2023 Respiratory Virus Response - NSSP Emergency Department Visits - COVID-19, Flu, RSV, Combined
공공데이터포털
2023 Respiratory Virus Response - NSSP Emergency Department Visits - COVID-19, Flu, RSV, Combined For additional information, please see: Companion Guide: NSSP Emergency Department Data on Respiratory Illness
2023 Respiratory Virus Response - NSSP Emergency Department Visit Trajectories by State- COVID-19, Flu, RSV, Combined
공공데이터포털
2023 Respiratory Viruses Response – National Syndromic Surveillance Program Emergency Department Visit Trajectories - COVID-19, Flu, RSV, Combined – by state. This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geography that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). In addition, the trend over time both as of the given row date and as of the most current data submitted is characterized as increasing, decreasing or stable to provide awareness of how the weekly trend is changing for the given geographic region. For the emergency department time series, trajectory classifications reported on the opening page are based on rolling regression model assessments of the slope for each respiratory illness. Weeks with a significant time term (p <0.05) are classified as increasing when the slope is positive and decreasing when the slope is negative. Weeks with a non-significant time term (p ≥ 0.05) are classified as stable. A 3-week moving average is applied to the time series prior to the regression procedure in order to smooth week-to-week variation. For additional information, please see:Companion Guide: NSSP Emergency Department Data on Respiratory Illness Updated once per week on Fridays.
NSSP Emergency Department Visit Trajectories by State and Sub State Regions- COVID-19, Flu, RSV, Combined
공공데이터포털
NSSP Emergency Department (ED) Visit Trajectories by State and Sub-State Regions- COVID-19, Flu, RSV, Combined. This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geographic part of the country that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). In addition, the trend over time is characterized as increasing, decreasing or no change, with exceptions for when there are no data available, the data are too sparse, or there are not enough data to compute a trend. These data are to provide awareness of how the weekly trend is changing for the given geographic region. Note that the reported sub-state trends are from Health Service Areas (HSA) and the data reported from the health care facilities located within the given HSA. Health Service Areas are regions of one or more counties that align to patterns of care seeking. The HSA level data are reported for each county in the HSA. More information on HSAs is available here. For the emergency department time series, trajectory classifications reported on for sub-state (HSA) emergency department time series, trajectory classifications are based on approximations of the first derivative (slope) of trends that are smoothed using generalized additive models (GAMs). To determine time intervals in which the slope is sufficiently changing (i.e., rate of change distinguishable from 0), 95% confidence intervals for the slope approximations are calculated and assessed. Weeks with a 95% confidence interval not containing 0 are classified as increasing if the slope estimate is positive and decreasing if the slope estimate is negative. Weeks with a 95% confidence interval containing 0 are classified as stable. In the scenario that an HSA's time series is determined to be too sparse (i.e., many weeks with percentages of 0%), a model is not fit, and the HSA is classified as “sparse”. For additional information, please see: Companion Guide: NSSP Emergency Department Data on Respiratory Illness Updated once per week on Fridays.
COVID-Like Illness (CLI) and COVID-19 Diagnosis Emergency Department Visits - Historical
공공데이터포털
NOTE: This dataset is no longer being updated but is being kept for historical reference. For current data on respiratory illness visits and respiratory laboratory testing data please see Influenza, COVID-19, RSV, and Other Respiratory Virus Laboratory Surveillance and Inpatient, Emergency Department, and Outpatient Visits for Respiratory Illnesses. This is the place to look for important information about how to use this dataset, so please expand this box and read on! This is the source data for some of the metrics available at https://www.chicago.gov/city/en/sites/covid-19/home/reopening-chicago.html#reopeningmetrics. For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19. The National Syndromic Surveillance Program (NSSP), a collaboration among CDC, federal partners, local and state health departments, and academic and private sector partners, is used to capture information during an Emergency Department (ED) visit. ED data can include information that are collected before cases are diagnosed or laboratory results are confirmed, providing an early warning system for infections, like COVID-19. This dataset includes reports of COVID-19-Like illness (CLI) and COVID-19 diagnosed during an ED visit. CLI is defined as fever and cough or shortness of breath or difficulty breathing with or without the presence of a coronavirus diagnosis code. Visits meeting the CLI definition that also have mention of flu or influenza are excluded. This dataset also includes ED visits among persons who have been diagnosed or laboratory confirmed to have COVID-19. During the initial months of the COVID-19 pandemic COVID-19 diagnoses counts are artificially low, due to varying eligibility requirements and availability of testing. Over the course of the COVID-19 pandemic, public health best practices migrated from focusing on CLI to focusing on diagnosed cases. This dataset originally contained only CLI columns. In June 2021, the diagnosis columns were added, back filled to the start of the pandemic but with the caveat noted above. Roughly simultaneously, updating of the CLI columns was discontinued, although previously existing data were kept. Reflecting the new columns, the name of the dataset was changed from “COVID-Like Illness (CLI) Emergency Department Visits” to “COVID-Like Illness (CLI) and COVID-19 Diagnosis Emergency Department Visits” at the same time. Data Source: Illinois Hospital Emergency Departments reporting to CDPH through the National Syndromic Surveillance Project (NSSP)
Respiratory Virus Response (RVR) United States Hospitalization Metrics by Jurisdiction, Timeseries
공공데이터포털
Note: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 and influenza hospital admissions, hospital capacity, or occupancy data to HHS through CDC’s National Healthcare Safety Network (NHSN). This dataset represents hospitalization data and metrics aggregated to country, HHS region, and state/territory. Hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to hospital admissions, and inpatient and ICU bed capacity occupancy. Data fields for new admissions of pediatric patients with confirmed COVID-19 for ages 0-4 years, 5-11 years, and 12-17 years were not required for reporting until February 2022; therefore, data for the following fields in this dataset begin on March 1, 2022 to account for delays in initial reporting of these fields: adm_00_04_covid_confirmed avg_adm_00_04_covid_confirmed avg_adm_00_04_covid_confirmed_per_100k adm_05_11_covid_confirmed avg_adm_05_11_covid_confirmed avg_adm_05_11_covid_confirmed_per_100k adm_12_17_covid_confirmed avg_adm_12_17_covid_confirmed avg_adm_12_17_covid_confirmed_per_100k Updated weekly each Friday at noon, ET.
Respiratory Virus Dashboard
공공데이터포털
__Data is from the California Department of Public Health (CDPH) Respiratory Virus Dashboard.__ The respiratory virus dashboard shows statewide and regional, weekly data for the following conditions: - COVID-19 - Influenza - Respiratory Syncytial Virus (RSV) This dashboard provides an overview of respiratory virus activity (test positivity, flu typing, emergency department visits) and severity (hospital admissions, deaths, and pediatric deaths). The data update most Fridays but may change in future updates as more information becomes available.
Respiratory Virus Dashboard
공공데이터포털
__Data is from the California Department of Public Health (CDPH) Respiratory Virus Dashboard.__ The respiratory virus dashboard shows statewide and regional, weekly data for the following conditions: - COVID-19 - Influenza - Respiratory Syncytial Virus (RSV) This dashboard provides an overview of respiratory virus activity (test positivity, flu typing, emergency department visits) and severity (hospital admissions, deaths, and pediatric deaths). The data update most Fridays but may change in future updates as more information becomes available.
Hospital Utilization Trends
공공데이터포털
The datasets provide medical encounter counts across three hospital settings (Inpatient Discharges, Emergency Department visits, and Ambulatory Surgery). The data is categorized by healthcare system and facility, and further grouped by common health conditions (including anxiety, asthma, behavioral syndromes, cancer, cardiac arrest, chronic obstructive pulmonary disease (COPD), COVID-19, depression, diabetes, homelessness, hypertension, mood disorders excluding depression, non-mood psychotic disorders, nonpsychotic disorders excluding anxiety, obesity, pneumonia, respiratory arrest/failure, sepsis, stroke, substance use disorders, and unspecified mental disorders), as well as demographic characteristics such as age group, race/ethnicity, assigned sex at birth, and expected payer.
Respiratory Virus Weekly Report (ARCHIVED)
공공데이터포털
__Data is from the California Department of Public Health (CDPH) Respiratory Virus Weekly Report.__ The report is updated each Friday. __Laboratory surveillance data__: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week. Laboratory surveillance for influenza, respiratory syncytial virus (RSV), and other respiratory viruses (parainfluenza types 1-4, human metapneumovirus, non-SARS-CoV-2 coronaviruses, adenovirus, enterovirus/rhinovirus) involves the use of data from clinical sentinel laboratories (hospital, academic or private) located throughout California. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for influenza, respiratory syncytial virus, and other respiratory viruses in California. These laboratories report the number of laboratory-confirmed influenza, respiratory syncytial virus, and other respiratory virus detections and isolations, and the total number of specimens tested by virus type on a weekly basis. Test positivity for a given week is calculated by dividing the number of positive COVID-19, influenza, RSV, or other respiratory virus results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday. __Hospitalization data__: Data on COVID-19 and influenza hospital admissions are from Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety Network (NHSN) Hospitalization dataset. The requirement to report COVID-19 and influenza-associated hospitalizations was effective November 1, 2024. CDPH pulls NHSN data from the CDC on the Wednesday prior to the publication of the report. Results may differ depending on which day data are pulled. Admission rates are calculated using population estimates from the P-3: Complete State and County Projections Dataset provided by the State of California Department of Finance (https://dof.ca.gov/forecasting/demographics/projections/). Reported weekly admission rates for the entire season use the population estimates for the year the season started. For more information on NHSN data including the protocol and data collection information, see the CDC NHSN webpage (https://www.cdc.gov/nhsn/index.html). CDPH collaborates with Northern California Kaiser Permanente (NCKP) to monitor trends in RSV admissions. The percentage of RSV admissions is calculated by dividing the number of RSV-related admissions by the total number of admissions during the same period. Admissions for pregnancy, labor and delivery, birth, and outpatient procedures are not included in total number of admissions. These admissions serve as a proxy for RSV activity and do not necessarily represent laboratory confirmed hospitalizations for RSV infections; NCKP members are not representative of all Californians. Weekly hospitalization data are defined as Sunday through Saturday. __Death certificate data__: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify influenza, respiratory syncytial virus, and COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all influenza, respiratory syncytial virus, and COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday. __Wastewater data__: This dataset represents statewide weekly SARS-CoV-2 wastewater summary values. SARS-CoV-2 wastewater concentrations from all sites in California are combined into a single, statewide, unit-less summary value for each week, using a method for data transformation and aggregation developed