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1.
BMJ Open ; 12(3): e059315, 2022 03 23.
Article in English | MEDLINE | ID: covidwho-1759371

ABSTRACT

OBJECTIVE: To examine victimisation rates, geographic patterns and neighbourhood characteristics associated with non-fatal firearm injury rates before and during the COVID-19 pandemic. DESIGN: A retrospective cohort study. SETTING: City of Indianapolis, Indiana, USA, 1 January 2017-30 June 2021. PARTICIPANTS: Intentional non-fatal firearm injury victims from Indianapolis Metropolitan Police Department records. The study included information on 2578 non-fatal firearm injury victims between ages 0 and 77 years. Of these victims, 82.5% were male and 77.4% were black. PRIMARY AND SECONDARY OUTCOME MEASURES: Rates of non-fatal firearm injuries per 100 000 population by victim age, race, sex and incident motive. Prepandemic and peripandemic non-fatal firearm injury rates. RESULTS: Non-fatal shooting rates increased 8.60%, from 57.0 per 100 000 person-years in prepandemic years to 65.6 per 100 000 person-years during the pandemic (p<0.001). Rates of female victims (15.2 vs 23.8 per 100,000; p<0.001) and older victims (91.3 vs 120.4 per 100,000; p<0.001) increased significantly during the pandemic compared with the prepandemic period. Neighbourhoods with higher levels of structural disadvantage (IRR: 1.157, 95% CI 1.012 to 1.324) and prepandemic firearm injury rates (IRR: 1.001, 95% CI 1.001 to 1.002) was positively associated with higher rates of non-fatal firearm injuries during the pandemic, adjusting for neighbourhood characteristics. CONCLUSIONS: Non-fatal firearm injuries increased significantly during the COVID-19 pandemic, particularly among female and older victims. Efforts are needed to expand and rethink current firearm prevention efforts that both address the diversification of victimisation and the larger societal trauma of firearm violence.


Subject(s)
COVID-19 , Firearms , Wounds, Gunshot , Adolescent , Adult , Aged , COVID-19/epidemiology , Child , Child, Preschool , Cohort Studies , Female , Humans , Indiana/epidemiology , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , Retrospective Studies , Wounds, Gunshot/epidemiology , Young Adult
2.
J Vasc Surg Venous Lymphat Disord ; 9(3): 605-614.e2, 2021 05.
Article in English | MEDLINE | ID: covidwho-1510080

ABSTRACT

OBJECTIVE: Early reports suggest that patients with novel coronavirus disease-2019 (COVID-19) infection carry a significant risk of altered coagulation with an increased risk for venous thromboembolic events. This report investigates the relationship of significant COVID-19 infection and deep venous thrombosis (DVT) as reflected in the patient clinical and laboratory characteristics. METHODS: We reviewed the demographics, clinical presentation, laboratory and radiologic evaluations, results of venous duplex imaging and mortality of COVID-19-positive patients (18-89 years) admitted to the Indiana University Academic Health Center. Using oxygen saturation, radiologic findings, and need for advanced respiratory therapies, patients were classified into mild, moderate, or severe categories of COVID-19 infection. A descriptive analysis was performed using univariate and bivariate Fisher's exact and Wilcoxon rank-sum tests to examine the distribution of patient characteristics and compare the DVT outcomes. A multivariable logistic regression model was used to estimate the adjusted odds ratio of experiencing DVT and a receiver operating curve analysis to identify the optimal cutoff for d-dimer to predict DVT in this COVID-19 cohort. Time to the diagnosis of DVT from admission was analyzed using log-rank test and Kaplan-Meier plots. RESULTS: Our study included 71 unique COVID-19-positive patients (mean age, 61 years) categorized as having 3% mild, 14% moderate, and 83% severe infection and evaluated with 107 venous duplex studies. DVT was identified in 47.8% of patients (37% of examinations) at an average of 5.9 days after admission. Patients with DVT were predominantly male (67%; P = .032) with proximal venous involvement (29% upper and 39% in the lower extremities with 55% of the latter demonstrating bilateral involvement). Patients with DVT had a significantly higher mean d-dimer of 5447 ± 7032 ng/mL (P = .0101), and alkaline phosphatase of 110 IU/L (P = .0095) than those without DVT. On multivariable analysis, elevated d-dimer (P = .038) and alkaline phosphatase (P = .021) were associated with risk for DVT, whereas age, sex, elevated C-reactive protein, and ferritin levels were not. A receiver operating curve analysis suggests an optimal d-dimer value of 2450 ng/mL cutoff with 70% sensitivity, 59.5% specificity, and 61% positive predictive value, and 68.8% negative predictive value. CONCLUSIONS: This study suggests that males with severe COVID-19 infection requiring hospitalization are at highest risk for developing DVT. Elevated d-dimers and alkaline phosphatase along with our multivariable model can alert the clinician to the increased risk of DVT requiring early evaluation and aggressive treatment.


Subject(s)
Alkaline Phosphatase/blood , COVID-19 , Extremities , Fibrin Fibrinogen Degradation Products/analysis , Risk Assessment/methods , Ultrasonography, Doppler, Duplex , Venous Thrombosis , Anticoagulants/administration & dosage , Biomarkers/blood , Blood Coagulation , COVID-19/blood , COVID-19/complications , COVID-19/mortality , COVID-19/therapy , Early Diagnosis , Extremities/blood supply , Extremities/diagnostic imaging , Female , Humans , Indiana/epidemiology , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , SARS-CoV-2/isolation & purification , Time-to-Treatment/statistics & numerical data , Ultrasonography, Doppler, Duplex/methods , Ultrasonography, Doppler, Duplex/statistics & numerical data , Venous Thrombosis/diagnosis , Venous Thrombosis/drug therapy , Venous Thrombosis/etiology , Venous Thrombosis/prevention & control
3.
Am J Public Health ; 111(S3): S197-S200, 2021 10.
Article in English | MEDLINE | ID: covidwho-1496724

ABSTRACT

COVID-19 highlights preexisting inequities that affect health outcomes and access to care for Black and Brown Americans. The Marion County Public Health Department in Indiana sought to address inequities in COVID-19 testing by using surveillance data to place community testing sites in areas with the highest incidence of disease. Testing site demographic data indicated that targeted testing reached populations with the highest disease burden, suggesting that local health departments can effectively use surveillance data as a tool to address inequities. (Am J Public Health. 2021;111(S3):S197-S200. https://doi.org/10.2105/AJPH.2021.306421).


Subject(s)
COVID-19 Testing , COVID-19/epidemiology , Health Equity , Population Surveillance , Public Health , Decision Making , Humans , Indiana/epidemiology
4.
MMWR Morb Mortal Wkly Rep ; 69(29): 960-964, 2020 07 24.
Article in English | MEDLINE | ID: covidwho-1389848

ABSTRACT

Population prevalence of persons infected with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), varies by subpopulation and locality. U.S. studies of SARS-CoV-2 infection have examined infections in nonrandom samples (1) or seroprevalence in specific populations* (2), which are limited in their generalizability and cannot be used to accurately calculate infection-fatality rates. During April 25-29, 2020, Indiana conducted statewide random sample testing of persons aged ≥12 years to assess prevalence of active infection and presence of antibodies to SARS-CoV-2; additional nonrandom sampling was conducted in racial and ethnic minority communities to better understand the impact of the virus in certain racial and ethnic minority populations. Estimates were adjusted for nonresponse to reflect state demographics using an iterative proportional fitting method. Among 3,658 noninstitutionalized participants in the random sample survey, the estimated statewide point prevalence of active SARS-CoV-2 infection confirmed by reverse transcription-polymerase chain reaction (RT-PCR) testing was 1.74% (95% confidence interval [CI] = 1.10-2.54); 44.2% of these persons reported no symptoms during the 2 weeks before testing. The prevalence of immunoglobulin G (IgG) seropositivity, indicating past infection, was 1.09% (95% CI = 0.76-1.45). The overall prevalence of current and previous infections of SARS-CoV-2 in Indiana was 2.79% (95% CI = 2.02-3.70). In the random sample, higher overall prevalences were observed among Hispanics and those who reported having a household contact who had previously been told by a health care provider that they had COVID-19. By late April, an estimated 187,802 Indiana residents were currently or previously infected with SARS-CoV-2 (9.6 times higher than the number of confirmed cases [17,792]) (3), and 1,099 residents died (infection-fatality ratio = 0.58%). The number of reported cases represents only a fraction of the estimated total number of infections. Given the large number of persons who remain susceptible in Indiana, adherence to evidence-based public health mitigation and containment measures (e.g., social distancing, consistent and correct use of face coverings, and hand hygiene) is needed to reduce surge in hospitalizations and prevent morbidity and mortality from COVID-19.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Public Health Surveillance/methods , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 , Child , Coronavirus Infections/ethnology , Female , Humans , Indiana/epidemiology , Male , Middle Aged , Pandemics , Pneumonia, Viral/ethnology , Prevalence , Young Adult
5.
J Med Internet Res ; 23(7): e28812, 2021 07 26.
Article in English | MEDLINE | ID: covidwho-1334873

ABSTRACT

BACKGROUND: The COVID-19 pandemic has changed public health policies and human and community behaviors through lockdowns and mandates. Governments are rapidly evolving policies to increase hospital capacity and supply personal protective equipment and other equipment to mitigate disease spread in affected regions. Current models that predict COVID-19 case counts and spread are complex by nature and offer limited explainability and generalizability. This has highlighted the need for accurate and robust outbreak prediction models that balance model parsimony and performance. OBJECTIVE: We sought to leverage readily accessible data sets extracted from multiple states to train and evaluate a parsimonious predictive model capable of identifying county-level risk of COVID-19 outbreaks on a day-to-day basis. METHODS: Our modeling approach leveraged the following data inputs: COVID-19 case counts per county per day and county populations. We developed an outbreak gold standard across California, Indiana, and Iowa. The model utilized a per capita running 7-day sum of the case counts per county per day and the mean cumulative case count to develop baseline values. The model was trained with data recorded between March 1 and August 31, 2020, and tested on data recorded between September 1 and October 31, 2020. RESULTS: The model reported sensitivities of 81%, 92%, and 90% for California, Indiana, and Iowa, respectively. The precision in each state was above 85% while specificity and accuracy scores were generally >95%. CONCLUSIONS: Our parsimonious model provides a generalizable and simple alternative approach to outbreak prediction. This methodology can be applied to diverse regions to help state officials and hospitals with resource allocation and to guide risk management, community education, and mitigation strategies.


Subject(s)
COVID-19/epidemiology , Computer Simulation , Datasets as Topic , Disease Outbreaks/statistics & numerical data , Forecasting/methods , Heuristics , Public Sector , COVID-19/prevention & control , California/epidemiology , Humans , Indiana/epidemiology , Iowa/epidemiology , Models, Biological , SARS-CoV-2
6.
PLoS One ; 16(7): e0255063, 2021.
Article in English | MEDLINE | ID: covidwho-1323016

ABSTRACT

BACKGROUND: Early studies on COVID-19 identified unequal patterns in hospitalization and mortality in urban environments for racial and ethnic minorities. These studies were primarily single center observational studies conducted within the first few weeks or months of the pandemic. We sought to examine trends in COVID-19 morbidity, hospitalization, and mortality over time for minority and rural populations, especially during the U.S. fall surge. METHODS: Data were extracted from a statewide cohort of all adult residents in Indiana tested for SARS-CoV-2 infection between March 1 and December 31, 2020, linked to electronic health records. Primary measures were per capita rates of infection, hospitalization, and death. Age adjusted rates were calculated for multiple time periods corresponding to public health mitigation efforts. Comparisons across time within groups were compared using ANOVA. RESULTS: Morbidity and mortality increased over time with notable differences among sub-populations. Initially, hospitalization rates among racial minorities were 3-4 times higher than whites, and mortality rates among urban residents were twice those of rural residents. By fall 2020, hospitalization and mortality rates in rural areas surpassed those of urban areas, and gaps between black/brown and white populations narrowed. Changes across time among demographic groups was significant for morbidity and hospitalization. Cumulative morbidity and mortality were highest among minority groups and in rural communities. CONCLUSIONS: The synchronicity of disparities in COVID-19 by race and geography suggests that health officials should explicitly measure disparities and adjust mitigation as well as vaccination strategies to protect those sub-populations with greater disease burden.


Subject(s)
COVID-19 , Health Status Disparities , Hospitalization , Minority Groups , Rural Population , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/ethnology , COVID-19/mortality , Female , Humans , Indiana/epidemiology , Male , Middle Aged , Morbidity
7.
J Am Geriatr Soc ; 69(9): 2412-2418, 2021 09.
Article in English | MEDLINE | ID: covidwho-1247239

ABSTRACT

INTRODUCTION: Older adults are at greater risk of both infection with and mortality from COVID-19. Many U.S. nursing homes have been devastated by the COVID-19 pandemic, yet little has been described regarding the typical disease course in this population. The objective of this study is to describe and identify patterns in the disease course of nursing home residents infected with COVID-19. SETTING AND METHODS: This is a case series of 74 residents with COVID-19 infection in a nursing home in central Indiana between March 28 and June 17, 2020. Data were extracted from the electronic medical record and from nursing home medical director tracking notes from the time of the index infection through August 31, 2020. The clinical authorship team reviewed the data to identify patterns in the disease course of the residents. RESULTS: The most common symptoms were fever, hypoxia, anorexia, and fatigue/malaise. The duration of symptoms was extended, with an average of over 3 weeks. Of those infected 25 died; 23 of the deaths were considered related to COVID-19 infection. A subset of residents with COVID-19 infection experienced a rapidly progressive, fatal course. DISCUSSION/CONCLUSIONS: Nursing home residents infected with COVID-19 from the facility we studied experienced a prolonged disease course regardless of the severity of their symptoms, with implications for the resources needed to care for and support of these residents during active infection and post-disease. Future studies should combine data from nursing home residents across the country to identify the risk factors for disease trajectories identified in this case series.


Subject(s)
COVID-19/pathology , Homes for the Aged/statistics & numerical data , Nursing Homes/statistics & numerical data , SARS-CoV-2 , Aged , Aged, 80 and over , COVID-19/mortality , Female , Humans , Indiana/epidemiology , Male , Risk Factors , Severity of Illness Index
8.
BMC Emerg Med ; 21(1): 36, 2021 03 24.
Article in English | MEDLINE | ID: covidwho-1150389

ABSTRACT

BACKGROUND: While COVID-19 has had far-reaching consequences on society and health care providers, there is a paucity of research exploring frontline emergency medicine (EM) provider wellness over the course of a pandemic. The objective of this study was to assess the well-being, resilience, burnout, and wellness factors and needs of EM physicians and advanced practice providers (e.g., nurse practitioners and physician assistants; APPs) during the initial phase of the COVID-19 pandemic. METHODS: A descriptive, prospective, cohort survey study of EM physicians and APPs was performed across ten emergency departments in a single state, including academic and community settings. Participants were recruited via email to complete four weekly, voluntary, anonymous questionnaires comprised of customized and validated tools for assessing wellness (Well Being Index), burnout (Physician Work Life Study item), and resilience (Brief Resilience Scale) during the initial acceleration phase of COVID-19. Univariate and multivariate analysis with Chi-squared, Fisher's Exact, and logistic regression was performed. RESULTS: Of 213 eligible participants, response rates ranged from 31 to 53% over four weeks. Women comprised 54 to 60% of responses. Nonrespondent characteristics were similar to respondents. Concern for personal safety decreased from 85 to 61% (p < 0.001). Impact on basic self-care declined from 66 to 32% (p < 0.001). Symptoms of stress, anxiety, or fear was initially 83% and reduced to 66% (p = 0.009). Reported strain on relationships and feelings of isolation affected > 50% of respondents initially without significant change (p = 0.05 and p = 0.30 respectively). Women were nearly twice as likely to report feelings of isolation as men (OR 1.95; 95% CI 1.82-5.88). Working part-time carried twice the risk of burnout (OR, 2.45; 95% CI, 1.10-5.47). Baseline resilience was normal to high. Provider well-being improved over the four weeks (30 to 14%; p = 0.01), but burnout did not significantly change (30 to 22%; p = 0.39). CONCLUSION: This survey of frontline EM providers, including physicians and APPs, during the initial surge of COVID-19 found that despite being a resilient group, the majority experienced stress, anxiety, fear, and concerns about personal safety due to COVID-19, putting many at risk for burnout. The sustained impact of the pandemic on EM provider wellness deserves further investigation to guide targeted interventions.


Subject(s)
Burnout, Professional/epidemiology , COVID-19/epidemiology , Emergency Service, Hospital , Academic Medical Centers , Adult , Female , Hospitals, Community , Humans , Indiana/epidemiology , Male , Middle Aged , Pandemics , Prospective Studies , SARS-CoV-2 , Surveys and Questionnaires
9.
PLoS One ; 16(3): e0241875, 2021.
Article in English | MEDLINE | ID: covidwho-1148240

ABSTRACT

BACKGROUND: Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods. METHODS: We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide prevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection. RESULTS: Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR = 5.34, p<0.001), anosmia (OR = 4.08, p<0.001), ageusia (OR = 2.38, p = 0.006), and cough (OR = 2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection. CONCLUSIONS: Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Mass Screening/methods , Adolescent , Adult , Aged , Aged, 80 and over , Ageusia/epidemiology , Ageusia/virology , COVID-19/prevention & control , Cough , Cross-Sectional Studies/methods , Dyspnea , Epidemiologic Studies , Female , Fever/epidemiology , Fever/virology , Humans , Indiana/epidemiology , Male , Middle Aged , Prevalence , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Syndrome
10.
J Public Health Manag Pract ; 27(3): 246-250, 2021.
Article in English | MEDLINE | ID: covidwho-1138026

ABSTRACT

CONTEXT: Existing hospitalization ratios for COVID-19 typically use case counts in the denominator, which problematically underestimates total infections because asymptomatic and mildly infected persons rarely get tested. As a result, surge models that rely on case counts to forecast hospital demand may be inaccurately influencing policy and decision-maker action. OBJECTIVE: Based on SARS-CoV-2 prevalence data derived from a statewide random sample (as opposed to relying on reported case counts), we determine the infection-hospitalization ratio (IHR), defined as the percentage of infected individuals who are hospitalized, for various demographic groups in Indiana. Furthermore, for comparison, we show the extent to which case-based hospitalization ratios, compared with the IHR, overestimate the probability of hospitalization by demographic group. DESIGN: Secondary analysis of statewide prevalence data from Indiana, COVID-19 hospitalization data extracted from a statewide health information exchange, and all reported COVID-19 cases to the state health department. SETTING: State of Indiana as of April 30, 2020. MAIN OUTCOME MEASURES: Demographic-stratified IHRs and case-hospitalization ratios. RESULTS: The overall IHR was 2.1% and varied more by age than by race or sex. Infection-hospitalization ratio estimates ranged from 0.4% for those younger than 40 years to 9.2% for those older than 60 years. Hospitalization rates based on case counts overestimated the IHR by a factor of 10, but this overestimation differed by demographic groups, especially age. CONCLUSIONS: In this first study of the IHR based on population prevalence, our results can improve forecasting models of hospital demand-especially in preparation for the upcoming winter period when an increase in SARS CoV-2 infections is expected.


Subject(s)
COVID-19/epidemiology , COVID-19/therapy , Civil Defense/organization & administration , Civil Defense/statistics & numerical data , Hospitalization/statistics & numerical data , Hospitalization/trends , Population Surveillance , Adolescent , Adult , Aged , Aged, 80 and over , Female , Forecasting , Humans , Indiana/epidemiology , Male , Middle Aged , Prevalence , SARS-CoV-2 , Young Adult
12.
MMWR Morb Mortal Wkly Rep ; 70(4): 118-122, 2021 Jan 29.
Article in English | MEDLINE | ID: covidwho-1112897

ABSTRACT

Institutions of higher education adopted different approaches for the fall semester 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic. Approximately 45% of colleges and universities implemented online instruction, more than one fourth (27%) provided in-person instruction, and 21% used a hybrid model (1). Although CDC has published COVID-19 guidance for institutions of higher education (2-4), little has been published regarding the response to COVID-19 outbreaks on college and university campuses (5). In August 2020, an Indiana university with approximately 12,000 students (including 8,000 undergraduate students, 85% of whom lived on campus) implemented various public health measures to reduce transmission of SARS-CoV-2, the virus that causes COVID-19. Despite these measures, the university experienced an outbreak involving 371 cases during the first few weeks of the fall semester. The majority of cases occurred among undergraduate students living off campus, and several large off-campus gatherings were identified as common sources of exposure. Rather than sending students home, the university switched from in-person to online instruction for undergraduate students and instituted a series of campus restrictions for 2 weeks, during which testing, contact tracing, and isolation and quarantine programs were substantially enhanced, along with educational efforts highlighting the need for strict adherence to the mitigation measures. After 2 weeks, the university implemented a phased return to in-person instruction (with 85% of classes offered in person) and resumption of student life activities. This report describes the outbreak and the data-driven, targeted interventions and rapid escalation of testing, tracing, and isolation measures that enabled the medium-sized university to resume in-person instruction and campus activities. These strategies might prove useful to other colleges and universities responding to campus outbreaks.


Subject(s)
COVID-19/prevention & control , Disease Outbreaks/prevention & control , Universities/organization & administration , COVID-19/epidemiology , COVID-19 Testing , Contact Tracing , Humans , Indiana/epidemiology , Patient Isolation , Quarantine
13.
J Contin Educ Nurs ; 52(3): 109-111, 2021 Mar 01.
Article in English | MEDLINE | ID: covidwho-1102576

ABSTRACT

This article describes how a health care organization optimized staffing during the COVID-19 crisis by capitalizing on the expertise of nursing professional development practitioners to create a rapid deployment onboarding plan. The rapid onboarding training plan provided Riley Hospital for Children at Indiana University Health with a sense of stability in an uncertain time. Designing a plan that easily could be modified allowed the organization to be prepared during the pandemic and at a point where staffing needs must meet surge capacity. [J Contin Educ Nurs. 2021;52(3):109-111.].


Subject(s)
COVID-19/nursing , Inservice Training , Nursing Staff, Hospital/organization & administration , Pediatric Nursing , Personnel Staffing and Scheduling , Algorithms , COVID-19/epidemiology , Clinical Competence , Hospitals, Pediatric , Humans , Indiana/epidemiology , Nursing Staff, Hospital/education , Pandemics , Pediatric Nursing/education , SARS-CoV-2 , Surge Capacity
14.
J Med Virol ; 93(5): 2883-2889, 2021 May.
Article in English | MEDLINE | ID: covidwho-1082475

ABSTRACT

INTRODUCTION: The rate of bacterial coinfection with SARS-CoV-2 is poorly defined. The decision to administer antibiotics early in the course of SARS-CoV-2 infection depends on the likelihood of bacterial coinfection. METHODS: We performed a retrospective chart review of all patients admitted through the emergency department with confirmed SARS-CoV-2 infection over a 6-week period in a large healthcare system in the United States. Blood and respiratory culture results were abstracted and adjudicated by multiple authors. The primary outcome was the rate of bacteremia. We secondarily looked to define clinical or laboratory features associated with bacteremia. RESULTS: There were 542 patients admitted with confirmed SARS-CoV-2 infection, with an average age of 62.8 years. Of these, 395 had blood cultures performed upon admission, with six true positive results (1.1% of the total population). An additional 14 patients had positive respiratory cultures treated as true pathogens in the first 72 h. Low blood pressure and elevated white blood cell count, neutrophil count, blood urea nitrogen, and lactate were statistically significantly associated with bacteremia. Clinical outcomes were not statistically significantly different between patients with and without bacteremia. CONCLUSIONS: We found a low rate of bacteremia in patients admitted with confirmed SARS-CoV-2 infection. In hemodynamically stable patients, routine antibiotics may not be warranted in this population.


Subject(s)
Bacterial Infections/epidemiology , COVID-19/epidemiology , Coinfection/epidemiology , Emergency Service, Hospital/statistics & numerical data , Anti-Bacterial Agents/therapeutic use , Bacteremia/diagnosis , Bacteremia/epidemiology , Bacteremia/therapy , Bacterial Infections/diagnosis , Bacterial Infections/therapy , COVID-19/diagnosis , COVID-19/therapy , Coinfection/diagnosis , Coinfection/therapy , Female , Hospitalization , Hospitals , Humans , Indiana/epidemiology , Male , Middle Aged , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Treatment Outcome
16.
J Am Med Inform Assoc ; 28(7): 1363-1373, 2021 07 14.
Article in English | MEDLINE | ID: covidwho-1041772

ABSTRACT

OBJECTIVE: We sought to support public health surveillance and response to coronavirus disease 2019 (COVID-19) through rapid development and implementation of novel visualization applications for data amalgamated across sectors. MATERIALS AND METHODS: We developed and implemented population-level dashboards that collate information on individuals tested for and infected with COVID-19, in partnership with state and local public health agencies as well as health systems. The dashboards are deployed on top of a statewide health information exchange. One dashboard enables authorized users working in public health agencies to surveil populations in detail, and a public version provides higher-level situational awareness to inform ongoing pandemic response efforts in communities. RESULTS: Both dashboards have proved useful informatics resources. For example, the private dashboard enabled detection of a local community outbreak associated with a meat packing plant. The public dashboard provides recent trend analysis to track disease spread and community-level hospitalizations. Combined, the tools were utilized 133 637 times by 74 317 distinct users between June 21 and August 22, 2020. The tools are frequently cited by journalists and featured on social media. DISCUSSION: Capitalizing on a statewide health information exchange, in partnership with health system and public health leaders, Regenstrief biomedical informatics experts rapidly developed and deployed informatics tools to support surveillance and response to COVID-19. CONCLUSIONS: The application of public health informatics methods and tools in Indiana holds promise for other states and nations. Yet, development of infrastructure and partnerships will require effort and investment after the current pandemic in preparation for the next public health emergency.


Subject(s)
COVID-19/epidemiology , Data Visualization , Public Health Informatics , Public Health Surveillance/methods , Health Information Exchange , Humans , Indiana/epidemiology , United States
17.
Proc Natl Acad Sci U S A ; 118(5)2021 02 02.
Article in English | MEDLINE | ID: covidwho-1030488

ABSTRACT

From 25 to 29 April 2020, the state of Indiana undertook testing of 3,658 randomly chosen state residents for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the agent causing COVID-19 disease. This was the first statewide randomized study of COVID-19 testing in the United States. Both PCR and serological tests were administered to all study participants. This paper describes statistical methods used to address nonresponse among various demographic groups and to adjust for testing errors to reduce bias in the estimates of the overall disease prevalence in Indiana. These adjustments were implemented through Bayesian methods, which incorporated all available information on disease prevalence and test performance, along with external data obtained from census of the Indiana statewide population. Both adjustments appeared to have significant impact on the unadjusted estimates, mainly due to upweighting data in study participants of non-White races and Hispanic ethnicity and anticipated false-positive and false-negative test results among both the PCR and antibody tests utilized in the study.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , SARS-CoV-2/isolation & purification , Bayes Theorem , COVID-19/ethnology , COVID-19/virology , COVID-19 Testing/statistics & numerical data , Humans , Indiana/epidemiology , Indiana/ethnology , Polymerase Chain Reaction , Prevalence , SARS-CoV-2/genetics , /statistics & numerical data
18.
Pediatr Pulmonol ; 56(5): 1271-1273, 2021 05.
Article in English | MEDLINE | ID: covidwho-1023307

ABSTRACT

To assess the impact of COVID-19 restrictions on cystic fibrosis (CF) pulmonary exacerbations (PEx) we performed a retrospective review of PEx events at our CF Center and compared the rate of PEx in 2019 versus 2020. Restrictions on social interaction due to the COVID-19 pandemic were associated with a lower number of PEx events at our pediatric CF Center, suggesting that these restrictions also reduced exposure to other respiratory viral infection in children with CF.


Subject(s)
COVID-19 , Cystic Fibrosis/complications , Physical Distancing , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Child , Child, Preschool , Disease Progression , Female , Humans , Indiana/epidemiology , Male , Pneumonia, Viral/complications , Retrospective Studies
19.
Front Public Health ; 8: 593861, 2020.
Article in English | MEDLINE | ID: covidwho-1000214

ABSTRACT

Objectives: To describe variations in coronavirus disease 2019 (COVID-19) diagnosis by zip code race and ethnicity in Indiana. Methods: Cross-sectional evaluation of subjects with SARS-CoV-2 at Indiana University Health. We performed two separate analyses, first evaluating likelihood of COVID-19 diagnosis by race (Caucasian, African American, Asian, or other) and ethnicity (Hispanic vs. non-Hispanic) in the cohort encompassing the entire state of Indiana. Subsequently, patient data was geolocated with zip codes in Marion County and the immediate surrounding counties, and descriptive statistical analyses were used to calculate the number of COVID-19 cases per 10,000 persons for each of these zip codes. Results: Indiana had a total of 3,892 positive COVID-19 cases from January 1 to April 30, 2020. The odds of testing positive for COVID-19 were four-fold higher in African Americans than non-African Americans (OR 4.58, 95% CI 4.25-4.94, P < 0.0001). Increased COVID-19 cases per 10,000 persons were seen in zip codes with higher percentage of African American (median infection rate of 17.4 per 10,000 population in zip codes above median % African American compared to 6.7 per 10,000 population in zip codes below median % African American, with an overall median infection rate 9.9 per 10,000 population, P < 0.0001) or Hispanic residents (median infection rate of 15.9 per 10,000 population in zip codes above median % Hispanic compared to 7.0 per 10,000 population in zip codes below median % Hispanic, overall median infection rate 9.6 per 10,000 population, P < 0.0001). Conclusions: Individuals from zip codes with higher percentages of African American, Hispanic, foreign-born, and/or residents living in poverty are disproportionately affected by COVID-19. Urgent work is needed to understand and address the disproportionate burden of COVID-19 in minority communities and when economic disparities are present.


Subject(s)
African Americans/statistics & numerical data , COVID-19/epidemiology , Health Status Disparities , /statistics & numerical data , COVID-19/ethnology , Cohort Studies , Cross-Sectional Studies , Female , Humans , Indiana/epidemiology , Male , Poverty , SARS-CoV-2
20.
Am Surg ; 87(8): 1214-1222, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-992192

ABSTRACT

Rural surgeons from disparate areas of the United States report on the effects of the COVID-19 pandemic in their communities as the virus has spread across the country. The pandemic has brought significant changes to the professional, economic, and social lives of the individual surgeons and their communities.


Subject(s)
COVID-19/epidemiology , Rural Health Services , Surgeons , Alaska/epidemiology , Arizona/epidemiology , Health Services, Indigenous/organization & administration , Health Services, Indigenous/statistics & numerical data , Hospitals, Rural/organization & administration , Hospitals, Rural/statistics & numerical data , Humans , Idaho/epidemiology , Illinois/epidemiology , Indiana/epidemiology , Ohio/epidemiology , Oregon/epidemiology , Rural Health Services/organization & administration , Rural Health Services/statistics & numerical data , Rural Population , West Virginia/epidemiology
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