Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d

Covid-19 Daily metrics at the county level As of 6/1/2023, this data set is no longer being updated. The COVID-19 Data Report is posted on the Open Data Portal every day at 3pm. The report uses data from multiple sources, including external partners; if data from external partners are not received by 3pm, they are not available for inclusion in the report and will not be displayed. Data that are received after 3pm will still be incorporated and published in the next report update. The cumulative number of COVID-19 cases (cumulative_cases) includes all cases of COVID-19 that have ever been reported to DPH. The cumulative number of COVID_19 cases in the last 7 days (cases_7days) only includes cases where the specimen collection date is within the past 7 days. While most cases are reported to DPH within 48 hours of specimen collection, there are a small number of cases that routinely are delayed, and will have specimen collection dates that fall outside of the rolling 7 day reporting window. Additionally, reporting entities may submit correction files to contribute historic data during initial onboarding or to address data quality issues; while this is rare, these correction files may cause a large amount of data from outside of the current reporting window to be uploaded in a single day; this would result in the change in cumulative_cases being much larger than the value of cases_7days. On June 4, 2020, the US Department of Health and Human Services issued guidance requiring the reporting of positive and negative test results for SARS-CoV-2; this guidance expired with the end of the federal PHE on 5/11/2023, and negative SARS-CoV-2 results were removed from the List of Reportable Laboratory Findings. DPH will no longer be reporting metrics that were dependent on the collection of negative test results, specifically total tests performed or percent positivity. Positive antigen and PCR/NAAT results will continue to be reportable.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on select population characteristic types are listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths.

Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

This table will no longer be updated after 5/30/2024 given the end of the 2023-2024 viral respiratory vaccine season.

This table shows the cumulative number and percentage of CT residents who have received an updated COVID-19 vaccine during the 2023-2024 viral respiratory season by age group (current age).
CDC recommends that people get at least one dose of this vaccine to protect against serious illness, whether or not they have had a COVID-19 vaccination before. Children and people with moderate to severe immunosuppression might be recommended more than one dose. For more information on COVID-19 vaccination recommendations, click here.
• Data are reported weekly on Thursday and include doses administered to Saturday of the previous week (Sunday – Saturday). All data in this report are preliminary. Data from the previous week may be changed because of delays in reporting, deduplication, or correction of errors.
• These analyses are based on data reported to CT WiZ which is the immunization information system for CT. CT providers are required by law to report all doses of vaccine administered. CT WiZ also receives records on CT residents vaccinated in other jurisdictions and by federal entities which share data with CT Wiz electronically. Electronic data exchange is being added jurisdiction-by-jurisdiction. Currently, this includes Rhode Island and New York City but not Massachusetts and New York State. Therefore, doses administered to CT residents in neighboring towns in Massachusetts and New York State will not be included. A full list of the jurisdiction with which CT has established electronic data exchange can be seen at the bottom of this page (https://portal.ct.gov/immunization/Knowledge-Base/Articles/Vaccine-Providers/CT-WiZ-for-Vaccine-Providers-and-Training/Query-and-Response-functionality-in-CT-WiZ?language=en_US)
• Population size estimates used to calculate cumulative percentages are based on 2020 DPH provisional census estimates*.
• People are included if they have an active jurisdictional status in CT WiZ at the time weekly data are pulled. This excludes people who live out of state, are deceased and a small percentage who have opted out of CT WiZ.
* DPH Provisional State and County Characteristics Estimates April 1, 2020. Hayes L, Abdellatif E, Jiang Y, Backus K (2022) Connecticut DPH Provisional April 1, 2020, State Population Estimates by 18 age groups, sex, and 6 combined race and ethnicity groups. Connecticut Department of Public Health, Health Statistics & Surveillance, SAR, Hartford, CT.

Analysis of ‘COVID-19 Cases by Population Characteristics Over Time’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a3291d85-0076-43c5-a59c-df49480cdc6d on 13 February 2022.

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

Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change. Due to the changes, starting on January 22, 2022, the number of new cases reported daily will be higher than under the old system as cases that would have taken longer to process will be reported earlier.

A. SUMMARY This dataset shows San Francisco COVID-19 cases by population characteristics and by specimen collection date. Cases are included on the date the positive test was collected.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how cases have been distributed among different subgroups. This information can reveal trends and disparities among groups.

Data is lagged by five days, meaning the most recent specimen collection date included is 5 days prior to today. Tests take time to process and report, so more recent data is less reliable.

B. HOW THE DATASET IS CREATED Data on the population characteristics of COVID-19 cases and deaths are from: * Case interviews * Laboratories * Medical providers

These multiple streams of data are merged, deduplicated, and undergo data verification processes. This data may not be immediately available for recently reported cases because of the time needed to process tests and validate cases. Daily case totals on previous days may increase or decrease. Learn more.

Data are continually updated to maximize completeness of information and reporting on San Francisco residents with COVID-19.

Data notes on each population characteristic type is listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups.

Sexual orientation * Sexual orientation data is collected from individuals who are 18 years old or older. These individuals can choose whether to provide this information during case interviews. Learn more about our data collection guidelines. * The City began asking for this information on April 28, 2020.

Gender * The City collects information on gender identity using these guidelines.

Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

Transmission type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation
* the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures.
These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing

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

NOTE: This dataset pertains only to the 2020-2021 school year and is no longer being updated. For additional data on COVID-19, visit data.ct.gov/coronavirus.

This dataset includes the leading and secondary metrics identified by the Connecticut Department of Health (DPH) and the Department of Education (CSDE) to support local district decision-making on the level of in-person, hybrid (blended), and remote learning model for Pre K-12 education.

Data represent daily averages for two-week periods by date of specimen collection (cases and positivity), date of hospital admission, or date of ED visit. Hospitalization data come from the Connecticut Hospital Association and are based on hospital location, not county of patient residence. COVID-19-like illness includes fever and cough or shortness of breath or difficulty breathing or the presence of coronavirus diagnosis code and excludes patients with influenza-like illness. All data are preliminary.

These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf).

These metrics were adapted from recommendations by the Harvard Global Institute and supplemented by existing DPH measures.

For national data on COVID-19, see COVID View, the national weekly surveillance summary of U.S. COVID-19 activity, at https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

DPH note about change from 7-day to 14-day metrics: Prior to 10/15/2020, these metrics were calculated using a 7-day average rather than a 14-day average. The 7-day metrics are no longer being updated as of 10/15/2020 but the archived dataset can be accessed here: https://data.ct.gov/Health-and-Human-Services/CT-School-Learning-Model-Indicators-by-County/rpph-4ysy

As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

Several additional data limitations should be kept in mind:

• Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

• Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

• However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

• Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

• The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

The following dashboards provide data on contagious respiratory viruses, including acute respiratory diseases, COVID-19, influenza (flu), and respiratory syncytial virus (RSV) in Massachusetts. The data presented here can help track trends in respiratory disease and vaccination activity across Massachusetts.

DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, the school learning model indicator metrics will be calculated using a 14-day average rather than a 7-day average. The new school learning model indicators dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/CT-School-Learning-Model-Indicators-by-County-14-d/e4bh-ax24 As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well. With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county). This dataset includes the leading and secondary metrics identified by the Connecticut Department of Health (DPH) and the Department of Education (CSDE) to support local district decision-making on the level of in-person, hybrid (blended), and remote learning model for Pre K-12 education. Data represent daily averages for each week by date of specimen collection (cases and positivity), date of hospital admission, or date of ED visit. Hospitalization data come from the Connecticut Hospital Association and are based on hospital location, not county of patient residence. COVID-19-like illness includes fever and cough or shortness of breath or difficulty breathing or the presence of coronavirus diagnosis code and excludes patients with influenza-like illness. All data are preliminary. These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020. These metrics were adapted from recommendations by the Harvard Global Institute and supplemented by existing DPH measures. For national data on COVID-19, see COVID View, the national weekly surveillance summary of U.S. COVID-19 activity, at https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 12+ and age 5+ denominators have been uploaded as archived tables.

Starting June 30, 2021, the dataset has been reconfigured so that all updates are appended to one dataset to make it easier for API and other interfaces. In addition, historical data has been extended back to January 5, 2021.

This dataset shows full, partial, and at least 1 dose coverage rates by zip code tabulation area (ZCTA) for the state of California. Data sources include the California Immunization Registry and the American Community Survey’s 2015-2019 5-Year data.

This is the data table for the LHJ Vaccine Equity Performance dashboard. However, this data table also includes ZTCAs that do not have a VEM score.

This dataset also includes Vaccine Equity Metric score quartiles (when applicable), which combine the Public Health Alliance of Southern California’s Healthy Places Index (HPI) measure with CDPH-derived scores to estimate factors that impact health, like income, education, and access to health care. ZTCAs range from less healthy community conditions in Quartile 1 to more healthy community conditions in Quartile 4.

The Vaccine Equity Metric is for weekly vaccination allocation and reporting purposes only. CDPH-derived quartiles should not be considered as indicative of the HPI score for these zip codes. CDPH-derived quartiles were assigned to zip codes excluded from the HPI score produced by the Public Health Alliance of Southern California due to concerns with statistical reliability and validity in populations smaller than 1,500 or where more than 50% of the population resides in a group setting.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

For some ZTCAs, vaccination coverage may exceed 100%. This may be a result of many people from outside the county coming to that ZTCA to get their vaccine and providers reporting the county of administration as the county of residence, and/or the DOF estimates of the population in that ZTCA are too low. Please note that population numbers provided by DOF are projections and so may not be accurate, especially given unprecedented shifts in population as a result of the pandemic.

This dataset includes aggregated weekly data on the percent of emergency department visits and the percent of hospital inpatient admissions due to influenza-like illness (ILI), COVID-19, influenza, RSV, and acute respiratory illness. The Illinois Department of Public Health (IDPH) collects data for Emergency Department visits to all 185 acute care hospitals in Illinois. The data are submitted from IDPH to the CDC’s BioSense Platform for access and analysis by health departments via the ESSENCE system. The CDC National Syndromic Surveillance Program (NSSP) utilizes diagnostic codes and clinical terms to create definitions for diagnosed COVID-19, influenza, RSV, and acute respiratory illness. For more information on diagnostic codes and clinical terms used, visit: https://www.cdc.gov/nssp/php/onboarding-resources/companion-guide-ed-data-respiratory-illness.html The data is characterized by selected demographic groups including age group and race/ethnicity. The dataset also includes percent of weekly outpatient visits due to ILI as reported by several outpatient clinics throughout Chicago that participate in CDC’s Influenza-like Illness Surveillance Network (ILINet). For more information on ESSENCE, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance For more information on ILINet, see https://www.cdc.gov/fluview/overview/index.html#cdc_generic_section_3-outpatient-illness-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.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

On 6/16/2023 CDPH replaced the booster measures with a new “Up to Date” measure based on CDC’s new recommendations, replacing the primary series, boosted, and bivalent booster metrics The definition of “primary series complete” has not changed and is based on previous recommendations that CDC has since simplified. A person cannot complete their primary series with a single dose of an updated vaccine. Whereas the booster measures were calculated using the eligible population as the denominator, the new up to date measure uses the total estimated population. Please note that the rates for some groups may change since the up to date measure is calculated differently than the previous booster and bivalent measures.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Previous updates:

• On March 3, 2023, with the release of HPI 3.0 in 2022, the previous equity scores have been updated to reflect more recent community survey information. This change represents an improvement to the way CDPH monitors health equity by using the latest and most accurate community data available. The HPI uses a collection of data sources and indicators to calculate a measure of community conditions ranging from the most to the least healthy based on economic, housing, and environmental measures.

• Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

• Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

NOTE: This dataset replaces two previous ones. Please see below.

Chicago residents who are up to date with COVID-19 vaccines, based on the reported address, race-ethnicity, sex, and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE).

“Up to date” refers to individuals who meet the CDC’s updated COVID-19 vaccination criteria based on their age and prior vaccination history. For surveillance purposes, up to date is defined based on the following criteria:

People ages 5 years and older: · Are up to date when they receive 1+ doses of a COVID-19 vaccine during the current season.

Children ages 6 months to 4 years: · Children who have received at least two prior COVID-19 vaccine doses are up to date when they receive one additional dose of COVID-19 vaccine during the current season, regardless of vaccine product. · Children who have received only one prior COVID-19 vaccine dose are up to date when they receive one additional dose of the current season's Moderna COVID-19 vaccine or two additional doses of the current season's Pfizer-BioNTech COVID-19 vaccine. · Children who have never received a COVID-19 vaccination are up to date when they receive either two doses of the current season's Moderna vaccine or three doses of the current season's Pfizer-BioNTech vaccine.

This dataset takes the place of two previous datasets, which cover doses administered from December 15, 2020 through September 13, 2023 and are marked has historical: - https://data.cityofchicago.org/Health-Human-Services/COVID-19-Daily-Vaccinations-Chicago-Residents/2vhs-cf6b - https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccinations-by-Age-and-Race-Ethnicity/37ac-bbe3.

Data Notes:

Weekly cumulative totals of people up to date are shown for each combination of race-ethnicity, sex, and age group. Note that race-ethnicity, age, and sex all have an option for “All” so care should be taken when summing rows.

Coverage percentages are calculated based on the cumulative number of people in each race-ethnicity/age/sex population subgroup who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller demographic groupings with smaller populations. Additionally, the medical provider may report incorrect demographic information for the person receiving the vaccination, which may lead to over- or underestimation of vaccination coverage. All coverage percentages are capped at 99%.

Weekly cumulative counts and coverage percentages are reported from the week ending Saturday, September 16, 2023 onward through the Saturday prior to the dataset being updated.

All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.

The Chicago Department of Public Health uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Individuals may receive vaccinations that are not recorded in the Illinois immunization registry, I-CARE, such as those administered in another state, causing underestimation of the number individuals who are up to date. Inconsistencies in records of separate doses administered to the same person, such as slight variations in dates of birth, can result in duplicate records for a person and underestimate the number of people who are up to date.

For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

As of 10/27/2022, this dataset will no longer update. To continue to access updated vaccination metrics given to SF residents, including newly added bivalent boosters, please navigate to the following page: COVID-19 Vaccinations Given to SF Residents Over Time.

A. SUMMARY This dataset represents the COVID-19 vaccinations given to San Franciscans by the San Francisco Department of Public Health (SF DPH) over time.

B. HOW THE DATASET IS CREATED Information on doses administered to those who live in San Francisco is from the California Immunization Registry (CAIR), run by the California Department of Public Health (CDPH).

C. UPDATE PROCESS Updated daily via automated process

D. HOW TO USE THIS DATASET Different vaccines have different dosage requirements. For example, the Moderna and the Pfizer vaccines require two doses in order for a resident to complete their primary vaccine series (as of December 21, 2021). Each dose is recorded separately in its respective dataset column. Other vaccines, such as Johnson & Johnson, only require a single dose for a resident to complete their primary vaccine series (as of December 21, 2021). Single dose vaccines counts are recorded in a separate dataset column.

Summing the NEW_1ST_DOSES, NEW_2ND_DOSES, NEW_SINGLE_DOSES columns gives you the total count of primary vaccine series doses administered on a given day. To count the number of individuals that have completed their primary vaccine series on a given day, use the NEW_SERIES_COMPLETED column. To count the number of individuals vaccinated (with any primary series dose) for the first time on a given day, use the NEW_RECIPIENTS column.

To count the number of individuals who got a vaccine booster on a given day, use the NEW_BOOSTER_RECIPIENTS column. To count the number of booster doses administered on a given day, use the NEW_BOOSTER_DOSES column. To count the total number of individuals who have received a booster over time, use the CUMULATIVE_BOOSTER_RECIPIENTS column. To count the total number of booster doses that have been administered over time, use the CUMULATIVE_BOOSTER_DOSES column.

In our public dashboards we combine this dataset with the US Census's 2019 five-year American Community Survey population estimates to estimate the percent of San Franciscans vaccinated.

This dataset is not being updated as hospitals are no longer mandated to report COVID Hospitalizations to CDPH.

Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/

Note: Hospitalization counts include all patients diagnosed with COVID-19 during their stay. This does not necessarily mean they were hospitalized because of COVID-19 complications or that they experienced COVID-19 symptoms.

Note: Cumulative totals are not available due to the fact that hospitals report the total number of patients each day (as opposed to new patients).

As of 6/1/2023, this data set is no longer being updated.

Connecticut nursing homes are required by the Centers for Medicare and Medicaid Services (CMS) to report on the impact of COVID-19 on their residents and staff through CDC’s National Healthcare Safety Network (NHSN). This reporting is intended to reflect recent COVID-19 activity in nursing homes.

Data presented here from NHSN reflect resident and staff COVID-19 cases and COVID-related deaths reported for Connecticut nursing homes for the previous week, Thursday–Wednesday. All nursing homes follow NHSN definitions and instructions when reporting to the NHSN COVID-19 module, ensuring data are reported in a systematic way. These data do not show where the resident or staff got infected.

Detailed information about COVID-19 reporting for nursing homes and NHSN can be found here: https://www.cdc.gov/nhsn/ltc/covid19/index.html

A. SUMMARY This dataset represents all San Francisco (SF) residents who have received a vaccine for certain respiratory viruses that circulate more heavily in the fall and winter months. All vaccines given to SF residents are included, even if they received their vaccination elsewhere in California. The data are broken down by demographic and geographical stratifications.

COVID-19: This dataset represents all SF residents who are considered up to date on their COVID-19 vaccine. A person is up to date if they have received at least one dose of the 2024–2025 COVID-19 vaccine. The specific up-to-date criteria can be found on the California Department of Public Health (CDPH) website.

(Note: As of November 2024, this dataset only contains data regarding COVID-19 vaccinations. This documentation will be updated as other seasonal vaccination data is added).

B. HOW THE DATASET IS CREATED Information on doses administered to those who live in SF is from the California Immunization Registry (CAIR2), run by CDPH. The information on individuals’ city of residence, age, race, and ethnicity are also recorded in CAIR and are self-reported at the time of vaccine administration.

In order to estimate the percent of San Franciscans vaccinated, we provide the 2018-2022 American Community Survey (ACS) population estimates for each demographic group and analysis neighborhood.

C. UPDATE PROCESS Updated daily via automated process.

D. HOW TO USE THIS DATASET SF population estimates for race/ethnicity and age groups can be found in a https://data.sfgov.org/Economy-and-Community/SF-COVID-19-reporting-demographics-population-esti/cedd-86uf">view based on the San Francisco Population and Demographic Census dataset. SF population estimates for analysis neighborhoods can be found in a view based on the San Francisco Population and Geography Census dataset. Both of these views use population estimates from the 2018-2022 5-year ACS.

Before analysis, you must filter the dataset to the desired stratification of data using the “vaccine_type” and "demographic_group" columns. For example, filtering “vaccine_type” to “COVID-19” will allow you to only look at rows corresponding to COVID-19 vaccinations. Filtering “demographic_subgroup” to “Analysis Neighborhood” will allow you to only look at rows corresponding to SF neighborhoods. You can then calculate the percentages of those up to date with their COVID-19 vaccinations by neighborhood. The “vaccine_subtype” field provides information about the current vaccine product being tracked in this dataset.

E. CHANGE LOG