Effects of Rurality on Distance and Time Traveled to Receive Vaccination Against Mpox-New Mexico and Idaho 2022-2023.

ABSTRACT: We compared mpox vaccination access between urban and rural residents who received ≥1 JYNNEOS dose using immunization data in Idaho and New Mexico. Rural residents traveled 5 times farther and 3 times longer than urban residents to receive mpox vaccination. Increasing mpox vaccine availability to health care facilities might increase uptake.

Changes in the Incidence of Invasive Bacterial Disease During the COVID-19 Pandemic in the United States, 2014-2020.

BACKGROUND: Descriptions of changes in invasive bacterial disease (IBD) epidemiology during the coronavirus disease 2019 (COVID-19) pandemic in the United States are limited. METHODS: We investigated changes in the incidence of IBD due to Streptococcus pneumoniae, Haemophilus influenzae, group A Streptococcus (GAS), and group B Streptococcus (GBS). We defined the COVID-19 pandemic period as 1 March to 31 December 2020. We compared observed IBD incidences during the pandemic to expected incidences, consistent with January 2014 to February 2020 trends. We conducted secondary analysis of a health care database to assess changes in testing by blood and cerebrospinal fluid (CSF) culture during the pandemic. RESULTS: Compared with expected incidences, the observed incidences of IBD due to S. pneumoniae, H. influenzae, GAS, and GBS were 58%, 60%, 28%, and 12% lower during the pandemic period of 2020, respectively. Declines from expected incidences corresponded closely with implementation of COVID-19-associated nonpharmaceutical interventions (NPIs). Significant declines were observed across all age and race groups, and surveillance sites for S. pneumoniae and H. influenzae. Blood and CSF culture testing rates during the pandemic were comparable to previous years. CONCLUSIONS: NPIs likely contributed to the decline in IBD incidence in the United States in 2020; observed declines were unlikely to be driven by reductions in testing.

Risk Factors for Severe COVID-19 in Children.

OBJECTIVES: Describe population-based rates and risk factors for severe coronavirus disease 2019 (COVID-19) (ie, ICU admission, invasive mechanical ventilation, or death) among hospitalized children. METHODS: During March 2020 to May 2021, the COVID-19-Associated Hospitalization Surveillance Network identified 3106 children hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection in 14 states. Among 2293 children primarily admitted for COVID-19, multivariable generalized estimating equations generated adjusted risk ratios (aRRs) and 95% confidence intervals (CIs) of the associations between demographic and medical characteristics abstracted from medical records and severe COVID-19. We calculated age-adjusted cumulative population-based rates of severe COVID-19 among all children. RESULTS: Approximately 30% of hospitalized children had severe COVID-19; 0.5% died during hospitalization. Among hospitalized children aged <2 years, chronic lung disease (aRR: 2.2; 95% CI: 1.1-4.3), neurologic disorders (aRR: 2.0; 95% CI: 1.5‒2.6), cardiovascular disease (aRR: 1.7; 95% CI: 1.2‒2.3), prematurity (aRR: 1.6; 95% CI: 1.1‒2.2), and airway abnormality (aRR: 1.6; 95% CI: 1.1‒2.2) were associated with severe COVID-19. Among hospitalized children aged 2 to 17 years, feeding tube dependence (aRR: 2.0; 95% CI: 1.5‒2.5), diabetes mellitus (aRR: 1.9; 95% CI: 1.6‒2.3) and obesity (aRR: 1.2; 95% CI: 1.0‒1.4) were associated with severe COVID-19. Severe COVID-19 occurred among 12.0 per 100 000 children overall and was highest among infants, Hispanic children, and non-Hispanic Black children. CONCLUSIONS: Results identify children at potentially higher risk of severe COVID-19 who may benefit from prevention efforts, including vaccination. Rates establish a baseline for monitoring changes in pediatric illness severity after increased availability of COVID-19 vaccines and the emergence of new variants.

Census tract socioeconomic indicators and COVID-19-associated hospitalization rates-COVID-NET surveillance areas in 14 states, March 1-April 30, 2020.

OBJECTIVES: Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. METHODS: Using data from COVID-NET population-based surveillance reported during March 1-April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. RESULTS: Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1-156.1) in census tracts with >15.2%-83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9-78.1) in census tracts with 0%-4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3-128.2), 252.2 (95% CI: 241.4-263.0), and 341.1 (95% CI: 317.3-365.0), respectively, compared with 58.2 (95% CI: 55.4-61.1), 304.0 (95%: 282.4-325.6), and 540.3 (95% CI: 477.0-603.6), respectively, in low-poverty census tracts. CONCLUSIONS: Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.

Effectiveness of COVID-19 Vaccines in Preventing Hospitalization Among Adults Aged ≥65 Years - COVID-NET, 13 States, February-April 2021.

Clinical trials of COVID-19 vaccines currently authorized for emergency use in the United States (Pfizer-BioNTech, Moderna, and Janssen [Johnson & Johnson]) indicate that these vaccines have high efficacy against symptomatic disease, including moderate to severe illness (1-3). In addition to clinical trials, real-world assessments of COVID-19 vaccine effectiveness are critical in guiding vaccine policy and building vaccine confidence, particularly among populations at higher risk for more severe illness from COVID-19, including older adults. To determine the real-world effectiveness of the three currently authorized COVID-19 vaccines among persons aged ≥65 years during February 1-April 30, 2021, data on 7,280 patients from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) were analyzed with vaccination coverage data from state immunization information systems (IISs) for the COVID-NET catchment area (approximately 4.8 million persons). Among adults aged 65-74 years, effectiveness of full vaccination in preventing COVID-19-associated hospitalization was 96% (95% confidence interval [CI] = 94%-98%) for Pfizer-BioNTech, 96% (95% CI = 95%-98%) for Moderna, and 84% (95% CI = 64%-93%) for Janssen vaccine products. Effectiveness of full vaccination in preventing COVID-19-associated hospitalization among adults aged ≥75 years was 91% (95% CI = 87%-94%) for Pfizer-BioNTech, 96% (95% CI = 93%-98%) for Moderna, and 85% (95% CI = 72%-92%) for Janssen vaccine products. COVID-19 vaccines currently authorized in the United States are highly effective in preventing COVID-19-associated hospitalizations in older adults. In light of real-world data demonstrating high effectiveness of COVID-19 vaccines among older adults, efforts to increase vaccination coverage in this age group are critical to reducing the risk for COVID-19-related hospitalization.

Characteristics and Maternal and Birth Outcomes of Hospitalized Pregnant Women with Laboratory-Confirmed COVID-19 - COVID-NET, 13 States, March 1-August 22, 2020.

Pregnant women might be at increased risk for severe coronavirus disease 2019 (COVID-19) (1,2). The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) (3) collects data on hospitalized pregnant women with laboratory-confirmed SARS-CoV-2, the virus that causes COVID-19; to date, such data have been limited. During March 1-August 22, 2020, approximately one in four hospitalized women aged 15-49 years with COVID-19 was pregnant. Among 598 hospitalized pregnant women with COVID-19, 54.5% were asymptomatic at admission. Among 272 pregnant women with COVID-19 who were symptomatic at hospital admission, 16.2% were admitted to an intensive care unit (ICU), and 8.5% required invasive mechanical ventilation. During COVID-19-associated hospitalizations, 448 of 458 (97.8%) completed pregnancies resulted in a live birth and 10 (2.2%) resulted in a pregnancy loss. Testing policies based on the presence of symptoms might miss COVID-19 infections during pregnancy. Surveillance of pregnant women with COVID-19, including those with asymptomatic infections, is important to understand the short- and long-term consequences of COVID-19 for mothers and newborns. Identifying COVID-19 in women during birth hospitalizations is important to guide preventive measures to protect pregnant women, parents, newborns, other patients, and hospital personnel. Pregnant women and health care providers should be made aware of the potential risks for severe COVID-19 illness, adverse pregnancy outcomes, and ways to prevent infection.

Characterization of Departures from Regulatory Requirements Identified During Inspections Conducted by the US Federal Select Agent Program, 2014-15.

We studied departures from regulatory requirements identified on US Federal Select Agent Program (FSAP) inspections to increase transparency regarding biosafety and security risk at FSAP-regulated entities and identify areas for programmatic improvement. Regulatory departures from inspections led by Centers for Disease Control and Prevention inspectors during 2014-15 were grouped into "biosafety," "security," and "other" observation categories and assigned a risk level and score reflecting perceived severity. The resulting 2,267 biosafety (n = 1,153) and security (n = 1,114) observations from 296 inspections were analyzed by frequency and risk across entity and inspection characteristics. The greatest proportion of biosafety observations involved equipment and facilities (28%), and the greatest proportion of security observations involved access restrictions (33%). The greatest proportion of higher-risk observations for biosafety were containment issues and for security were inventory discrepancies. Commercial entities had the highest median cumulative risk score per inspection (17), followed by private (13), academic (10), federal government (10), and nonfederal government (8). Maximum containment (BSL-4) inspections had higher median biosafety risk per inspection (13) than other inspections (5) and lower security risk (0 vs 4). Unannounced inspections had proportionally more upper risk level observations than announced (biosafety, 21% vs 12%; security, 18% vs 7%). Possessors of select agents had higher median biosafety risk per inspection (6) than nonpossessors (4) and more upper risk level security observations (10% vs 0%). Programmatic changes to balance resources according to entity risk may strengthen FSAP oversight. Varying inspection methods by select agent possession and entity type, and conducting more unannounced inspections, may be beneficial.

Planning for baseline medical care needs of a displaced population after a disaster.

OBJECTIVE: To build a tool to assist disaster response planning and estimate the numbers of displaced persons that will require special medical care during a disaster. METHODS: We developed a tool, titled MedCon:PreEvent, which incorporates data from the 2006 National Health Interview Survey, 2005 National Hospital Discharge Survey, and 2004 National Nursing Home Survey to calculate numbers of emergency room/emergency department (ER/ED) visits, surgeries, health care home visits, overnight hospital stays, office visits, and self-rated health status. We then used thresholds of more than 12 office visits or 6 or more ER/ED visits or 6 or more surgeries or more than 4 home visits or more than 6 overnight hospital stays within the past 12 months to calculate rates per million evacuees requiring special medical care, including daily bed hospital and nursing home bed occupancy. RESULTS: We calculated that 79 428 (95% CI = 76 940-81 770) per million evacuees would need special medical care. The daily occupation of hospital beds would be 1710 beds (95% CI = 1328-2160) per million. The occupation of nursing home beds would be 5094 beds (95% CI = 5040-5148) per million. Changing the threshold to just those who self-rated health as "poor," the demand for special medical care would be 24 348 (95% CI = 23 087-25 535) per million. Using threshold utilization values at half the original level would increase the estimate to 226 988 (95% CI = 224 444-229 384) per million. CONCLUSIONS: A substantial number of persons with preexisting conditions will need suitable medical care following a disaster. The MedCon:PreEvent tool can assist disaster planners to prepare for medical care needs of large numbers of evacuees and consider re-evaluating the approach to utilizing and augmenting medical care services.

Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group.

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health surveillance systems for early detection of outbreaks. State and local health departments are enhancing existing surveillance systems and developing new systems to better detect outbreaks through public health surveillance. However, information is limited about the usefulness of surveillance systems for outbreak detection or the best ways to support this function. This report supplements previous guidelines for evaluating public health surveillance systems. Use of this framework is intended to improve decision-making regarding the implementation of surveillance for outbreak detection. Use of a standardized evaluation methodology, including description of system design and operation, also will enhance the exchange of information regarding methods to improve early detection of outbreaks. The framework directs particular attention to the measurement of timeliness and validity for outbreak detection. The evaluation framework is designed to support assessment and description of all surveillance approaches to early detection, whether through traditional disease reporting, specialized analytic routines for aberration detection, or surveillance using early indicators of disease outbreaks, such as syndromic surveillance.

Evaluation challenges for syndromic surveillance--making incremental progress.

INTRODUCTION: The 2003 National Syndromic Surveillance Conference provided an opportunity to examine challenges and progress in evaluating syndromic surveillance systems. OBJECTIVES: Using the conference abstracts as a focus, this paper describes the status of performance measurement of syndromic surveillance systems and ongoing challenges in system evaluation. METHODS: Ninety-nine original abstracts were reviewed and classified descriptively and according to their presentation of evaluation attributes. RESULTS: System evaluation was the primary focus of 35% of the abstracts submitted. Of those abstracts, 63% referenced prospective evaluation methods and 57% reported on outbreak detection. However, no data were provided in 34% of the evaluation abstracts, and only 37% referred to system signals, 20% to investigation of system signals, and 20% to timeliness. CONCLUSIONS: Although this abstract review is not representative of all current syndromic surveillance efforts, it highlights recent attention to evaluation and the need for a basic set of system performance measures. It also proposes questions to be answered of all public health systems used for outbreak detection.

Draft framework for evaluating syndromic surveillance systems.

Interest in public health surveillance to detect outbreaks from terrorism is driving the exploration of nontraditional data sources and development of new performance priorities for surveillance systems. A draft framework for evaluating syndromic surveillance systems will help researchers and public health practitioners working on nontraditional surveillance to review their work in a systematic way and communicate their efforts. The framework will also guide public health practitioners in their efforts to compare and contrast aspects of syndromic surveillance systems and decide whether and how to develop and maintain such systems. In addition, a common framework will allow the identification and prioritization of research and evaluation needs. The evaluation framework is comprised of five components: a thorough description of the system (e.g., purpose, stakeholders, how the system works); system performance experience (e.g., usefulness, acceptability to stakeholders, generalizability to other settings, operating stability, costs); capacity for outbreak detection (e.g., flexibility to adapt to changing risks and data inputs, sensitivity to detect outbreaks, predictive value of system alarms for true outbreaks, timeliness of detection); assessment of data quality (e.g., representativeness of the population covered by the system, completeness of data capture, reliability of data captured over time); and conclusions and recommendations. The draft framework is intended to evolve into guidance to support public health practice for terrorism preparedness and outbreak detection.