Mmwr Surveillance Summaries最新文献

{"title":"Laboratory-Confirmed Influenza-Associated Hospitalizations Among Children and Adults - Influenza Hospitalization Surveillance Network, United States, 2010-2023.","authors":"Angelle Naquin, Alissa O'Halloran, Dawud Ujamaa, Devi Sundaresan, Svetlana Masalovich, Charisse N Cummings, Kameela Noah, Seema Jain, Pam Daily Kirley, Nisha B Alden, Elizabeth Austin, James Meek, Kimberly Yousey-Hindes, Kyle Openo, Lucy Witt, Maya L Monroe, Justin Henderson, Val Tellez Nunez, Ruth Lynfield, Melissa McMahon, Yomei P Shaw, Caroline McCahon, Nancy Spina, Kerianne Engesser, Brenda L Tesini, Maria A Gaitan, Eli Shiltz, Krista Lung, Melissa Sutton, M Andraya Hendrick, William Schaffner, H Keipp Talbot, Andrea George, Hafsa Zahid, Carrie Reed, Shikha Garg, Catherine H Bozio","doi":"10.15585/mmwr.ss7706a1","DOIUrl":"10.15585/mmwr.ss7706a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Seasonal influenza accounts for 9.3 million-41 million illnesses, 100,000-710,000 hospitalizations, and 4,900-51,000 deaths annually in the United States. Since 2003, the Influenza Hospitalization Surveillance Network (FluSurv-NET) has been conducting population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in the United States, including weekly rate estimations and descriptions of clinical characteristics and outcomes for hospitalized patients. However, a comprehensive summary of trends in hospitalization rates and clinical data collected from the surveillance platform has not been available.</p><p><strong>Reporting period: </strong>2010-11 through 2022-23 influenza seasons.</p><p><strong>Description of system: </strong>FluSurv-NET conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations among children and adults. During the reporting period, the surveillance network included 13-16 participating sites each influenza season, with prespecified geographic catchment areas that covered 27 million-29 million persons and included an estimated 8.8%-9.5% of the U.S. population. A case was defined as a person residing in the catchment area within one of the participating states who had a positive influenza laboratory test result within 14 days before or at any time during their hospitalization. Each site abstracted case data from hospital medical records into a standardized case report form, with selected variables submitted to CDC on a weekly basis for rate estimations. Weekly and cumulative laboratory-confirmed influenza-associated hospitalization rates per 100,000 population were calculated for each season from 2010-11 through 2022-23 and stratified by patient age (0-4 years, 5-17 years, 18-49 years, 50-64 years, and ≥65 years), sex, race and ethnicity, influenza type, and influenza A subtype. During the 2020-21 season, only the overall influenza hospitalization rate was reported because case counts were insufficient to estimate stratified rates.</p><p><strong>Results: </strong>During the 2010-11 to 2022-23 influenza seasons, laboratory-confirmed influenza-associated hospitalization rates varied significantly across seasons. Before the COVID-19 pandemic, hospitalization rates per 100,000 population ranged from 8.7 (2011-12) to 102.9 (2017-18) and had consistent seasonality. After SARS-CoV-2 emerged, the hospitalization rate for 2020-21 was 0.8, and the rate did not return to recent prepandemic levels until 2022-23. Inconsistent seasonality also was observed during 2020-21 through 2022-23, with influenza activity being very low during 2020-21, extending later than usual during 2021-22, and occurring early during 2022-23. Molecular assays, particularly multiplex standard molecular assays, were the most common influenza test type in recent seasons, increasing from 12% during 2017-18 for both pediatric and adult cases to 43% and 55% durin","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":37.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11537671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance for Violent Deaths - National Violent Death Reporting System, 48 States, the District of Columbia, and Puerto Rico, 2021.","authors":"Brenda L Nguyen, Bridget H Lyons, Kaitlin Forsberg, Rebecca F Wilson, Grace S Liu, Carter J Betz, Janet M Blair","doi":"10.15585/mmwr.ss7305a1","DOIUrl":"10.15585/mmwr.ss7305a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In 2021, approximately 75,000 persons died of violence-related injuries in the United States. This report summarizes data from CDC's National Violent Death Reporting System (NVDRS) on violent deaths that occurred in 48 states, the District of Columbia, and Puerto Rico in 2021. Results are reported by sex, age group, race and ethnicity, method of injury, type of location where the injury occurred, circumstances of injury, and other selected characteristics. This report introduces additional incident and circumstance variables, which now include child victim-specific circumstance information. This report also incorporates new U.S. Census Bureau race and ethnicity categories, which now account for more than one race and Native Hawaiian or other Pacific Islander categories and include updated denominators to calculate rates for these populations.</p><p><strong>Period covered: </strong>2021.</p><p><strong>Description of system: </strong>NVDRS collects data regarding violent deaths from death certificates, coroner and medical examiner records, and law enforcement reports. This report includes data collected for violent deaths that occurred in 2021. Data were collected from 48 states (all states with exception of Florida and Hawaii), the District of Columbia, and Puerto Rico. Forty-six states had statewide data, two additional states had data from counties representing a subset of their population (31 California counties, representing 64% of its population, and 13 Texas counties, representing 63% of its population), and the District of Columbia and Puerto Rico had jurisdiction-wide data. NVDRS collates information for each violent death and links deaths that are related (e.g., multiple homicides, homicide followed by suicide, or multiple suicides) into a single incident.</p><p><strong>Results: </strong>For 2021, NVDRS collected information on 68,866 fatal incidents involving 70,688 deaths that occurred in 48 states (46 states collecting statewide data, 31 California counties, and 13 Texas counties), and the District of Columbia. The deaths captured in NVDRS accounted for 86.5% of all homicides, legal intervention deaths, suicides, unintentional firearm injury deaths, and deaths of undetermined intent in the United States in 2021. In addition, information was collected for 816 fatal incidents involving 880 deaths in Puerto Rico. Data for Puerto Rico were analyzed separately. Of the 70,688 deaths, the majority (58.2%) were suicides, followed by homicides (31.5%), deaths of undetermined intent that might be due to violence (8.2%), legal intervention deaths (1.3%) (i.e., deaths caused by law enforcement and other persons with legal authority to use deadly force acting in the line of duty, excluding legal executions), and unintentional firearm injury deaths (<1.0%). The term \"legal intervention\" is a classification incorporated into the International Classification of Diseases, Tenth Revision, and does not denote the la","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":37.3,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11262823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141564863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progress Toward Tuberculosis Elimination and Tuberculosis Program Performance - National Tuberculosis Indicators Project, 2016-2022.","authors":"Rachel Woodruff, Robert Pratt, Maureen Kolasa","doi":"10.15585/mmwr.ss7304a1","DOIUrl":"10.15585/mmwr.ss7304a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Elimination of tuberculosis (TB) is defined as reducing TB disease incidence in the United States to less than 1 case per million persons per year. In 2022, TB incidence in the United States was 2.5 TB cases per 100,000 persons. CDC's TB program developed a set of national TB indicators to evaluate progress toward TB elimination through monitoring performance of state and city TB program activities. Examining TB indicator data enables state- and city-level TB programs to identify areas for program evaluation and improvement activities. These data also help CDC identify states and cities that might benefit from technical assistance.</p><p><strong>Period covered: </strong>The 5-year period for which the most recent data were available for each of five indicators: 1) overall TB incidence (2018-2022), 2) TB incidence among non-U.S.-born persons (2018-2022), 3) percentage of persons with drug susceptibility results reported (2018-2022), 4) percentage of contacts to sputum acid-fast bacillus (AFB) smear-positive TB patients with newly diagnosed latent TB infection (LTBI) who completed treatment (2017-2021), and 5) percentage of patients with completion of TB therapy within 12 months (2016-2020).</p><p><strong>Description of system: </strong>The National TB Indicators Project (NTIP) is a web-based performance monitoring tool that uses national TB surveillance data reported through the National TB Surveillance System and the Aggregate Reports for TB Program Evaluation. NTIP was developed to facilitate the use of existing data to help TB program staff members prioritize activities, monitor progress, and focus program improvement efforts. The following five indicators were selected for this report because of their importance in Federal TB funding allocation and in accelerating the decline in TB cases: 1) overall TB incidence in the United States, 2) TB incidence among non-U.S.-born persons, 3) percentage of persons with drug susceptibility results reported, 4) percentage of contacts to sputum AFB smear-positive TB cases who completed treatment for LTBI, and 5) percentage of patients with completion of TB therapy within 12 months. For this report, 52 TB programs (50 states, the District of Columbia, and New York City) were categorized into terciles based on the 5-year average number of TB cases reported to National TB Surveillance System. This grouping allows comparison of TB programs that have similar numbers of TB cases and allocates a similar number of TB programs to each category. The following formula was used to calculate the relative change by TB program for each indicator: [(% from year 5 - % from year 1 ÷ % from year 1) × 100].</p><p><strong>Results: </strong>During the 5-year period for which the most recent data were available, most TB programs had improvements in reducing overall TB incidence (71.2%) and increasing the percentage of contacts receiving a diagnosis of LTBI who completed LTBI treatment (55.8%)","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":37.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sentinel Enhanced Dengue Surveillance System - Puerto Rico, 2012-2022.","authors":"Zachary J Madewell, Alfonso C Hernandez-Romieu, Joshua M Wong, Laura D Zambrano, Hannah R Volkman, Janice Perez-Padilla, Dania M Rodriguez, Olga Lorenzi, Carla Espinet, Jorge Munoz-Jordan, Verónica M Frasqueri-Quintana, Vanessa Rivera-Amill, Luisa I Alvarado-Domenech, Diego Sainz, Jorge Bertran, Gabriela Paz-Bailey, Laura E Adams","doi":"10.15585/mmwr.ss7303a1","DOIUrl":"10.15585/mmwr.ss7303a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Dengue is the most prevalent mosquitoborne viral illness worldwide and is endemic in Puerto Rico. Dengue's clinical spectrum can range from mild, undifferentiated febrile illness to hemorrhagic manifestations, shock, multiorgan failure, and death in severe cases. The disease presentation is nonspecific; therefore, various other illnesses (e.g., arboviral and respiratory pathogens) can cause similar clinical symptoms. Enhanced surveillance is necessary to determine disease prevalence, to characterize the epidemiology of severe disease, and to evaluate diagnostic and treatment practices to improve patient outcomes. The Sentinel Enhanced Dengue Surveillance System (SEDSS) was established to monitor trends of dengue and dengue-like acute febrile illnesses (AFIs), characterize the clinical course of disease, and serve as an early warning system for viral infections with epidemic potential.</p><p><strong>Reporting period: </strong>May 2012-December 2022.</p><p><strong>Description of system: </strong>SEDSS conducts enhanced surveillance for dengue and other relevant AFIs in Puerto Rico. This report includes aggregated data collected from May 2012 through December 2022. SEDSS was launched in May 2012 with patients with AFIs from five health care facilities enrolled. The facilities included two emergency departments in tertiary acute care hospitals in the San Juan-Caguas-Guaynabo metropolitan area and Ponce, two secondary acute care hospitals in Carolina and Guayama, and one outpatient acute care clinic in Ponce. Patients arriving at any SEDSS site were eligible for enrollment if they reported having fever within the past 7 days. During the Zika epidemic (June 2016-June 2018), patients were eligible for enrollment if they had either rash and conjunctivitis, rash and arthralgia, or fever. Eligibility was expanded in April 2020 to include reported cough or shortness of breath within the past 14 days. Blood, urine, nasopharyngeal, and oropharyngeal specimens were collected at enrollment from all participants who consented. Diagnostic testing for dengue virus (DENV) serotypes 1-4, chikungunya virus, Zika virus, influenza A and B viruses, SARS-CoV-2, and five other respiratory viruses was performed by the CDC laboratory in San Juan.</p><p><strong>Results: </strong>During May 2012-December 2022, a total of 43,608 participants with diagnosed AFI were enrolled in SEDSS; a majority of participants (45.0%) were from Ponce. During the surveillance period, there were 1,432 confirmed or probable cases of dengue, 2,293 confirmed or probable cases of chikungunya, and 1,918 confirmed or probable cases of Zika. The epidemic curves of the three arboviruses indicate dengue is endemic; outbreaks of chikungunya and Zika were sporadic, with case counts peaking in late 2014 and 2016, respectively. The majority of commonly identified respiratory pathogens were influenza A virus (3,756), SARS-CoV-2 (1,586), human adenovirus (1,550), respirat","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":37.3,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11152364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141162634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preventable Premature Deaths from the Five Leading Causes of Death in Nonmetropolitan and Metropolitan Counties, United States, 2010-2022.","authors":"Macarena C García, Lauren M Rossen, Kevin Matthews, Gery Guy, Katrina F Trivers, Cheryll C Thomas, Linda Schieb, Michael F Iademarco","doi":"10.15585/mmwr.ss7302a1","DOIUrl":"10.15585/mmwr.ss7302a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>A 2019 report quantified the higher percentage of potentially excess (preventable) deaths in U.S. nonmetropolitan areas compared with metropolitan areas during 2010-2017. In that report, CDC compared national, regional, and state estimates of preventable premature deaths from the five leading causes of death in nonmetropolitan and metropolitan counties during 2010-2017. This report provides estimates of preventable premature deaths for additional years (2010-2022).</p><p><strong>Period covered: </strong>2010-2022.</p><p><strong>Description of system: </strong>Mortality data for U.S. residents from the National Vital Statistics System were used to calculate preventable premature deaths from the five leading causes of death among persons aged <80 years. CDC's National Center for Health Statistics urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Preventable premature deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Preventable premature deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and the District of Columbia.</p><p><strong>Results: </strong>During 2010-2022, the percentage of preventable premature deaths among persons aged <80 years in the United States increased for unintentional injury (e.g., unintentional poisoning including drug overdose, unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall) and stroke, decreased for cancer and chronic lower respiratory disease (CLRD), and remained stable for heart disease. The percentages of preventable premature deaths from the five leading causes of death were higher in rural counties in all years during 2010-2022. When assessed by the six urban-rural county classifications, percentages of preventable premature deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan and fringe metropolitan) for the five leading causes of death during the study period.During 2010-2022, preventable premature deaths from heart disease increased most in noncore (+9.5%) and micropolitan counties (+9.1%) and decreased most in large central metropolitan counties (-10.2%). Preventable premature deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan and large fringe metropolitan counties (-100.0%; benchmark achieved in bot","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":37.3,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11065459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140856572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance of Waterborne Disease Outbreaks Associated with Drinking Water - United States, 2015-2020.","authors":"Jasen M Kunz, Hannah Lawinger, Shanna Miko, Megan Gerdes, Muhammad Thuneibat, Elizabeth Hannapel, Virginia A Roberts","doi":"10.15585/mmwr.ss7301a1","DOIUrl":"10.15585/mmwr.ss7301a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Public health agencies in U.S. states, territories, and freely associated states investigate and voluntarily report waterborne disease outbreaks to CDC through the National Outbreak Reporting System (NORS). This report summarizes NORS drinking water outbreak epidemiologic, laboratory, and environmental data, including data for both public and private drinking water systems. The report presents outbreak-contributing factors (i.e., practices and factors that lead to outbreaks) and, for the first time, categorizes outbreaks as biofilm pathogen or enteric illness associated.</p><p><strong>Period covered: </strong>2015-2020.</p><p><strong>Description of system: </strong>CDC launched NORS in 2009 as a web-based platform into which public health departments voluntarily enter outbreak information. Through NORS, CDC collects reports of enteric disease outbreaks caused by bacterial, viral, parasitic, chemical, toxin, and unknown agents as well as foodborne and waterborne outbreaks of nonenteric disease. Data provided by NORS users, when known, for drinking water outbreaks include 1) the number of cases, hospitalizations, and deaths; 2) the etiologic agent (confirmed or suspected); 3) the implicated type of water system (e.g., community or individual or private); 4) the setting of exposure (e.g., hospital or health care facility; hotel, motel, lodge, or inn; or private residence); and 5) relevant epidemiologic and environmental data needed to describe the outbreak and characterize contributing factors.</p><p><strong>Results: </strong>During 2015-2020, public health officials from 28 states voluntarily reported 214 outbreaks associated with drinking water and 454 contributing factor types. The reported etiologies included 187 (87%) biofilm associated, 24 (11%) enteric illness associated, two (1%) unknown, and one (<1%) chemical or toxin. A total of 172 (80%) outbreaks were linked to water from public water systems, 22 (10%) to unknown water systems, 17 (8%) to individual or private systems, and two (0.9%) to other systems; one (0.5%) system type was not reported. Drinking water-associated outbreaks resulted in at least 2,140 cases of illness, 563 hospitalizations (26% of cases), and 88 deaths (4% of cases). Individual or private water systems were implicated in 944 (43%) cases, 52 (9%) hospitalizations, and 14 (16%) deaths.Enteric illness-associated pathogens were implicated in 1,299 (61%) of all illnesses, and 10 (2%) hospitalizations. No deaths were reported. Among these illnesses, three pathogens (norovirus, Shigella, and Campylobacter) or multiple etiologies including these pathogens resulted in 1,225 (94%) cases. The drinking water source was identified most often (n = 34; 7%) as the contributing factor in enteric disease outbreaks. When water source (e.g., groundwater) was known (n = 14), wells were identified in 13 (93%) of enteric disease outbreaks.Most biofilm-related outbreak reports implicated Legionella (n =","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":24.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140111922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abortion Surveillance - United States, 2021.","authors":"Katherine Kortsmit, Antoinette T Nguyen, Michele G Mandel, Lisa M Hollier, Stephanie Ramer, Jessica Rodenhizer, Maura K Whiteman","doi":"10.15585/mmwr.ss7209a1","DOIUrl":"10.15585/mmwr.ss7209a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>CDC conducts abortion surveillance to document the number and characteristics of women obtaining legal induced abortions and number of abortion-related deaths in the United States.</p><p><strong>Period covered: </strong>2021.</p><p><strong>Description of system: </strong>Each year, CDC requests abortion data from the central health agencies for the 50 states, the District of Columbia, and New York City. For 2021, a total of 48 reporting areas voluntarily provided aggregate abortion data to CDC. Of these, 47 reporting areas provided data each year during 2012-2021. Census and natality data were used to calculate abortion rates (number of abortions per 1,000 women aged 15-44 years) and ratios (number of abortions per 1,000 live births), respectively. Abortion-related deaths from 2020 were assessed as part of CDC's Pregnancy Mortality Surveillance System (PMSS).</p><p><strong>Results: </strong>A total of 625,978 abortions for 2021 were reported to CDC from 48 reporting areas. Among 47 reporting areas with data each year during 2012-2021, in 2021, a total of 622,108 abortions were reported, the abortion rate was 11.6 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 204 abortions per 1,000 live births. From 2020 to 2021, the total number of abortions increased 5% (from 592,939 total abortions), the abortion rate increased 5% (from 11.1 abortions per 1,000 women aged 15-44 years), and the abortion ratio increased 4% (from 197 abortions per 1,000 live births). From 2012 to 2021, the total number of reported abortions decreased 8% (from 673,634), the abortion rate decreased 11% (from 13.1 abortions per 1,000 women aged 15-44 years), and the abortion ratio decreased 1% (from 207 abortions per 1,000 live births).In 2021, women in their 20s accounted for more than half of abortions (57.0%). Women aged 20-24 and 25-29 years accounted for the highest percentages of abortions (28.3% and 28.7%, respectively) and had the highest abortion rates (19.7 and 19.4 abortions per 1,000 women aged 20-24 and 25-29 years, respectively). By contrast, adolescents aged <15 years and women aged ≥40 years accounted for the lowest percentages of abortions (0.2% and 3.6%, respectively) and had the lowest abortion rates (0.4 and 2.5 abortions per 1,000 women aged <15 and ≥40 years, respectively). However, abortion ratios were highest among adolescents (aged ≤19 years) and lowest among women aged 30-39 years.From 2020 to 2021, abortion rates increased among women aged 20-39 years, decreased among adolescents aged 15-19 years, and did not change among adolescents aged <15 years and women aged ≥40 years. Abortion rates decreased from 2012 to 2021 among all age groups, except women aged 30-34 years for whom it increased. The decrease in the abortion rate from 2012 to 2021 was highest among adolescents compared with any other age group. From 2020 to 2021, abortion ratios increased for women aged 15-24 years, decreased among a","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":24.9,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138296198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatalities in Oil and Gas Extraction Database, an Industry-Specific Worker Fatality Surveillance System - United States, 2014-2019.","authors":"Kaitlin C Wingate,&nbsp;Alejandra Ramirez-Cardenas,&nbsp;Ryan Hill,&nbsp;Sophia Ridl,&nbsp;Kyla Hagan-Haynes","doi":"10.15585/mmwr.ss7208a1","DOIUrl":"10.15585/mmwr.ss7208a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>The U.S. oil and gas extraction (OGE) industry faces unique safety and health hazards and historically elevated fatality rates. The lack of existing surveillance data and occupational safety and health research called for increased efforts to better understand factors contributing to worker fatalities in the OGE industry. This report describes the creation of the Fatalities in Oil and Gas Extraction (FOG) database, presents initial findings from the first 6 years of data collection (2014-2019), highlights ways that FOG data have been used, and describes the benefits and challenges of maintaining the surveillance system.</p><p><strong>Period covered: </strong>2014-2019.</p><p><strong>Description of system: </strong>In 2013, the National Institute for Occupational Safety and Health (NIOSH) created the FOG database, a surveillance system comprising an industry-specific worker fatality database. NIOSH researchers worked with OGE partners to establish inclusion criteria for the database and develop unique database variables to elucidate industry-specific factors related to each fatality (e.g., phase of operation, worker activity, and working alone). FOG cases are identified through various sources, such as Occupational Safety and Health Administration (OSHA) reports, media reports, and notifications from professional contacts. NIOSH researchers compile source documents; OGE-specific database variables are coded by multiple researchers to ensure accuracy. Data collection ceased in 2019 because grant funding ended.</p><p><strong>Results: </strong>During 2014-2019, a total of 470 OGE worker fatalities were identified in the FOG database. A majority of these fatalities (69.4%) were identified from OSHA reports and Google Alerts (44.7% and 24.7%, respectively). Unique database variables created to characterize fatalities in the OGE industry (i.e., phase of operation, worker activity, working alone, and working unobserved) were identified in approximately 85% of OGE worker fatality cases. The most frequent fatal events were vehicle incidents (26.8%), contact injuries (21.7%), and explosions (14.5%). The event type was unknown among 5.7% of worker fatalities. Approximately three fourths of fatalities identified through the FOG database were among contractors. Approximately 20% of cases included workers who were working alone.</p><p><strong>Interpretation: </strong>The FOG database is a resource for identifying safety and health trends and emerging issues among OGE workers (e.g., exposure to hydrocarbon gases and vapors and fatalities resulting from cardiac events) that might not be available in other surveillance systems. The FOG database also helps researchers better identify groups of workers that are at increased risk for injury in an already high-risk industry. Challenges exist when maintaining an industry-specific surveillance system, including labor-intensive data collection, the need for researchers with substant","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":24.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10136148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Travel-Related Diagnoses Among U.S. Nonmigrant Travelers or Migrants Presenting to U.S. GeoSentinel Sites - GeoSentinel Network, 2012-2021.","authors":"Ashley B Brown, Charles Miller, Davidson H Hamer, Phyllis Kozarsky, Michael Libman, Ralph Huits, Aisha Rizwan, Hannah Emetulu, Jesse Waggoner, Lin H Chen, Daniel T Leung, Daniel Bourque, Bradley A Connor, Carmelo Licitra, Kristina M Angelo","doi":"10.15585/mmwr.ss7207a1","DOIUrl":"10.15585/mmwr.ss7207a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>During 2012-2021, the volume of international travel reached record highs and lows. This period also was marked by the emergence or large outbreaks of multiple infectious diseases (e.g., Zika virus, yellow fever, and COVID-19). Over time, the growing ease and increased frequency of travel has resulted in the unprecedented global spread of infectious diseases. Detecting infectious diseases and other diagnoses among travelers can serve as sentinel surveillance for new or emerging pathogens and provide information to improve case identification, clinical management, and public health prevention and response.</p><p><strong>Reporting period: </strong>2012-2021.</p><p><strong>Description of system: </strong>Established in 1995, the GeoSentinel Network (GeoSentinel), a collaboration between CDC and the International Society of Travel Medicine, is a global, clinical-care-based surveillance and research network of travel and tropical medicine sites that monitors infectious diseases and other adverse health events that affect international travelers. GeoSentinel comprises 71 sites in 29 countries where clinicians diagnose illnesses and collect demographic, clinical, and travel-related information about diseases and illnesses acquired during travel using a standardized report form. Data are collected electronically via a secure CDC database, and daily reports are generated for assistance in detecting sentinel events (i.e., unusual patterns or clusters of disease). GeoSentinel sites collaborate to report disease or population-specific findings through retrospective database analyses and the collection of supplemental data to fill specific knowledge gaps. GeoSentinel also serves as a communications network by using internal notifications, ProMed alerts, and peer-reviewed publications to alert clinicians and public health professionals about global outbreaks and events that might affect travelers. This report summarizes data from 20 U.S. GeoSentinel sites and reports on the detection of three worldwide events that demonstrate GeoSentinel's notification capability.</p><p><strong>Results: </strong>During 2012-2021, data were collected by all GeoSentinel sites on approximately 200,000 patients who had approximately 244,000 confirmed or probable travel-related diagnoses. Twenty GeoSentinel sites from the United States contributed records during the 10-year surveillance period, submitting data on 18,336 patients, of which 17,389 lived in the United States and were evaluated by a clinician at a U.S. site after travel. Of those patients, 7,530 (43.3%) were recent migrants to the United States, and 9,859 (56.7%) were returning nonmigrant travelers.Among the recent migrants to the United States, the median age was 28.5 years (range = <19 years to 93 years); 47.3% were female, and 6.0% were U.S. citizens. A majority (89.8%) were seen as outpatients, and among 4,672 migrants with information available, 4,148 (88.8%) did not receive ","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":24.9,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9772552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foodborne Illness Outbreaks at Retail Food Establishments - National Environmental Assessment Reporting System, 25 State and Local Health Departments, 2017-2019.","authors":"Erin D Moritz,&nbsp;Shideh Delrahim Ebrahim-Zadeh,&nbsp;Beth Wittry,&nbsp;Meghan M Holst,&nbsp;Bresa Daise,&nbsp;Adria Zern,&nbsp;Tonia Taylor,&nbsp;Adam Kramer,&nbsp;Laura G Brown","doi":"10.15585/mmwr.ss7206a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss7206a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Each year, state and local public health departments report hundreds of foodborne illness outbreaks associated with retail food establishments (e.g., restaurants or caterers) to CDC. Typically, investigations involve epidemiology, laboratory, and environmental health components. Health departments voluntarily report epidemiologic and laboratory data from their foodborne illness outbreak investigations to CDC through the National Outbreak Reporting System (NORS); however, minimal environmental health data from outbreak investigations are reported to NORS. This report summarizes environmental health data collected during outbreak investigations and reported to the National Environmental Assessment Reporting System (NEARS).</p><p><strong>Period covered: </strong>2017-2019.</p><p><strong>Description of system: </strong>In 2014, CDC launched NEARS to complement NORS surveillance and to use these data to enhance prevention efforts. State and local health departments voluntarily enter data from their foodborne illness outbreak investigations of retail food establishments into NEARS. These data include characteristics of foodborne illness outbreaks (e.g., etiologic agent and factors contributing to the outbreak), characteristics of establishments with outbreaks (e.g., number of meals served daily), and food safety policies in these establishments (e.g., ill worker policy requirements). NEARS is the only available data source that collects environmental characteristics of retail establishments with foodborne illness outbreaks.</p><p><strong>Results: </strong>During 2017-2019, a total of 800 foodborne illness outbreaks associated with 875 retail food establishments were reported to NEARS by 25 state and local health departments. Among outbreaks with a confirmed or suspected agent (555 of 800 [69.4%]), the most common pathogens were norovirus and Salmonella, accounting for 47.0% and 18.6% of outbreaks, respectively. Contributing factors were identified in 62.5% of outbreaks. Approximately 40% of outbreaks with identified contributing factors had at least one reported factor associated with food contamination by an ill or infectious food worker. Investigators conducted an interview with an establishment manager in 679 (84.9%) outbreaks. Of the 725 managers interviewed, most (91.7%) said their establishment had a policy requiring food workers to notify their manager when they were ill, and 66.0% also said these policies were written. Only 23.0% said their policy listed all five illness symptoms workers needed to notify managers about (i.e., vomiting, diarrhea, jaundice, sore throat with fever, and lesion with pus). Most (85.5%) said that their establishment had a policy restricting or excluding ill workers from working, and 62.4% said these policies were written. Only 17.8% said their policy listed all five illness symptoms that would require restriction or exclusion from work. Only 16.1% of establishments with outbreaks","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":null,"pages":null},"PeriodicalIF":24.9,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10231936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9564273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}