Metadata Summary of Directories Directory: 235m-gsry Metadata Found: { "id": "235m-gsry", "name": "Pulmonary evaluation of whole-body inhalation exposure of polycarbonate (PC) filament 3D printer emissions in rats", "assetType": "file", "averageRating": 0, "blobFilename": "rd-1083-2024-0.zip", "blobFileSize": 306191, "blobId": "ab4e1fbc-2da0-474e-b48f-3d342ae43661", "blobMimeType": "application/x-zip-compressed", "category": "National Institute for Occupational Safety and Health", "createdAt": 1731698082, "description": "Additive manufacturing (AM) is a broad manufacturing term that encompasses a range of processes that create objects by adding material through a computer-aided design model. Three-dimensional (3D) printing is a form of AM, which builds objects layer-by-layer deposition of feedstock material using a 3D printer machine and computer software. Fused filament fabrication (FFF, also known as Filament Freeform Fabrication) is one 3D printing process in which filaments are melted and extruded from a heated nozzle to deposit material. FFF is an emerging technology and one of the most popular additive manufacturing processes, especially for consumers and small manufacturers. Polycarbonate (PC) is a versatile material and PC filaments are widely used for fused filament fabrication 3D printing. PC filaments are often loaded with additives to achieve different properties of the print objects. These additives range from dyes, organometallic compounds, carbon nanomaterials, nanometal oxides to micrometer-scale particles such as copper, bronze, steel, tungsten, gold, and aluminum nitride (Vance et al., 2017). Several engineered nanomaterials were infused into PC filaments, such as silicon dioxide nanoparticles, titanium nitride nanoparticles (Vidakis et al., 2021), titanium carbide nanopowder (Vidakis et al., 2022a), aluminum nitride nanoparticles (Vidakis et al., 2022b), and carbon nanotubes (Potter et al., 2021).\n\nDuring heating, PC filament undergoes thermal degradation and releases fine particles (0.1 to 2.5 um) and incidental nanoparticles (d < 100 nm) as well as numerous volatile, and semi-volatile organic compounds that are likely derived from PC polymer and additives in the polymer (Azimi et al., 2016; Byrley et al., 2020; Gu et al., 2019; Stefaniak et al., 2017; Stefaniak et al., 2019; Alijagic et al., 2022; Tedla et al., 2022). These emissions could pose a potential hazard to human health. Currently, the potential health hazard of PC filament printing emissions has not been determined.\n\nA NIOSH research group used a condensation nuclei counter to study PC filament emission rates, and determined that the number-based particle emission rates from an industrial-scale material extrusion AM machine were around 2.2 x1011 number/minute and the total volatile organic compound emission rates were around 1.9 x 104 µg/minute (Stefaniak et al., 2019). The same group also found low levels of acetone, benzene, toluene, and m,p-xylene during PC filament printing processes. Potter et al showed that PC filament emissions contained bisphenol A (BPA), phenol, chlorobenzene, DEHP, and di-tert-butylphenol (Potter et al., 2019). In our previous studies on PC filament printer emission-induced cell toxicity (Farcas et al., 2019), emissions from a commercial PC 3D printer were generated in a chamber using a 3D printer and collected in cell culture medium. The number-based size distribution of the particles inside the chamber was between 140-170 nm and the mean particle sizes in cell culture medium were 201±18 nm. Analysis of elemental composition of particles collected in the cell culture medium found C, O, Ca, Na, Si, Ni, Cr, Fe, S, Al, and Cl. The organic compounds in the emission collection cell culture medium were BPA, p-isopropenylphenol, and phenol. At 24 h post-exposure, PC emissions were internalized in human small airway epithelial cells (SAEC) and induced a dose-dependent cytotoxicity, oxidative stress, apoptosis, necrosis, and increases in pro-inflammatory cytokine and chemokine production in SAEC (Farcas et al., 2019). The results demonstrated that PC filament 3D printing emissions induce a cellular toxicity in SAEC.\n\nAlthough cell-based in vitro toxicity analysis is increasingly applied to screen and rank chemicals for prioritizing toxicity studies, as well as to study toxic mechanisms, the toxicological significance of in vitro study-generated data in hazard and risk assessment is limited. In comparison with animal-based in vivo studies, in vitro cell studies can lack tissue-specific differentiated functions, physiological context with other cells and tissues, and biological concordance in metabolism of xenobiotic chemicals (Blaauboer, 2008).\n\nThis study sought to evaluate PC filament printer emission-induced pulmonary and systemic toxicity in rats. A real-time 3D printer emission generation system was applied to simultaneously use three commercially available 3D PC filament printers to generate PC filament aerosols consisting of a mixture of particles and volatile organic compounds (VOCs) that were delivered to an animal exposure chamber. Male Sprague-Dawley rats were exposed to 3D PC filament emissions in a time-course via whole body inhalation. The rats were exposed to a single concentration (0.529 mg/m3 average, 40 nm mean diameter) of the emissions for 1, 4, 8, 15, and 30 days (4 h/day, 4 days/week), and were sacrificed at 24 h after the last exposure. Bronchoalveolar lavage (BAL) samples were collected to analyze inflammatory, fibrotic, and oxidative stress responses. Lung and nasal tissues underwent histopathological analysis to evaluate the emission-induced tissue damages. Several blood biomarkers were tested for the emission-induced systemic toxicity in rats.", "displayType": "blob", "downloadCount": 29, "hideFromCatalog": false, "hideFromDataJson": false, "locked": false, "newBackend": false, "numberOfComments": 0, "oid": 40957818, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1731698173, "publicationGroup": 19691433, "publicationStage": "published", "rowsUpdatedAt": 1731698082, "tableId": 19691433, "totalTimesRated": 0, "viewCount": 152, "viewLastModified": 1732121070, "viewType": "blobby", "approvals": [ { "reviewedAt": 1731951836, "reviewedAutomatically": true, "state": "approved", "submissionId": 6617126, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1731951836, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "endedAt": 1731951836, "failureCount": 0, "startedAt": 1731951836, "status": "success" }, "submitter": { "id": "6gky-eu6y", "displayName": "kye1" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "metadata": { "custom_fields": { "Common Core": { "Contact Email": "sa-cin-webteam@cdc.gov", "Contact Name": "Pathology and Physiology Branch, Health Effects Laboratory Division", "Program Code": "009:034", "Bureau Code": "009:20" } }, "availableDisplayTypes": [ "table", "fatrow", "page" ] }, "owner": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": {}, "rights": [ "read" ], "tableAuthor": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "flags": [ "default", "ownerMayBeContacted" ] } ----------------------------- Directory: 2389-pvg9 Metadata Found: { "id": "2389-pvg9", "name": "Table of Smokefree Indoor Air for Private Worksites, Restaurants, and Bars (CDC STATE System Tobacco Legislation- Smokefree Indoor Air)", "assetType": "filter", "attribution": "Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health", "attributionLink": "http://www.cdc.gov/STATESystem/", "averageRating": 0, "category": "Legislation", "createdAt": 1425314352, "description": "1995-2024. Centers for Disease Control and Prevention (CDC). State Tobacco Activities Tracking and Evaluation (STATE) System. Legislation – Smokefree Indoor Air for Private Worksites, Restaurants, and Bars (CDC STATE System Tobacco Legislation). The STATE System houses current and historical state-level legislative data on tobacco use prevention and control policies. Data are reported on a quarterly basis. Data include information related to state Smokefree indoor air policies in areas such as: Private Worksites, Restaurants, and Bars.", "displayType": "table", "downloadCount": 539, "hideFromCatalog": false, "hideFromDataJson": false, "licenseId": "ODC_BY", "locked": false, "modifyingViewUid": "32fd-hyzc", "newBackend": true, "numberOfComments": 0, "oid": 40505241, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1711980228, "publicationGroup": 1650228, "publicationStage": "published", "queryString": "SELECT `year`, `quarter`, `locationabbr`, `locationdesc`, `topicdesc`, `measuredesc`, `datasource`, `provisiongroupdesc`, `provisiondesc`, `provisionvalue`, `citation`, `provisionaltvalue`, `datatype`, `comments`, `enacted_date`, `effective_date`, `geolocation`, `displayorder`, `topictypeid`, `topicid`, `measureid`, `provisiongroupid`, `provisionid` WHERE (upper(`measuredesc`) = \"PRIVATE WORKSITES\") or (upper(`measuredesc`) = \"RESTAURANTS\") or (upper(`measuredesc`) = \"BARS\") ORDER BY `year` DESC NULL LAST,`quarter` DESC NULL LAST,`locationdesc` ASC NULL LAST", "rowClass": "", "rowsUpdatedAt": 1736534851, "rowsUpdatedBy": "sn5p-uz6k", "tableId": 19217549, "totalTimesRated": 0, "viewCount": 4267, "viewLastModified": 1738280964, "viewType": "tabular", "approvals": [ { "reviewedAt": 1425314352, "reviewedAutomatically": true, "state": "approved", "submissionId": 6245110, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1425314352, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "failureCount": 0, "status": "success" }, "submitter": { "id": "p5wh-zttj", "displayName": "OSHData" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [ { "id": 591351408, "name": "Year", "dataTypeName": "number", "description": "Year", "fieldName": "year", "position": 1, "renderTypeName": "number", "tableColumnId": 20829899, "width": 55, "format": { "precisionStyle": "standard", "noCommas": "true", "align": "right" } }, { "id": 591351409, "name": "Quarter", "dataTypeName": "number", "description": "Quarter", "fieldName": "quarter", "position": 2, "renderTypeName": "number", "tableColumnId": 20829900, "width": 85, "format": {} }, { "id": 591351410, "name": "LocationAbbr", "dataTypeName": "text", "description": "Location abbreviation", "fieldName": "locationabbr", "position": 3, "renderTypeName": "text", "tableColumnId": 20829901, "width": 105, "format": { "align": "left" } }, { "id": 591351411, "name": "LocationDesc", "dataTypeName": "text", "description": "Location description", "fieldName": "locationdesc", "position": 4, "renderTypeName": "text", "tableColumnId": 20829902, "width": 208, "format": { "align": "left" } }, { "id": 591351412, "name": "TopicDesc", "dataTypeName": "text", "description": "Topic description", "fieldName": "topicdesc", "position": 5, "renderTypeName": "text", "tableColumnId": 20829903, "width": 208, "format": {} }, { "id": 591351413, "name": "MeasureDesc", "dataTypeName": "text", "description": "Measure description", "fieldName": "measuredesc", "position": 6, "renderTypeName": "text", "tableColumnId": 20829904, "width": 232, "format": {} }, { "id": 591351414, "name": "DataSource", "dataTypeName": "text", "description": "Data source", "fieldName": "datasource", "position": 7, "renderTypeName": "text", "tableColumnId": 20829905, "width": 220, "format": {} }, { "id": 591351415, "name": "ProvisionGroupDesc", "dataTypeName": "text", "description": "Provision group description", "fieldName": "provisiongroupdesc", "position": 8, "renderTypeName": "text", "tableColumnId": 20829906, "width": 316, "format": {} }, { "id": 591351416, "name": "ProvisionDesc", "dataTypeName": "text", "description": "Provision description", "fieldName": "provisiondesc", "position": 9, "renderTypeName": "text", "tableColumnId": 20829907, "width": 256, "format": {} }, { "id": 591351417, "name": "ProvisionValue", "dataTypeName": "text", "description": "Provision value", "fieldName": "provisionvalue", "position": 10, "renderTypeName": "text", "tableColumnId": 20829908, "width": 268, "format": {} }, { "id": 591351418, "name": "Citation", "dataTypeName": "text", "description": "Citation details", "fieldName": "citation", "position": 11, "renderTypeName": "text", "tableColumnId": 20829909, "width": 196, "format": {} }, { "id": 591351419, "name": "ProvisionAltValue", "dataTypeName": "number", "description": "Alternate numeric value for non-numeric provision value; 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used in application", "fieldName": "displayorder", "position": 18, "renderTypeName": "number", "tableColumnId": 20829916, "width": 244, "format": {} }, { "id": 591351430, "name": "TopicTypeId", "dataTypeName": "text", "description": "Topic type identifier code - can be used for filtering; used in application", "fieldName": "topictypeid", "position": 19, "renderTypeName": "text", "tableColumnId": 20829917, "width": 232, "format": {} }, { "id": 591351431, "name": "TopicId", "dataTypeName": "text", "description": "Topic identifier code - can be used for filtering; used in application", "fieldName": "topicid", "position": 20, "renderTypeName": "text", "tableColumnId": 20829918, "width": 184, "format": {} }, { "id": 591351432, "name": "MeasureId", "dataTypeName": "text", "description": "Measure identifier code - can be used for filtering; used in application", "fieldName": "measureid", "position": 21, "renderTypeName": "text", "tableColumnId": 20829919, "width": 208, "format": {} }, { "id": 591351433, "name": "ProvisionGroupID", "dataTypeName": "text", "description": "Provision group identifier - can be used for filtering; 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The tobacco disparities dashboard data utilized the Behavioral Risk Factor Surveillance System (BRFSS) data to measure cigarette smoking disparities by sex. The disparity value is the relative difference in the cigarette smoking prevalence among adults 18 and older in a focus group divided by the cigarette smoking prevalence among adults 18 and older in a reference group. A disparity value above 1 indicates that adults in the focus group smoke cigarettes at a higher rate, as reflected by the disparity value, compared with the rate among adults in the reference group who smoke cigarettes. A disparity value below 1 indicates that adults in the focus group smoke cigarettes at a lower rate, as reflected by the disparity value, compared with the rate among adults in the reference group who smoke cigarettes. A disparity value of 1 means there is no relative difference in the rate of adults who smoke cigarettes for the two groups compared.", "displayType": "table", "downloadCount": 46, "hideFromCatalog": false, "hideFromDataJson": false, "licenseId": "ODC_BY", "locked": false, "modifyingViewUid": "jxu8-x79m", "newBackend": true, "numberOfComments": 0, "oid": 40535689, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1713929021, "publicationGroup": 19503383, "publicationStage": "published", "queryString": "SELECT\n `year`,\n `state`,\n `tobacco_use`,\n `demographic`,\n `comparing_focus_group`,\n `cigarette_use_prevalence`,\n `to_reference_group`,\n `cigarette_use_prevalence_1`,\n `disparity_value`\nWHERE caseless_one_of(`demographic`, \"Sex at Birth\")", "rowsUpdatedAt": 1737040214, "rowsUpdatedBy": "7rcq-3w3j", "tableId": 19503383, "totalTimesRated": 0, "viewCount": 254, "viewLastModified": 1737040935, "viewType": "tabular", "approvals": [ { "reviewedAt": 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"Louisiana", "count": "26" }, { "item": "New York", "count": "26" }, { "item": "West Virginia", "count": "26" }, { "item": "South Carolina", "count": "26" }, { "item": "New Jersey", "count": "26" }, { "item": "New Mexico", "count": "26" }, { "item": "Hawaii", "count": "26" }, { "item": "Arkansas", "count": "26" }, { "item": "Missouri", "count": "26" }, { "item": "Connecticut", "count": "26" }, { "item": "South Dakota", "count": "26" }, { "item": "District of Columbia", "count": "26" }, { "item": "Oklahoma", "count": "26" } ], "smallest": "Alabama", "count": "1326", "cardinality": "51" }, "format": {} }, { "id": 591874681, "name": "Tobacco Use", "dataTypeName": "text", "description": "Type of Tobacco Use", "fieldName": "tobacco_use", "position": 3, "renderTypeName": "text", "tableColumnId": 152297146, "cachedContents": { "non_null": "1326", "largest": "Cigarette Use among Adults", "null": "0", "top": [ { "item": "Cigarette Use among Adults", "count": "1326" } ], "smallest": "Cigarette 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Invasive Pneumococcal to Legionellosis", "assetType": "dataset", "attribution": "Division of Health Informatics and Surveillance (DHIS), Centers for Disease Control and Prevention", "averageRating": 0, "category": "NNDSS", "createdAt": 1394400023, "description": "NNDSS - Table II. Invasive Pneumococcal to Legionellosis - 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. 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NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. \n\nFootnotes:\nU: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data.\n-: No reported cases — The reporting jurisdiction did not submit any cases to CDC.\nN: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction.\nNN: Not nationally notifiable — This condition was not designated as being nationally notifiable.\nNP: Nationally notifiable but not published.\nNC: Not calculated — There is insufficient data available to support the calculation of this statistic.\nCum: Cumulative year-to-date counts.\nMax: Maximum — Maximum case count during the previous 52 weeks.\n* Case counts for reporting years 2019 and 2020 are provisional and subject to change. 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A concern with FFRs with an exhalation valve is that individuals may spread disease if unfiltered, virus-laden aerosols pass through the valve.\n\nDuring the COVID-19 pandemic, guidance from the Centers for Disease Control and Prevention (CDC) did not recommend using an FFR with an exhalation valve for source control (i.e., to filter respiratory secretions to prevent disease transmission to others) and advised that if only this option isavailable and source control was needed, then the valve should be covered with a surgical mask, procedure mask, or a cloth face covering that does not interfere with the respirator fit. The CDC requested research to provide improved science-based recommendations on the use of exhalation valves.\n\nThis study had three aims: (1) to measure the filtration efficiency provided by FFRs with an exhalation valve under conditions of inward airflow (i.e., in the direction of inhalation) and outward airflow (i.e., in the direction of exhalation); (2) to evaluate how particle penetration in FFRs with an exhalation valve compares to particle penetration in surgical masks, procedure masks, cloth face coverings, and fabric from cotton t-shirts; and (3) to determine the filtration efficiency of three modifications to the exhalation valve in FFRs with the goal of mitigating the emission of unfiltered particles. To accomplish these three aims, thirteen FFR models were each tested in two positions: inward position, which is used by the NIOSH Respirator Approval Program when testing N-type respirators, and outward position, which was used experimentally to channel airflow in the direction of exhalation. For the inward position, three mitigation strategies were used:\n(1)covering the valve on the interior of the FFR with commonly available surgical tape,\n(2)covering the valve on the interior of the FFR with an electrocardiogram (ECG) pad; and\n(3)stretching a surgical mask over the exterior of the FFR.\n\nThe purpose of these three strategies was to measure the varying filtration efficiencies to determine their contribution toward source control. Both positions and all mitigation strategies were tested at three airflow rates: 25, 55, and 85 lpm (liters per minute). 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All four datasets may be linked by “ClinicID.” ClinicID is a unique identifier for each clinic that reported cycles. The Summary dataset provides a full snapshot of clinic services and profile, patient characteristics, and ART success rates. It is worth noting that patient medical characteristics, such as age, diagnosis, and ovarian reserve, affect ART treatment’s success. Comparison of success rates across clinics may not be meaningful because of differences in patient populations and ART treatment methods. The success rates displayed in this dataset do not reflect any one patient’s chance of success. 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Respondents who answered affirmatively were asked if they had been told they had hypertension (or high blood pressure) during the past 12 months. Respondents who ever had hypertension were also asked if they were taking prescribed medication for high blood pressure. Respondents had to have been taking those medications or had hypertension or high blood pressure during the past 12 months to be classified as having diagnosed hypertension.", "count": "380" } ], "smallest": "A person was defined as uninsured if he or she did not have any private health insurance, Medicare, Medicaid, Children’s Health Insurance Program (CHIP), state-sponsored or other government-sponsored health plan, or military plan. 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At this time, the dataset does not include data reported through the MakeMyTestCount website. All fields are self-reported by the user voluntarily reporting the test result. This dataset will be updated monthly.\n\nPlease note that there are limitations with these data, including:\n1.\tData are not comprehensive of all self-tests performed. Data represent results voluntarily reported by an individual via manufacturer-provided website or companion mobile applications. Not all self-test manufacturers are currently capturing and sending data to CDC. Similarly, these data do not include self-test results that were reported to state and local health departments if they were not also reported through the manufacturer-provided website or companion mobile applications. The true denominator (number of tests completed) cannot be ascertained, but based on manufacturer production numbers, this dataset reflects a small fraction of the number of self-tests used. \n\n2.\tData are not verified. The quality of specimen, appropriate execution of self-test, result produced, and person tested are unverified; therefore, reported interpretation of results cannot be confirmed. All results and accompanying demographic information are also self-reported and cannot be verified. \n\n3.\tData reports are not complete. Manufacturer-provided websites and companion mobile applications vary widely in terms of the data elements collected. Not all data elements are required, and many results are missing demographic information. \n\n4.\tData are not representative. Based on the limited number of self-reported test results, this dataset is not representative of the use of self-testing by demographic, nor is the dataset inclusive of all self-testing completed within each jurisdiction. This dataset represents a small proportion of overall COVID-19 testing conducted in each jurisdiction and reported volumes are much lower than testing conducted in point of care and laboratory settings. \n\n5.\tData represent individual test results, not persons tested. Data in this dataset are not linkable and do not allow for analyses around serial testing. Data also cannot be disaggregated to identify multiple reports by the same individual. \n\nAll analyses should be completed with these limitations in mind.\n\nFor more information about the challenges and opportunities around self-test data, please refer to the following article: Ritchey MD, Rosenblum HG, Del Guercio K, et al. COVID-19 Self-Test Data: Challenges and Opportunities — United States, October 31, 2021–June 11, 2022. MMWR Morb Mortal Wkly Rep 2022;71:1005–1010. 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Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. \r\n\r\nFootnotes: \r\nU: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data.\r\n-: No reported cases — The reporting jurisdiction did not submit any cases to CDC.\r\nN: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction.\r\nNN: Not nationally notifiable — This condition was not designated as being nationally notifiable.\r\nNP: Nationally notifiable but not published — CDC does not have data because of changes in how conditions are categorized.\r\nCum: Cumulative year-to-date counts.\r\n Max: Maximum — Maximum case count during the previous 52 weeks.\r\n* Case counts for reporting years 2018 and 2019 are provisional and subject to change. 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This identifier is consistent over time, such that the same plant retains the same ID regardless of the addition or subtraction of other plants from the data set.", "fieldName": "wwtp_id", "position": 2, "renderTypeName": "text", "tableColumnId": 140506782, "cachedContents": { "non_null": "986670", "largest": "999", "null": "0", "top": [ { "item": "891", "count": "11528" }, { "item": "363", "count": "8045" }, { "item": "889", "count": "4418" }, { "item": "890", "count": "4418" }, { "item": "1125", "count": "4040" }, { "item": "675", "count": "3599" }, { "item": "1212", "count": "3582" }, { "item": "1040", "count": "3388" }, { "item": "1090", "count": "3171" }, { "item": "1096", "count": "3161" }, { "item": "635", "count": "2767" }, { "item": "1048", "count": "2044" }, { "item": "1631", "count": "1664" }, { "item": "259", "count": "1660" }, { "item": "269", "count": "1659" }, { "item": "268", "count": "1659" }, { "item": "267", "count": "1659" }, { "item": "266", "count": "1659" }, { "item": "265", "count": "1659" }, { "item": "195", "count": "1659" } ], "smallest": "1", "count": "986670", "cardinality": "1347" }, "format": {} }, { "id": 558578731, "name": "reporting_jurisdiction", "dataTypeName": "text", "description": "The CDC Epidemiology and Laboratory Capacity (ELC) jurisdiction, most frequently a state, reporting these data (2-letter abbreviation)", "fieldName": "reporting_jurisdiction", "position": 3, "renderTypeName": "text", "tableColumnId": 140506783, "cachedContents": { "non_null": "986670", "largest": "Wyoming", "null": "0", "top": [ { "item": "New York", "count": "135168" }, { "item": "Michigan", "count": "91031" }, { "item": "Illinois", "count": "75427" }, { "item": "Missouri", "count": "74857" }, { "item": "California", "count": "58941" }, { "item": "Oregon", "count": "50377" }, { "item": "Wisconsin", "count": "38046" }, { "item": "Ohio", "count": "36388" }, { "item": "Minnesota", "count": "33400" }, { "item": "Louisiana", "count": "29887" }, { "item": "West Virginia", "count": "26679" }, { "item": "Virginia", "count": "23522" }, { "item": "North Carolina", "count": "22757" }, { "item": "Oklahoma", "count": "20233" }, { "item": "Washington", "count": "20210" }, { "item": "Texas", "count": "17899" }, { "item": "Georgia", "count": "17754" }, { "item": "Florida", "count": "17536" }, { "item": "Indiana", "count": "17462" }, { "item": "New Jersey", "count": "16779" } ], "smallest": "Alabama", "count": "986670", "cardinality": "54" }, "format": {} }, { "id": 558578732, "name": "sample_location", "dataTypeName": "text", "description": "Sample collection location in the wastewater system, whether at a wastewater treatment plant (or other community level treatment infrastructure such as community-scale septic) or upstream in the wastewater system.", "fieldName": "sample_location", "position": 4, "renderTypeName": "text", "tableColumnId": 140506784, "cachedContents": { "non_null": "986670", "largest": "Treatment plant", "null": "0", "top": [ { "item": "Treatment plant", "count": "940971" }, { "item": "Before treatment plant", "count": "45699" } ], "smallest": "Before treatment plant", "count": "986670", "cardinality": "2" }, "format": {} }, { "id": 558578733, "name": "sample_location_specify", "dataTypeName": "text", "description": "A unique identifier for \"upstream\" sample locations. Specifically, when 'sample_location' is \"upstream\", this field has a non-empty value, which provides a unique, but anonymous identifier for the upstream sample collection sites. This identifier is consistent over time, such that the same sample collection site retains the same ID regardless of the addition or subtraction of other sample collection sites from the data set.", "fieldName": "sample_location_specify", "position": 5, "renderTypeName": "text", "tableColumnId": 140506785, "cachedContents": { "non_null": "48301", "largest": "99", "null": "938369", "top": [ { "item": "82", "count": "1446" }, { "item": "90", "count": "1224" }, { "item": "89", "count": "1106" }, { "item": "16", "count": "1069" }, { "item": "17", "count": "1069" }, { "item": "19", "count": "1069" }, { "item": "229", "count": "1057" }, { "item": "227", "count": "1057" }, { "item": "75", "count": "1049" }, { "item": "80", "count": "1049" }, { "item": "79", "count": "1049" }, { "item": "78", "count": "1049" }, { "item": "77", "count": "1049" }, { "item": "76", "count": "1049" }, { "item": "141", "count": "1029" }, { "item": "142", "count": "1029" }, { "item": "113", "count": "1029" }, { "item": "147", "count": "1029" }, { "item": "145", "count": "1029" }, { "item": "114", "count": "1029" } ], "smallest": "113", "count": "986670", "cardinality": "67" }, "format": {} }, { "id": 558578734, "name": "key_plot_id", "dataTypeName": "text", "description": "A unique identifier for the geographic area served by this sampling site, called a sewershed. This is an underscore-separated concatenation of the fields 'wwtp_jurisdiction', 'wwtp_id', and, if 'sample_location' is \"upstream\", then also 'sample_location_specify', and sample_matrix.", "fieldName": "key_plot_id", "position": 6, "renderTypeName": "text", "tableColumnId": 140506786, "cachedContents": { "non_null": "986670", "largest": "WWS_wv_2604_Treatment plant_primary sludge", "null": "0", "top": [ { "item": "NWSS_mo_259_Treatment plant_raw wastewater", "count": "1660" }, { "item": "NWSS_mo_386_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_230_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_270_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_240_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_381_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_267_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_191_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_266_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_195_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_119_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_192_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_268_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_365_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_269_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_264_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_380_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_190_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_265_Treatment plant_raw wastewater", "count": "1659" }, { "item": "NWSS_mo_423_Treatment plant_raw wastewater", "count": "1659" } ], "smallest": "CDC_VERILY_ak_1490_Treatment plant_raw wastewater", "count": "986670", "cardinality": "1422" }, "format": {} }, { "id": 558578735, "name": "county_names", "dataTypeName": "text", "description": "The county and county-equivalent names corresponding to the FIPS codes in 'county_fips'", "fieldName": "county_names", "position": 7, "renderTypeName": "text", "tableColumnId": 140506787, "cachedContents": { "non_null": "986670", "largest": "Yuma", "null": "0", "top": [ { "item": "Orange", "count": "16924" }, { "item": "Jefferson", "count": "15840" }, { "item": "Washington", "count": "15607" }, { "item": "Ottawa", "count": "15079" }, { "item": "Cook", "count": "14489" }, { "item": "Kalamazoo", "count": "11528" }, { "item": "Marion", "count": "9834" }, { "item": "Du Page", "count": "9471" }, { "item": "Jackson", "count": "9328" }, { "item": "Kent", "count": "9034" }, { "item": "Fulton", "count": "8841" }, { "item": "Onondaga", "count": "7407" }, { "item": "Erie", "count": "7344" }, { "item": "Madison", "count": "7338" }, { "item": "Franklin", "count": "7102" }, { "item": "Johnson", "count": "6907" }, { "item": "Suffolk", "count": "6852" }, { "item": "Montgomery", "count": "6798" }, { "item": "Livingston", "count": "6419" }, { "item": "Lake", "count": "6335" } ], "smallest": "Acadia", "count": "986670", "cardinality": "655" }, "format": {} }, { "id": 558578736, "name": "county_fips", "dataTypeName": "text", "description": "5-digit numeric FIPS codes of all counties and county equivalents served by this sampling site (i.e., served by this wastewater treatment plant or, if 'sample_location' is \"upstream\", then by this upstream location). Note that multiple sampling sites or treatment plants may serve a single county, and that a single sampling site or treatment plant may serve multiple counties. Counties listed may be entirely or only partly served by this sampling site.", "fieldName": "county_fips", "position": 8, "renderTypeName": "text", "tableColumnId": 140506788, "cachedContents": { "non_null": "986670", "largest": "56039", "null": "0", "top": [ { "item": "26139", "count": "14588" }, { "item": "17031", "count": "14489" }, { "item": "26077", "count": "11528" }, { "item": "36071", "count": "9532" }, { "item": "17043", "count": "9471" }, { "item": "26081", "count": "8215" }, { "item": "36067", "count": "7407" }, { "item": "36103", "count": "6852" }, { "item": "36029", "count": "6734" }, { "item": "41067", "count": "6404" }, { "item": "04027", "count": "6302" }, { "item": "12095", "count": "6281" }, { "item": "13121", "count": "6194" }, { "item": "36119", "count": "6132" }, { "item": "41047", "count": "6021" }, { "item": "36087", "count": "5731" }, { "item": "04013", "count": "5500" }, { "item": "06075", "count": "5245" }, { "item": "36059", "count": "5020" }, { "item": "29189", "count": "4977" } ], "smallest": "01005", "count": "986670", "cardinality": "830" }, "format": {} }, { "id": 558578737, "name": "population_served", "dataTypeName": "text", "description": "Estimated number of persons served by this sampling site (i.e., served by this wastewater treatment plant or, if 'sample_location' is \"upstream\", then by this upstream location).", "fieldName": "population_served", "position": 9, "renderTypeName": "text", "tableColumnId": 140506789, "cachedContents": { "non_null": "986670", "largest": "9975", "null": "0", "top": [ { "item": "12000", "count": "11117" }, { "item": "50000", "count": "9498" }, { "item": "40000", "count": "8254" }, { "item": "25000", "count": "8239" }, { "item": "15000", "count": "8165" }, { "item": "30000", "count": "8146" }, { "item": "60000", "count": "7921" }, { "item": "90000", "count": "7779" }, { "item": "20000", "count": "7435" }, { "item": "7000", "count": "6246" }, { "item": "10000", "count": "6234" }, { "item": "70000", "count": "5953" }, { "item": "8000", "count": "5575" }, { "item": "120000", "count": "5490" }, { "item": "45000", "count": "5341" }, { "item": "3500", "count": "5233" }, { "item": "16000", "count": "5123" }, { "item": "100000", "count": "4932" }, { "item": "300000", "count": "4766" }, { "item": "5000", "count": "4465" } ], "smallest": "1000", "count": "986670", "cardinality": "1003" }, "format": {} }, { "id": 558578738, "name": "date_start", "dataTypeName": "text", "description": "The start date of the interval over which the metric is calculated. Intervals are inclusive of start and end dates.", "fieldName": "date_start", "position": 10, "renderTypeName": "text", "tableColumnId": 140506790, "cachedContents": { "non_null": "986670", "largest": "2025-01-05", "null": "0", "top": [ { "item": "2024-12-31", "count": "1422" }, { "item": "2025-01-01", "count": "1422" }, { "item": "2024-12-25", "count": "1421" }, { "item": "2025-01-05", "count": "1421" }, { "item": "2024-12-27", "count": "1421" }, { "item": "2024-12-26", "count": "1421" }, { "item": "2025-01-02", "count": "1421" }, { "item": "2024-12-28", "count": "1421" }, { "item": "2024-12-30", "count": "1421" }, { "item": "2025-01-04", "count": "1421" }, { "item": "2025-01-03", "count": "1421" }, { "item": "2024-12-29", "count": "1421" }, { "item": "2024-12-24", "count": "1421" }, { "item": "2024-12-22", "count": "1420" }, { "item": "2024-12-23", "count": "1420" }, { "item": "2024-12-13", "count": "1419" }, { "item": "2024-12-19", "count": "1419" }, { "item": "2024-12-11", "count": "1419" }, { "item": "2024-12-18", "count": "1419" }, { "item": "2024-12-20", "count": "1419" } ], "smallest": "2020-06-21", "count": "986670", "cardinality": "1660" }, "format": {} }, { "id": 558578739, "name": "date_end", "dataTypeName": "text", "description": "The end date of the interval over which metric is calculated. Intervals are inclusive of start and end dates.", "fieldName": "date_end", "position": 11, "renderTypeName": "text", "tableColumnId": 140506791, "cachedContents": { "non_null": "986670", "largest": "2025-01-19", "null": "0", "top": [ { "item": "2025-01-15", "count": "1422" }, { "item": "2025-01-14", "count": "1422" }, { "item": "2025-01-18", "count": "1421" }, { "item": "2025-01-17", "count": "1421" }, { "item": "2025-01-16", "count": "1421" }, { "item": "2025-01-13", "count": "1421" }, { "item": "2025-01-12", "count": "1421" }, { "item": "2025-01-11", "count": "1421" }, { "item": "2025-01-10", "count": "1421" }, { "item": "2025-01-09", "count": "1421" }, { "item": "2025-01-07", "count": "1421" }, { "item": "2025-01-08", "count": "1421" }, { "item": "2025-01-19", "count": "1421" }, { "item": "2025-01-06", "count": "1420" }, { "item": "2025-01-05", "count": "1420" }, { "item": "2024-12-25", "count": "1419" }, { "item": "2025-01-04", "count": "1419" }, { "item": "2025-01-03", "count": "1419" }, { "item": "2025-01-02", "count": "1419" }, { "item": "2025-01-01", "count": "1419" } ], "smallest": "2020-07-05", "count": "986670", "cardinality": "1660" }, "format": {} }, { "id": 558578740, "name": "ptc_15d", "dataTypeName": "text", "description": "The percent change in SARS-CoV-2 RNA levels over the 15-day interval defined by 'date_start' and 'date_end'. Percent change is calculated as the modeled change over the interval, based on linear regression of log-transformed SARS-CoV-2 levels. SARS-CoV-2 RNA levels are wastewater concentrations that have been normalized for wastewater composition. ", "fieldName": "ptc_15d", "position": 12, "renderTypeName": "text", "tableColumnId": 140506792, "cachedContents": { "non_null": "902314", "largest": "9999", "null": "84356", "top": [ { "item": "-100", "count": "20189" }, { "item": "0", "count": "17506" }, { "item": "-99", "count": "11163" }, { "item": "-98", "count": "7803" }, { "item": "-5", "count": "7191" }, { "item": "-2", "count": "7124" }, { "item": "-4", "count": "7116" }, { "item": "-1", "count": "7079" }, { "item": "1", "count": "6988" }, { "item": "-6", "count": "6906" }, { "item": "-3", "count": "6903" }, { "item": "3", "count": "6884" }, { "item": "2", "count": "6559" }, { "item": "-97", "count": "6518" }, { "item": "-7", "count": "6484" }, { "item": "4", "count": "6318" }, { "item": "-8", "count": "6272" }, { "item": "5", "count": "6246" }, { "item": "-9", "count": "6245" }, { "item": "6", "count": "6160" } ], "smallest": "0", "count": "986670", "cardinality": "12937" }, "format": {} }, { "id": 558578741, "name": "detect_prop_15d", "dataTypeName": "text", "description": "The proportion of tests with SARS-CoV-2 detected, meaning a cycle threshold (Ct) value <40 for RT-qPCR or at least 3 positive droplets/partitions for RT-ddPCR, by sewershed over the 15-day window defined by 'date_start' and \"date_end'. The detection proportion is the percent calculated by dividing the 15-day rolling sum of SARS-CoV-2 detections by the 15-day rolling sum of the number of tests for each sewershed and multiplying by 100.", "fieldName": "detect_prop_15d", "position": 13, "renderTypeName": "text", "tableColumnId": 140506793, "cachedContents": { "non_null": "936484", "largest": "93", "null": "50186", "top": [ { "item": "100", "count": "674898" }, { "item": "0", "count": "79081" }, { "item": "50", "count": "60580" }, { "item": "75", "count": "34854" }, { "item": "25", "count": "18768" }, { "item": "67", "count": "16408" }, { "item": "80", "count": "12441" }, { "item": "33", "count": "9802" }, { "item": "60", "count": "7284" }, { "item": "40", "count": "5978" }, { "item": "20", "count": "5530" }, { "item": "83", "count": "2885" }, { "item": "86", "count": "1833" }, { "item": "71", "count": "619" }, { "item": "93", "count": "466" }, { "item": "89", "count": "393" }, { "item": "88", "count": "385" }, { "item": "92", "count": "371" }, { "item": "91", "count": "335" }, { "item": "57", "count": "324" } ], "smallest": "0", "count": "986670", "cardinality": "63" }, "format": {} }, { "id": 558578743, "name": "percentile", "dataTypeName": "text", "description": "This metric shows whether SARS-CoV-2 virus levels at a site are currently higher or lower than past historical levels at the same site. 0% means levels are the lowest they have been at the site; 100% means levels are the highest they have been at the site. Public health officials watch for increasing levels of the virus in wastewater over time and use this data to help make public health decisions. ", "fieldName": "percentile", "position": 14, "renderTypeName": "text", "tableColumnId": 141710329, "cachedContents": { "non_null": "905897", "largest": "999.0", "null": "80773", "top": [ { "item": "0.0", "count": "3772" }, { "item": "50.0", "count": "3534" }, { "item": "55.0", "count": "3258" }, { "item": "44.0", "count": "3228" }, { "item": "42.0", "count": "3162" }, { "item": "45.0", "count": "3145" }, { "item": "69.0", "count": "3120" }, { "item": "48.0", "count": "3117" }, { "item": "59.0", "count": "3117" }, { "item": "58.0", "count": "3067" }, { "item": "52.0", "count": "3066" }, { "item": "43.0", "count": "3059" }, { "item": "36.0", "count": "3052" }, { "item": "30.0", "count": "3031" }, { "item": "57.0", "count": "3011" }, { "item": "68.0", "count": "3009" }, { "item": "46.0", "count": "3002" }, { "item": "62.0", "count": "2995" }, { "item": "47.0", "count": "2992" }, { "item": "38.0", "count": "2960" } ], "smallest": "0.0", "count": "986670", "cardinality": "5936" }, "format": {} }, { "id": 558578744, "name": "sampling_prior", "dataTypeName": "text", "description": "Indicates whether the site was collecting wastewater samples before or on December 1, 2021.", "fieldName": "sampling_prior", "position": 15, "renderTypeName": "text", "tableColumnId": 141710330, "cachedContents": { "non_null": "986670", "largest": "yes", "null": "0", "top": [ { "item": "no", "count": "794322" }, { "item": "yes", "count": "192348" } ], "smallest": "no", "count": "986670", "cardinality": "2" }, "format": {} }, { "id": 558578745, "name": "first_sample_date", "dataTypeName": "text", "description": "The first date samples were collected at a site.", "fieldName": "first_sample_date", "position": 16, "renderTypeName": "text", "tableColumnId": 141710331, "cachedContents": { "non_null": "986670", "largest": "2025-01-14", "null": "0", "top": [ { "item": "2020-07-06", "count": "38157" }, { "item": "2022-02-14", "count": "29988" }, { "item": "2023-09-17", "count": "29460" }, { "item": "2022-01-31", "count": "20615" }, { "item": "2023-04-10", "count": "18879" }, { "item": "2022-04-11", "count": "17255" }, { "item": "2022-04-12", "count": "15210" }, { "item": "2022-08-08", "count": "15169" }, { "item": "2021-10-14", "count": "14328" }, { "item": "2022-02-15", "count": "11770" }, { "item": "2023-03-07", "count": "9590" }, { "item": "2022-04-19", "count": "9063" }, { "item": "2022-01-27", "count": "8712" }, { "item": "2022-02-10", "count": "8600" }, { "item": "2020-07-07", "count": "8290" }, { "item": "2020-09-02", "count": "8005" }, { "item": "2023-09-18", "count": "7840" }, { "item": "2022-02-13", "count": "7504" }, { "item": "2022-03-08", "count": "7343" }, { "item": "2022-08-28", "count": "7008" } ], "smallest": "2020-07-05", "count": "986670", "cardinality": "507" }, "format": {} } ], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "metadata": { "custom_fields": { "Data Quality": { "Geographic Unit of Analysis": "Sampling 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Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. 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Centers for Disease Control and Prevention (CDC). State Tobacco Activities Tracking and Evaluation (STATE) System. Funding Data, Appropriations (1991-2016) and Expenditures (2008-2016). Appropriations data show public funds allocated to/by a particular state for tobacco prevention and control. They are not necessarily expended. Appropriations are from four major funding sources, Federal, state, Robert Wood Johnson Foundation (RWJF), and the American Legacy Foundation (Legacy). Expenditures are amounts spent by state tobacco control programs on tobacco prevention and control. Expenditure data are available by CDC Best Practices Program Components (State and Community Interventions, Health Communication Interventions, Cessation Interventions, Surveillance and Evaluation, and Administration and Management). Expenditures from 2008 to 2014 are compared against 2007 CDC Best Practices Recommendations; expenditures from 2015 and forward are compared against 2014 CDC Best Practices Recommendations.", "displayType": "table", "downloadCount": 435, "hideFromCatalog": false, "hideFromDataJson": false, "licenseId": "ODC_BY", "locked": false, "modifyingViewUid": "vw7y-v3uk", "newBackend": true, "numberOfComments": 0, "oid": 39772308, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1597324705, "publicationGroup": 1698043, "publicationStage": "published", "queryString": "SELECT `year`, `locationabbr`, `locationdesc`, `topicdesc`, `measuredesc`, `source`, `datasource`, `data_value_unit`, `data_value`, `geolocation` WHERE (`year` = 2016) and (upper(`measuredesc`) = \"EXPENDITURES\") and (contains(upper(`source`), \"TOTAL EXPENDITURES\")) ORDER BY `locationdesc` ASC NULL LAST", "rowsUpdatedAt": 1538559413, "tableId": 19214714, "totalTimesRated": 0, "viewCount": 995, 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"width": 232, "format": {} } ], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "license": { "name": "Open Data Commons Attribution License", "termsLink": "http://opendatacommons.org/licenses/by/1.0/" }, "metadata": { "rdfSubject": "0", "custom_fields": { "Common Core": { "Contact Email": "nccdoshinquiries@cdc.gov", "Contact Name": "OSHData Support", "Program Code": "009:020", "Publisher": "Centers for Disease Control and Prevention", "Bureau Code": "009:20", "Public Access Level": "Public Domain" } }, "availableDisplayTypes": [ "table", "fatrow", "page" ], "renderTypeConfig": { "visible": { "table": true } } }, "owner": { "id": "fjjr-gap9", "displayName": "CDC UserSA", "screenName": "CDC UserSA", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": {}, "rights": [ "read" ], "tableAuthor": { "id": "fjjr-gap9", "displayName": "CDC UserSA", "screenName": "CDC UserSA", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "tags": [ "tobacco", "osh", "state system", "interactive map", "funding", "expenditures" ], "flags": [ "calculatedView", "ownerMayBeContacted", "restorable", "restorePossibleForType", "soqlBasedView" ] } ----------------------------- Directory: 2juy-3evq Metadata Found: { "id": "2juy-3evq", "name": "Release of Crystalline Silica Nanoparticles During Engineered Stone Fabrication", "assetType": "file", "averageRating": 0, "blobFilename": "RD-1106-2024-0.zip", "blobFileSize": 468969, "blobId": "bf752833-600e-488c-84c6-10780b199830", "blobMimeType": "application/x-zip-compressed", "category": "National Institute for Occupational Safety and Health", "createdAt": 1735316899, "description": "Inhalation exposure to respirable crystalline silica (RCS) during fabrication of engineered stone-based kitchen countertops has been on the rise in recent years and has become a significant occupational health problem in the United States and globally. Little is known about the presence of nano-crystalline silica (NCS), i.e., particles below 100 nm. We present a methodology to quantify the crystalline silica content in the sub-100 nm size fraction of the aerosol released during engineered stone fabrication using X-ray diffraction (XRD) and Fourier transform Infrared (FT-IR) spectroscopy. Aerosol was generated in test chamber designed per EN 1093-3 and sampled using cascade impactors. XRD and FT-IR analysis showed the presence of both α-quartz (15 – 60 %) and cristobalite (10 – 50 %) polymorphs in all size fractions. With increasing particle size, the cristobalite content increased. 70 % of the total aerosol mass in the sub-100 nm fraction was found to be crystalline silica, qualitatively confirmed by electron diffraction and electron energy loss spectroscopy. Presence of other minerals was detected in all size fractions; no polymeric resin binder was detected in the sub-100 nm fraction. Although, the sub-100 nm fraction was about 1 % of the aerosol mass, it accounted for 4 – 24 % of the aerosol surface area based on total lung deposition. If the surface area is a more relevant exposure metric, the assessment of efficacy of current engineering control systems using mass as an exposure metric may not provide adequate protection.", "displayType": "blob", "downloadCount": 14, "hideFromCatalog": false, "hideFromDataJson": false, "locked": false, "newBackend": false, "numberOfComments": 0, "oid": 41024594, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1735316994, "publicationGroup": 19722778, "publicationStage": "published", "rowsUpdatedAt": 1735316899, "tableId": 19722778, "totalTimesRated": 0, "viewCount": 78, "viewLastModified": 1735935511, "viewType": "blobby", "approvals": [ { "reviewedAt": 1735316994, "reviewedAutomatically": true, "state": "approved", "submissionId": 6663645, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1735316994, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "endedAt": 1735316994, "failureCount": 0, "startedAt": 1735316994, "status": "success" }, "submitter": { "id": "6gky-eu6y", "displayName": "kye1" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "metadata": { "custom_fields": { "Common Core": { "Contact Email": "sa-cin-webteam@cdc.gov", "Contact Name": "Health Effects Laboratory Division (HELD), National Institute for Occupational Safety and Health (NIOSH)", "Program Code": "009:034", "Bureau Code": "009:20" } }, "availableDisplayTypes": [ "table", "fatrow", "page" ] }, "owner": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": {}, "rights": [ "read" ], "tableAuthor": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "flags": [ "default", "ownerMayBeContacted" ] } ----------------------------- Directory: 2kh7-g39q Metadata Found: { "id": "2kh7-g39q", "name": "Exposure to emissions generated by 3-dimensional printing with polycarbonate affects vascular morphology and expression of markers of oxidative stress and vascular dysfunction in cardiac tissue", "assetType": "file", "averageRating": 0, "blobFilename": "rd-1085-2024-0.zip", "blobFileSize": 310442, "blobId": "cc9b238d-b3e8-448f-8cfb-755caeb78a23", "blobMimeType": "application/x-zip-compressed", "category": "National Institute for Occupational Safety and Health", "createdAt": 1731698299, "description": "Three-dimensional (3D) printing is increasingly being used in manufacturing settings, homes and schools. Fused deposition modeling (FDM) 3D printers are the most widely used systems with standard thermoplastics such as acrylonitrile butadiene styrene (ABS), polylactic acid and polycarbonate (PC) commonly used in the manufacturing processes. Heating of the thermoplastic generates and releases particulates and fumes. Emission constituents frequently measured include aldehydes, benzene, toluene, ethylbenzene, and xylenes. Inhalation of the emitted particulates and/or the fumes, that contain bisphenol A (BPA) may pose health problems to users of these systems as well as bystanders.\n\nThe goal of the current study was to examine the effects of inhalation of PC-emissions generated during 3D-printing. PC-emissions can include bisphenol A (BPA). Bisphenols are known endocrine and metabolic disruptors (i.e., they interfere with actions of steroid and thyroid hormones) and have been shown to have significant effects on a number of physiological systems including the endocrine and cardiovascular systems. Because steroid hormones have major effects on cardiovascular function, it is possible that inhalation of PC particulate and/or BPA impact cardiovascular function.\n\nTo begin to understand how inhalation of PC-emissions generated during 3D printing might affect the cardiovascular system, the current study examined the effects of inhaling PC-emissions after 1, 4, 8, 15 and 30d of exposure, on peripheral vascular responses to vaso-modulating agents, on cardiac morphology and on the expression of proteins and transcripts that are markers of inflammation, oxidative stress and cardiovascular dysfunction.", "displayType": "blob", "downloadCount": 28, "hideFromCatalog": false, "hideFromDataJson": false, "locked": false, "newBackend": false, "numberOfComments": 0, "oid": 40957820, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1731698363, "publicationGroup": 19691435, "publicationStage": "published", "rowsUpdatedAt": 1731698299, "tableId": 19691435, "totalTimesRated": 0, "viewCount": 169, "viewLastModified": 1732120888, "viewType": "blobby", "approvals": [ { "reviewedAt": 1731951850, "reviewedAutomatically": true, "state": "approved", "submissionId": 6617128, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1731951850, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "endedAt": 1731951850, "failureCount": 0, "startedAt": 1731951850, "status": "success" }, "submitter": { "id": "6gky-eu6y", "displayName": "kye1" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "metadata": { "custom_fields": { "Common Core": { "Contact Email": "sa-cin-webteam@cdc.gov", "Contact Name": "Physical Effects Research Branch (PERB), Health Effects Laboratory Division (HELD)", "Program Code": "009:034", "Bureau Code": "009:20" } }, "availableDisplayTypes": [ "table", "fatrow", "page" ] }, "owner": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": {}, "rights": [ "read" ], "tableAuthor": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "flags": [ "default", "ownerMayBeContacted" ] } ----------------------------- Directory: 2khz-k7sv Metadata Found: { "id": "2khz-k7sv", "name": "NNDSS - TABLE 1DD. Rubella to Rubella, congenital syndrome", "assetType": "dataset", "attribution": "Division of Health Informatics and Surveillance (DHIS), Centers for Disease Control and Prevention", "averageRating": 0, "category": "NNDSS", "createdAt": 1554142564, "description": "NNDSS - TABLE 1DD. Rubella to Rubella, congenital syndrome - 2019. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents. \r\n\r\nNote: \r\nThis table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. \r\n\r\nFootnotes:\r\nU: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data.\r\n-: No reported cases — The reporting jurisdiction did not submit any cases to CDC.\r\nN: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction.\r\nNN: Not nationally notifiable — This condition was not designated as being nationally notifiable.\r\nNP: Nationally notifiable but not published — CDC does not have data because of changes in how conditions are categorized.\r\nCum: Cumulative year-to-date counts.\r\nMax: Maximum — Maximum case count during the previous 52 weeks.\r\n* Case counts for reporting years 2018 and 2019 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the US, a US territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-US Residents' category. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. \r\n† 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).", "displayType": "table", "downloadCount": 4896, "hideFromCatalog": false, "hideFromDataJson": false, "indexUpdatedAt": 1567104317, "locked": false, "newBackend": true, "numberOfComments": 0, "oid": 31345352, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1556062258, "publicationGroup": 16080408, "publicationStage": "published", "rowIdentifierColumnId": 405358072, "rowsUpdatedAt": 1577997789, "rowsUpdatedBy": "2ucb-naf2", "tableId": 16146988, "totalTimesRated": 0, "viewCount": 544, "viewLastModified": 1556154026, "viewType": "tabular", "approvals": [ { "reviewedAt": 1556905332, "reviewedAutomatically": true, 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"item": "COLORADO", "count": "52" }, { "item": "CONNECTICUT", "count": "52" }, { "item": "DELAWARE", "count": "52" }, { "item": "DISTRICT OF COLUMBIA", "count": "52" }, { "item": "EAST NORTH CENTRAL", "count": "52" }, { "item": "EAST SOUTH CENTRAL", "count": "52" }, { "item": "FLORIDA", "count": "52" }, { "item": "GEORGIA", "count": "52" }, { "item": "GUAM", "count": "52" }, { "item": "HAWAII", "count": "52" }, { "item": "IDAHO", "count": "52" }, { "item": "ILLINOIS", "count": "52" }, { "item": "INDIANA", "count": "52" }, { "item": "IOWA", "count": "52" } ], "smallest": "ALABAMA", "not_null": "3220", "count": "3640", "cardinality": "70" }, "format": {} }, { "id": 405358023, "name": "MMWR Year", "dataTypeName": "text", "fieldName": "mmwr_year", "position": 2, "renderTypeName": "text", "tableColumnId": 78813191, "width": 208, "cachedContents": { "largest": "2019", "non_null": "3640", "null": "0", "top": [ { "item": "2019", "count": "3640" } ], "smallest": "2019", "not_null": "3220", 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The second study is a mixed methods research to inform how best to tailor a mental health preventiveintervention for Asian American cancer patients and post-treatment survivors that can be integrated in ongoing oncology and survivorship programs at the Perlmutter Cancer Center.", "count": "1" }, { "item": "Cancer registries are used to track new cancer cases and identify any trends across time or patterns in certain populations. Some people with certain cancers listed in the registries may be at elevated risk of having their cancer recur or of developing another cancer. Their close relatives also may be at elevated risk of developing cancer. People in these two groups may benefit from targeted cancer screening interventions. By using the information recorded in these registries, a research team may be able to develop effective ways to identify and contact people at high risk of developing certain cancers and inform them about the benefits of cancer screening. Researchers also could use registry information to develop ways to remind physicians to talk with their patients about the importance of cancer screening and schedule them for screening. Establishing new, effective programs that communicate with people at high risk of developing cancer and the doctors who treat them could increase screening and, over time, help to lower cancer mortality rates.Center researchers are using data from the Georgia Comprehensive Cancer Registry from 2000 to 2009 to identify and contact women who developed breast cancer at a young age (aged 25 to 45 years old) or who had the disease in both breasts at any age and their close female relatives. In the second phase of the study, the researchers will identify and contact men and women who developed colorectal cancer at a young age (younger than 45 years old) and their close relatives. Three medical centers in Atlanta, Georgia, and four medical facilities in rural Southwest Georgia are participating in the study. The researchers will invite people listed in the registry who have been treated at one of these participating centers and who meet study requirements to join the study. Then the researchers will invite family members (who have been identified by the study participants and meet study requirements) to join the study. The researchers also will team up with the primary-care physicians and cancer specialists who treat these study participants. Thedoctors will sign the recruitment letters for their patients and will receive reminders from the research team to schedule cancer screening for individual patients.Cancer survivors and their relatives who agree to participate will be randomly assigned (as a unit) to receive either a low-intensity intervention consisting of printed educational materials or a high-intensity intervention of printed materials, telephone counseling, and screening reminders for participants and the doctors who treat them. Three months after the invitation to participate, and again1 year after the invitation, the researchers will follow up with participants for feedback about the intervention, find out if they received a mammogram or colonoscopy, and ask if their doctors encouraged them to be screened. The team will assess overall feasibility of the participant recruitment process, the delivery of the intervention to people in both urban and rural settings, and the acceptability and effectiveness of each program used to promote cancer screening.", "count": "1" }, { "item": "Every year of this 4-year project, up to 4 studies are conducted among health care providers and policymakers on issues critical to CDCs National Center for Immunization and Respiratory Diseases. The goal is to understand health care providers attitudes, behaviors, and barriers related to immunization delivery. The specific focus of each study is determined by CDC in collaboration with a team of external researchers. Researchers are recruiting a network of pediatricians, family practitioners, and general internists who commit to responding rapidly to issue-specific surveys. The arrangement allows studies to be conducted on short notice in response to new immunization recommendations, vaccine supply problems, changes in state or federal immunization policies, or new trends in insurance coverage. Rapid reporting allows CDC to apply results to current and future efforts in child and adult immunization, including policy recommendations for new vaccines, strategies to improve immunization coverage, contingency plans for urgent issues, and public health messages to promote immunization. Researchers will conduct a minimum of3 surveys or qualitative studies about immunization delivery policy each year with physicians in1-3 of the specialties of interest and quickly report results to the CDC and the national associations that represent members of the specialty disciplines.", "count": "1" }, { "item": "Many effective sex education programs have been developed for middle school students but insufficient progress has been made in disseminating these curricula. A systematic process is not in place for packaging intervention resources, getting buy-in from school administrators, training school staff to implement interventions, and evaluating the impact of the curricula on students health.In Harris County, Texas, which includes Houston, statistics describing young peoples sexual health are of concern: by the 9th grade, 35% students have had sexual intercourse; teenage mothers accounted for 12% of all births in 2004, and of these mothers, most were Latina or African American girls; Chlamydia and gonorrhea cases are highest among girls 15 and 19 years of age; and more than half of all new HIV infections occur in persons less than 25 years old. The county lacks effective curricula to help prevent pregnancy and sexually transmitted infections (STI), and researchers are studying how to disseminate sex education to county schools.Twenty two school districts comprising 187 schools, more than 3,000 education professionals, and about 178,000 students are involved in the study. Recruitment for the study starts with superintendents, who invite individual schools, and then teachers to participate. Parents and school staff meet with researchers to determine the best mix of curriculum components for specific schools. Researchers are working with advisory groups to develop program products such as a Web site, promotional videos, and training programs for parents and teachers. Center staff is developing surveys to describe the key actors in adopting a curriculum. The researchers are also refining measures of organizational and individual factors that contribute to implementation and maintenance. A second set of middle schools is receiving a brochure about the effective sex education curricula.Students current sexual behavior is collected by using the Youth Risk Behavior Survey at the beginning of the project, and changes are measured in a follow-up survey. Ongoing evaluation will compare the two groups of middle schools to identify which sex education curricula are adopted from the offered array of effective programs. Researchers will also evaluate the financial cost-benefit of offering sex education, measured by dissemination costs and lifetime costs of teen pregnancy, HIV infection, and STI.", "count": "1" }, { "item": "The Washington University Prevention Research Center in St. Louis (PRC-StL) will develop and disseminate approaches to increase implementation of evidence-based policies (EBPs) to reduce obesity disparities and promote health equity, focusing on the uptake of effective local-level policies. PRC-StL will target two specific types of policy makers at the community level: elected local officials (mayors, city council members) and appointed local officials (heads of local departments). PRC-StL will test the research translation of policy briefs into local policy makers decisions to support EBP adoption with a Randomized Control Trial (RCT). Additionally, PRC-StL will test the effect of social network-informed tailoring of implementation strategies on a variety of policy-relevant processes and outcomes related to EBPs to address obesity. Network models in 20 communities (10 intervention, 10 control) will highlight the differences in network structure (e.g., density, presence of isolates) that are likely to influence communication about and uptake of obesity EBPs. Building on data collected from these two tests, PRC-StL will apply andevaluate the effects of stakeholder-driven implementation strategies (e.g., policy briefs, social media) on policy-relevant outcomes such as communication about and uptake of EBPs.", "count": "1" }, { "item": "Childhood obesity is a serious public health concern in the United States, and both physical inactivity and sedentary behaviors are important contributing factors. Youth who participate in daily moderate to vigorous intensity physical activity are less likely to develop a number of chronic diseases as adults, including obesity. Illinois and Chicago, in particular, suffer from higher than national average obesity rates, especially for children. Obesity rates among young children were 15% and 22% in Illinois and Chicago, respectively, almost twice the U.S. average (12%). Recent data shows that parks play an important role in youth physical activity, and playgrounds are a common park feature that are used more by children than any other park feature. Park condition and specific features (e.g., slides, climbers) also play an important role in ultimate park usage. Some studies show increased park use and physical activity following a park renovation, while others are inconclusive or show no change. Therefore, there is a need to further examine the impact of park renovations on park utilization and physical activity. Researchers at the University of Illinois at Chicago Prevention Research Center will work with identified community stakeholders to conduct a comprehensive, rigorous evaluation of the impact of a Chicago Park District (CPD) park-based renovation. The two-phase research project will develop, implement and evaluate measureable strategies regarding how park-based playground renovations can increase local park access and use, addressing a key CDC Physical Activity Winnable Battles priority strategy. The findings of the study will be applied to ongoing park renovations by implementing a park coalition building intervention to increase local capacity and influence park-based utilization and physical activity. During the studys first two years, the project will involve examining how differences in community engagement and park programming, maintenance and safety, and variations in newly installed playground features influence park-based use and physical activity. During the third through fifth years, the project will develop, implement and evaluate a park coalition building intervention, based on lessons learned in Phase 1. This intervention will be aimed at renovated playgrounds to increase park-based use and physical activity through improved programming and ongoing maintenance and safety. Results of this study will contribute to an understanding about how urban park revitalization and community engagement can help to increase physical activity and improve individual and community health.", "count": "1" }, { "item": "Emory Prevention Research Center will study a cohort of over 4,000 childhood and adolescent cancer survivors diagnosed before the age of 20 and treated between 2002;2016 with all types of childhood cancers and of a diverse racial/ethnic background. The aims of the research are to 1) Investigate the association between receiving apersonalized survivorship care plan (SCP)and mortality.2) Compare cause-specific mortality between those who did or did not receive a SCP.3) Investigate the association of receiving a SCP with adherence to screening for key late effects, presence of specific late effects, andpatientshealth care use. This study will also helpto makeinformeddecisions on optimal allocation of healthcare resources to support these efforts.Few studies have examined theeffectof SCPs on adherence to the evidence-based Childrens Oncology Group-recommended surveillance and the associatedeffecton reducing premature mortality using a population-based approach. This study will provide the first evidence of the effectiveness of SCPs in decreasing mortality and morbidity among survivors of childhood cancer.", "count": "1" }, { "item": "In partnership with YMCA of the USA (Y-USA), Sound Generations, and the National Digital Equity Center, the University of Washington Prevention Research Center (PRC) will conduct a trial of Livestream EnhanceFitness (tele-EF) versus in-person EnhanceFitness (EF) among adults with arthritis. EnhanceFitness is a multicomponent, instructor-led, group exercise program that is recommended by the CDC for adults with arthritis. Participants will self-select to attend either tele-EF or in-person EF for 16 weeks, 3 days\n a week for 1-hour. In both groups, half of the participants will be 18-64 years old and either have low socioeconomic status, have moderate-to-severe functional limitations, or live in a rural area. The primary outcome is self-reported physical function as measured by the Patient-Reported Outcome Measurement Information System (PROMIS) 10-item short form. Secondary outcomes include pain severity, pain interference, depression, social participation, and loneliness. Outcomes will be assessed at study months 0, 4, 10, and 16. In addition to assessing the effectiveness of tele-EF versus in-person EF on clinical outcomes, the University of Washington PRC will compare the cost of delivering these programs. The PRC will also conduct a scoping review on best practices for recruiting and retaining participants in exercise programs, particularly focused on hard-to-reach populations. Lastly, the PRC will develop a toolkit for sites to engage adults with arthritis and deliver tele-EF.", "count": "1" }, { "item": "University of North Carolina at Chapel Hill Center for Health Promotion and Disease Prevention will serve as the UNC Coordinating Center and provide experienced, effective leadership to guide the Cancer Prevention and Control Research Network (CPCRN) through a significant transition in membership while enhancing the networks productivity and influence. The specific aims are to: 1) coordinate and evaluate collaborative research activities with network members, their collaborating partners, and affiliates focused onaccelerating the adoption and implementation of evidence-based cancer prevention and control strategies in communities; 2) facilitate linkages among network members, network affiliates, national, state, and local partners to advance the mission of the network and develop workforce capacity; and 3) participate in the CPCRN as a Collaborating Center through the Comprehensive Cancer Control Collaborative of North Carolina (CCNC).", "count": "1" }, { "item": "African Americans are the racial/ethnic group most affected by HIV. In 2010, an estimated 7,000 African American youth accounted for all new HIV infections, while Hispanic and white youth accounted for an estimated 2,390 and 2,380 of new HIV infections, respectively. In addition, African Americans bear a disproportionate burden of chlamydia, gonorrhea, and syphilis. Having an STI can make one more likely to get HIV. To address this health disparity, researchers at the Morehouse School of Medicine Prevention Research Center (PRC) will conduct a research project to reduce STI and HIV infections among African American youth. The Morehouse PRCs research project consists of four arms: 1. The Be A Responsible Teen (BART) program 2. A social marketing program and a parental component 3. An approach based on the HIV-RAAP program (a HIV risk reduction program for African American men and women) that will include media literacy 4. A comparison group Researchers will compare each of the arms to determine the most effective method for decreasing sexual encounters and risky sexual behaviors among African American youth. They plan to recruit a total of 384 African American youth, ages 14-18, through four Neighborhood Planning Units (NPU) in Atlanta (a fifth site will also be used for social media messages developed from Arm 3). These NPU sites include local Boys and Girls clubs, YMCAs, and other community organizations and will also serve as locations for the four arms of the research study to be conducted. All four arms will happen simultaneously for eight weeks each with up to 12 participants. They will meet from 90-120 minutes on a weekly basis. Comparisons of participants will be assessed prior to the eight weeks, at the end of the eight weeks, and then six and 12 months following the research study. This research study aims to decrease the number of new HIV/STI infections among young African Americans by reducing risky sexual behaviors. Research results will be shared through presentations, manuscripts, and a book.", "count": "1" }, { "item": "University of Washington Health Promotion Research Center will: 1) translate the Program for Active Consumer Engagement in Self-Management (PACES) intervention into Spanish; 2) conduct a randomized controlled trial (RCT) on the effectiveness of this self-management program with a sample of native Spanish-speaking adults with epilepsy in collaboration with the University of Texas Southwestern (UT Southwestern); 3) test PACES with a wider geographic and demographic coverage to include minorities, individuals with lower educational levels, et cetera; 4) examine factors that affect participant engagement and diverse entity adoption of the PACES program for utilization; and 5) implement the knowledge translation and application template across all project years to allow for continual emphasis on publication/further dissemination of findings, PACES program marketing, implementation partner development, and full collaboration in the Managing Epilepsy Well 2.0 (MEW) partnership of universities engaged in epilepsy self-management research/dissemination.", "count": "1" }, { "item": "The University of Maryland Prevention Research Center (UMD-PRC) will focus on resources utilized in the field to address LGBT mental health care competency at the organization, clinician, and client levels. The study intends to test one level of intervention against another in preparing healthcare providers (HCP) to care for the LGBT population. The specific aims of the proposed research are to: 1) conduct a randomized controlled trial (RCT) with 10 mental health organizations from 5 regions of Maryland (Western, Central, Capital, Eastern Shore, and Southern) to evaluate the effectiveness of the Studies of the Sexual and Gender Diversity Learning Community (SGDLC) and 5 selected tools for assessing and improving mental health care experiences for LGBT people; 2) perform a cost\n analysis; and 3) develop a dissemination plan for study results. The organizations will be from 5 regions of Maryland. Clinicians in both the intervention and control condition will be provided with information about, on-line publicly and nationally accessible, voluntary SAMHSA guidelines for LGBT care, Fenway webinars, and post-test standardized patient interviews and feedback. Organizational leads in the intervention group will also receive feedback about gaps in organization LGBT cultural sensitivity. In addition to\n organization level data, this study will collect both clinician and client level data through multiple assessment tools (Healthcare Equity Index, Consumer Satisfaction Survey, LGBT Health Literacy Scale, LGBT Development of Clinical Skills Scale, and the Integrated Screening Tool), qualitative interviews, and simulated patient observations.", "count": "1" }, { "item": "In low-income, Texas communities of the Brazos Valley and Lower Rio Grande Valley, access to healthy, affordable foods is difficult: food stores are scant; prices are high; and the variety of healthy foods is limited. Residents often must travel long distances to a supermarket, and they lack access to public transportation. Residents of these two regions tend to eat more energy-dense food, which can put them at higher risk of obesity, diabetes, and cardiovascular disease due to the high sugar, fat or salt content.Researchers are working with their partner communities to make healthy food accessible and affordable. Researchers are assessing the food sources in the communities, noting how food is distributed through markets, charities, federal programs, and community food systems (farmers markets, neighborhood gardens, schools, and microenterprises). Researchers identify, photograph and map all food sources in the communities and several miles beyond them. Then, the researchers record the availability, variety, and price of foods at traditional, nontraditional, and convenience food stores. Investigators will ask community members and food suppliers about the difficulties they face when trying to bring healthy foods into the community or trying to find healthy foods to purchase.After completing the food inventory, the researchers will work with community members to develop four interventions in Brazos Valley and two in Hidalgo County. Interventions may include strategies to help residents create demand for healthy food at their local convenience stores, train convenience-store owners how to sell healthy foods successfully, and promote healthy eating and stores that sell healthy foods. The partners may also devise ways to start and maintain farmers markets supplied by small farms and personal gardens and help communities and families start their own gardens and mobile markets. To evaluate how well the interventions help improve the food supply, researchers will conduct focus groups, interviews, and surveys to determine if the residents find it easier to get healthy food on an ongoing basis. Graduate students, community health workers, and other participants working with the researchers will complete before and after surveys to assess the value of this project as a part of their public health education.", "count": "1" }, { "item": "This brief explores the implementation of pedestrian-friendly zoning in 15 jurisdictions across the US. This can be used as resource for the best practices and lessons learned in the implementation of pedestrian friendly zones in communities.", "count": "1" }, { "item": "According to the International Agency for Research on Cancer that is part of the World Health Organization, approximately 25%-30% of cancers may be caused by lack of physical activity, poor nutrition, and excess weight.In 2010, 69.2%of American adults were overweight or obese, and similarly large portions of adults were physically inactive and had poor dietary habits.Behavioral counseling in primary care settings is effective in changing lifestyle choices, but many medical residents do not feel well prepared in this skill. Equipping these professionals with the knowledge, confidence, and communication skills to effectively counsel patients in physical activity, nutrition, and obesity (PANO) may help reduce a patients risk for cancer. Senior medical residents from primary care residency programs (Family Medicine, Internal Medicine, and Obstetrics/Gynecology) in Ohio will answer questions about their knowledge, confidence, and practice in PANO counseling for cancer prevention.Researchers will meet with program directors and review program curriculum to assess programmatic aspects such as faculty expertise in PANO, curriculum changes from 2010 to 2012, and counseling electives available to medical residents. The findings from this study will give a clearer pictureabout which medical residents are able to learn and use PANO counseling with their patients for cancer prevention. The results willalso potentially highlight necessary changes in the curriculum of medical residency programs regarding PANO counseling for cancer preventionthat may generate interest from other medical residency programs around the country to engage in similar assessment.", "count": "1" }, { "item": "The goal of this study is to create a short survey tool to understand the behaviors of men who have sex with men (MSM). MSM patients sometimes use their HIV status to make decisions about their sexual behavior. The researchers want to test their short survey tool in a medical setting and in the community. The findings from the study will give doctors, nurses, and other health care workers a way to quickly and correctly determine MSM patient behaviors and habits. Understanding MSM behaviors and habits will help doctors, nurses, and other health care workers create specific and useful educational messages to help lower the chances of getting HIV.", "count": "1" }, { "item": "This video provides a brief introduction to the CHEER (Community Health through Engagement and Environmental Renewal) research project, looking at parenting practices and youth behavior in 8 Birmingham neighborhoods. This can used to for informational purposes and to learn about implementation of the CHEER project.", "count": "1" } ], "smallest": "Academic-community partnerships have produced many successful public health strategies that focus on preventing or controlling chronic diseases in underserved populations. Despite these advances, adoption of proven strategies by public health practitioners has been slowless than 1% of proven programs have achieved widespread application. Researchers publish information about successful interventions in academic journals. Resources like the Guide to Community Preventive Services aggregate proven programs and policies. These sources, however, lack training information and tools or materials that facilitate program tailoring and implementation.Researchers are developing a training program for public health workers and other community members to conduct community-based prevention marketing (CBPM). CBPM is a multistep process designed to improve the adoption of new or existing interventions by translating or adapting them to fit local circumstances. CBPM is a multi-step process that enables public health workers and other participants to1. Mobilize their community.2. Build community capacity for conducting consumer research.3. Develop a profile of local health issues.4. Identify priority behaviors and audiences.5. Select an evidence-based intervention.6. Create a comprehensive marketing plan for tailoring the intervention.7. Develop and test program materials that support the intervention.8. Implement the intervention.9. Evaluate its effectiveness so that responsive adjustments can be made if needed.Researchers are creating a CBPM online training program and electronic resource kit for practitioners to use when creating new programs or translating evidence-based practices for their local setting. Community partners are working with the researchers to identify and select evidence-based obesity prevention practices and apply the CBPM framework to translate them for local implementation using the e-training program. Researchers will test the translational framework with a community coalition. Then, they will study the extent to which the coalition uses intervention materials to implement proven obesity programs. The coalition and the researchers will work together to identify factors related to marketing, advocacy, and policy changes that influence uptake and sustain use of prevention practices.", "count": "446", "cardinality": "443" }, "format": {} }, { "id": 601902353, "name": "File Type", "dataTypeName": "text", "description": "", "fieldName": "file_type", "position": 7, "renderTypeName": "text", "tableColumnId": 155631185, "cachedContents": { "non_null": "200", "largest": "Website", "null": "246", "top": [ { "item": "Website", "count": "74" }, { "item": "PDF or Word", "count": "72" }, { "item": "Audio or video", "count": "26" }, { "item": "Image or graphic", "count": "14" }, { "item": "Audio or video,Website", "count": "6" }, { "item": "Audio or video,PDF or Word,Website", "count": "2" }, { "item": "PPT Presentation", "count": "2" }, { "item": "PDF or Word,PDF or Word", "count": "1" }, { "item": "PDF or Word,Website", "count": "1" }, { "item": "Image or graphic,PDF or Word", "count": "1" 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American Lung Association. Cessation Coverage – Medicaid Coverage of Treatments – Counseling. Medicaid data compiled by the Centers for Disease Control and Prevention’s Office on Smoking and Health were obtained from the State Tobacco Cessation Coverage Database, developed and administered by the American Lung Association. Data from 2008-2012 are reported on an annual basis; beginning in 2013 data are reported on a quarterly basis. Data include state-level information on types of counseling recommended by the Public Health Service (PHS). The types of counseling recommended by the PHS are: individual counseling, group counseling and phone counseling. Data do not include phone counseling which is available in every state through quitlines.", "displayType": "table", "downloadCount": 659, "hideFromCatalog": false, "hideFromDataJson": false, "licenseId": "PUBLIC_DOMAIN", "locked": false, "modifyingViewUid": "ntaa-dtex", "newBackend": true, "numberOfComments": 0, "oid": 40516908, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1712849001, "publicationGroup": 1553919, "publicationStage": "published", "queryString": "SELECT `year`, `quarter`, `locationabbrv`, `locationdesc`, `topictype`, `topic`, `measure`, `submeasure`, `fee_for_service_plans`, `fee_for_service_plans_altvalue`, `managed_care_plans`, `managed_care_plans_altvalue`, `summary`, `summary_altvalue`, `tempgeolocation`, `topictypeid`, `topicid`, `measureid` WHERE ((upper(`submeasure`) = \"INDIVIDUAL COUNSELING\") or (upper(`submeasure`) = \"GROUP COUNSELING\")) and (upper(`measure`) = \"MEDICAID COVERAGE OF CESSATION TREATMENTS\") ORDER BY `year` DESC NULL LAST,`quarter` DESC NULL LAST,`locationdesc` ASC NULL LAST", "rowClass": "", "rowsUpdatedAt": 1721236589, "rowsUpdatedBy": "fjjr-gap9", "tableId": 19218402, "totalTimesRated": 0, "viewCount": 2167, "viewLastModified": 1738280981, "viewType": "tabular", "approvals": [ { "reviewedAt": 1400498901, "reviewedAutomatically": true, "state": "approved", "submissionId": 6270024, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1400498901, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "failureCount": 0, "status": "success" }, "submitter": { "id": "p5wh-zttj", "displayName": "OSHData" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [ { "id": 591566407, "name": "Year", "dataTypeName": "number", "description": "Year", "fieldName": "year", "position": 1, "renderTypeName": "number", "tableColumnId": 19308528, "width": 66, "format": { "precisionStyle": "standard", "noCommas": "true", "align": "right" } }, { "id": 591566408, "name": "Quarter", "dataTypeName": "number", "description": "Quarter", "fieldName": "quarter", "position": 2, "renderTypeName": "number", "tableColumnId": 19308529, "width": 88, "format": {} }, { "id": 591566409, "name": "LocationAbbr", "dataTypeName": "text", "description": "Location abbreviation", "fieldName": "locationabbrv", "position": 3, "renderTypeName": "text", "tableColumnId": 19308526, "width": 129, "format": {} }, { "id": 591566410, "name": "LocationDesc", "dataTypeName": "text", "description": "Location description", "fieldName": "locationdesc", "position": 4, "renderTypeName": "text", "tableColumnId": 19308527, "width": 138, "format": {} }, { "id": 591566411, "name": "TopicType", "dataTypeName": "text", "description": "Type of topic", "fieldName": "topictype", "position": 5, "renderTypeName": "text", "tableColumnId": 19308530, "width": 160, "format": {} }, { "id": 591566412, "name": "Topic", "dataTypeName": "text", "description": "Topic description", "fieldName": "topic", "position": 6, "renderTypeName": "text", "tableColumnId": 19308531, "width": 184, "format": {} }, { "id": 591566413, "name": "MeasureDesc", "dataTypeName": "text", "description": "Measure description", "fieldName": "measure", "position": 7, "renderTypeName": "text", "tableColumnId": 19308532, "width": 232, "format": {} }, { "id": 591566414, "name": "Sub_Measure", "dataTypeName": "text", "description": "Submeasure description", "fieldName": "submeasure", "position": 8, "renderTypeName": "text", "tableColumnId": 19308533, "width": 196, "format": {} }, { "id": 591566415, "name": "Fee-For-Service Plans", "dataTypeName": "text", "description": "Plan availability - 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NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. 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For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. \n†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). \n§ Please refer to the CDC WONDER publication for weekly updates to the footnote for this condition.", "displayType": "table", "downloadCount": 1434, "hideFromCatalog": false, "hideFromDataJson": false, "locked": false, "newBackend": true, "numberOfComments": 0, "oid": 36259170, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1611251124, "publicationGroup": 17919260, "publicationStage": "published", "rowIdentifierColumnId": 520408276, "rowsUpdatedAt": 1642012576, "rowsUpdatedBy": "vu8q-ns5k", "tableId": 17957380, "totalTimesRated": 0, "viewCount": 607, "viewLastModified": 1614284927, "viewType": "tabular", 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Little is known about the health effects associated with these aerosols. Sprague-Dawley rats were exposed to aerosols (25 mg/m3 x 4 hr/d x 4 d) generated during thermal spray coating using different consumables [i.e., stainless-steel wire (PMET731), Ni-based wire (PMET885), Zn-based wire (PMET540)]. Control animals received air. Bronchoalveolar lavage was performed at 4 and 30 d post-exposure to assess lung toxicity. The particles were chain-like agglomerates and similar in size (310–378 nm). Inhalation of PMET885 aerosol caused a significant increase in lung injury and inflammation at both time points. Inhalation of PMET540 aerosol caused a slight but significant increase in lung toxicity at 4 but not 30 d. Exposure to PMET731 aerosol had no effect on lung toxicity. Overall, the lung responses were in the order: PMET885>>PMET540>PMT731. Following a shorter exposure (25 mg/m3 x 4 h/d x 1d), lung burdens of metals from the different aerosols were determined by ICP-AES at 0, 1, 4 and 30 d post-exposure. Zn was cleared from the lungs at the fastest rate with complete clearance by 4 d post-exposure. Ni, Cr, and Mn had similar rates of clearance as nearly half of the deposited metal was cleared by 4 d. A small but significant percentage of each of these metals persisted in the lungs at 30 d. The pulmonary clearance of Fe was difficult to assess because of inherently high levels of Fe in control lungs.", "displayType": "blob", "downloadCount": 21, "hideFromCatalog": false, "hideFromDataJson": false, "locked": false, "newBackend": false, "numberOfComments": 0, "oid": 40957795, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1731697437, "publicationGroup": 19691413, "publicationStage": "published", "rowsUpdatedAt": 1731697363, "tableId": 19691413, "totalTimesRated": 0, "viewCount": 126, "viewLastModified": 1732121138, "viewType": "blobby", "approvals": [ { "reviewedAt": 1731951812, "reviewedAutomatically": true, "state": "approved", "submissionId": 6617122, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1731951812, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "endedAt": 1731951812, "failureCount": 0, "startedAt": 1731951812, "status": "success" }, "submitter": { "id": "6gky-eu6y", "displayName": "kye1" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "metadata": { "custom_fields": { "Common Core": { "Contact Email": "sa-cin-webteam@cdc.gov", "Contact Name": "Pathology and Physiology Research Branch (PPRB), Health Effects Laboratory Division (HELD)", "Program Code": "009:034", "Bureau Code": "009:20" } }, "availableDisplayTypes": [ "table", "fatrow", "page" ] }, "owner": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": {}, "rights": [ "read" ], "tableAuthor": { "id": "6gky-eu6y", "displayName": "kye1", "screenName": "kye1", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "flags": [ "default", "ownerMayBeContacted" ] } ----------------------------- Directory: 2snk-eav4 Metadata Found: { "id": "2snk-eav4", "name": "CDC STATE System Tobacco Legislation - Smokefree Indoor Air Summary", "assetType": "dataset", "attribution": "Centers for Disease Control and Prevention", "attributionLink": "http://www.cdc.gov/STATESystem/", "averageRating": 0, "category": "Legislation", "createdAt": 1418756443, "description": "1995-2024. Centers for Disease Control and Prevention (CDC). State Tobacco Activities Tracking and Evaluation (STATE) System. Legislation – Smokefree Indoor Air. The STATE System houses current and historical state-level legislative data on tobacco use prevention and control policies. Data are reported on a quarterly basis. Data include information related to state legislation on smokefree indoor air in private worksites, restaurants, and bars.", "displayType": "table", "downloadCount": 8967, "hideFromCatalog": false, "hideFromDataJson": false, "iconUrl": "fileId:Mnyn3o6zyfCg6YrbpU56Us8JNnej1V1xPJLU9rR-Ih8", "licenseId": "ODC_BY", "locked": false, "newBackend": true, "numberOfComments": 0, "oid": 39790657, "provenance": "official", "publicationAppendEnabled": false, "publicationDate": 1689776041, "publicationGroup": 1983736, "publicationStage": "published", "rowsUpdatedAt": 1736535911, "rowsUpdatedBy": "sn5p-uz6k", "tableId": 19224004, "totalTimesRated": 0, "viewCount": 5030, "viewLastModified": 1711980814, "viewType": "tabular", "approvals": [ { "reviewedAt": 1550147844, "reviewedAutomatically": true, "state": "approved", "submissionId": 5645529, "submissionObject": "public_audience_request", "submissionOutcome": "change_audience", "submittedAt": 1550147844, "targetAudience": "public", "workflowId": 2100, "submissionDetails": { "permissionType": "READ" }, "submissionOutcomeApplication": { "failureCount": 0, "status": "success" }, "submitter": { "id": "fjjr-gap9", "displayName": "CDC UserSA" } } ], "clientContext": { "clientContextVariables": [], "inheritedVariables": {} }, "columns": [ { "id": 578366016, "name": "YEAR", "dataTypeName": "number", "description": "Year", "fieldName": "year", "position": 1, "renderTypeName": "number", "tableColumnId": 23379731, "width": 62, "cachedContents": { "non_null": "5104", "largest": "2025", "null": "0", "top": [ { "item": "2014", "count": "232" }, { "item": "2015", "count": "232" }, { "item": "2016", "count": "232" }, { "item": "2017", "count": "232" }, { "item": "2018", "count": "232" }, { "item": "2019", "count": "232" }, { "item": "2020", "count": "232" }, { "item": "2021", "count": "232" }, { "item": "2022", "count": "232" }, { "item": "2023", "count": "232" }, { "item": "2024", "count": "232" }, { "item": "2006", "count": "232" }, { "item": "2007", "count": "232" }, { "item": "2008", "count": "232" }, { "item": "2009", "count": "232" }, { "item": "2010", "count": "232" }, { "item": "2011", "count": "232" }, { "item": "2012", "count": "232" }, { "item": "2013", "count": "232" }, { "item": "2025", "count": "58" } ], "smallest": "1995", "count": "5104", "cardinality": "31" }, "format": { "precisionStyle": "standard", "noCommas": "true", "align": "right" } }, { "id": 578366017, "name": "Quarter", "dataTypeName": "number", "description": "Quarter", "fieldName": "quarter", "position": 2, "renderTypeName": "number", "tableColumnId": 23379732, "width": 53, "cachedContents": { "non_null": "5104", "largest": "4", "null": "0", "top": [ { "item": "4", "count": "1740" }, { "item": "1", "count": "1160" }, { "item": "2", "count": "1102" }, { "item": "3", "count": "1102" } ], "smallest": "1", "count": "5104", "cardinality": "4" }, "format": { "precisionStyle": "standard", "align": "right" } }, { "id": 578366018, "name": 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"align": "left" } }, { "id": 578366019, "name": "LocationDesc", "dataTypeName": "text", "description": "Location description", "fieldName": "locationdesc", "position": 4, "renderTypeName": "text", "tableColumnId": 23379734, "width": 141, "cachedContents": { "non_null": "5104", "largest": "Wyoming", "null": "0", "top": [ { "item": "Alabama", "count": "88" }, { "item": "Alaska", "count": "88" }, { "item": "American Samoa", "count": "88" }, { "item": "Arizona", "count": "88" }, { "item": "Arkansas", "count": "88" }, { "item": "California", "count": "88" }, { "item": "Colorado", "count": "88" }, { "item": "Connecticut", "count": "88" }, { "item": "Delaware", "count": "88" }, { "item": "District of Columbia", "count": "88" }, { "item": "Florida", "count": "88" }, { "item": "Georgia", "count": "88" }, { "item": "Guam", "count": "88" }, { "item": "Hawaii", "count": "88" }, { "item": "Idaho", "count": "88" }, { "item": "Illinois", "count": "88" }, { "item": "Indiana", "count": "88" }, { "item": "Iowa", "count": "88" }, { "item": "Kansas", "count": "88" }, { "item": "Kentucky", "count": "88" } ], "smallest": "Alabama", "count": "5104", "cardinality": "58" }, "format": { "align": "left" } }, { "id": 578366020, "name": "TopicTypeDesc", "dataTypeName": "text", "description": "Topic type description", "fieldName": "topictypedesc", "position": 5, "renderTypeName": "text", "tableColumnId": 23379735, "width": 148, "cachedContents": { "non_null": "5104", "largest": "Legislation", "null": "0", "top": [ { "item": "Legislation", "count": "5104" } ], "smallest": "Legislation", "count": "5104", "cardinality": "1" }, "format": { "align": "left" } }, { "id": 578366021, "name": "TopicDesc", "dataTypeName": "text", "description": "Topic description", "fieldName": "topicdesc", "position": 6, "renderTypeName": "text", "tableColumnId": 23379736, "width": 208, "cachedContents": { "non_null": "5104", "largest": "Smokefree Indoor Air", "null": "0", "top": [ { "item": "Smokefree Indoor Air", "count": "5104" } ], "smallest": "Smokefree Indoor Air", "count": "5104", "cardinality": "1" }, "format": { "align": "left" } }, { "id": 578366022, "name": "MeasureDesc", "dataTypeName": "text", "description": "Measure description", "fieldName": "measuredesc", "position": 7, "renderTypeName": "text", "tableColumnId": 23379737, "width": 232, "cachedContents": { "non_null": "5104", "largest": "Private Worksites, Restaurants, Bars - OSH", "null": "0", "top": [ { "item": "Private Worksites, Restaurants, Bars - OSH", "count": "5104" } ], "smallest": "Private Worksites, Restaurants, Bars - OSH", "count": "5104", "cardinality": "1" }, "format": { "align": "left" } }, { "id": 578366023, "name": "Private_Worksites", "dataTypeName": "text", "description": "Value of restriction in private worksites", "fieldName": "private_worksites", "position": 8, "renderTypeName": "text", "tableColumnId": 23379738, "width": 151, "cachedContents": { "non_null": "5104", "largest": "Separate Ventilated Areas", "null": "0", "top": [ { "item": "Banned", "count": "2856" }, { "item": "No Provision", "count": "1221" }, { "item": "Designated Areas", "count": "777" }, { "item": "Separate Ventilated Areas", "count": "134" }, { "item": "Designated Smoking Area", "count": "116" } ], "smallest": "Banned", "count": "5104", "cardinality": "5" }, "format": { "align": "left" } }, { "id": 578366024, "name": "Restaurants", "dataTypeName": "text", "description": "Value of restriction in restaurants", "fieldName": "restaurants", "position": 9, "renderTypeName": "text", "tableColumnId": 23379739, "width": 150, "cachedContents": { "non_null": "5104", "largest": "Separate Ventilated Areas", "null": "0", "top": [ { "item": "Banned", "count": "2861" }, { "item": "Designated Areas", "count": "877" }, { "item": "No Provision", "count": "781" }, { "item": "Separate Ventilated Areas", "count": "321" }, { "item": "None", "count": "132" }, { "item": "Designated Smoking Area", "count": "126" }, { "item": "Designated Smoking Areas", "count": "6" } ], "smallest": "Banned", "count": "5104", "cardinality": "7" }, "format": { "align": "left" } }, { "id": 578366025, "name": "Bars", "dataTypeName": "text", "description": "Value of restriction in bars", "fieldName": "bars", "position": 10, "renderTypeName": "text", "tableColumnId": 23379740, "width": 148, "cachedContents": { "non_null": "5104", "largest": "Separate Ventilated Areas", "null": "0", "top": [ { "item": "Banned", "count": "2279" }, { "item": "No Provision", "count": "1197" }, { "item": "None", "count": "1193" }, { "item": "Designated Areas", "count": "206" }, { "item": "Separate Ventilated Areas", "count": "176" }, { "item": "Designated Smoking Area", "count": "53" } ], "smallest": "Banned", "count": "5104", "cardinality": "6" }, "format": { "align": "left" } }, { "id": 578366026, "name": "Type_Of_Restriction", "dataTypeName": "text", "description": "Summary of restrictions across Bars, Restaurants, and Private Worksites", "fieldName": "type_of_restriction", "position": 11, "renderTypeName": "text", "tableColumnId": 23379741, "width": 328, "cachedContents": { "non_null": "5104", "largest": "No Law, designated areas, or separate ventilation Law", "null": "0", "top": [ { "item": "100 % smokefree in three locations", "count": "2169" }, { "item": "No Law, designated areas, or separate ventilation Law", "count": "1933" }, { "item": "100 % smokefree in one location", "count": "515" }, { "item": "100 % smokefree in two locations", "count": "487" } ], "smallest": "100 % smokefree in one location", "count": "5104", "cardinality": "4" }, "format": { "align": "left" } }, { "id": 578366027, "name": "SummaryAltValue", "dataTypeName": "number", "description": "Alternate numeric value for non-numeric Type of Restriction value; used for mapping and graphing", "fieldName": "summaryaltvalue", "position": 12, "renderTypeName": "number", "tableColumnId": 23379742, "width": 50, "cachedContents": { "non_null": "5104", "largest": "3", "null": "0", "top": [ { "item": "3", "count": "2169" }, { "item": "0", "count": "1933" }, { "item": "1", "count": "515" }, { "item": "2", "count": "487" } ], "smallest": "0", "count": "5104", "cardinality": "4" }, "format": { "precisionStyle": "standard", "align": "right" } }, { "id": 578366028, "name": "GeoLocation", "dataTypeName": "location", "description": "Geolocation codes for mapping purposes", "fieldName": "geolocation", "position": 13, "renderTypeName": "location", "tableColumnId": 23379743, "width": 232, "format": { "align": "left" } }, { "id": 578366033, "name": "TopicTypeId", "dataTypeName": "text", "description": "Topic type identifier code - can be used for filtering; used in application", "fieldName": "topictypeid", "position": 18, "renderTypeName": "text", "tableColumnId": 23379744, "width": 50, "cachedContents": { "non_null": "5104", "largest": "LEG", "null": "0", "top": [ { "item": "LEG", "count": "5104" } ], "smallest": "LEG", "count": "5104", "cardinality": "1" }, "format": { "align": "left" } }, { "id": 578366034, "name": "TopicId", "dataTypeName": "number", "description": "Topic identifier code - can be used for filtering; used in application", "fieldName": "topicid", "position": 19, "renderTypeName": "number", "tableColumnId": 23379745, "width": 50, "cachedContents": { "non_null": "5104", "largest": "600", "null": "0", "top": [ { "item": "600", "count": "5104" } ], "smallest": "600", "count": "5104", "cardinality": "1" }, "format": { "precisionStyle": "standard", "align": "right" } }, { "id": 578366035, "name": "MeasureId", "dataTypeName": "text", "description": "Measure identifier code - can be used for filtering; used in application", "fieldName": "measureid", "position": 20, "renderTypeName": "text", "tableColumnId": 23379746, "width": 91, "cachedContents": { "non_null": "5104", "largest": "600COMB", "null": "0", "top": [ { "item": "600COMB", "count": "5104" } ], "smallest": "600COMB", "count": "5104", "cardinality": "1" }, "format": { "align": "left" } } ], "grants": [ { "inherited": false, "type": "viewer", "flags": [ "public" ] } ], "license": { "name": "Open Data Commons Attribution License", "termsLink": "http://opendatacommons.org/licenses/by/1.0/" }, "metadata": { "jsonQuery": { "order": [ { "columnFieldName": "year", "ascending": false }, { "columnFieldName": "quarter", "ascending": false }, { "columnFieldName": "locationdesc", "ascending": true } ] }, "custom_fields": { "Common Core": { "Contact Email": "nccdoshinquiries@cdc.gov", "Homepage": "https://www.cdc.gov/statesystem/index.html", "Described By": "https://chronicdata.cdc.gov/Legislation/CDC-STATE-System-Tobacco-Legislation-Smokefree-Ind/2snk-eav4", "Contact Name": "OSHData Support", "Issued": "7/27/2023", "Program Code": "009:020", "Publisher": "Centers for Disease Control and Prevention", "Bureau Code": "009:20", "Public Access Level": "public" } }, "rowLabel": "Row", "availableDisplayTypes": [ "table", "fatrow", "page" ] }, "owner": { "id": "fjjr-gap9", "displayName": "CDC UserSA", "screenName": "CDC UserSA", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "query": { "orderBys": [ { "ascending": false, "expression": { "columnId": 578366016, "type": "column" } }, { "ascending": false, "expression": { "columnId": 578366017, "type": "column" } }, { "ascending": true, "expression": { "columnId": 578366019, "type": "column" } } ] }, "rights": [ "read" ], "tableAuthor": { "id": "fjjr-gap9", "displayName": "CDC UserSA", "screenName": "CDC UserSA", "type": "interactive", "flags": [ "acceptedEula", "mayBeStoriesCoOwner" ] }, "tags": [ "tobacco", "osh", "state system", "legislation", "policy", "smokefree indoor air" ], "flags": [ "default", "ownerMayBeContacted", "restorable", "restorePossibleForType" ] } ----------------------------- Directory: 2sxq-n8zu Metadata Found: { "id": "2sxq-n8zu", "name": "Nowcast Predictions for Chikungunya Virus-Infected Travelers", "assetType": "dataset", "averageRating": 0, "createdAt": 1409939255, "description": "Interactive visualization: http://www.cdc.gov/chikungunya/modeling/index.html. 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In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents.\n\nNotice: Due to data processing issues at CDC, data for the following jurisdictions may be incomplete for week 7: Alaska, Arizona, California, Connecticut, Delaware, Florida, Hawaii, Louisiana, Maryland, Michigan, Missouri, North Dakota, New Hampshire, New York City, Oregon, Pennsylvania, and Rhode Island.\n\nNote: \nThis table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. \n\nFootnotes:\nU: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data.\n-: No reported cases — The reporting jurisdiction did not submit any cases to CDC.\nN: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction.\nNN: Not nationally notifiable — This condition was not designated as being nationally notifiable.\nNP: Nationally notifiable but not published.\nNC: Not calculated — There is insufficient data available to support the calculation of this statistic.\nCum: Cumulative year-to-date counts.\n Max: Maximum — Maximum case count during the previous 52 weeks.\n * Case counts for reporting years 2020 and 2021 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. \n†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). \n§ In previous years, cases were reported as Salmonellosis. Beginning in January 2019, cases began to be reported as Salmonella Paratyphi infection.\n¶ In previous years, cases were reported as typhoid fever. 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