Emergency department (ED) visits during influenza seasons represent a critical yet less examined indicator of the acute burden of influenza. This study investigates the burden of influenza-associated ED visits in six U.S. cities during influenza seasons from 2005-06 to 2016-17. Using a time-series design, we estimated associations between daily ED visits and weekly influenza activity data from the Influenza Hospitalization Surveillance Network (FluSurv-NET). A counterfactual approach was then used to calculate attributable expected ED. Highest influenza-associated rates were observed among the youngest (0-4 years) and oldest (65+ years) age groups. Combining estimates across seasons, the influenza-associated ED visit rate for respiratory diseases was almost six times larger compared to the subset of ED visits that resulted in hospitalization: 364 per 100,000 population (95% CI: 294-435) for total ED visits versus 58 per 100,000 population (95% CI: 45-71) for hospitalization. This difference was particularly large for the 0-4 year age group: 911 per 100,000 population (95% CI: 558-1,263) for total ED visits versus 43 per 100,000 population (95% CI: 15-71) for hospitalization. This study highlights the substantial burden of influenza on emergency healthcare services and the importance of integrating such data into public health planning and influenza management strategies.

Background: Pollen exposure is associated with substantial respiratory morbidity, but its potential impact on cardiovascular disease (CVD) remains less understood. This study aimed to investigate the associations between daily levels of 13 pollen types and emergency department (ED) visits for eight CVD outcomes over a 26-year period in Atlanta, GA. Methods: We acquired pollen data from Atlanta Allergy & Asthma, a nationally certified pollen counting station, and ED visit data from individual hospitals and the Georgia Hospital Association. We performed time-series analyses using quasi-Poisson distributed lag models, with primary analyses assessing 3-day (lag 0-2 days) pollen levels. Models controlled for temporally varying covariates, including air pollutants. Results: During 1993-2018, there were 1,573,968 CVD ED visits. Most pairwise models of the 13 pollen types and eight CVD outcomes showed no association, with a few exceptions potentially due to chance. Conclusion: We found limited evidence of the impact of pollen on cardiovascular morbidity in Atlanta. Further study on pollen exposures in different climactic zones and exploration of pollen-pollution mixture effects is warranted. Copyright © 2024 The Author(s).

The purpose of this study is to test, for the first time, the association between spatial social polarization and incarceration among people who inject drugs (PWID) in 19 large U.S. metropolitan statistical areas (MSAs) in 2015. PWID were recruited from MSAs for the Centers for Disease Control and Prevention's 2015 National HIV Behavioral Surveillance. Administrative data were used to describe the ZIP-code areas, counties, and MSAs where PWID lived. We operationalized spatial polarization using the Index of Concentration at the Extremes (ICE), a measure that reflects polarization in race and household income at the ZIP-code level. We tested the association between spatial polarization and odds of past-year arrest and detainment using multilevel multivariable models. We found 37% of the sample reported being incarcerated in the past year. Report of past-year incarceration varied by race/ethnicity: 45% of non-Hispanic white PWID reported past-year incarceration, as did 25% of non-Hispanic Black PWID, and 43% of Hispanic/Latino PWID (N = 9047). Adjusted odds ratios suggest that Black PWID living in ZIP-code areas with a higher ICE score, meaning more white and affluent, had higher odds of past-year incarceration, compared to white PWID. In previous research, incarceration has been found to be associated with HIV acquisition and can deter PWID from engaging in harm reduction activities. © 2023

BACKGROUND: Compared to many environmental risk factors, the relationship between pollen and asthma is understudied, including how associations may differ by pollen type and between subgroups, and how associations may be changing over time. OBJECTIVES: We evaluated the association between ambient pollen concentrations and emergency department (ED) visits for asthma and wheeze in Atlanta, Georgia during 1993-2018. We estimated overall associations for 13 individual pollen taxa, as well as associations by decade, race, age (5-17, 18-64, 65+), and insurance status (Medicaid vs non-Medicaid). METHODS: Speciated pollen data were acquired from Atlanta Allergy & Asthma, a nationally certified pollen counting station. ED visit data were obtained from individual hospitals and from the Georgia Hospital Association. We performed time-series analyses using quasi-Poisson distributed lag models, with primary analyses assessing 3-day (lag 0-2 days) pollen levels. Models controlled for day of week, holidays, air temperature, month, year, and month-by-year interactions. RESULTS: From 1993 to 2018, there were 686,259 ED visits for asthma and wheeze in the dataset, and the number of ED visits increased over time. We observed positive associations of asthma and wheeze ED visits with nine of the 13 pollen taxa: trees (maple, birch, pine, oak, willow, sycamore, and mulberry), two weeds (nettle and pigweed), and grasses. Rate ratios indicated 1-8% increases in asthma and wheeze ED visits per standard deviation increases in pollen. In general, we observed stronger associations in the earliest period (1993-2000), in younger people, and in Black patients; however, results varied by pollen taxa. CONCLUSIONS: Some, but not all, types of pollen are associated with increased ED visits for asthma/wheeze. Associations are generally higher in Black and younger patients and appear to have decreased over time.

In the United States, COVID-19 has become a leading cause of death since 2020. However, the number of COVID-19 deaths reported from death certificates is likely to represent an underestimate of the total deaths related to SARS-CoV-2 infections. Estimating those deaths not captured through death certificates is important to understanding the full burden of COVID-19 on mortality. In this work, we explored enhancements to an existing approach by employing Bayesian hierarchical models to estimate unrecognized deaths attributed to COVID-19 using weekly state-level COVID-19 viral surveillance and mortality data in the United States from March 2020 to April 2021. We demonstrated our model using those aged 85 years who died. First, we used a spatial-temporal binomial regression model to estimate the percent of positive SARS-CoV-2 test results. A spatial-temporal negative-binomial model was then used to estimate unrecognized COVID-19 deaths by exploiting the spatial-temporal association between SARS-CoV-2 percent positive and all-cause mortality counts using an excess mortality approach. Computationally efficient Bayesian inference was accomplished via the Polya-Gamma representation of the binomial and negative-binomial models. Among those aged 85 years, we estimated 58,200 (95% CI: 51,300, 64,900) unrecognized COVID-19 deaths, which accounts for 26% (95% CI: 24%, 29%) of total COVID-19 deaths in this age group. Our modeling results suggest that COVID-19 mortality and the proportion of unrecognized deaths among deaths attributed to COVID-19 vary by time and across states.

BACKGROUND: In the United States, Coronavirus Disease 2019 (COVID-19) deaths are captured through the National Notifiable Disease Surveillance System and death certificates reported to the National Vital Statistics System (NVSS). However, not all COVID-19 deaths are recognized and reported because of limitations in testing, exacerbation of chronic health conditions that are listed as the cause of death, or delays in reporting. Estimating deaths may provide a more comprehensive understanding of total COVID-19-attributable deaths. METHODS: We estimated COVID-19 unrecognized attributable deaths, from March 2020-April 2021, using all-cause deaths reported to NVSS by week and six age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) for 50 states, New York City, and the District of Columbia using a linear time series regression model. Reported COVID-19 deaths were subtracted from all-cause deaths before applying the model. Weekly expected deaths, assuming no SARS-CoV-2 circulation and predicted all-cause deaths using SARS-CoV-2 weekly percent positive as a covariate were modelled by age group and including state as a random intercept. COVID-19-attributable unrecognized deaths were calculated for each state and age group by subtracting the expected all-cause deaths from the predicted deaths. FINDINGS: We estimated that 766,611 deaths attributable to COVID-19 occurred in the United States from March 8, 2020-May 29, 2021. Of these, 184,477 (24%) deaths were not documented on death certificates. Eighty-two percent of unrecognized deaths were among persons aged ≥65 years; the proportion of unrecognized deaths were 0•24-0•31 times lower among those 0-17 years relative to all other age groups. More COVID-19-attributable deaths were not captured during the early months of the pandemic (March-May 2020) and during increases in SARS-CoV-2 activity (July 2020, November 2020-February 2021). DISCUSSION: Estimating COVID-19-attributable unrecognized deaths provides a better understanding of the COVID-19 mortality burden and may better quantify the severity of the COVID-19 pandemic. FUNDING: None.

BACKGROUND: The 2008 Recession was a global event that led to funding cuts for programs and services in the United States; though this recession officially ended in 2009, its aftershocks continued through 2012. We evaluated the relationship between the severity of the Great Recession's aftermath and spatial access to combined prevention services (i.e. HIV testing, syringe service programs, substance use disorder treatment program) for people who inject drugs (PWID) living in 19 metropolitan statistical areas (MSAs) in the United States. METHODS: The unit of analysis was the ZIP code; we sampled ZIP codes in these 19 MSAs where ≥1 PWID lived in 2009 and 2012, according to the CDC's National HIV Behavioral Surveillance. We used administrative data to describe the combined prevention environment (i.e., spatial access to HIV testing) for each ZIP code, and measured the severity of the recession's aftermath in each ZIP code, and in the counties and MSAs where these ZIP codes were located. Multilevel modeling estimated associations between changes in the aftermath of the Great Recession and ZIP code-level changes in spatial access to combined prevention services from 2009 to 2012. RESULTS: 675 ZIP codes located in 36 counties and 19 MSAs were included in this analysis. From 2009 to 2012, 21% of ZIP code areas lost access to combined prevention services and 14% gained access. ZIP codes with higher poverty rates relative to their respective MSAs were less likely to lose access (aOR: 0.91; 95% CI: 0.88, 0.95) and more likely to gain access (aOR: 1.05; 95% CI: 1.01, 1.09); there is some evidence to suggest the former association was attenuated for ZIP codes with higher percentages of non-Hispanic white residents. CONCLUSION: Combined prevention services for PWID living in these 675 ZIP codes demonstrated resilience in the aftermath of the Great Recession. Future research should explore whether community-based and federal HIV prevention initiatives contributed to this resilience, particularly in areas with higher concentrations of people of color.

BACKGROUND: Influenza vaccination during pregnancy prevents influenza among women and their infants but remains underused among pregnant women. We aimed to quantify the risk of antenatal influenza and examine its association with perinatal outcomes. METHODS: We did a prospective cohort study in pregnant women in India, Peru, and Thailand. Before the 2017 and 2018 influenza seasons, we enrolled pregnant women aged 18 years or older with expected delivery dates 8 weeks or more after the season started. We contacted women twice weekly until the end of pregnancy to identify illnesses with symptoms of myalgia, cough, runny nose or nasal congestion, sore throat, or difficulty breathing and collected mid-turbinate nasal swabs from symptomatic women for influenza real-time RT-PCR testing. We assessed the association of antenatal influenza with preterm birth, late pregnancy loss (≥13 weeks gestation), small for gestational age (SGA), and birthweight of term singleton infants using Cox proportional hazards models or generalised linear models to adjust for potential confounders. FINDINGS: Between March 13, 2017, and Aug 3, 2018, we enrolled 11 277 women with a median age of 26 years (IQR 23-31) and gestational age of 19 weeks (14-24). 1474 (13%) received influenza vaccines. 310 participants (3%) had influenza (270 [87%] influenza A and 40 [13%] influenza B). Influenza incidences weighted by the population of women of childbearing age in each study country were 88·7 per 10 000 pregnant woman-months (95% CI 68·6 to 114·8) during the 2017 season and 69·6 per 10 000 pregnant woman-months (53·8 to 90·2) during the 2018 season. Antenatal influenza was not associated with preterm birth (adjusted hazard ratio [aHR] 1·4, 95% CI 0·9 to 2·0; p=0·096) or having an SGA infant (adjusted relative risk 1·0, 95% CI 0·8 to 1·3, p=0·97), but was associated with late pregnancy loss (aHR 10·7, 95% CI 4·3 to 27·0; p<0·0001) and reduction in mean birthweight of term, singleton infants (-55·3 g, 95% CI -109·3 to -1·4; p=0·0445). INTERPRETATION: Women had a 0·7-0·9% risk of influenza per month of pregnancy during the influenza season, and antenatal influenza was associated with increased risk for some adverse pregnancy outcomes. These findings support the added value of antenatal influenza vaccination to improve perinatal outcomes. FUNDING: US Centers for Disease Control and Prevention. TRANSLATIONS: For the Thai, Hindi, Marathi and Spanish translations of the abstract see Supplementary Materials section.

Prior to updating global influenza-associated mortality estimates, the World Health Organization convened a consultation in July 2017 to understand differences in methodology and implications on results of three influenza mortality projects from the United States Centers for Disease Control and Prevention (CDC), the Netherlands Institute for Health Service Research (GLaMOR), and the Institute for Health Metrics and Evaluation (IHME). The expert panel reviewed estimates and discussed differences in data sources, analysis, and modeling assumptions. We performed a comparison analysis of the estimates. Influenza-associated respiratory death counts were comparable between CDC and GLaMOR; IHME estimate was considerably lower. The greatest country-specific influenza-associated mortality rate fold differences between CDC/IHME and between GLaMOR/IHME estimates were among countries in South-East Asia and Eastern Mediterranean region. The data envelope used for the calculation was one of the major differences (CDC and GLaMOR: all respiratory deaths; IHME: low respiratory infection deaths). With the assumption that there is only one cause of death for each death, IHME estimates a fraction of the full influenza-associated respiratory mortality that is measured by the other two groups. Wide variability of parameters was observed. Continued coordination between groups could assist with better understanding of methodological differences and new approaches to estimating influenza deaths globally.

RATIONALE: While associations between air pollution and respiratory morbidity for adults 65 and older are well-documented in the United States, the evidence for people under 65 is less extensive. To address this gap, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program collected respiratory emergency department (ED) data from 17 states. OBJECTIVES: Estimate age-specific acute effects of ozone and fine particulate matter (PM2.5) on respiratory ED visits. METHODS: We conducted time-series analyses in 894 counties by linking daily respiratory ED visits with estimated ozone and PM2.5 concentrations during the week before the date of the visit. Overall effect estimates were obtained using a Bayesian hierarchical model to combine county estimates for each pollutant by age group (children 0-18, adults 19-64, adults >/=65, and all ages) and by outcome group (acute respiratory infection, asthma, chronic obstructive pulmonary disease, pneumonia, and all respiratory ED visits). MEASUREMENTS AND MAIN RESULTS: Rate ratios (95% credible interval) per 10 microg/m3 increase in PM2.5 and all respiratory ED visits were 1.024 (1.018, 1.029) among children, 1.008 (1.004, 1.012) among adults <65, and 1.002 (0.996, 1.007) among adults 65 and older. Per 20 ppb increase in ozone, rate ratios were 1.017 (1.011, 1.023) among children, 1.051 (1.046, 1.056) among adults <65, and 1.033 (1.026, 1.040) among adults 65 and older. Associations varied in magnitude by age group for each outcome group. CONCLUSIONS: These results address a gap in the evidence used to ensure adequate public health protection under national air pollution policies.

BACKGROUND: Evidence from recent studies assessing the impact of school water, sanitation and hygiene (WASH) interventions on child health has been mixed. Self-reports of disease are subject to bias, and few WASH impact evaluations employ objective health measures to assess reductions in disease and exposure to pathogens. We utilized antibody responses from dried blood spots (DBS) to measure the impact of a school WASH intervention on infectious disease among pupils in Mali. METHODOLOGY/PRINCIPAL FINDINGS: We randomly selected 21 beneficiary primary schools and their 21 matched comparison schools participating in a matched-control trial of a comprehensive school-based WASH intervention in Mali. DBS were collected from 20 randomly selected pupils in each school (n = 807). We analyzed eluted IgG from the DBS using a Luminex multiplex bead assay to 28 antigens from 17 different pathogens. Factor analysis identified three distinct latent variables representing vector-transmitted disease (driven primarily by dengue), food/water-transmitted enteric disease (driven primarily by Escherichia coli and Vibrio cholerae), and person-to-person transmitted enteric disease (driven primarily by norovirus). Data were analyzed using a linear latent variable model. Antibody evidence of food/water-transmitted enteric disease (change in latent variable mean (beta) = -0.24; 95% CI: -0.53, -0.13) and person-to-person transmitted enteric disease (beta = -0.17; 95% CI: -0.42, -0.04) was lower among pupils attending beneficiary schools. There was no difference in antibody evidence of vector-transmitted disease (beta = 0.11; 95% CI: -0.05, 0.33). CONCLUSIONS/SIGNIFICANCE: Evidence of enteric disease was lower among pupils attending schools benefitting from school WASH improvements than students attending comparison schools. These findings support results from the parent study, which also found reduced incidence of self-reported diarrhea among pupils of beneficiary schools. DBS collection was feasible in this resource-poor field setting and provided objective evidence of disease at a low cost per antigen analyzed, making it an effective measurement tool for the WASH field. TRIAL REGISTRATION: The trial was registered at ClinicalTrials.gov (NCT01787058).

BACKGROUND: Estimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250 000-500 000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015. METHODS: We estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and >/=75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods. FINDINGS: EMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0.1 to 6.4 per 100 000 individuals for people younger than 65 years, 2.9 to 44.0 per 100 000 individuals for people aged between 65 and 74 years, and 17.9 to 223.5 per 100 000 for people older than 75 years. We estimated that 291 243-645 832 seasonal influenza-associated respiratory deaths (4.0-8.8 per 100 000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2.8-16.5 per 100 000 individuals), southeast Asia (3.5-9.2 per 100 000 individuals), and among people aged 75 years or older (51.3-99.4 per 100 000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105 690 influenza-associated respiratory deaths occur annually. INTERPRETATION: These global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated. FUNDING: None.

This study uses county-level surveillance data to systematically analyze geographic variation and clustering of persons living with diagnosed HIV (PLWH) in the southern United States in 2011. Clusters corresponding to large metropolitan areas - including Miami, Atlanta, and Baltimore - had HIV prevalence rates higher (p < .001) than the regional rate. Regression analysis within the counties included in these clusters determined that race was a significant indicator for PLWH. These results provide a general picture of the distribution of PLWH in the southern United States at the county level and provide insights for identifying local geographic areas with a high number of PLWH, as well as subpopulations that may have an increased risk of infection.

Melioidosis is caused by the soil-borne pathogen Burkholderia pseudomallei. To investigate whether the distinct phenotypic and virulent characteristics result from environmental adaptations in the soil or from the host body, two pairs of isogenic strains were generated by passages in soil or mice. After cultivation in soil, the levels of 3-hydroxytetradecanoic acid, biofilm formation, flagellar expression, and ultrastructure were altered in the bacteria. Uniformly fatal melioidosis developed as a result of infection with mouse-derived strains; however, the survival rates of mice infected with soil-derived strains prolonged. After primary infection or reinfection with soil-derived strains, the mice developed a low degree of bacterial hepatitis and bacterial colonization in the liver and bone marrow compared with mice that were infected with isogenic or heterogenic mouse-derived strains. We suggest that specific phenotypic and pathogenic patterns can be induced through infection with B. pseudomallei that has been cultured in different (soil versus mouse) environments.