, drinking water, and socioeconomic prosperities, the results of this study can help researchers and policymakers in these areas to distinguish areas in need of higher attention for interdisciplinary study and planning in national or regional scales.