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This submission includes publicly available data extracted in its original form. Please reference the Related Publication listed here for source and citation information: Hall WJ, Chapman MV, Lee KM, et al. Implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: a systematic review. Am J Public Health. 2015;105:e60–e76. If you have questions about the underlying data stored here, please contact The Centers for Disease Control and Prevention. If you have questions or recommendations related to this metadata entry and extracted data, please contact the CAFE Data Management team at: climatecafe@bu.edu. "The Centers for Disease Control and Prevention (CDC) conducts national surveillance to better understand the causes of pregnancy-related deaths. The Pregnancy Mortality Surveillance System (PMSS) defines a pregnancy-related death as a death during or within 1 year of the end of pregnancy from any cause related to or aggravated by the pregnancy. Medical epidemiologists review and analyze applicable vital records, and additional available data from all 50 states, New York City, and Washington, DC. Beginning in 2020, data from Puerto Rico are included, and in 2021, data from Northern Mariana Islands are included in PMSS." [Quote from https://www.cdc.gov/maternal-mortality/php/pregnancy-mortality-surveillance/index.html]

This data visualization presents county-level provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. County-level provisional counts include deaths occurring within the 50 states and the District of Columbia, as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts (see Technical Notes). The provisional data presented on the dashboard below include reported 12 month-ending provisional counts of death due to drug overdose by the decedent’s county of residence and the month in which death occurred. Percentages of deaths with a cause of death pending further investigation and a note on historical completeness (e.g. if the percent completeness was under 90% after 6 months) are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical Notes). Counts between 1-9 are suppressed in accordance with NCHS confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Technical Notes Nature and Sources of Data Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from the state vital registration offices through the Vital Statistics Cooperative Program (VSCP). The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death and jurisdiction in which the death occurred. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death due to the time often needed to investigate these deaths (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death. Provisional death counts presented in this data visualization are for “12 month-ending periods,” defined as the number of deaths occurring in the 12 month period ending in the month indicated. For example, the 12 month-ending period in June 2020 would include deaths occurring from July 1, 2019 through June 30, 2020. The 12 month-ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12 month-ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation. Cause of Death Classification and Definition of Drug Deaths Mortality statistics are compiled in accordance with the World Health Organizations (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regul

Users can search this database pertaining to respiratory conditions such as asthma, pneumonia, bronchitis, and tuberculosis. BackgroundThe National Occupational Respiratory Mortality System (NORMS) is developed and maintained by National Institute of Occupational Safety and Health (NIOSH) of the Centers for Disease Control and Prevention (CDC). This surveillance system includes respiratory conditions such as: asthma, pneumonia, bronchitis, tuberculosis, lung cancer, and silicosis, among others. User FunctionalityUsers can generate national- or occupation-specific queries. Users can gener ate tables, charts and maps containing the summary statistics such as number of deaths, crude death rates, age-adjusted death rates, and years of potential life lost (YPLL ). Users can also download the dataset and/or data queries into Microsoft Excel. Data NotesThis website provides data history regarding revisions to the dataset. Data from additional sources (i.e., population estimates, comparative standard population, and life-table values) are also available. National mortality data is derived from the National Center for Health Statistics (NCHS) multiple cause of death records. These data are updated annually since 1968, unless otherwise indicated. Data are available on national, state, and county levels. The most recent d ata available is from 2007.

The National Violent Death Reporting System (NVDRS) provides states and communities with a clearer understanding of violent deaths to guide local decisions about efforts to prevent violence and helps them track progress over time. To stop violent deaths, we must first understand all the facts. Created in 2002, the NVDRS is a surveillance system that pulls together data on violent deaths in 18 states (see map below), including information about homicides, such as homicides perpetrated by a intimate partner (e.g., boyfriend, girlfriend, wife, husband), child maltreatment (or child abuse) fatalities, suicides, deaths where individuals are killed by law enforcement in the line of duty, unintentional firearm injury deaths, and deaths of undetermined intent. These data are supported by WISQARS, an interactive query system that provides data on injury deaths, violent deaths, and nonfatal injuries.

This data contains provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National provisional counts include deaths occurring within the 50 states and the District of Columbia as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation (see Technical notes) resulting in an underestimate relative to final counts. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts (see Technical notes). Starting in June 2018, this monthly data release will include both reported and predicted provisional counts.

The provisional data include: (a) the reported and predicted provisional counts of deaths due to drug overdose occurring nationally and in each jurisdiction; (b) the percentage changes in provisional drug overdose deaths for the current 12 month-ending period compared with the 12-month period ending in the same month of the previous year, by jurisdiction; and (c) the reported and predicted provisional counts of drug overdose deaths involving specific drugs or drug classes occurring nationally and in selected jurisdictions. The reported and predicted provisional counts represent the numbers of deaths due to drug overdose occurring in the 12-month periods ending in the month indicated. These counts include all seasons of the year and are insensitive to variations by seasonality. Deaths are reported by the jurisdiction in which the death occurred.

Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical notes). Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made (see Technical notes). Provisional data will be updated on a monthly basis as additional records are received.

Technical notes

Nature and sources of data

Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from state vital registration offices through the Vital Statistics Cooperative Program (VSCP).

The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death.

Provisional death counts presented in this data visualization are for “12-month ending periods,” defined as the number of deaths occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2017 would include deaths occurring from July 1, 2016, through June 30, 2017. The 12-month ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. Counts for the 12-month period ending in the same month of the previous year are shown for comparison. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12-month ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation. Methods to adjust provisional counts have been developed to provide predicted provisional counts of drug overdose deaths, accounting for delayed reporting (see Percentage of records pending investigation and Adjustments for delayed reporting).

Provisional data are based on available records that meet certain data quality criteria at the time of analysis and may not include all deaths that occurred during a given time period. Therefore, they should not be considered comparable with final data and are subject to change.

Cause-of-death classification and definition of drug deaths
Mortality statistics are compiled in accordance with World Health Organization (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regulations on use of the classification. Causes of death for data presented in this report were coded according to ICD guidelines described in annual issues of Part 2a of the NCHS Instruction Manual (2).

Drug overdose deaths are identified using underlying cause-of-death codes from the Tenth Revision of ICD (ICD–10): X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and Y10–Y14 (undetermined). Drug overdose deaths involving selected drug categories are identified by specific multiple cause-of-death codes. Drug categories presented include: heroin (T40.1); natural opioid analgesics, including morphine and codeine, and semisynthetic opioids, including drugs such as oxycodone, hydrocodone, hydromorphone, and oxymorphone (T40.2); methadone, a synthetic opioid (T40.3); synthetic opioid analgesics other than methadone, including drugs such as fentanyl and tramadol (T40.4); cocaine (T40.5); and psychostimulants with abuse potential, which includes methamphetamine (T43.6). Opioid overdose deaths are identified by the presence of any of the following MCOD codes: opium (T40.0); heroin (T40.1); natural opioid analgesics (T40.2); methadone (T40.3); synthetic opioid analgesics other than methadone (T40.4); or other and unspecified narcotics (T40.6). This latter category includes drug overdose deaths where ‘opioid’ is reported without more specific information to assign a more specific ICD–10 code (T40.0–T40.4) (3,4). Among deaths with an underlying cause of drug overdose, the percentage with at least one drug or drug class specified is defined as that with at least one ICD–10 multiple cause-of-death code in the range T36–T50.8.

Drug overdose deaths may involve multiple drugs; therefore, a single death might be included in more than one category when describing the number of drug overdose deaths involving specific drugs. For example, a death that involved both heroin and fentanyl would be included in both the number of drug overdose deaths involving heroin and the number of drug overdose deaths involving synthetic opioids other than methadone.

Selection of specific states and other jurisdictions to report
Provisional counts are presented by the jurisdiction in which the death occurred (i.e., the reporting jurisdiction). Data quality and timeliness for drug overdose deaths vary by reporting jurisdiction. Provisional counts are presented for reporting jurisdictions based on measures of data quality: the percentage of records where the manner of death is listed as “pending investigation,” the overall completeness of the data, and the percentage of drug overdose death records with specific drugs or drug classes recorded. These criteria are defined below.

Percentage of records pending investigation

Drug overdose deaths often require lengthy investigations, and death certificates may be initially filed with a manner of death “pending investigation” and/or with a preliminary or unknown cause of death. When the percentage of records reported as “pending investigation” is high for a given jurisdiction, the number of drug overdose deaths is likely to be underestimated. For jurisdictions reporting fewer than 1% of records as “pending investigation”, the provisional number of drug overdose deaths occurring in the fourth quarter of 2015 was approximately 5% lower than the final count of drug overdose deaths occurring in that same time period. For jurisdictions reporting greater than 1% of records as “pending investigation” the provisional counts of drug overdose deaths may underestimate the final count of drug overdose deaths by as much as 30%. Thus, jurisdictions are included in Table 2 if 1% or fewer of their records in NVSS are reported as “pending investigation,” following a 6-month lag for the 12-month ending periods included in the dashboard. Values for records pending investigation are updated with each monthly release and reflect the most current data available.

Percent completeness

NCHS receives monthly counts of the estimated number of deaths from each jurisdictional vital registration offices (referred to as “control counts”). This number represents the best estimate of how many

MOMOTemp is a monitoring system for daily mortality associated with temperature, which has been implemented at the National Center for Epidemiology, with the aim of contributing to the National Plan of preventive actions against the effects of excess temperatures on health of the Ministry of Health. Data collection started in 2008.

NNDSS - TABLE 1R. Hepatitis C, perinatal infection to Influenza-associated pediatric mortality - 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). § Please refer to the CDC WONDER publication for weekly updates to the footnote for this condition. 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.

More than 450 public health and clinical laboratories located throughout the United States participate in surveillance for severe acute respiratory virus coronavirus type 2 (SARS-CoV-2), the virus that causes COVID-19, through CDC's National Respiratory and Enteric Virus Surveillance System (NREVSS). The dataset contains a weekly summary of aggregate counts of the total SARS-CoV-2 tests and SARS-CoV-2 detections reported to NREVSS since March 14, 2020. These data are reported weekly on a voluntary basis. Clinical laboratories do not report demographic data through NREVSS. Testing practices may vary regionally, and the number of participating laboratories may change from year to year. Results can be changed for up to 2 years after the initial reporting week. However, discrepancies may be noted and updated at the discretion of the data stewards and key stakeholders.

While NREVSS strives to present the most precise estimates of respiratory viral trends with reporting burden minimized for participating laboratories, there are several inherent limitations to this surveillance system.

NREVSS does not collect patient-specific data or demographic information. Multiple samples may be collected from a single patient, so NREVSS results do not necessarily reflect the number of patients tested, nor do they directly reflect hospitalizations or deaths related to COVID-19.

Participating laboratories vary in size, testing capabilities, and areas served. Some institutions may receive and test samples from sites across a given state or even from multiple states. Without direct knowledge of the population base, NREVSS cannot be used to determine the prevalence or incidence of infection.

For more information on NREVSS and COVID-19 surveillance please visit: https://www.cdc.gov/surveillance/nrevss. These data appear starting May 25, 2023 on the CDC COVID Data Tracker at the following URLs: https://covid.cdc.gov/covid-data-tracker/#trends ; https://covid.cdc.gov/covid-data-tracker/#cases.

NREVSS data are reported at the national and HHS regional levels. The ten (10) U.S. Department of HHS regions are defined here: https://www.hhs.gov/about/agencies/iea/regional-offices/index.html.

The data represent SARS-CoV-2 Nucleic Acid Amplification Test (NAAT) results, which include reverse transcriptase-polymerase chain reaction (RT-PCR) tests from a voluntary, sentinel network of participating laboratories in the United States, including clinical, public health and commercial laboratories (https://www.cdc.gov/surveillance/nrevss/labs/index.html).

These data exclude antigen, antibody, and at-home test results.

All data are provisional and subject to change. Reporting is less complete for the past 1 week, and more complete (>90%) for the period 2 weeks earlier.

There are data from all states across the 10 HHS regions. Because the data are from a sentinel network of laboratories, however, results may vary geographically. The data do not include all test results within a jurisdiction and therefore do not reflect all SARS-CoV-2 NAATs administered in the United States.

Percent positivity is one of the surveillance metrics used to monitor COVID-19 transmission over time and by area. Percent positivity is calculated by dividing the number of positive NAATs by the total number of NAATs administered, then multiplying by 100 [(# of positive NAAT tests / total NAAT tests) x 100].

The data represent laboratory tests performed, not individual (deduplicated) results in people. In the table and upon hovering on the map, the total test counts in the data reflect the latest data reported from NREVSS laboratories and may not match the data presented by various jurisdictions.

On May 11, 2023, CDC discontinued utilizing the COVID electronic laboratory reporting (CELR) platform as the primary laboratory source of COVID-19 results. These data are archived at health.data.gov.

For more information about NREVSS, please see: https://www.cdc.gov/surveillance/nrevss/index.html.

Data is from the California Department of Public Health (CDPH) Respiratory Virus Weekly Report.

The report is updated each Friday.

Laboratory surveillance data: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week.

Laboratory surveillance for influenza, respiratory syncytial virus (RSV), and other respiratory viruses (parainfluenza types 1-4, human metapneumovirus, non-SARS-CoV-2 coronaviruses, adenovirus, enterovirus/rhinovirus) involves the use of data from clinical sentinel laboratories (hospital, academic or private) located throughout California. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for influenza, respiratory syncytial virus, and other respiratory viruses in California. These laboratories report the number of laboratory-confirmed influenza, respiratory syncytial virus, and other respiratory virus detections and isolations, and the total number of specimens tested by virus type on a weekly basis.

Test positivity for a given week is calculated by dividing the number of positive COVID-19, influenza, RSV, or other respiratory virus results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday.

Hospitalization data: Data on COVID-19 and influenza hospital admissions are from Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety Network (NHSN) Hospitalization dataset. The requirement to report COVID-19 and influenza-associated hospitalizations was effective November 1, 2024. CDPH pulls NHSN data from the CDC on the Wednesday prior to the publication of the report. Results may differ depending on which day data are pulled. Admission rates are calculated using population estimates from the P-3: Complete State and County Projections Dataset provided by the State of California Department of Finance (https://dof.ca.gov/forecasting/demographics/projections/). Reported weekly admission rates for the entire season use the population estimates for the year the season started. For more information on NHSN data including the protocol and data collection information, see the CDC NHSN webpage (https://www.cdc.gov/nhsn/index.html).

CDPH collaborates with Northern California Kaiser Permanente (NCKP) to monitor trends in RSV admissions. The percentage of RSV admissions is calculated by dividing the number of RSV-related admissions by the total number of admissions during the same period. Admissions for pregnancy, labor and delivery, birth, and outpatient procedures are not included in total number of admissions. These admissions serve as a proxy for RSV activity and do not necessarily represent laboratory confirmed hospitalizations for RSV infections; NCKP members are not representative of all Californians.

Weekly hospitalization data are defined as Sunday through Saturday.

Death certificate data: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify influenza, respiratory syncytial virus, and COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all influenza, respiratory syncytial virus, and COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday.

Wastewater data: This dataset represents statewide weekly SARS-CoV-2 wastewater summary values. SARS-CoV-2 wastewater concentrations from all sites in California are combined into a single, statewide, unit-less summary value for each week, using a method for data transformation and aggregation developed by the CDC National Wastewater Surveillance System (NWSS). Please see the CDC NWSS data methods page for a description of how these summary values are calculated. Weekly wastewater data are defined as Sunday through Saturday.

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

NNDSS - Table II. Varicella to West Nile virus disease - 2014.In this Table, all conditions with a 5-year average annual national total of more than or equals 1,000 cases but less than or equals 10,000 cases will be displayed (��� 1,000 and ��_ 10,000). The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. 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 this table 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. Footnotes:C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Case counts for reporting years 2013 and 2014 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. ��� Updated weekly from reports to the Division of Vector-Borne Infectious Diseases, National Center for Zoonotic, Vector-Borne, and Enteric Diseases (ArboNet Surveillance). Data for California serogroup, eastern equine, Powassan, St. Louis, and western equine diseases are available in Table I. �� Not reportable in all states. Data from states where the condition is not reportable are excluded from this table, except starting in 2007 for the Arboviral diseases and influenza-associated pediatric mortality, and in 2003 for SARS-CoV. Reporting exceptions are available at http://wwwn.cdc.gov/nndss/document/SRCA_FINAL_REPORT_2006-2012_final.xlsx.More information on NNDSS is available at http://wwwn.cdc.gov/nndss/.

Lymphoma is a malignant disease that threatens human health and imposes a significant burden on the society burden; however, there are limited accurate mortality data on lymphoma in China. The present study aimed to analyse lymphoma-associated mortality at the national and provincial levels in mainland China. Mortality data of lymphoma was extracted from the disease surveillance system of the Chinese Center for Disease Control and Prevention. Mortality was represented by the number of deaths, crude mortality rate, and age-standardized mortality rate. Temporal trends in mortality rates were examined using the fitting joinpoint models. Lymphoma accounted for 31,225 deaths in 2020, of which 1,838 and 29,387 were due to Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL), respectively. The age-standardized mortality rate per 100,000 population was 1.76 for lymphoma, 0.10 for HL, and 1.66 for NHL. The mortality rate increased with age, reaching a peak in the age group of 80–84 years for HL and over 85 years for NHL. Moreover, the death risk due to lymphoma was approximately 1.5–2 times greater in males than in females in all age groups. The mortality rate was higher in eastern China than in central and western China, indicating a heterogeneous distribution at the provincial level. During 2013–2020, the mortality rate of lymphoma decreased by 1.85% (−22.94% for HL and −0.14% for NHL). In conclusion, the mortality of lymphoma varied by sex, age, and regions, which highlighted the need of establish differentiated strategy for disease control and prevention.

COVID-19 Cases information is reported through the Pennsylvania State Department’s National Electronic Disease Surveillance System (PA-NEDSS). As new cases are passed to the Allegheny County Health Department they are investigated by case investigators. During investigation some cases which are initially determined by the State to be in the Allegheny County jurisdiction may change, which can account for differences between publication of the files on the number of cases, deaths and tests. Additionally, information is not always reported to the State in a timely manner, delays can range from days to weeks, which can also account for discrepancies between previous and current files. Test and Case information will be updated daily. This resource contains individuals who received a COVID-19 test and individuals whom are probable cases. Every day, these records are overwritten with updates. Each row in the data reflects a person that is tested, not tests that are conducted. People that are tested more than once will have their testing and case data updated using the following rules:

1. Positive tests overwrite negative tests.
2. Polymerase chain reaction (PCR) tests overwrite antibody or antigen (AG) tests.
3. The first positive PCR test is never overwritten. Data collected from additional tests do not replace the first positive PCR test.

Note: On April 4th 2022 the Pennsylvania Department of Health no longer required labs to report negative AG tests. Therefore aggregated counts that included AG tests have been removed from the Municipality/Neighborhood files going forward. Versions of this data up to this cut-off have been retained as archived files.

Individual Test information is also updated daily. This resource contains the details and results of individual tests along with demographic information of the individual tested. Only PCR and AG tests are included. Every day, these records are overwritten with updates. This resource should be used to determine positivity rates.

The remaining datasets provide statistics on death demographics. Demographic, municipality and neighborhood information for deaths are reported on a weekly schedule and are not included with individual cases or tests. This has been done to protect the privacy and security of individuals and their families in accordance with the Health Insurance Portability and Accountability Act (HIPAA). Municipality or City of Pittsburgh Neighborhood is based off the geocoded home address of the individual tested.

Individuals whose home address is incomplete may not be in Allegheny County but whose temporary residency, work or other mitigating circumstance are determined to be in Allegheny County by the Pennsylvania Department of Health are counted as "Undefined".

Since the start of the pandemic, the ACHD has mapped every day’s COVID tests, cases, and deaths to their Allegheny County municipality and neighborhood. Tests were mapped to patient address, and if this was not available, to the provider location. This has recently resulted in apparent testing rates that exceeded the populations of various municipalities -- mostly those with healthcare providers. As this was brought to our attention, the health department and our data partners began researching and comparing methods to most accurately display the data. This has led us to leave those with missing home addresses off the map. Although these data will still appear in test, case and death counts, there will be over 20,000 fewer tests and almost 1000 fewer cases on the map. In addition to these map changes, we have identified specific health systems and laboratories that had data uploading errors that resulted in missing locations, and are working with them to correct these errors.

Due to minor discrepancies in the Municipal boundary and the City of Pittsburgh Neighborhood files individuals whose City Neighborhood cannot be identified are be counted as “Undefined (Pittsburgh)”.

On May 19, 2023, with the rescinding of the COVID-19 public health emergency, changes in data and reporting mechanisms prompted a change to an annual data sharing schedule for tests, cases, hospitalizations, and deaths. Dates for annual release are TBD. The weekly municipal counts and individual data produced before this changed are maintained as archive files.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

description:

NNDSS - Table II. West Nile virus disease - 2015.In this Table, provisional cases of selected notifiable diseases ( 1,000 cases reported during the preceding year), and selected low frequency diseases are displayed.The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. 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 this table 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. Footnotes:C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Three low incidence conditions, rubella, rubella congenital, and tetanus, have been moved to Table 2 to facilitate case count verification with reporting jurisdictions. Case counts for reporting year 2015 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesS.... Data for TB are displayed in Table IV, which appears quarterly. Updated weekly from reports to the Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases (ArboNET Surveillance). Data for California serogroup, Chikungunya virus, eastern equine, Powassan, St. Louis, and western equine diseases are available in Table I. Not reportable in all states. Data from states where the condition is not reportable are excluded from this table, except starting in 2007 for the domestic arboviral diseases, influenza-associated pediatric mortality, and in 2003 for SARS-CoV. Reporting exceptions are available at http://wwwn.cdc.gov/nndss/downloads.html.

NNDSS - Table II. West Nile virus disease - 2015.In this Table, provisional cases of selected notifiable diseases ( 1,000 cases reported during the preceding year), and selected low frequency diseases are displayed.The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. 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 this table 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. Footnotes:C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Three low incidence conditions, rubella, rubella congenital, and tetanus, have been moved to Table 2 to facilitate case count verification with reporting jurisdictions. Case counts for reporting year 2015 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesS.... Data for TB are displayed in Table IV, which appears quarterly. Updated weekly from reports to the Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases (ArboNET Surveillance). Data for California serogroup, Chikungunya virus, eastern equine, Powassan, St. Louis, and western equine diseases are available in Table I. Not reportable in all states. Data from states where the condition is not reportable are excluded from this table, except starting in 2007 for the domestic arboviral diseases, influenza-associated pediatric mortality, and in 2003 for SARS-CoV. Reporting exceptions are available at http://wwwn.cdc.gov/nndss/downloads.html.

The dashboard contains statewide, county of COVID-19 confirmed cases, probable cases, negative tests, deaths, and hospitalizations. Dashboard also contains cases by demographics and deaths by demographics at state level and cases information at zip code level. Case count data, map and new cases per day data are gotten from Pennsylvania National Electronic Disease Surveillance System (PA-NEDSS). Deaths by day graph data are gotten from the PA Electronic Death Registration System (EDRS).

In accordance with the SARS-CoV-2 surveillance methodology, laboratory confirmed cases are covered with the date of the previous day. The number of reported cases of SARS-CoV-2 infection underestimates the number of real infections. Changing the number depends not only on changing the number of new infections, but also on changing testing recommendations and testing practices. Due to additional entries and verifications of data in the Infectious Diseases Record under the Health Care Databases Act (NIJZ 48 database), the data may be entered subsequently. As data are in a continuous process of collection and updating, the daily dynamics of data are therefore even more pronounced. From 1.2.2022 onwards, the time period is changed or the interval between two positive findings for SARS-CoV-2 infection is reduced from ≥ 90 to ≥ 45 days as a condition for re-recovery of the result in the NIJZ 48 database (re-infections). Since the start of surveillance for SARS-CoV-2 infections, the daily number of confirmed cases includes cases confirmed by PCR, and between 21.12.2020 and 12.2.2021 and 1.2.2022, the daily number of confirmed cases includes cases confirmed by PCR or HAGT.

The National Institute of Public Health (NIJZ) monitors data on the number of deaths through the system of official declaration of death from infectious disease. The daily number of deaths with confirmed SARS-CoV-2 infection is one of the key indicators in the epidemiological surveillance of the COVID-19 epidemic. The official report of death under the Infectious Diseases Act is based on the clinical judgement of a doctor or coroner that an individual has died from COVID-19. In addition, the NIJZ monitors data on causes of death through the data source Medical Report on the deceased person. In order to keep up-to-date monitoring and reporting of deceased persons with confirmed SARS-CoV-2 infection, due to limitations such as incomplete data reporting, time lag in obtaining data, additional follow-up enquiries about the deceased, we have established an adapted method of monitoring the number of deaths.

DEFINITIONS

A confirmed case of SARS-COV-2 infection for the purpose of epidemiological surveillance of the number of confirmed persons with confirmed SARS-CoV-2 infection is:

Person with SARS-CoV-2 nucleic acid present in a clinical specimen. OR A person who has a positive SARS-CoV-2 antigen in a clinical specimen.

A deceased person with confirmed SARS-CoV-2 infection for the purpose of epidemiological surveillance of the number of deceased persons with confirmed SARS-CoV-2 infection is:

death of a person with a confirmed SARS-CoV-2 infection occurring within 28 days after the date of positive SARS-CoV-2 testing OR death of a person who tested for SARS-CoV-2 positive post-mortem (after death) AND the date of death is recorded in the CRPP.* The last seven days is a period of greater uncertainty about the data of the deceased. The data source of the Infectious Diseases Record under the Health Care Databases Act (ZZPPZ) (Report of Disease-Deaths for Infectious Diseases) has been used for the last seven days, provided that the deceased is not recorded in the Central Patient Data Register (CRPP).

Abstract

The Chókwè Health And Demographic Surveillance System (Chókwè HDSS), is a core research platform of Chókwè Health and Research Centre, affiliated to National Institute of Health, Ministry of Health, Mozambique. The centre is located in Chókwè District, Gaza Province, southern Mozambique., about 230 Km north of the capital Maputo, on the flood plain of the Limpopo River. It was established in June 2010, to provide a platform for implementation and evaluation of clinical trials and health intervention, especially against HIV and related diseases, based on locally generated data.

Chokwe HDSS is a member of the International Network for Demographic Evaluation of the Population and Their Health (INDEPTH), since October 2014. The surveillance area covers an area of approximately 600 square kms within a 25 kms radius of Chokwe City, including 15 (fifteen) villages of which, eight (8) villages are part of Chókwè Municipality (classified as urban) and seven (7) are rural villages namely, Lionde Administrative Post (Lionde Sede, Massavasse, Conhane) and Macarretane (Muzumuia, Matuba, Manjangue and Barragem). The population under surveillance is 97,939 inhabitants (~ 50% of total the district population), in 21,498 households.

The baseline census took place between May and July 2010 and covered all the population of Chókwè City. The census registered 56,727 inhabitants in 12,326 households and each household and individual assigned a unique permanent identification number which enables the follow up of the population. All households are geolocated and enumerated. A resident is defined as any person living in the study area or planning to stay for at least the 3 following months.

Based on recommended INDEPTH methodology for demographic surveillance, monitoring of households and members within households is undertaken in regular 6-month cycles known as 'rounds'. Since its implementation, data collection consists on demographic history including details on birth outcomes (births, still births and abortions), deaths, migration (in-migration and out-migration). The updating of demographic data is done in the three following ways: - Update rounds: In each round, a team of field interviewers and supervisors visit their assigned households to update the demographic data. - Continuous update through community informants: Local leaders report occurring demographic events in their community to the concerned HDSS team.
- Birth and death registrations in health facilities: data collectors are responsible for the daily registration of all births and deaths occurring in the health facilities in the surveillance area.

The data are double entered into a relational database designated Household Registration System (HRS1) implemented in Microsoft Visual FoxPro version 5. Consistence checking and validation are performed and resolved. Verbal autopsy using modified WHO standardized questionnaires, based on physician coded approach has been conducted on all deaths since 2012. Currently, data collection is in the process of migration to electronic data capture and interpretation with InterVA applying the WHO 2012 modified questionnaire.

The Site Leader is Dr Ricardo Thompson.

Geographic coverage

The surveillance area covers an area of approximately 600 square km around Chokwe City (-24.528981, 32.981228), including 15 (fifteen) villages of which, eight (8) villages are part of Chókwè Municipality (classified as urban) and seven (7) are rural villages namely, Lionde Administrative Post (Lionde Sede, Massavasse, Conhane) and Macarretane (Muzumuia, Matuba, Manjangue and Barragem). The population under surveillance is 97,939 inhabitants (~ 50% of total the district population), in 21,498 households.

Analysis unit

Individual

Universe

The population under surveillance is 97,939 inhabitants (~ 50% of total District population), residing in 21498 households. All households and members are assigned a unique identification number (Perm_ID). A member is defined as somebody living in the Demographic Surveillance Area (DSA) for more than three (3) months or intending to remain in the DSA for at least three months.

Kind of data

Event history data

Frequency of data collection

Round (baseline) 1 to Round 2 : once a year Round 3 to 4: twice a year Round 5 : once a year

Sampling procedure

This dataset covers the whole population int he surveillance area.

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

The core HDSS questionnaires are:
1. Household Enumeration and Member Registration Form 2. New Household Form
3. Emigration Registration Form 4. Immigration Registration Form 5. Death Registration Form 6. Pregnancy Registration Form 7. Pregnancy Outcome Registration Form

Response rate

On an average the response rate is 100% over the years for all rounds.

Sampling error estimates

Not Applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate MZ021 MicroDataCleaned Starts 1 137121 137122 0, 2017-05-23 09:56
MZ021 MicroDataCleaned Transitions 0 318278 318278 0, 2017-05-23 09:56
MZ021 MicroDataCleaned Ends 137122 2017-05-23 09:56
MZ021 MicroDataCleaned SexValues 318278 2017-05-23 09:56
MZ021 MicroDataCleaned DoBValues 318278 2017-05-23 09:56

Data is from the California Department of Public Health (CDPH) Respiratory Virus Weekly Report. The report is updated each Friday. Laboratory surveillance data: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week. Laboratory surveillance for influenza, respiratory syncytial virus (RSV), and other respiratory viruses (parainfluenza types 1-4, human metapneumovirus, non-SARS-CoV-2 coronaviruses, adenovirus, enterovirus/rhinovirus) involves the use of data from clinical sentinel laboratories (hospital, academic or private) located throughout California. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for influenza, respiratory syncytial virus, and other respiratory viruses in California. These laboratories report the number of laboratory-confirmed influenza, respiratory syncytial virus, and other respiratory virus detections and isolations, and the total number of specimens tested by virus type on a weekly basis. Test positivity for a given week is calculated by dividing the number of positive COVID-19, influenza, RSV, or other respiratory virus results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday. Hospitalization data: Data on COVID-19 and influenza hospital admissions will be included after the National Healthcare Safety Network (NHSN) Hospitalization Data reporting requirement goes into effect on November 1, 2024. Data will not be available immediately after November 1, 2024, to account for data preparation and quality checks. CDPH collaborates with Northern California Kaiser Permanente (NCKP) to monitor trends in RSV admissions. The percentage of RSV admissions is calculated by dividing the number of RSV-related admissions by the total number of admissions during the same period. Admissions for pregnancy, labor and delivery, birth, and outpatient procedures are not included in total number of admissions. These admissions serve as a proxy for RSV activity and do not necessarily represent laboratory confirmed hospitalizations for RSV infections; NCKP members are not representative of all Californians. Weekly hospitalization data are defined as Sunday through Saturday. Death certificate data: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify influenza, respiratory syncytial virus, and COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all influenza, respiratory syncytial virus, and COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday. Wastewater data: This dataset represents statewide weekly SARS-CoV-2 wastewater summary values. SARS-CoV-2 wastewater concentrations from all sites in California are combined into a single, statewide, unit-less summary value for each week, using a method for data transformation and aggregation developed by the CDC National Wastewater Surveillance System (NWSS). Please see the CDC NWSS data methods page for a description of how these summary values are calculated. Weekly wastewater data are defined as Sunday through Saturday.