Coronavirus Disease Case Definitions, Diagnostic Testing Criteria, and Surveillance in 25 Countries with Highest Reported Case Counts.
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ABSTRACT:
SUBMITTER: Suthar AB
PROVIDER: S-EPMC8714223 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Purpose To evaluate the number, characteristics, and outcomes of patients identified hospitalized with coronavirus disease 2019 (COVID-19) using two different case definitions. Procedures Electronic Health Record data were evaluated from patients hospitalized with COVID-19 through May 2020 at 52 health systems across the United States. Characteristics of inpatients with positive laboratory tests for SARS-CoV-2 were compared with those with clinical diagnosis of COVID-19 but without a confirmatory lab result. Findings Of 14,371 inpatients with COVID-19, 6623 (46.1 %) had a positive laboratory result, and n = 7748 (52.9 %) had only a clinical diagnosis of COVID-19. Compared with clinically diagnosed cases, those with laboratory-confirmed COVID were similar in age and sex, but differed by race, ethnicity, and insurance status. Laboratory-confirmed cases were more likely to receive certain COVID-19 therapies including hydroxychloroquine, anti-IL6 agents and antivirals (p < 0.001). Those with laboratory–confirmed COVID-19 had lower rates of most complications such as myocardial infarction, but higher overall mortality (p < 0.001). Conclusion We observed a two–fold difference in the number of patients hospitalized with COVID-19 depending on whether the case definition required laboratory confirmation. Variations in case definitions also led to differences in cohort characteristics, treatments, and outcomes.
| S-EPMC9359535 | biostudies-literature
Project description:BackgroundMost asthma diagnoses and patient care take place in primary care settings. Electronic medical records (EMRs) offer an opportunity to utilize technology to improve asthma diagnosis and care. The purpose of this study was to create and validate separate case definitions for suspected and confirmed asthma in primary care EMRs, to enable surveillance, benchmarking, and quality improvement in primary care settings. The objective of this study was to develop a case definition for suspected and confirmed asthma for use in a primary care sentinel surveillance system.MethodsA single chart abstractor conducted a manual audit of 776 randomly selected patient charts from an academic primary care practice EMR in Kingston, Ontario. Following the single chart abstractor classification, a consensus on chart classification as "not asthma", "suspected asthma", or "confirmed asthma" was achieved between the abstractor, a family physician, and a respirologist using Canadian Thoracic Society (CTS) criteria. Case definition algorithms based on billing codes, clinical data elements and medications were applied to the site's Canadian Primary Care Sentinel Surveillance Network (CPCSSN) data for the same charts and compared to abstractor classifications to determine each algorithm's measurement properties.ResultsThe prevalence of suspected and confirmed asthma were 7.3% (n = 54) and 2.4% (n = 18), respectively. None of the proposed case definitions could differentiate between suspected and confirmed asthma. One algorithm consisting of billing, clinical, and medication elements had the highest Youden's Index for either suspected or confirmed asthma. The algorithm had a sensitivity of 81%, a specificity of 96%, positive predictive value of 71%, negative predictive value of 98%, and a Youden's Index of 0.77 for combined suspected or confirmed asthma cases.ConclusionAn EMR case definition for suspected or confirmed adult asthma has been validated for use in CPCSSN. Implementation of this case definition will enable the development of a surveillance electronic tool (eTool) for adult asthma that can foster quality improvement.
| S-EPMC10644606 | biostudies-literature
Project description:Newborn screening (NBS) identifies infants with rare conditions to prevent death or the onset of irreversible morbidities. Conditions on the Health and Human Services Secretary's Recommended Uniform Screening Panel have been adopted by most state NBS programs, providing a consistent approach for identification of affected newborns across the United States. Screen-positive newborns are identified and referred for confirmatory diagnosis and follow-up. The designation of a clinically significant phenotype precursor to a clinical diagnosis may vary between clinical specialists, resulting in diagnostic variation. Determination of disease burden and birth prevalence of the screened conditions by public health tracking is made challenging by these variations. This report describes the development of a core group of new case definitions, along with implications, plans for their use, and links to the definitions that were developed by panels of clinical experts. These definitions have been developed through an iterative process and are piloted in NBS programs. Consensus public health surveillance case definitions for newborn screened disorders will allow for consistent categorization and tracking of short- and long-term follow-up of identified newborns at the local, regional, and national levels.
| S-EPMC5978752 | biostudies-literature
Project description:Syndromic surveillance systems are plagued by high false-positive rates. In chronic disease monitoring, investigators have identified several factors that predict the accuracy of case definitions based on diagnoses in administrative data, and some have even incorporated these predictors into novel case detection methods, resulting in a significant improvement in case definition accuracy. Based on findings from these studies, we sought to identify physician, patient, encounter, and billing characteristics associated with the positive predictive value (PPV) of case definitions for 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory (including influenza-like illness)).The study sample comprised 4,330 syndrome-positive visits from the claims of 1,098 randomly-selected physicians working in Quebec, Canada in 2005-2007. For each visit, physician-facilitated chart review was used to assess whether the same syndrome was present in the medical chart (gold standard). We used multivariate logistic regression analyses to estimate the association between claim-chart agreement about the presence of a syndrome and physician, patient, encounter, and billing characteristics.The likelihood of the medical chart agreeing with the physician claim about the presence of a syndrome was higher when the treating physician had billed many visits for the same syndrome recently (ORper 10 visit, 1.05; 95% CI, 1.01-1.08), had a lower workload (ORper 10 claims, 0.93; 95% CI, 0.90-0.97), and when the patient was younger (ORper 5 years of age, 0.96; 95% CI, 0.94-0.97), and less socially deprived (ORmost versus least deprived, 0.76; 95% CI, 0.60-0.95).Many physician, patient, encounter, and billing characteristics associated with the PPV of surveillance case definition are accessible to public health, and could be used to reduce false-positive alerts by surveillance systems, either by focusing on the data most likely to be accurate, or by adjusting the observed data for known biases in diagnosis reporting and performing surveillance using the adjusted values.
| S-EPMC3378465 | biostudies-other
Project description:After three national point prevalence studies (PPS) of healthcare associated infections (HAI) conducted in Serbian acute care hospitals using US (CDC/NHSN) surveillance definitions, Serbia is about to switch to European (ECDC) criteria for the purpose of the fourth HAI PPS. The aim of this study was to compare the US and the European HAI definitions in Serbian trauma intensive care unit (ICU). Prospective surveillance was performed at two surgical-trauma ICUs of the Emergency department of Clinical Center of Serbia. HAIs were prospectively diagnosed by experienced clinician and epidemiologists using both types of HAI definitions simultaneously. The level of agreement between two case definitions was assessed by Cohen's kappa statistic (k). Of 406 patients, 107 (26.3%) acquired at least one HAI (total of 107 according to US definitions and 141 according to European criteria). For microbiologically confirmed pneumonia agreement was k = 0.99 (95% CI, 0.96-1.00) and for clinically defined k = 0.86 (95% CI, 0.58-1.00). Agreement for bloodstream infections (BSI) was 0.79 (CI 95%, 0.70-0.89). When secondary BSI was excluded from the European classification, (30.9% of all BSI), concordance was k = 1.00 and when microbiologically confirmed catheter related BSI were reported separately as recommended by latest ECDC protocol update, (20.0% of all BSI), concordance was 0.60 (CI 95%, 0.41-0.80). No agreement was found between CLABSI and CRI while slight agreement was found when compared CLABSI and CRI3 (k = 0.11; 95%CI, 0.0-0.22). Agreement for overall UTI was moderate (k = 0.66; 95%CI, 0.53-0.79) while for microbiologically-confirmed symptomatic UTI was perfect (k = 1.00). For CAUTI good agreement was observed (k = 0.77; 95%CI, 0.34-1.0). Microbiological confirmation of PN and UTI should be stimulated and comparison of BSI should be done with emphasis on whether secondary BSI is included.
| S-EPMC6171870 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic resulted in 5,817,385 reported cases and 362,705 deaths worldwide through May, 30, 2020,† including 1,761,503 aggregated reported cases and 103,700 deaths in the United States.§ Previous analyses during February-early April 2020 indicated that age ?65 years and underlying health conditions were associated with a higher risk for severe outcomes, which were less common among children aged <18 years (1-3). This report describes demographic characteristics, underlying health conditions, symptoms, and outcomes among 1,320,488 laboratory-confirmed COVID-19 cases individually reported to CDC during January 22-May 30, 2020. Cumulative incidence, 403.6 cases per 100,000 persons,¶ was similar among males (401.1) and females (406.0) and highest among persons aged ?80 years (902.0). Among 599,636 (45%) cases with known information, 33% of persons were Hispanic or Latino of any race (Hispanic), 22% were non-Hispanic black (black), and 1.3% were non-Hispanic American Indian or Alaska Native (AI/AN). Among 287,320 (22%) cases with sufficient data on underlying health conditions, the most common were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%). Overall, 184,673 (14%) patients were hospitalized, 29,837 (2%) were admitted to an intensive care unit (ICU), and 71,116 (5%) died. Hospitalizations were six times higher among patients with a reported underlying condition (45.4%) than those without reported underlying conditions (7.6%). Deaths were 12 times higher among patients with reported underlying conditions (19.5%) compared with those without reported underlying conditions (1.6%). The COVID-19 pandemic continues to be severe, particularly in certain population groups. These preliminary findings underscore the need to build on current efforts to collect and analyze case data, especially among those with underlying health conditions. These data are used to monitor trends in COVID-19 illness, identify and respond to localized incidence increase, and inform policies and practices designed to reduce transmission in the United States.
| S-EPMC7302472 | biostudies-literature
Project description:BackgroundFollowing an outbreak of cases of vesicular-pustular rash with fever, evocative of human monkeypox, in Bas-Uélé province, Democratic Republic of Congo, surveillance was strengthened.MethodsHouseholds with at least one active generalized vesicular-pustular rash case were visited, and contact and clinical history information were collected from all household members. Whenever possible, skin lesions were screened by polymerase chain reaction for the monkeypox virus, followed by the varicella-zoster virus, when negative for the former.ResultsPolymerase chain reaction results were obtained for 77 suspected cases, distributed in 138 households, of which 27.3% were positive for monkeypox, 58.4% positive for chickenpox, and 14.3% negative for both. Confirmed monkeypox cases presented more often with monomorphic skin lesions on the palms of the hands and on the soles of the feet. Integrating these three features into the case definition raised the specificity to 85% but would miss 50% of true monkeypox cases. A predictive model fit on patient demographics and symptoms had 97% specificity and 80% sensitivity but only 80% and 33% in predicting out-of-sample cases.ConclusionFew discriminating features were identified and the performance of clinical case definitions was suboptimal. Rapid field diagnostics are needed to optimize worldwide early detection and surveillance of monkeypox.
| S-EPMC9628793 | biostudies-literature
Project description:BACKGROUND: Public health surveillance is the monitoring of data to detect and quantify unusual health events. Monitoring pre-diagnostic data, such as emergency department (ED) patient chief complaints, enables rapid detection of disease outbreaks. There are many sources of variation in such data; statistical methods need to accurately model them as a basis for timely and accurate disease outbreak methods. METHODS: Our new methods for modeling daily chief complaint counts are based on a seasonal-trend decomposition procedure based on loess (STL) and were developed using data from the 76 EDs of the Indiana surveillance program from 2004 to 2008. Square root counts are decomposed into inter-annual, yearly-seasonal, day-of-the-week, and random-error components. Using this decomposition method, we develop a new synoptic-scale (days to weeks) outbreak detection method and carry out a simulation study to compare detection performance to four well-known methods for nine outbreak scenarios. RESULT: The components of the STL decomposition reveal insights into the variability of the Indiana ED data. Day-of-the-week components tend to peak Sunday or Monday, fall steadily to a minimum Thursday or Friday, and then rise to the peak. Yearly-seasonal components show seasonal influenza, some with bimodal peaks.Some inter-annual components increase slightly due to increasing patient populations. A new outbreak detection method based on the decomposition modeling performs well with 90 days or more of data. Control limits were set empirically so that all methods had a specificity of 97%. STL had the largest sensitivity in all nine outbreak scenarios. The STL method also exhibited a well-behaved false positive rate when run on the data with no outbreaks injected. CONCLUSION: The STL decomposition method for chief complaint counts leads to a rapid and accurate detection method for disease outbreaks, and requires only 90 days of historical data to be put into operation. The visualization tools that accompany the decomposition and outbreak methods provide much insight into patterns in the data, which is useful for surveillance operations.
| S-EPMC2680402 | biostudies-other
Project description:BackgroundInfluenza is a major cause of morbidity and mortality in Africa. However, a lack of epidemiological data remains for this pathology, and the performances of the influenza-like illness (ILI) case definitions used for sentinel surveillance have never been evaluated in Senegal. This study aimed to i) assess the performance of three different ILI case definitions, adopted by the WHO, USA-CDC (CDC) and European-CDC (ECDC) and ii) identify clinical factors associated with a positive diagnosis for Influenza in order to develop an algorithm fitted for the Senegalese context.MethodsAll 657 patients with a febrile pathological episode (FPE) between January 2013 and December 2016 were followed in a cohort study in two rural villages in Senegal, accounting for 1653 FPE observations with nasopharyngeal sampling and influenza virus screening by rRT-PCR. For each FPE, general characteristics and clinical signs presented by patients were collected. Sensitivity, Specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) for the three ILI case definitions were assessed using PCR result as the reference test. Associations between clinical signs and influenza infection were analyzed using logistic regression with generalized estimating equations. Sore throat, arthralgia or myalgia were missing for children under 5 years.ResultsWHO, CDC and ECDC case definitions had similar sensitivity (81.0%; 95%CI: 77.0-85.0) and NPV (91.0%; 95%CI: 89.0-93.1) while the WHO and CDC ILI case definitions had the highest specificity (52.0%; 95%CI: 49.1-54.5) and PPV (32.0%; 95%CI: 30.0-35.0). These performances varied by age groups. In children < 5 years, the significant predictors of influenza virus infection were cough and nasal discharge. In patients from 5 years, cough, nasal discharge, sore throat and asthenia grade 3 best predicted influenza infection. The addition of "nasal discharge" as a symptom to the WHO case definition decreased sensitivity but increased specificity, particularly in the pediatric population.ConclusionIn summary, all three definitions studies (WHO, ECDC & CDC) have similar performance, even by age group. The revised WHO ILI definition could be chosen for surveillance purposes for its simplicity. Symptomatic predictors of influenza virus infection vary according the age group.
| S-EPMC7790019 | biostudies-literature
Project description:BackgroundOptimized symptom-based COVID-19 case definitions that guide public health surveillance and individual patient management in the community may assist pandemic control.MethodsWe assessed diagnostic performance of existing cases definitions (e.g. influenza-like illness, COVID-like illness) using symptoms reported from 185 household contacts to a PCR-confirmed case of COVID-19 in Wisconsin and Utah, United States. We stratified analyses between adults and children. We also constructed novel case definitions for comparison.ResultsExisting COVID-19 case definitions generally showed high sensitivity (86-96%) but low positive predictive value (PPV) (36-49%; F-1 score 52-63) in this community cohort. Top performing novel symptom combinations included taste or smell dysfunction and improved the balance of sensitivity and PPV (F-1 score 78-80). Performance indicators were generally lower for children (< 18 years of age).ConclusionsExisting COVID-19 case definitions appropriately screened in household contacts with COVID-19. Novel symptom combinations incorporating taste or smell dysfunction as a primary component improved accuracy. Case definitions tailored for children versus adults should be further explored.
| S-EPMC8465785 | biostudies-literature