Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format. Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc. Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:

Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported. Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

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 dataset includes aggregated weekly metrics of the surveillance indicators that the Department of Public Health uses to monitor influenza activity in Chicago. These indicators include:

• Influenza-associated ICU hospitalizations for Chicago residents, which is a reportable condition in Illinois (HOSP_ columns)

• Influenza laboratory data provided by participating sentinel laboratories in Chicago (LAB_ columns)

• Influenza-like illness data for outpatient clinic visits and emergency department visits. (ILI_ columns)

For more information on ILINET, see https://www.cdc.gov/flu/weekly/overview.htm#anchor_1539281266932.

For more information on ESSENCE, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance

All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

This dataset contains the following files for California influenza surveillance data: 1) Outpatient Influenza-like Illness Surveillance Data by Region and Influenza Season from volunteer sentinel providers; 2) Clinical Sentinel Laboratory Influenza and Other Respiratory Virus Surveillance Data by Region and Influenza Season from volunteer sentinel laboratories; and 3) Public Health Laboratory Influenza Respiratory Virus Surveillance Data by Region and Influenza Season from California public health laboratories. The Immunization Branch at the California Department of Public Health (CDPH) collects, compiles and analyzes information on influenza activity year-round in California and produces a weekly influenza surveillance report during October through May. The California influenza surveillance system is a collaborative effort between CDPH and its many partners at local health departments, public health and clinical laboratories, vital statistics offices, healthcare providers, clinics, emergency departments, and the Centers for Disease Control and Prevention (CDC). California data are also included in the CDC weekly influenza surveillance report, FluView, and help contribute to the national picture of Influenza activity in the United States. The information collected allows CDPH and CDC to: 1) find out when and where influenza activity is occurring; 2) track influenza-related illness; 3) determine what influenza viruses are circulating; 4) detect changes in influenza viruses; and 5) measure the impact influenza is having on hospitalizations and deaths.

FluWatch is Canada's national surveillance system that monitors the spread of flu and flu-like illnesses on an on-going basis.

Activity Level surveillance is a component of FluWatch that provides an overall assessment of the intensity and geographical spread of laboratory-confirmed influenza cases, influenza-like-illness (ILI) and reported outbreaks for a given surveillance region. Activity Levels are assigned and reported by Provincial and Territorial Ministries of Health. A surveillance region can be classified under one of the four following categories: no activity, sporadic, localized or widespread.

For a description of the categories, see the data dictionary resource. For more information on flu activity in Canada, see the FluWatch report.

(https://www.canada.ca/en/public-health/services/diseases/flu-influenza/influenza-surveillance/weekly-influenza-reports.html)

Note: The reported activity levels are a reflection of the surveillance data available to FluWatch at the time of production. Delays in reporting of data may cause data to change retrospectively.

This dataset contains the weekly estimated influenza risk level for each ZIP Code in Chicago. Estimates are made during flu season, which goes from MMWR week 40 to week 20 of the following year.

The risk level is based on observed level of Influenza-Like Illness (ILI). ILI Activity Level is determined as follows: ILI percentage for each ZIP Code for the week is compared to the mean ILI percentage during the non-influenza months (summer months). Level 1 corresponds to an ILI percentage below the mean, level 2 to an ILI percentage less than one standard deviation (SD) above the mean, level 3 to an ILI percentage more than one, but less than two SDs above mean, and so on, with level 10 corresponding to an ILI percentage more than eight SDs above the mean.

For more information on ESSENCE, which compiles the estimates, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance

All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

The Respiratory Virus Hospitalization Surveillance Network (RESP-NET) is a network that conducts, active, population-based surveillance for laboratory confirmed hospitalizations associated with Influenza, COVID-19, and RSV. The RESP-NET platforms have overlapping surveillance areas and use similar methods to collect data. Hospitalization rates show how many people in the surveillance area are hospitalized with influenza, COVID-19, and RSV compared to the total number of people residing in that area.

Data will be updated weekly. Data are preliminary and subject to change as more data become available.

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. In Illinois, influenza associated Intensive Care Unit (ICU) hospitalizations are reportable as soon as possible, but within 24 hours. Influenza associated ICU hospitalizations are defined as individuals hospitalized in an ICU with a positive laboratory test for influenza A or B, including specimens identified as influenza A/H3N2, A/H1N1pdm09, and specimens not subtyped (e.g., influenza positive cases by PCR or any rapid test such as EIA). This dataset represents weekly aggregated information for influenza-associated ICU hospitalizations among Chicago residents, which is a reportable condition in Illinois. Information includes demographics, influenza laboratory results, vaccination status, and death status. Column names containing "REPORTED" indicate the number of cases for which the indicated data element was reported. This, rather than the total number of cases, is used to calculate the corresponding percentage. All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.

The following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Sunday to Saturday). These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities.

The hospital population includes all hospitals registered with Centers for Medicare & Medicaid Services (CMS) as of June 1, 2020. It includes non-CMS hospitals that have reported since July 15, 2020. It does not include psychiatric, rehabilitation, Indian Health Service (IHS) facilities, U.S. Department of Veterans Affairs (VA) facilities, Defense Health Agency (DHA) facilities, and religious non-medical facilities.

For a given entry, the term “collection_week” signifies the start of the period that is aggregated. For example, a “collection_week” of 2020-11-15 means the average/sum/coverage of the elements captured from that given facility starting and including Sunday, November 15, 2020, and ending and including reports for Saturday, November 21, 2020.

Reported elements include an append of either “_coverage”, “_sum”, or “_avg”.

• A “_coverage” append denotes how many times the facility reported that element during that collection week.
• A “_sum” append denotes the sum of the reports provided for that facility for that element during that collection week.
• A “_avg” append is the average of the reports provided for that facility for that element during that collection week.

The file will be updated weekly. No statistical analysis is applied to impute non-response. For averages, calculations are based on the number of values collected for a given hospital in that collection week. Suppression is applied to the file for sums and averages less than four (4). In these cases, the field will be replaced with “-999,999”.

A story page was created to display both corrected and raw datasets and can be accessed at this link: https://healthdata.gov/stories/s/nhgk-5gpv

This data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020.

Sometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect.

For influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied.

For recent updates to the dataset, scroll to the bottom of the dataset description.

On May 3, 2021, the following fields have been added to this data set.

• hhs_ids
• previous_day_admission_adult_covid_confirmed_7_day_coverage
• previous_day_admission_pediatric_covid_confirmed_7_day_coverage
• previous_day_admission_adult_covid_suspected_7_day_coverage
• previous_day_admission_pediatric_covid_suspected_7_day_coverage
• previous_week_personnel_covid_vaccinated_doses_administered_7_day_sum
• total_personnel_covid_vaccinated_doses_none_7_day_sum
• total_personnel_covid_vaccinated_doses_one_7_day_sum
• total_personnel_covid_vaccinated_doses_all_7_day_sum
• previous_week_patients_covid_vaccinated_doses_one_7_day_sum
• previous_week_patients_covid_vaccinated_doses_all_7_day_sum

On May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added.

On May 13, 2021 Changed vaccination fields from sum to max or min fields. This reflects the maximum or minimum number reported for that metric in a given week.

On June 7, 2021 Changed vaccination fields from max or min fields to Wednesday reported only. This reflects that the number reported for that metric is only reported on Wednesdays in a given week.

On September 20, 2021, the following has been updated: The use of analytic dataset as a source.

On January 19, 2022, the following fields have been added to this dataset:

• inpatient_beds_used_covid_7_day_avg
• inpatient_beds_used_covid_7_day_sum
• inpatient_beds_used_covid_7_day_coverage

On April 28, 2022, the following pediatric fields have been added to this dataset:

• all_pediatric_inpatient_bed_occupied_7_day_avg
• all_pediatric_inpatient_bed_occupied_7_day_coverage
• all_pediatric_inpatient_bed_occupied_7_day_sum
• all_pediatric_inpatient_beds_7_day_avg
• all_pediatric_inpatient_beds_7_day_coverage
• all_pediatric_inpatient_beds_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_0_4_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_12_17_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_5_11_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_unknown_7_day_sum
• staffed_icu_pediatric_patients_confirmed_covid_7_day_avg
• staffed_icu_pediatric_patients_confirmed_covid_7_day_coverage
• staffed_icu_pediatric_patients_confirmed_covid_7_day_sum
• staffed_pediatric_icu_bed_occupancy_7_day_avg
• staffed_pediatric_icu_bed_occupancy_7_day_coverage
• staffed_pediatric_icu_bed_occupancy_7_day_sum
• total_staffed_pediatric_icu_beds_7_day_avg
• total_staffed_pediatric_icu_beds_7_day_coverage
• total_staffed_pediatric_icu_beds_7_day_sum

On October 24, 2022, the data includes more analytical calculations in efforts to provide a cleaner dataset. For a raw version of this dataset, please follow this link: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb

Due to changes in reporting requirements, after June 19, 2023, a collection week is defined as starting on a Sunday and ending on the next Saturday.

This dataset includes aggregated weekly respiratory virus laboratory data that the Chicago Department of Public Health (CDPH) uses to monitor influenza, COVID-19, respiratory syncytial virus (RSV), and other respiratory virus activity in Chicago. The data represents respiratory viral PCR tests performed by several hospital laboratories in Chicago as well as two commercial laboratories serving Chicago facilities. Data are voluntarily reported on a weekly basis and do not contain patient demographic or geographic information. The data reported represent both Chicago and non-Chicago residents tested by the reporting facility.

The respiratory viruses included are influenza, RSV, SARS-CoV-2, parainfluenza, rhinovirus/enterovirus, adenovirus, human metapneumovirus, and seasonal coronaviruses. Influenza laboratory data are available from 2010-2011 to present; for all other respiratory viruses data are available from 2019-2020 to present.

All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

Analysis of ‘Influenza ICU Cases by Week and Demographic/Medical Category’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/72607063-5909-469e-bd44-84cca51dc82d on 13 February 2022.

--- Dataset description provided by original source is as follows ---

In Illinois, influenza associated Intensive Care Unit (ICU) hospitalizations are reportable as soon as possible, but within 24 hours. Influenza associated ICU hospitalizations are defined as individuals hospitalized in an ICU with a positive laboratory test for influenza A or B, including specimens identified as influenza A/H3N2, A/H1N1pdm09, and specimens not subtyped (e.g., influenza positive cases by PCR or any rapid test such as EIA).

This dataset represents weekly aggregated information for influenza-associated ICU hospitalizations among Chicago residents, which is a reportable condition in Illinois.

Information includes demographics, influenza laboratory results, vaccination status, and death status.

Column names containing "REPORTED" indicate the number of cases for which the indicated data element was reported. This, rather than the total number of cases, is used to calculate the corresponding percentage.

All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘NNDSS - TABLE 1Y. Mumps to Novel influenza A virus infections’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/37a7c7eb-1382-4571-849e-b371f6f471b1 on 11 February 2022.

--- Dataset description provided by original source is as follows ---

NNDSS - TABLE 1Y. Mumps to Novel influenza A virus infections - 2022. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents.

Notes:

• These are weekly cases of selected infectious national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables available at https://www.cdc.gov/nndss/data-statistics/index.html. Cases reported by state health departments to CDC for weekly publication are subject to ongoing revision of information and delayed reporting. Therefore, numbers listed in later weeks may reflect changes made to these counts as additional information becomes available. Case counts in the tables are presented as published each week. See also Guide to Interpreting Provisional and Finalized NNDSS Data at https://www.cdc.gov/nndss/docs/Readers-Guide-WONDER-Tables-20210421-508.pdf. • Notices, errata, and other notes are available in the Notice To Data Users page at https://wonder.cdc.gov/nndss/NTR.html. • The list of national notifiable infectious diseases and conditions and their national surveillance case definitions are available at https://ndc.services.cdc.gov/. This list incorporates the Council of State and Territorial Epidemiologists (CSTE) position statements approved by CSTE for national surveillance.

Footnotes:

*Case counts for reporting years 2021 and 2022 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://www.cdc.gov/nndss/docs/Readers-Guide-WONDER-Tables-20210421-508.pdf. †Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data). U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published. NC: Not calculated — There is insufficient data available to support the calculation of this statistic. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks.

--- Original source retains full ownership of the source dataset ---

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)

Note: On April 30, 2024, the Federal mandate for COVID-19 and influenza associated hospitalization data to be reported to CDC’s National Healthcare Safety Network (NHSN) expired. Hospitalization data beyond April 30, 2024, will not be updated on the Open Data Portal. Hospitalization and ICU admission data collected from summer 2020 to May 10, 2023, are sourced from the California Hospital Association (CHA) Survey. Data collected on or after May 11, 2023, are sourced from CDC's National Healthcare Safety Network (NHSN).

Data is from the California Department of Public Health (CDPH) Respiratory Virus State Dashboard at https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx.

Data are updated each Friday around 2 pm.

For COVID-19 death data: As of January 1, 2023, data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2023–Present. Prior to January 1, 2023, death data was sourced from the COVID-19 case registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023. Influenza death data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2020–Present.

COVID-19 testing data represent data received by CDPH through electronic laboratory reporting of test results for COVID-19 among residents of California. Testing date is the date the test was administered, and tests have a 1-day lag (except for the Los Angeles County, which has an additional 7-day lag). Influenza testing data represent data received by CDPH from clinical sentinel laboratories in California. These laboratories report the aggregate number of laboratory-confirmed influenza virus detections and total tests performed on a weekly basis. These data do not represent all influenza testing occurring in California and are available only at the state level.

NNDSS - TABLE 1R. Hepatitis C, perinatal infection to Influenza-associated pediatric mortality - 2019. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents.

Note: This table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html.

Footnotes: U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published — CDC does not have data because of changes in how conditions are categorized. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks. * Case counts for reporting years 2018 and 2019 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the US, a US territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-US Residents' category. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. † Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data). § Since [INSERT DATE], XXX influenza-associated pediatric deaths occurring during the 2017-18 season have been reported.

This dataset represents preliminary weekly estimates of cumulative U.S. COVID-19-associated hospitalizations for the 2024-2025 period. The weekly cumulatve COVID-19 –associated hospitalization estimates are preliminary, and use reported weekly hospitalizations among laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data are updated week-by-week as new COVID-19 hospitalizations are reported to CDC from the COVID-NET system and include both new admissions that occurred during the reporting week, as well as those admitted in previous weeks that may not have been included in earlier reporting. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated hospitalizations that have occurred since October 1, 2024. For details, please refer to the publication [7].

Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

References

1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413  
7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

The Coronavirus Disease 2019 (COVID-19) Hospitalization Surveillance Network (COVID-NET) a network that conducts active, population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations among children and adults. COVID-NET, along with the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET) and the Influenza Hospitalization Surveillance Network (FluSurv-NET), comprise the Respiratory Virus Hospitalization Surveillance Network (RESP-NET). The RESP-NET platforms have overlapping surveillance areas and use similar methods to collect data. COVID-NET is CDC’s source for important data on rates of hospitalizations associated with COVID-19. Hospitalization rates show how many people in the surveillance area are hospitalized with COVID-19, compared to the total number of people residing in that area. Data are preliminary and subject to change as more data become available. Data will be updated weekly.

NNDSS - Table I. infrequently reported notifiable diseases - 2017. In this Table, provisional cases of selected infrequently reported notifiable diseases (<1,000 cases reported during the preceding year) are displayed.

Note: These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting.

Case counts in these tables are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available.

Footnote: —: No reported cases. N: Not reportable. NA: Not available. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts.

• Case counts for reporting year 2017 are provisional and subject to change. Data for years 2012 through 2016 are finalized. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf.

† This table does not include cases from the U.S. territories. Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions.

§ Calculated by summing the incidence counts for the current week, the 2 weeks preceding the current week, and the 2 weeks following the current week, for a total of 5 preceding years. Additional information is available at http://wwwn.cdc.gov/nndss/document/5yearweeklyaverage.pdf.

¶ Updated weekly reports from the Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases (ArboNET Surveillance). Data for West Nile virus are available in Table II.

** Not reportable in all jurisdictions. Data from states where the condition is not reportable are excluded from this table, except for the arboviral diseases and influenza-associated pediatric mortality. Reporting exceptions are available at http://wwwn.cdc.gov/nndss/downloads.html.

†† Data for Haemophilus influenzae (all ages, all serotypes) are available in Table II.

§§ In 2016, the nationally notifiable condition ‘Hepatitis B Perinatal Infection’ was renamed to ‘Perinatal Hepatitis B Virus Infection’ and reflects updates in the 2016 CSTE position statement for Perinatal Hepatitis B Virus Infection.

¶¶ Please refer to the MMWR publication for weekly updates to the footnote for this condition.

*** Please refer to the MMWR publication for weekly updates to the footnote for this condition.

††† Data for meningococcal disease (all serogroups) are available in Table II.

§§§ Novel influenza A virus infections are human infections with influenza A viruses that are different from currently circulating human seasonal influenza viruses. With the exception of one avian lineage influenza A (H7N2) virus, all novel influenza A virus infections reported to CDC since 2011 have been variant influenza viruses. Total case counts are provided by the Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD).

¶¶¶ Updated weekly from reports to the Division of STD Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention.

**** Prior to 2015, CDC's National Notifiable Diseases Surveillance System (NNDSS) did not receive electronic data about incident cases of specific viral hemorrhagic fevers; instead data were collected in aggregate as "viral hemorrhagic fevers". Beginning in 2015, NNDSS has been updated to receive data for each of

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.

This dataset represents preliminary weekly estimates of cumulative U.S. RSV-associated hospitalizations for the 2024-2025 season. Estimates are preliminary, and use reported weekly hospitalizations among laboratory-confirmed respiratory syncytial virus (RSV) infections. The data are updated week-by-week as new RSV-associated hospitalizations are reported to CDC from the RSV-NET surveillance system and include both new admissions that occurred during the reporting week, as well as those admitted in previous weeks that may not have been included in earlier reporting. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of RSV-associated hospitalizations that have occurred since October 1, 2024. For details, please refer to the publication [7].

Note: Data are preliminary and subject to change as more data become available. Rates for recent RSV-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

Note: Preliminary burden estimates are not inclusive of data from all RSV-NET sites. Due to model limitations, sites with small sample sizes can impact estimates in unpredictable ways and are excluded for the benefit of model stability. CDC is working to address model limitations and include data from all sites in final burden estimates.

References

1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413  
7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

NNDSS - TABLE 1Y. Mumps to Novel influenza A virus infections - 2020. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents.

Notice: Data from California published in week 29 for years 2019 and 2020 were incomplete when originally published on July 24, 2020. On August 4, 2020, incomplete case counts were replaced with a "U" indicating case counts are not available for specified time period.

Note: This table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html.

Footnotes: U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published. NC: Not calculated — There is insufficient data available to support the calculation of this statistic. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks. * Case counts for reporting years 2019 and 2020 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. †Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data). § Novel influenza A virus infections are human infections with influenza A viruses that are different from currently circulating human seasonal influenza viruses. With the exception of one avian lineage influenza A (H7N2) virus, all novel influenza A virus infections reported to CDC since 2012 have been variant influenza viruses.