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2.
MMWR Morb Mortal Wkly Rep ; 70(44): 1553-1559, 2021 Nov 05.
Article in English | MEDLINE | ID: covidwho-1502903

ABSTRACT

Immunocompromised persons, defined as those with suppressed humoral or cellular immunity resulting from health conditions or medications, account for approximately 3% of the U.S. adult population (1). Immunocompromised adults are at increased risk for severe COVID-19 outcomes (2) and might not acquire the same level of protection from COVID-19 mRNA vaccines as do immunocompetent adults (3,4). To evaluate vaccine effectiveness (VE) among immunocompromised adults, data from the VISION Network* on hospitalizations among persons aged ≥18 years with COVID-19-like illness from 187 hospitals in nine states during January 17-September 5, 2021 were analyzed. Using selected discharge diagnoses,† VE against COVID-19-associated hospitalization conferred by completing a 2-dose series of an mRNA COVID-19 vaccine ≥14 days before the index hospitalization date§ (i.e., being fully vaccinated) was evaluated using a test-negative design comparing 20,101 immunocompromised adults (10,564 [53%] of whom were fully vaccinated) and 69,116 immunocompetent adults (29,456 [43%] of whom were fully vaccinated). VE of 2 doses of mRNA COVID-19 vaccine against COVID-19-associated hospitalization was lower among immunocompromised patients (77%; 95% confidence interval [CI] = 74%-80%) than among immunocompetent patients (90%; 95% CI = 89%-91%). This difference persisted irrespective of mRNA vaccine product, age group, and timing of hospitalization relative to SARS-CoV-2 (the virus that causes COVID-19) B.1.617.2 (Delta) variant predominance in the state of hospitalization. VE varied across immunocompromising condition subgroups, ranging from 59% (organ or stem cell transplant recipients) to 81% (persons with a rheumatologic or inflammatory disorder). Immunocompromised persons benefit from mRNA COVID-19 vaccination but are less protected from severe COVID-19 outcomes than are immunocompetent persons, and VE varies among immunocompromised subgroups. Immunocompromised persons receiving mRNA COVID-19 vaccines should receive 3 doses and a booster, consistent with CDC recommendations (5), practice nonpharmaceutical interventions, and, if infected, be monitored closely and considered early for proven therapies that can prevent severe outcomes.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Hospitalization/statistics & numerical data , Immunocompromised Host/immunology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/immunology , COVID-19/therapy , COVID-19 Vaccines/immunology , Female , Humans , Immunization Schedule , Laboratories , Male , Middle Aged , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , United States/epidemiology , Vaccines, Synthetic/administration & dosage , Young Adult
3.
MMWR Morb Mortal Wkly Rep ; 70(44): 1539-1544, 2021 Nov 05.
Article in English | MEDLINE | ID: covidwho-1502901

ABSTRACT

Previous infection with SARS-CoV-2 (the virus that causes COVID-19) or COVID-19 vaccination can provide immunity and protection from subsequent SARS-CoV-2 infection and illness. CDC used data from the VISION Network* to examine hospitalizations in adults with COVID-19-like illness and compared the odds of receiving a positive SARS-CoV-2 test result, and thus having laboratory-confirmed COVID-19, between unvaccinated patients with a previous SARS-CoV-2 infection occurring 90-179 days before COVID-19-like illness hospitalization, and patients who were fully vaccinated with an mRNA COVID-19 vaccine 90-179 days before hospitalization with no previous documented SARS-CoV-2 infection. Hospitalized adults aged ≥18 years with COVID-19-like illness were included if they had received testing at least twice: once associated with a COVID-19-like illness hospitalization during January-September 2021 and at least once earlier (since February 1, 2020, and ≥14 days before that hospitalization). Among COVID-19-like illness hospitalizations in persons whose previous infection or vaccination occurred 90-179 days earlier, the odds of laboratory-confirmed COVID-19 (adjusted for sociodemographic and health characteristics) among unvaccinated, previously infected adults were higher than the odds among fully vaccinated recipients of an mRNA COVID-19 vaccine with no previous documented infection (adjusted odds ratio [aOR] = 5.49; 95% confidence interval [CI] = 2.75-10.99). These findings suggest that among hospitalized adults with COVID-19-like illness whose previous infection or vaccination occurred 90-179 days earlier, vaccine-induced immunity was more protective than infection-induced immunity against laboratory-confirmed COVID-19. All eligible persons should be vaccinated against COVID-19 as soon as possible, including unvaccinated persons previously infected with SARS-CoV-2.


Subject(s)
COVID-19/diagnosis , COVID-19/immunology , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/therapy , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/immunology , Female , Hospitalization/statistics & numerical data , Humans , Laboratories , Male , Middle Aged , SARS-CoV-2/immunology , Vaccines, Synthetic/administration & dosage , Vaccines, Synthetic/immunology , Young Adult
4.
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
5.
BMC Public Health ; 21(1): 1786, 2021 10 03.
Article in English | MEDLINE | ID: covidwho-1448223

ABSTRACT

BACKGROUND: Much of what is known about COVID-19 risk factors comes from patients with serious symptoms who test positive. While risk factors for hospitalization or death include chronic conditions and smoking; less is known about how health status or nicotine consumption is associated with risk of SARS-CoV-2 infection among individuals who do not present clinically. METHODS: Two community-based population samples (including individuals randomly and nonrandomly selected for statewide testing, n = 8214) underwent SARS-CoV-2 testing in nonclinical settings. Each participant was tested for current (viral PCR) and past (antibody) infection in either April or June of 2020. Before testing, participants provided demographic information and self-reported health status and nicotine and tobacco behaviors (smoking, chewing, vaping/e-cigarettes). Using descriptive statistics and a bivariate logistic regression model, we examined the association between health status and use of tobacco or nicotine with SARS-CoV-2 positivity on either PCR or antibody tests. RESULTS: Compared to people with self-identified "excellent" or very good health status, those reporting "good" or "fair" health status had a higher risk of past or current infections. Positive smoking status was inversely associated with SARS-CoV-2 infection. Chewing tobacco was associated with infection and the use of vaping/e-cigarettes was not associated with infection. CONCLUSIONS: In a statewide, community-based population drawn for SARS-CoV-2 testing, we find that overall health status was associated with infection rates. Unlike in studies of COVID-19 patients, smoking status was inversely associated with SARS-CoV-2 positivity. More research is needed to further understand the nature of this relationship.


Subject(s)
COVID-19 , Electronic Nicotine Delivery Systems , COVID-19 Testing , Health Status , Humans , Nicotine/adverse effects , SARS-CoV-2
6.
N Engl J Med ; 385(15): 1355-1371, 2021 10 07.
Article in English | MEDLINE | ID: covidwho-1397961

ABSTRACT

BACKGROUND: There are limited data on the effectiveness of the vaccines against symptomatic coronavirus disease 2019 (Covid-19) currently authorized in the United States with respect to hospitalization, admission to an intensive care unit (ICU), or ambulatory care in an emergency department or urgent care clinic. METHODS: We conducted a study involving adults (≥50 years of age) with Covid-19-like illness who underwent molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We assessed 41,552 admissions to 187 hospitals and 21,522 visits to 221 emergency departments or urgent care clinics during the period from January 1 through June 22, 2021, in multiple states. The patients' vaccination status was documented in electronic health records and immunization registries. We used a test-negative design to estimate vaccine effectiveness by comparing the odds of a positive test for SARS-CoV-2 infection among vaccinated patients with those among unvaccinated patients. Vaccine effectiveness was adjusted with weights based on propensity-for-vaccination scores and according to age, geographic region, calendar time (days from January 1, 2021, to the index date for each medical visit), and local virus circulation. RESULTS: The effectiveness of full messenger RNA (mRNA) vaccination (≥14 days after the second dose) was 89% (95% confidence interval [CI], 87 to 91) against laboratory-confirmed SARS-CoV-2 infection leading to hospitalization, 90% (95% CI, 86 to 93) against infection leading to an ICU admission, and 91% (95% CI, 89 to 93) against infection leading to an emergency department or urgent care clinic visit. The effectiveness of full vaccination with respect to a Covid-19-associated hospitalization or emergency department or urgent care clinic visit was similar with the BNT162b2 and mRNA-1273 vaccines and ranged from 81% to 95% among adults 85 years of age or older, persons with chronic medical conditions, and Black or Hispanic adults. The effectiveness of the Ad26.COV2.S vaccine was 68% (95% CI, 50 to 79) against laboratory-confirmed SARS-CoV-2 infection leading to hospitalization and 73% (95% CI, 59 to 82) against infection leading to an emergency department or urgent care clinic visit. CONCLUSIONS: Covid-19 vaccines in the United States were highly effective against SARS-CoV-2 infection requiring hospitalization, ICU admission, or an emergency department or urgent care clinic visit. This vaccine effectiveness extended to populations that are disproportionately affected by SARS-CoV-2 infection. (Funded by the Centers for Disease Control and Prevention.).


Subject(s)
Ambulatory Care/statistics & numerical data , COVID-19 Vaccines , COVID-19/prevention & control , Hospitalization/statistics & numerical data , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19 Vaccines/immunology , Female , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Patient Readmission/statistics & numerical data , United States/epidemiology
7.
Yearb Med Inform ; 30(1): 69-74, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1392943

ABSTRACT

OBJECTIVE: To summarize significant research contributions on managing pandemics with health informatics published in 2020. METHODS: An extensive search using PubMed and Scopus was conducted to identify peer-reviewed articles published in 2020 that examined health informatics systems used during the global COVID-19 pandemic. The selection process comprised three steps: 1) 15 candidate best papers were first selected by the two section editors; 2) external reviewers from internationally renowned research teams reviewed each candidate best paper; and 3) the final selection of three best papers was conducted by the editorial committee of the International Medical Informatics Association (IMIA) Yearbook. RESULTS: Selected best papers represent the important and diverse ways that health informatics supported clinical and public health responses to the global COVID-19 pandemic. Selected papers represent four groups of papers: 1) Use of analytics to screen, triage, and manage patients; 2) Use of telehealth and remote monitoring to manage patients and populations; 3) Use of EHR systems and administrative systems to manage internal operations of a hospital or health system; and 4) Use of informatics methods and systems by public health authorities to capture, store, manage, and visualize population-level data and information. CONCLUSION: Health informatics played a critical role in managing patients and populations during the COVID-19 pandemic. Health care and public health organizations both leveraged available information systems and standards to rapidly identify cases, triage infected individuals, and monitor population trends. The selected best papers represent a fraction of the body of knowledge stemming from COVID-19, most of which is focused on pandemic response. Future work will be needed to help the world recover from the pandemic and strengthen the health information infrastructure in preparation for the next pandemic.


Subject(s)
COVID-19 , Medical Informatics , COVID-19/epidemiology , COVID-19/therapy , Humans , Medical Records Systems, Computerized , Public Health Practice , Telemedicine
8.
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
9.
Online J Public Health Inform ; 12(1): e7, 2020.
Article in English | MEDLINE | ID: covidwho-1389682

ABSTRACT

Background:Public Health Informatics (PHI) has taken on new importance in recent years as health and well-being face a number of challenges, including environmental disasters, emerging infectious diseases, such as Zika, Ebola and SARS-CoV-2, the growing impact of the Influenza virus, the opioid epidemic, and social determinants of health. Understanding the relationship between climate change and the health of populations adds further complexity to global health issues. Objectives: To describe four examples of curricula that exist in U.S. based graduate-level public and population health informatics training programs. Methods: Biomedical informatics educators are challenged to provide learners with relevant, interesting, and meaningful educational experiences in working with and learning from the many data sources that comprise the domain of PHI. Programs at four institutions were reviewed to examine common teaching practices that stimulate learners to explore the field of public health informatics. Results: Four case studies represent a range of pedagogical approaches to meeting the requirements of three established accreditation/certification agencies relevant to PHI education. Despite their differences, each program achieved the established learning objectives along with a substantive record of student learning achievements. Conclusion: The overarching goal of empowering learners to serve an active and dynamic role in enhancing preventive measures, informing policy, improving personal health behaviors, and clarifying issues such as quality, cost of care, and the social determinants of health, are essential components of PHI education and training, and must receive additional consideration now and in the future by educators, policy makers, administrators, and government officials.

10.
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
11.
J Med Internet Res ; 23(5): e24742, 2021 05 20.
Article in English | MEDLINE | ID: covidwho-1256238

ABSTRACT

BACKGROUND: Identifying new COVID-19 cases is challenging. Not every suspected case undergoes testing, because testing kits and other equipment are limited in many parts of the world. Yet populations increasingly use the internet to manage both home and work life during the pandemic, giving researchers mediated connections to millions of people sheltering in place. OBJECTIVE: The goal of this study was to assess the feasibility of using an online news platform to recruit volunteers willing to report COVID-19-like symptoms and behaviors. METHODS: An online epidemiologic survey captured COVID-19-related symptoms and behaviors from individuals recruited through banner ads offered through Microsoft News. Respondents indicated whether they were experiencing symptoms, whether they received COVID-19 testing, and whether they traveled outside of their local area. RESULTS: A total of 87,322 respondents completed the survey across a 3-week span at the end of April 2020, with 54.3% of the responses from the United States and 32.0% from Japan. Of the total respondents, 19,631 (22.3%) reported at least one symptom associated with COVID-19. Nearly two-fifths of these respondents (39.1%) reported more than one COVID-19-like symptom. Individuals who reported being tested for COVID-19 were significantly more likely to report symptoms (47.7% vs 21.5%; P<.001). Symptom reporting rates positively correlated with per capita COVID-19 testing rates (R2=0.26; P<.001). Respondents were geographically diverse, with all states and most ZIP Codes represented. More than half of the respondents from both countries were older than 50 years of age. CONCLUSIONS: News platforms can be used to quickly recruit study participants, enabling collection of infectious disease symptoms at scale and with populations that are older than those found through social media platforms. Such platforms could enable epidemiologists and researchers to quickly assess trends in emerging infections potentially before at-risk populations present to clinics and hospitals for testing and/or treatment.


Subject(s)
Advertising/methods , COVID-19 Testing/methods , Internet Use/statistics & numerical data , Social Media/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Pandemics , Pilot Projects , SARS-CoV-2/isolation & purification , Surveys and Questionnaires , Young Adult
12.
Online J Public Health Inform ; 13(1): e1, 2021.
Article in English | MEDLINE | ID: covidwho-1212060

ABSTRACT

Objective: To develop a conceptual model and novel, comprehensive framework that encompass the myriad ways informatics and technology can support public health response to a pandemic. Method: The conceptual model and framework categorize informatics solutions that could be used by stakeholders (e.g., government, academic institutions, healthcare providers and payers, life science companies, employers, citizens) to address public health challenges across the prepare, respond, and recover phases of a pandemic, building on existing models for public health operations and response. Results: Mapping existing solutions, technology assets, and ideas to the framework helped identify public health informatics solution requirements and gaps in responding to COVID-19 in areas such as applied science, epidemiology, communications, and business continuity. Two examples of technologies used in COVID-19 illustrate novel applications of informatics encompassed by the framework. First, we examine a hub from The Weather Channel, which provides COVID-19 data via interactive maps, trend graphs, and details on case data to individuals and businesses. Second, we examine IBM Watson Assistant for Citizens, an AI-powered virtual agent implemented by healthcare providers and payers, government agencies, and employers to provide information about COVID-19 via digital and telephone-based interaction. Discussion: Early results from these novel informatics solutions have been positive, showing high levels of engagement and added value across stakeholders. Conclusion: The framework supports development, application, and evaluation of informatics approaches and technologies in support of public health preparedness, response, and recovery during a pandemic. Effective solutions are critical to success in recovery from COVID-19 and future pandemics.

13.
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
14.
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
15.
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
16.
medRxiv ; 2020 Oct 22.
Article in English | MEDLINE | ID: covidwho-900757

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 seroprevalence 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. Research in Context: Evidence before this study: Using multiple journal articles queried from MEDLINE as well as a Cochrane systematic review, we examined all studies that described symptoms known to be associated with COVID-19. We further examined the guidelines from WHO and CDC on the symptoms those public health authorities consider to be associated with COVID-19. Most of the evidence comes from China, Italy, and the United States. Collectively prior research and guidance suggests there are a dozen symptoms reported by individuals who tested positive for COVID-19 in multiple countries. Symptoms include fever, cough, fatigue, anosmia, ageusia, shortness of breath, chills, myalgias, headache, sore throat, chest pain, and gastrointestinal issues. The evidence is generally of low quality as it is descriptive in nature, and it is biased towards hospitalized patients. Most studies report the proportion of patients hospitalized or testing positive for infection who report one or more symptoms within 3-14 days prior to hospitalization or infection. There has been little validation of symptoms among hospitalized or non-hospitalized patients. Furthermore, according to a Cochrane review, no studies to date assess combinations of different signs and symptoms.Added value of this study: This study employs multiple, rigorous methods to examine the ability of specific symptoms as well as symptom combinations/groups to predict laboratory-confirmed (RT-PCR) infection of SARS-CoV-2. Furthermore, the study is unique in its large sample drawn exclusively from community-based populations rather than hospitalized patients.Implication of all the available evidence: Combining the evidence from this study with prior research suggests that anosmia and ageusia are key symptoms that differentiate COVID-19 from influenza-like symptoms. Clinical screening protocols for COVID-19 should look for these symptoms, which are not commonly asked of patients who present to urgent care or hospital with flu-like symptoms. Key points: Important symptoms specific to COVID-19 are fever, anosmia, ageusia, and cough. Two-thirds of symptoms were highly specific (>90.0%), yet most symptoms individually possessed a PPV <50.0%. This study confirms using robust methods the key symptoms associated with COVID-19 infection, and it also identifies combinations of symptoms strongly associated with positive infection.

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