Monitoring trends in lacrimator exposures using the National Poison Data System: 2000-2021.

CONTEXT: Lacrimators are used by individuals for personal defense and by police for crowd control during periods of civil unrest. Increased public awareness about their use has raised concerns about their application and safety. OBJECTIVE: To characterize patterns of lacrimator exposures in the United States, we describe temporal trends of calls to poison centers by demographics, substances, medical outcomes, exposure sites, and scenarios. METHODS: A retrospective data analysis was performed for all single-substance lacrimator exposures in the United States reported to the National Poison Data System between 2000 and 2021. Descriptive analyses were performed to examine demographic characteristics, geographic distribution, product types and medical outcomes associated with lacrimator exposures. RESULTS: A total of 107,149 lacrimator exposure calls were identified. There was an overall decrease in calls per year, from 6,521 calls in 2000 to 2,520 in 2020, followed by an increase to 3,311 calls in 2021. A declining trend was observed independent of total poison center call volume. Oleoresin capsicum was the most commonly reported substance (81,990, 76.5%). Individuals ages 19 years and younger accounted for 62% of calls, but adults ages 20 and over were more likely to develop major clinical effects (odds ratio 3.03; 95% confidence interval 1.91-4.81; P < 0.0001). The most common exposure site was "own residence," followed by schools. School exposures accounted for 15.8% of exposures in children ages 6-12 years and 37.7% in adolescents. Among calls with documented scenarios, 19.7% involved unintentional exposures due to children accessing lacrimators. CONCLUSION: Lacrimator exposure calls to United States poison centers decreased from 2000 to 2021. Most calls pertain to oleoresin capsicum and individuals ages 19 and younger. Improper storage allowing children to have access to these chemicals, is a common scenario. Public safety interventions such as education about safe storage and use of lacrimators, improved product design, or regulatory changes may prevent unintentional exposures.

Assessment of trace elements directly from archived total suspended particulate filters by laser ablation ICP-MS: A case study of South Carolina.

Background: Exposure to particulate air pollution is one of the greatest environmental risk factors for adverse human health outcomes. However, the constituents that may be responsible for such adverse health effects have not been fully studied. Methods: Total suspended particulates filters collected every 6 days in 2011 from three South Carolina locations were used in this case study. An inductively coupled plasma mass spectrometer interfaced with a laser ablation system (LA-ICP-MS) was used to directly analyze 41 inorganic elemental species on air pollution filters. Then, machine learning and multivariate statistical methods was employed to identify combinatorial patterns in the data and classify sites based on their elemental composition. Results: Forty-one elements were assessed and 33 were used in subsequent analysis. Correlations between United States Environmental Protection Agency (US EPA)'s chemical analysis dataset and data from the current study revealed significant associations between 7/15 elements with enough variation for comparison (r between 0.28 to 0.66, p<0.05). Subsequent multivariate analyses revealed four distinct patterns in the distribution of elements by sample location throughout the year. Conclusion: The different airborne elements may need to be assessed to understand combinations of elements which occur together over space and/or time. Such information can be helpful in planning effective counter measures and strategies to control particulate air pollution.

COVID-19 Scientific Publications From the Centers for Disease Control and Prevention, January 2020-January 2022.

OBJECTIVE: High-quality scientific evidence underpins public health decision making. The Centers for Disease Control and Prevention (CDC) agency provides scientific data, including during public health emergencies. To understand CDC's contributions to COVID-19 science, we conducted a bibliometric evaluation of publications authored by CDC scientists from January 20, 2020, through January 20, 2022, by using a quality improvement approach (SQUIRE 2.0). METHODS: We catalogued COVID-19 articles with ≥1 CDC-affiliated author published in a scientific journal and indexed in the World Health Organization's COVID-19 database. We identified priority topic areas from the agency's COVID-19 Public Health Science Agenda by using keyword scripts in EndNote and then assessed the impact of the published articles by using Scopus and Altmetric. RESULTS: During the first 2 years of the agency's pandemic response, CDC authors contributed to 1044 unique COVID-19 scientific publications in 208 journals. Publication topics included testing (n = 853, 82%); prevention strategies (n = 658, 63%); natural history, transmission, breakthrough infections, and reinfections (n = 587, 56%); vaccines (n = 567, 54%); health equity (n = 308, 30%); variants (n = 232, 22%); and post-COVID-19 conditions (n = 44, 4%). Publications were cited 40 427 times and received 81 921 news reports and 1 058 893 social media impressions. As the pandemic evolved, CDC adapted to address new scientific questions, including vaccine effectiveness, safety, and access; viral variants, including Delta and Omicron; and health equity. CONCLUSION: The agency's COVID-19 Public Health Science Agenda helped guide impactful scientific activities. CDC continues to evaluate COVID-19 priority topic areas and contribute to development of new scientific work. CDC is committed to monitoring emerging issues and addressing gaps in evidence needed to improve health.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis.

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Using Bayesian time-stratified case-crossover models to examine associations between air pollution and "asthma seasons" in a low air pollution environment.

Many areas of the United States have air pollution levels typically below Environmental Protection Agency (EPA) regulatory limits. Most health effects studies of air pollution use meteorological (e.g., warm/cool) or astronomical (e.g., solstice/equinox) definitions of seasons despite evidence suggesting temporally-misaligned intra-annual periods of relative asthma burden (i.e., "asthma seasons"). We introduce asthma seasons to elucidate whether air pollutants are associated with seasonal differences in asthma emergency department (ED) visits in a low air pollution environment. Within a Bayesian time-stratified case-crossover framework, we quantify seasonal associations between highly resolved estimates of six criteria air pollutants, two weather variables, and asthma ED visits among 66,092 children ages 5-19 living in South Carolina (SC) census tracts from 2005 to 2014. Results show that coarse particulates (particulate matter <10 µm and >2.5 µm: PM10-2.5) and nitrogen oxides (NOx) may contribute to asthma ED visits across years, but are particularly implicated in the highest-burden fall asthma season. Fine particulate matter (<2.5 µm: PM2.5) is only associated in the lowest-burden summer asthma season. Relatively cool and dry conditions in the summer asthma season and increased temperatures in the spring and fall asthma seasons are associated with increased ED visit odds. Few significant associations in the medium-burden winter and medium-high-burden spring asthma seasons suggest other ED visit drivers (e.g., viral infections) for each, respectively. Across rural and urban areas characterized by generally low air pollution levels, there are acute health effects associated with particulate matter, but only in the summer and fall asthma seasons and differing by PM size.

Update of the Blood Lead Reference Value - United States, 2021.

The negative impact of lead exposure on young children and those who become pregnant is well documented but is not well known by those at highest risk from this hazard. Scientific evidence suggests that there is no known safe blood lead level (BLL), because even small amounts of lead can be harmful to a child's developing brain (1). In 2012, CDC introduced the population-based blood lead reference value (BLRV) to identify children exposed to more lead than most other children in the United States. The BLRV should be used as a guide to 1) help determine whether medical or environmental follow-up actions should be initiated for an individual child and 2) prioritize communities with the most need for primary prevention of exposure and evaluate the effectiveness of prevention efforts. The BLRV is based on the 97.5th percentile of the blood lead distribution in U.S. children aged 1-5 years from National Health and Nutrition Examination Survey (NHANES) data. NHANES is a complex, multistage survey designed to provide a nationally representative assessment of health and nutritional status of the noninstitutionalized civilian adult and child populations in the United States (2). The initial BLRV of 5 µg/dL, established in 2012, was based on data from the 2007-2008 and 2009-2010 NHANES cycles. Consistent with recommendations from a former advisory committee, this report updates CDC's BLRV in children to 3.5 µg/dL using NHANES data derived from the 2015-2016 and 2017-2018 cycles and provides helpful information to support adoption by state and local health departments, health care providers (HCPs), clinical laboratories, and others and serves as an opportunity to advance health equity and environmental justice related to preventable lead exposure. CDC recommends that public health and clinical professionals focus screening efforts on populations at high risk based on age of housing and sociodemographic risk factors. Public health and clinical professionals should collaborate to develop screening plans responsive to local conditions using local data. In the absence of such plans, universal BLL testing is recommended. In addition, jurisdictions should follow the Centers for Medicare & Medicaid Services requirement that all Medicaid-enrolled children be tested at ages 12 and 24 months or at age 24-72 months if they have not previously been screened (3).

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters.

The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.

A Bayesian spatio-temporal analysis of neighborhood pediatric asthma emergency department visit disparities.

Asthma disparities have complex, neighborhood-level drivers that are not well understood. Consequently, identifying particular contextual factors that contribute to disparities is a public health goal. We study pediatric asthma emergency department (ED) visit disparities and neighborhood factors associated with them in South Carolina (SC) census tracts from 1999 to 2015. Leveraging a Bayesian framework, we identify risk clusters, spatially-varying relationships, and risk percentile-specific associations. Clusters of high risk occur in both rural and urban census tracts with high probability, with neighborhood-specific associations suggesting unique risk factors for each locale. Bayesian methods can help clarify the neighborhood drivers of health disparities.

Climate Change and Health: Local Solutions to Local Challenges.

PURPOSE OF REVIEW: Climate change has direct impacts on human health, but those impacts vary widely by location. Local health impacts depend on a large number of factors including specific regional climate impacts, demographics and human vulnerabilities, and existing local adaptation capacity. There is a need to incorporate local data and concerns into climate adaptation plans and evaluate different approaches. RECENT FINDINGS: The Centers for Disease Control and Prevention (CDC) has provided funding, technical assistance, and an adaptation framework to assist localities with climate planning and activities. The differing processes with which states, cities, and tribes develop and implement adaptation plans have been observed. We outline examples of the implementation of CDC's framework and activities for local adaptation, with a focus on case studies at differing jurisdictional levels (a state, a city, and a sovereign tribe). The use of local considerations and data are important to inform climate adaptation. The adaptable implementation of CDC's framework is helping communities protect health.

Correction to: A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma.

Unfortunately, the original version of the article [1] contained an error. A typo in the main equation (Eq. 1) has been introduced during the production process. The operator " = " in Eq. 1 "log(θik) =  α + ui…" was missing.

Cleaning and Disinfectant Chemical Exposures and Temporal Associations with COVID-19 - National Poison Data System, United States, January 1, 2020-March 31, 2020.

On January 19, 2020, the state of Washington reported the first U.S. laboratory-confirmed case of coronavirus disease 2019 (COVID-19) caused by infection with SARS-CoV-2 (1). As of April 19, a total of 720,630 COVID-19 cases and 37,202 associated deaths* had been reported to CDC from all 50 states, the District of Columbia, and four U.S. territories (2). CDC recommends, with precautions, the proper cleaning and disinfection of high-touch surfaces to help mitigate the transmission of SARS-CoV-2 (3). To assess whether there might be a possible association between COVID-19 cleaning recommendations from public health agencies and the media and the number of chemical exposures reported to the National Poison Data System (NPDS), CDC and the American Association of Poison Control Centers surveillance team compared the number of exposures reported for the period January-March 2020 with the number of reports during the same 3-month period in 2018 and 2019. Fifty-five poison centers in the United States provide free, 24-hour professional advice and medical management information regarding exposures to poisons, chemicals, drugs, and medications. Call data from poison centers are uploaded in near real-time to NPDS. During January-March 2020, poison centers received 45,550 exposure calls related to cleaners (28,158) and disinfectants (17,392), representing overall increases of 20.4% and 16.4% from January-March 2019 (37,822) and January-March 2018 (39,122), respectively. Although NPDS data do not provide information showing a definite link between exposures and COVID-19 cleaning efforts, there appears to be a clear temporal association with increased use of these products.

Public Health Responses to COVID-19 Outbreaks on Cruise Ships - Worldwide, February-March 2020.

An estimated 30 million passengers are transported on 272 cruise ships worldwide each year* (1). Cruise ships bring diverse populations into proximity for many days, facilitating transmission of respiratory illness (2). SARS-CoV-2, the virus that causes coronavirus disease (COVID-19) was first identified in Wuhan, China, in December 2019 and has since spread worldwide to at least 187 countries and territories. Widespread COVID-19 transmission on cruise ships has been reported as well (3). Passengers on certain cruise ship voyages might be aged ≥65 years, which places them at greater risk for severe consequences of SARS-CoV-2 infection (4). During February-March 2020, COVID-19 outbreaks associated with three cruise ship voyages have caused more than 800 laboratory-confirmed cases among passengers and crew, including 10 deaths. Transmission occurred across multiple voyages of several ships. This report describes public health responses to COVID-19 outbreaks on these ships. COVID-19 on cruise ships poses a risk for rapid spread of disease, causing outbreaks in a vulnerable population, and aggressive efforts are required to contain spread. All persons should defer all cruise travel worldwide during the COVID-19 pandemic.

A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma.

BACKGROUND: Ecologic health studies often rely on outcomes from health service utilization data that are limited by relatively coarse spatial resolutions and missing geographic information, particularly neighborhood level identifiers. When fine-scale geographic data are missing, the ramifications and strategies for addressing them are not well researched or developed. This study illustrates a novel spatio-temporal framework that combines a geographic identifier assignment (i.e., geographic imputation) algorithm with predictive Bayesian variable selection to identify neighborhood factors associated with disparities in emergency department (ED) visits for asthma. METHODS: ED visit records with missing fine-scale spatial identifiers (~ 20%) were geocoded using information from known, coarser, misaligned spatial units using an innovative geographic identifier assignment algorithm. We then employed systematic variable selection in a spatio-temporal Bayesian hierarchical model (BHM) predictive framework within the NIMBLE package in R. Our novel methodology is illustrated in an ecologic case study aimed at identifying neighborhood-level predictors of asthma ED visits in South Carolina, United States, from 1999 to 2015. The health outcome was annual ED visit counts in small areas (i.e., census tracts) with primary diagnoses of asthma (ICD9 codes 493.XX) among children ages 5 to 19 years. RESULTS: We maintained 96% of ED visit records for this analysis. When the algorithm used areal proportions as probabilities for assignment, which addressed differential missingness of census tract identifiers in rural areas, variable selection consistently identified significant neighborhood-level predictors of asthma ED visit risk including pharmacy proximity, average household size, and carbon monoxide interactions. Contrasted with common solutions of removing geographically incomplete records or scaling up analyses, our methodology identified critical differences in parameters estimated, predictors selected, and inferences. We posit that the differences were attributable to improved data resolution, resulting in greater power and less bias. Importantly, without this methodology, we would have inaccurately identified predictors of risk for asthma ED visits, particularly in rural areas. CONCLUSIONS: Our approach innovatively addressed several issues in ecologic health studies, including missing small-area geographic information, multiple correlated neighborhood covariates, and multiscale unmeasured confounding factors. Our methodology could be widely applied to other small-area studies, useful to a range of researchers throughout the world.

Reported Neighborhood Traffic and the Odds of Asthma/Asthma-Like Symptoms: A Cross-Sectional Analysis of a Multi-Racial Cohort of Children.

Asthma in children poses a significant clinical and public health burden. We examined the association between reported neighborhood traffic (a proxy for traffic-related air pollution) and asthma among 855 multi-racial children aged 4-8 years old who participated in the Environmental Influences on Child Health Outcomes (ECHO) cohort. We hypothesized that high neighborhood traffic density would be associated with the prevalence of asthma. Asthma/asthma-like symptoms (defined as current and/or past physician diagnosed asthma, past wheezing, or nighttime cough or wheezing in the past 12 months) was assessed by parental report. The relationship between neighborhood traffic and asthma/asthma-like symptoms was assessed using logistic regression. The prevalence of asthma/asthma-like symptoms among study participants was 23%, and 15% had high neighborhood traffic. Children with significant neighborhood traffic had a higher odds of having asthma/asthma-like symptoms than children without neighborhood traffic [adjusted OR = 2.01 (95% CI: 1.12, 3.62)] after controlling for child's race-ethnicity, age, sex, maternal education, family history of asthma, play equipment in the home environment, public parks, obesity and prescribed asthma medication. Further characterization of neighborhood traffic is needed since many children live near high traffic zones and significant racial/ethnic disparities exist.

Designing and executing a functional exercise to test a novel informatics tool for mass casualty triage.

OBJECTIVE: The testing of informatics tools designed for use during mass casualty incidents presents a unique problem as there is no readily available population of victims or identical exposure setting. The purpose of this article is to describe the process of designing, planning, and executing a functional exercise to accomplish the research objective of validating an informatics tool specifically designed to identify and triage victims of irritant gas syndrome agents. MATERIALS AND METHODS: During a 3-year time frame, the research team and partners developed the Emergency Department Informatics Computational Tool and planned a functional exercise to test it using medical records data from 298 patients seen in 1 emergency department following a chlorine gas exposure in 2005. RESULTS: The research team learned valuable lessons throughout the planning process that will assist future researchers with developing a functional exercise to test informatics tools. Key considerations for a functional exercise include contributors, venue, and information technology needs (ie, hardware, software, and data collection methods). DISCUSSION: Due to the nature of mass casualty incidents, testing informatics tools and technology for these incidents is challenging. Previous studies have shown a functional exercise as a viable option to test informatics tools developed for use during mass casualty incidents. CONCLUSION: Utilizing a functional exercise to test new mass casualty management technology and informatics tools involves a painstaking and complex planning process; however, it does allow researchers to address issues inherent in studying informatics tools for mas casualty incidents.