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In a retrospective cohort study, among 131 773 patients with previous coronavirus disease 2019 (COVID-19), reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) was suspected in 253 patients (0.2%) at 238 US healthcare facilities between 1 June 2020 and 28 February 2021. Women displayed a higher cumulative reinfection risk. Healthcare burden and illness severity were similar between index and reinfection encounters. [ABSTRACT FROM AUTHOR]

Abstract Background Seasonal respiratory syncytial virus (RSV) epidemics occur annually in temperate climates and result in significant pediatric morbidity and increased health care costs. Although RSV epidemics generally occur between October and April, the size and timing vary across epidemic seasons and are difficult to predict accurately. Prediction of epidemic characteristics would support management of resources and treatment. Methods The goals of this research were to examine the empirical relationships among early exponential growth rate, total epidemic size, and timing, and the utility of specific parameters in compartmental models of transmission in accounting for variation among seasonal RSV epidemic curves. RSV testing data from Primary Children's Medical Center were collected on children under two years of age (July 2001-June 2008). Simple linear regression was used explore the relationship between three epidemic characteristics (final epidemic size, days to peak, and epidemic length) and exponential growth calculated from four weeks of daily case data. A compartmental model of transmission was fit to the data and parameter estimated used to help describe the variation among seasonal RSV epidemic curves. Results The regression results indicated that exponential growth was correlated to epidemic characteristics. The transmission modeling results indicated that start time for the epidemic and the transmission parameter co-varied with the epidemic season. Conclusions The conclusions were that exponential growth was somewhat empirically related to seasonal epidemic characteristics and that variation in epidemic start date as well as the transmission parameter over epidemic years could explain variation in seasonal epidemic size. These relationships are useful for public health, health care providers, and infectious disease researchers.

Prospective surveillance for influenza was performed during the 2002 Salt Lake City Winter Olympics. Oseltamivir was administered to patients with influenzalike illness and confirmed influenza, while their close contacts were [...]

Abstract This paper presents the rationale for designing and implementing the next-generation of public health information systems using grid computing concepts and tools. Our attempt is to evaluate all grid types including data grids for sharing information and computational grids for accessing computational resources on demand. Public health is a broad domain that requires coordinated uses of disparate and heterogeneous information systems. System interoperability in public health is limited. The next-generation public health information systems must overcome barriers to integration and interoperability, leverage advances in information technology, address emerging requirements, and meet the needs of all stakeholders. Grid-based architecture provides one potential technical solution that deserves serious consideration. Within this context, we describe three discrete public health information system problems and the process by which the Utah Department of Health (UDOH) and the Department of Biomedical Informatics at the University of Utah in the United States has approached the exploration for eventual deployment of a Utah Public Health Informatics Grid. These three problems are: i) integration of internal and external data sources with analytic tools and computational resources; ii) provide external stakeholders with access to public health data and services; and, iii) access, integrate, and analyze internal data for the timely monitoring of population health status and health services. After one year of experience, we have successfully implemented federated queries across disparate administrative domains, and have identified challenges and potential solutions concerning the selection of candidate analytic grid services, data sharing concerns, security models, and strategies for reducing expertise required at a public health agency to implement a public health grid.

Obesity* is a recognized risk factor for severe COVID-19 (1,2), possibly related to chronic inflammation that disrupts immune and thrombogenic responses to pathogens (3) as well as to impaired lung function from excess weight (4). Obesity is a common metabolic disease, affecting 42.4% of U.S. adults (5), and is a risk factor for other chronic diseases, including type 2 diabetes, heart disease, and some cancers.† The Advisory Committee on Immunization Practices considers obesity to be a high-risk medical condition for COVID-19 vaccine prioritization (6). Using data from the Premier Healthcare Database Special COVID-19 Release (PHD-SR),§ CDC assessed the association between body mass index (BMI) and risk for severe COVID-19 outcomes (i.e., hospitalization, intensive care unit [ICU] or stepdown unit admission, invasive mechanical ventilation, and death). Among 148,494 adults who received a COVID-19 diagnosis during an emergency department (ED) or inpatient visit at 238 U.S. hospitals during March-December 2020, 28.3% had overweight and 50.8% had obesity. Overweight and obesity were risk factors for invasive mechanical ventilation, and obesity was a risk factor for hospitalization and death, particularly among adults aged <65 years. Risks for hospitalization, ICU admission, and death were lowest among patients with BMIs of 24.2 kg/m2, 25.9 kg/m2, and 23.7 kg/m2, respectively, and then increased sharply with higher BMIs. Risk for invasive mechanical ventilation increased over the full range of BMIs, from 15 kg/m2 to 60 kg/m2. As clinicians develop care plans for COVID-19 patients, they should consider the risk for severe outcomes in patients with higher BMIs, especially for those with severe obesity. These findings highlight the clinical and public health implications of higher BMIs, including the need for intensive COVID-19 illness management as obesity severity increases, promotion of COVID-19 prevention strategies including continued vaccine prioritization (6) and masking, and policies to ensure community access to nutrition and physical activities that promote and support a healthy BMI. [ABSTRACT FROM AUTHOR]

Background: A better understanding of the long-term health effects of combat injury is important for the management of veterans' health in the Department of Defense (DoD) and Veterans Affairs (VA) health care systems and may have implications for primary care management of civilian trauma patients. Objective: To determine the impact of traumatic injury on the subsequent development of hypertension (HTN), diabetes mellitus (DM), and coronary artery disease (CAD) after adjustment for sociodemographic, health behavior, and mental health factors. Design: Retrospective cohort study of current and former US military personnel with data obtained from both the DoD and VA health care systems. Participants: Combat injured (n = 8727) service members between 1 February 2002 and 14 June 2016 randomly selected from the DoD Trauma Registry matched 1:1 based on year of birth, sex, and branch of service to subjects that deployed to a combat zone but were not injured. Main Measures: Traumatic injury, stratified by severity, compared with no documented injury. Diagnoses of HTN, DM, and CAD defined by International Classification of Diseases 9th or 10th Revision Clinical Modification codes. Key Results: After adjustment, severe traumatic injury was significantly associated with HTN (HR 2.78, 95% CI 2.18–3.55), DM (HR 4.45, 95% CI 2.15–9.18), and CAD (HR 4.87, 95% CI 2.11–11.25), compared with no injury. Less severe injury was associated with HTN (HR 1.14, 95% CI 1.05–1.24) and CAD (HR 1.62, 95% CI 1.11–2.37). Conclusions: Severe traumatic injury is associated with the subsequent development of HTN, DM, and CAD. These findings have profound implications for the primary care of injured service members in both the DoD/VA health systems and may be applicable to civilian trauma patients as well. Further exploration of pathophysiologic, health behavior, and mental health changes after trauma is warranted to guide future intervention strategies. [ABSTRACT FROM AUTHOR]

Background Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. Methods Using data from the Premier Healthcare Database on 181 813 hospitalized adults diagnosed with COVID-19 during March–September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. Results Overall, 84 497 (47%) patients were admitted to the ICU, 29 078 (16%) received IMV, and 27 864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92–0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09–1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09–1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06–1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. Conclusions These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes. [ABSTRACT FROM AUTHOR]

Background There is a need for validated and standardized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quantitative immunoglobulin G (IgG) and neutralization assays that can be used to understand the immunology and pathogenesis of SARS-CoV-2 infection and support the coronavirus disease 2019 (COVID-19) pandemic response. Methods Literature searches were conducted to identify English language publications from peer-reviewed journals and preprints from January 2020 through November 6, 2020. Relevant publications were reviewed for mention of IgG or neutralization assays for SARS-CoV-2, or both, and the methods of reporting assay results. Results Quantitative SARS-CoV-2 IgG results have been reported from a limited number of studies; most studies used in-house laboratory-developed tests in limited settings, and only two semiquantitative tests have received US Food and Drug Administration (FDA) Emergency Use Authorization (EUA). As of November 6, 2020, there is only one SARS-CoV-2 neutralization assay with FDA EUA. Relatively few studies have attempted correlation of quantitative IgG titers with neutralization results to estimate surrogates of protection. The number of individuals tested is small compared with the magnitude of the pandemic, and persons tested are not representative of disproportionately affected populations. Methods of reporting quantitative results are not standardized to enable comparisons and meta-analyses. Conclusions Lack of standardized SARS-CoV-2 quantitative IgG and neutralization assays precludes comparison of results from published studies. Interassay and interlaboratory validation and standardization of assays will support efforts to better understand antibody kinetics and longevity of humoral immune responses postillness, surrogates of immune protection, and vaccine immunogenicity and efficacy. Public–private partnerships could facilitate realization of these advances in the United States and worldwide. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is a complex clinical illness with potential complications that might require ongoing clinical care (1-3). Few studies have investigated discharge patterns and hospital readmissions among large groups of patients after an initial COVID-19 hospitalization (4-7). Using electronic health record and administrative data from the Premier Healthcare Database,* CDC assessed patterns of hospital discharge, readmission, and demographic and clinical characteristics associated with hospital readmission after a patient's initial COVID-19 hospitalization (index hospitalization). Among 126,137 unique patients with an index COVID-19 admission during March-July 2020, 15% died during the index hospitalization. Among the 106,543 (85%) surviving patients, 9% (9,504) were readmitted to the same hospital within 2 months of discharge through August 2020. More than a single readmission occurred among 1.6% of patients discharged after the index hospitalization. Readmissions occurred more often among patients discharged to a skilled nursing facility (SNF) (15%) or those needing home health care (12%) than among patients discharged to home or self-care (7%). The odds of hospital readmission increased with age among persons aged ≥65 years, presence of certain chronic conditions, hospitalization within the 3 months preceding the index hospitalization, and if discharge from the index hospitalization was to a SNF or to home with health care assistance. These results support recent analyses that found chronic conditions to be significantly associated with hospital readmission (6,7) and could be explained by the complications of underlying conditions in the presence of COVID-19 (8), COVID-19 sequelae (3), or indirect effects of the COVID-19 pandemic (9). Understanding the frequency of, and risk factors for, readmission can inform clinical practice, discharge disposition decisions, and public health priorities such as health care planning to ensure availability of resources needed for acute and follow-up care of COVID-19 patients. With the recent increases in cases nationwide, hospital planning can account for these increasing numbers along with the potential for at least 9% of patients to be readmitted, requiring additional beds and resources. [ABSTRACT FROM AUTHOR]

Objectives: We present the development and validation of a portable NLP approach for automated surveillance of SSIs. Summary of Background Data: The surveillance of SSIs is labor-intensive limiting the generalizability and scalability of surgical quality surveillance programs. Methods: We abstracted patient clinical text notes after surgical procedures from 2 independent healthcare systems using different electronic healthcare records. An SSI detected as part of the American College of Surgeons' National Surgical Quality Improvement Program was used as the reference standard. We developed a rules-based NLP system (Easy Clinical Information Extractor [CIE]-SSI) for operative event-level detection of SSIs using an training cohort (4574 operative events) from 1 healthcare system and then conducted internal validation on a blind cohort from the same healthcare system (1850 operative events) and external validation on a blind cohort from the second healthcare system (15,360 operative events). EasyCIE-SSI performance was measured using sensitivity, specificity, and area under the receiveroperating- curve (AUC). Results: The prevalence of SSI was 4% and 5% in the internal and external validation corpora. In internal validation, EasyCIE-SSI had a sensitivity, specificity, AUC of 94%, 88%, 0.912 for the detection of SSI, respectively. In external validation, EasyCIE-SSI had sensitivity, specificity, AUC of 79%, 92%, 0.852 for the detection of SSI, respectively. The sensitivity of EasyCIESSI decreased in clean, skin/subcutaneous, and outpatient procedures in the external validation compared to internal validation. Conclusion: Automated surveillance of SSIs can be achieved using NLP of clinical notes with high sensitivity and specificity. [ABSTRACT FROM AUTHOR]

As of September 21, 2020, the coronavirus disease 2019 (COVID-19) pandemic had resulted in more than 6,800,000 reported U.S. cases and more than 199,000 associated deaths.* Early in the pandemic, COVID-19 incidence was highest among older adults (1). CDC examined the changing age distribution of the COVID-19 pandemic in the United States during May-August by assessing three indicators: COVID-19-like illness-related emergency department (ED) visits, positive reverse transcription-polymerase chain reaction (RT-PCR) test results for SARS-CoV-2, the virus that causes COVID-19, and confirmed COVID-19 cases. Nationwide, the median age of COVID-19 cases declined from 46 years in May to 37 years in July and 38 in August. Similar patterns were seen for COVID-19-like illness-related ED visits and positive SARS-CoV-2 RT-PCR test results in all U.S. Census regions. During June-August, COVID-19 incidence was highest in persons aged 20-29 years, who accounted for >20% of all confirmed cases. The southern United States experienced regional outbreaks of COVID-19 in June. In these regions, increases in the percentage of positive SARS-CoV-2 test results among adults aged 20-39 years preceded increases among adults aged ≥60 years by an average of 8.7 days (range = 4-15 days), suggesting that younger adults likely contributed to community transmission of COVID-19. Given the role of asymptomatic and presymptomatic transmission (2), strict adherence to community mitigation strategies and personal preventive behaviors by younger adults is needed to help reduce their risk for infection and subsequent transmission of SARS-CoV-2 to persons at higher risk for severe illness. [ABSTRACT FROM AUTHOR]

Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use† and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.§ Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.¶ In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for ≤2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks. [ABSTRACT FROM AUTHOR]

On March 13, 2020, the United States declared a national emergency in response to the coronavirus disease 2019 (COVID-19) pandemic. Subsequently, states enacted stay-at-home orders to slow the spread of SARS-CoV-2, the virus that causes COVID-19, and reduce the burden on the U.S. health care system. CDC* and the Centers for Medicare & Medicaid Services (CMS)† recommended that health care systems prioritize urgent visits and delay elective care to mitigate the spread of COVID-19 in health care settings. By May 2020, national syndromic surveillance data found that emergency department (ED) visits had declined 42% during the early months of the pandemic (1). This report describes trends in ED visits for three acute life-threatening health conditions (myocardial infarction [MI, also known as heart attack], stroke, and hyperglycemic crisis), immediately before and after declaration of the COVID-19 pandemic as a national emergency. These conditions represent acute events that always necessitate immediate emergency care, even during a public health emergency such as the COVID-19 pandemic. In the 10 weeks following the emergency declaration (March 15-May 23, 2020), ED visits declined 23% for MI, 20% for stroke, and 10% for hyperglycemic crisis, compared with the preceding 10-week period (January 5-March 14, 2020). EDs play a critical role in diagnosing and treating life-threatening conditions that might result in serious disability or death. Persons experiencing signs or symptoms of serious illness, such as severe chest pain, sudden or partial loss of motor function, altered mental state, signs of extreme hyperglycemia, or other life-threatening issues, should seek immediate emergency care, regardless of the pandemic. Clear, frequent, highly visible communication from public health and health care professionals is needed to reinforce the importance of timely care for medical emergencies and to assure the public that EDs are implementing infection prevention and control guidelines that help ensure the safety of their patients and health care personnel. [ABSTRACT FROM AUTHOR]