Background
COVID‐19 hospitalizations of non‐institutionalized persons during the first COVID‐19 wave in Connecticut disproportionately affected the elderly, communities of color, and individuals of ...low socioeconomic status (SES). Whether the magnitude of these disparities changed after the initial lockdown and before vaccine rollout is not well documented.
Methods
All first‐time hospitalizations with laboratory‐confirmed COVID‐19 during July to December 2020, including patients' geocoded residential addresses, were obtained from the Connecticut Department of Public Health. Those living in congregate settings, including nursing homes, were excluded. Community‐dwelling patients were assigned census tract‐level poverty and crowding measures from the 2014–2018 American Community Survey by linking their geocoded addresses to census tracts. Age‐adjusted incidence and relative rates were calculated across demographic and SES measures and compared with those from a similar analysis of hospitalized cases during the initial wave.
Results
During July to December 2020, there were 5652 COVID‐19 hospitalizations in community residents in Connecticut. Incidence was highest among those >85 years, non‐Hispanic Blacks and Hispanic/Latinx compared with non‐Hispanic Whites {relative rate (RR) 3.1 (95% confidence interval CI 2.83–3.32) and 5.9 (95% CI 5.58–6.28)}, and persons living in high poverty and high crowding census tracts. Although racial/ethnic and SES disparities during the study period were substantial, they were significantly decreased compared with the first wave of COVID‐19.
Conclusions
The finding of persistent, if reduced, large racial/ethnic disparities in COVID‐19 hospitalizations 2–7 months after the initial lockdown was relaxed and before vaccination was widely available is of concern. These disparities cause a challenge to achieving health equity and are relevant for future pandemic planning.
We examined surveillance data for disparities in pediatric influenza-associated hospitalizations according to neighborhood socioeconomic status (SES) measures in New Haven County, Connecticut.
We ...geocoded influenza-associated hospitalization case data from the past 7 years for children from birth to age 17 years and linked these to US Census 2000 tract-level SES data. Following the methods of Harvard's Public Health Disparities Geocoding Project, we examined neighborhood SES variables, including measures of poverty and crowding. We calculated influenza-associated hospitalization incidence by influenza season and individual case characteristics, stratified by SES measures.
Overall, the mean annual incidence of pediatric influenza-associated hospitalization in high-poverty and high-crowding census tracts was at least 3 times greater than that in low-poverty and low-crowding tracts. This disparity could not be fully explained by prevalence of underlying conditions or receipt of influenza vaccination.
Linkage of geocoded surveillance data and census information allows for ongoing monitoring of SES correlates of health and may help target interventions. Our analysis indicates a correlation between residence in impoverished or crowded neighborhoods and incidence of influenza-associated hospitalization among children in Connecticut.
Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk ...factors for severe outcomes among adults hospitalized with COVID-19.
We analyzed data from 2491 adults hospitalized with laboratory-confirmed COVID-19 between 1 March-2 May 2020, as identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network, which comprises 154 acute-care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality.
The data show that 92% of patients had ≥1 underlying condition; 32% required ICU admission; 19% required invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84, and ≥85 years versus 18-39 years (adjusted risk ratios aRRs, 1.53, 1.65, 1.84, and 1.43, respectively); male sex (aRR, 1.34); obesity (aRR, 1.31); immunosuppression (aRR, 1.29); and diabetes (aRR, 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84, and ≥ 85 years versus 18-39 years (aRRs, 3.11, 5.77, 7.67, and 10.98, respectively); male sex (aRR, 1.30); immunosuppression (aRR, 1.39); renal disease (aRR, 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR, 1.28); neurologic disorders (aRR, 1.25); and diabetes (aRR, 1.19).
In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.
Background
Prior to the introduction of vaccines, COVID‐19 hospitalizations of non‐institutionalized persons in Connecticut disproportionately affected communities of color and individuals of low ...socioeconomic status (SES). Whether the magnitude of these disparities changed 7–9 months after vaccine rollout during the Delta wave is not well documented.
Methods
All initially hospitalized patients with laboratory‐confirmed COVID‐19 during July–September 2021 were obtained from the Connecticut COVID‐19‐Associated Hospitalization Surveillance Network database, including patients' geocoded residential addresses. Census tract measures of poverty and crowding were determined by linking geocoded residential addresses to the 2014–2018 American Community Survey. Age‐adjusted incidence and relative rates of COVID‐19 hospitalization were calculated and compared with those from July to December 2020. Vaccination levels by age and race/ethnicity at the beginning and end of the study period were obtained from Connecticut's COVID vaccine registry, and age‐adjusted average values were determined.
Results
There were 708 COVID‐19 hospitalizations among community residents of the two counties, July–September 2021. Age‐adjusted incidence was the highest among non‐Hispanic Blacks and Hispanic/Latinx compared with non‐Hispanic Whites (RR 4.10 95% CI 3.41–4.94 and 3.47 95% CI 2.89–4.16). Although RR decreased significantly among Hispanic/Latinx and among the lowest SES groups, it increased among non‐Hispanic Blacks (from RR 3.2 95% CI 2.83–3.32 to RR 4.10). Average age‐adjusted vaccination rates among those ≥12 years were the lowest among non‐Hispanic Blacks compared with Hispanic/Latinx and non‐Hispanic Whites (50.6% vs. 64.7% and 66.6%).
Conclusions
Although racial/ethnic and SES disparities in COVID‐19 hospitalization have mostly decreased over time, disparities among non‐Hispanic Blacks increased, possibly due to differences in vaccination rates.
Abstract
Background
Data on risk factors for coronavirus disease 2019 (COVID-19)–associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors ...independently associated with COVID-19–associated hospitalizations.
Methods
Community-dwelling adults (aged ≥18 years) in the United States hospitalized with laboratory-confirmed COVID-19 during 1 March–23 June 2020 were identified from the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET), a multistate surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity, severe obesity, chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRRs) for hospitalization.
Results
Among 5416 adults, hospitalization rates (all reported as aRR 95% confidence interval) were higher among those with ≥3 underlying conditions (vs without) (5.0 3.9–6.3), severe obesity (4.4 3.4–5.7), chronic kidney disease (4.0 3.0–5.2), diabetes (3.2 2.5–4.1), obesity (2.9 2.3–3.5), hypertension (2.8 2.3–3.4), and asthma (1.4 1.1–1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65 or 45–64 years (vs 18–44 years), males (vs females), and non-Hispanic black and other race/ethnicities (vs non-Hispanic whites).
Conclusions
Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.
Severe obesity, chronic kidney disease, diabetes, obesity, hypertension, asthma, age ≥45 years, male sex, and non-Hispanic black and other race/ethnicity are associated with increased risk of coronavirus disease 2019–associated hospitalizations.
Objectives
To help guide universal influenza vaccination efforts in the United States, it is important to know which demographic groups are currently at highest risk of costly complications of ...influenza infection. Few studies have examined the relationship between hospitalization with influenza and either socioeconomic status (SES) or sex. We examined associations between census tract‐level SES and sex and incidence of influenza‐related hospitalizations among adults.
Design
Descriptive analysis of data collected by active population‐based surveillance for persons >18 years old hospitalized with laboratory confirmed influenza during the 2007–2008 through 2010–2011 influenza seasons. Case residential addresses were geocoded and linked to data from the 2006–2010 American Community Survey to obtain census‐tract level (neighborhood) SES measures. Census‐tract level SES variables included measures of poverty, education, crowding, primary language, and median income. Four levels were created for each.
Setting
New Haven, County, Connecticut.
Sample
Entire New Haven County population >18 years old.
Main Outcome Measures
Age‐adjusted incidence of influenza hospitalizations and relative risk by sex and by each of five SES measures.
Results
Crude and age‐adjusted incidence progressively increased with decreasing neighborhood SES for each measure both overall and for each influenza season. Female incidence was higher than male for each age group, and female age‐adjusted incidence was higher for each SES level and influenza season.
Conclusions
Female sex and lower neighborhood SES were independently and consistently associated with higher incidence of hospitalization of adults with influenza. If this is more broadly the case, these findings have implications for future influenza vaccination efforts. Analysis using census tract SES measures can provide additional perspective on health disparities.
Background
Influenza hospitalizations result in substantial morbidity and mortality each year. Little is known about the association between influenza hospitalization and census tract‐based ...socioeconomic determinants beyond the effect of individual factors.
Objective
To evaluate whether census tract‐based determinants such as poverty and household crowding would contribute significantly to the risk of influenza hospitalization above and beyond individual‐level determinants.
Methods
We analyzed 33 515 laboratory‐confirmed influenza‐associated hospitalizations that occurred during the 2009‐2010 through 2013‐2014 influenza seasons using a population‐based surveillance system at 14 sites across the United States.
Results
Using a multilevel regression model, we found that individual factors were associated with influenza hospitalization with the highest adjusted odds ratio (AOR) of 9.20 (95% CI 8.72‐9.70) for those ≥65 vs 5‐17 years old. African Americans had an AOR of 1.67 (95% CI 1.60‐1.73) compared to Whites, and Hispanics had an AOR of 1.21 (95% CI 1.16‐1.26) compared to non‐Hispanics. Among census tract‐based determinants, those living in a tract with ≥20% vs <5% of persons living below poverty had an AOR of 1.31 (95% CI 1.16‐1.47), those living in a tract with ≥5% vs <5% of persons living in crowded conditions had an AOR of 1.17 (95% CI 1.11‐1.23), and those living in a tract with ≥40% vs <5% female heads of household had an AOR of 1.32 (95% CI 1.25‐1.40).
Conclusion
Census tract‐based determinants account for 11% of the variability in influenza hospitalization.
Peridomestic Lyme disease-prevention initiatives promote personal protection, landscape modification, and chemical control.
A 32-month prospective age- and neighborhood-matched case-control study was ...conducted in Connecticut to evaluate the effects of peridomestic prevention measures on risk of Lyme disease.
The study was conducted in 24 disease-endemic Connecticut communities from 2005 to 2007. Subjects were interviewed by telephone using a questionnaire designed to elicit disease-prevention measures during the month prior to the case onset of erythema migrans. Data were analyzed in 2008 by conditional logistic regression. Potential confounders, such as occupational/recreational exposures, were examined.
Between April 2005 and November 2007, interviews were conducted with 364 participants with Lyme disease, and 349 (96%) were matched with a suitable control. Checking for ticks within 36 hours of spending time in the yard at home was protective against Lyme disease (OR=0.55; 95% CI=0.32, 0.94). Bathing within 2 hours after spending time in the yard was also protective (OR=0.42; 95% CI=0.23, 0.78). Fencing of any type or height in the yard, whether it was contiguous or not, was protective (OR=0.54; 95% CI=0.33, 0.90). No other landscape modifications or features were significantly protective against Lyme disease.
The results of this study suggest that practical activities such as checking for ticks and bathing after spending time in the yard may reduce the risk of Lyme disease in regions where peridomestic risk is high. Fencing did appear to protect against infection, but the mechanism of its protection is unclear.
Influenza virus and SARS-CoV-2 are significant causes of respiratory illness in children.
Influenza- and COVID-19-associated hospitalizations among children <18 years old were analyzed from ...FluSurv-NET and COVID-NET, 2 population-based surveillance systems with similar catchment areas and methodology. The annual COVID-19-associated hospitalization rate per 100 000 during the ongoing COVID-19 pandemic (1 October 2020-30 September 2021) was compared with influenza-associated hospitalization rates during the 2017-2018 through 2019-2020 influenza seasons. In-hospital outcomes, including intensive care unit (ICU) admission and death, were compared.
Among children <18 years, the COVID-19-associated hospitalization rate (48.2) was higher than influenza-associated hospitalization rates: 2017-2018 (33.5), 2018-2019 (33.8), and 2019-2020 (41.7). The COVID-19-associated hospitalization rate was higher among adolescents 12-17 years old (COVID-19: 59.9; influenza range: 12.2-14.1), but similar or lower among children 5-11 (COVID-19: 25.0; influenza range: 24.3-31.7) and 0-4 (COVID-19: 66.8; influenza range: 70.9-91.5) years old. Among children <18 years, a higher proportion with COVID-19 required ICU admission compared with influenza (26.4% vs 21.6%; P < .01). Pediatric deaths were uncommon during both COVID-19- and influenza-associated hospitalizations (0.7% vs 0.5%; P = .28).
In the setting of extensive mitigation measures during the COVID-19 pandemic, the annual COVID-19-associated hospitalization rate during 2020-2021 was higher among adolescents and similar or lower among children <12 years compared with influenza during the 3 seasons before the COVID-19 pandemic. COVID-19 adds substantially to the existing burden of pediatric hospitalizations and severe outcomes caused by influenza and other respiratory viruses.
Background
Influenza is a substantial cause of annual morbidity and mortality; however, correctly identifying those patients at increased risk for severe disease is often challenging. Several ...severity indices have been developed; however, these scores have not been validated for use in patients with influenza. We evaluated the discrimination of three clinical disease severity scores in predicting severe influenza‐associated outcomes.
Methods
We used data from the Influenza Hospitalization Surveillance Network to assess outcomes of patients hospitalized with influenza in the United States during the 2017–2018 influenza season. We computed patient scores at admission for three widely used disease severity scores: CURB‐65, Quick Sepsis‐Related Organ Failure Assessment (qSOFA), and the Pneumonia Severity Index (PSI). We then grouped patients with severe outcomes into four severity tiers, ranging from ICU admission to death, and calculated receiver operating characteristic (ROC) curves for each severity index in predicting these tiers of severe outcomes.
Results
Among 8252 patients included in this study, we found that all tested severity scores had higher discrimination for more severe outcomes, including death, and poorer discrimination for less severe outcomes, such as ICU admission. We observed the highest discrimination for PSI against in‐hospital mortality, at 0.78.
Conclusions
We observed low to moderate discrimination of all three scores in predicting severe outcomes among adults hospitalized with influenza. Given the substantial annual burden of influenza disease in the United States, identifying a prediction index for severe outcomes in adults requiring hospitalization with influenza would be beneficial for patient triage and clinical decision‐making.
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