Kaitlin C Wingate, Alejandra Ramirez-Cardenas, Ryan Hill, Sophia Ridl, Kyla Hagan-Haynes
<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
{"title":"Fatalities in Oil and Gas Extraction Database, an Industry-Specific Worker Fatality Surveillance System - United States, 2014-2019.","authors":"Kaitlin C Wingate, Alejandra Ramirez-Cardenas, Ryan Hill, Sophia Ridl, 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":"72 8","pages":"1-15"},"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}
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
<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
{"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":"72 7","pages":"1-22"},"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}
Erin D Moritz, Shideh Delrahim Ebrahim-Zadeh, Beth Wittry, Meghan M Holst, Bresa Daise, Adria Zern, Tonia Taylor, Adam Kramer, Laura G Brown
<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
{"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, Shideh Delrahim Ebrahim-Zadeh, Beth Wittry, Meghan M Holst, Bresa Daise, Adria Zern, Tonia Taylor, Adam Kramer, 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":"72 6","pages":"1-11"},"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}
Grace S Liu, Brenda L Nguyen, Bridget H Lyons, Kameron J Sheats, Rebecca F Wilson, Carter J Betz, Katherine A Fowler
<p><strong>Problem/condition: </strong>In 2020, approximately 71,000 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 2020. 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.</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>NVDRS collects data regarding violent deaths obtained from death certificates, coroner and medical examiner records, and law enforcement reports. This report includes data collected for violent deaths that occurred in 2020. 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 (35 California counties, representing 71% of its population, and four Texas counties, representing 39% 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 2020, NVDRS collected information on 64,388 fatal incidents involving 66,017 deaths that occurred in 48 states (46 states collecting statewide data, 35 California counties, and four Texas counties), and the District of Columbia. In addition, information was collected for 729 fatal incidents involving 790 deaths in Puerto Rico. Data for Puerto Rico were analyzed separately. Of the 66,017 deaths, the majority (58.4%) were suicides, followed by homicides (31.3%), deaths of undetermined intent (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 deaths (<1.0%). The term "legal intervention" is a classification incorporated into the International Classification of Diseases, Tenth Revision, and does not denote the lawfulness or legality of the circumstances surrounding a death caused by law enforcement.Demographic patterns and circumstances varied by manner of death. The suicide rate was higher for males than for females. Across all age groups, the suicide rate was highest among adults aged ≥85 years. In addition, non-Hispanic American Indian or Alaska Native (AI/AN) persons had the highest suicide rates among all racial and ethnic groups. Among both males and females, the most common method of injury for suicide was a firearm. Among all suicide victims, when circumstances were known, suicide was most often preceded by a mental
{"title":"Surveillance for Violent Deaths - National Violent Death Reporting System, 48 States, the District of Columbia, and Puerto Rico, 2020.","authors":"Grace S Liu, Brenda L Nguyen, Bridget H Lyons, Kameron J Sheats, Rebecca F Wilson, Carter J Betz, Katherine A Fowler","doi":"10.15585/mmwr.ss7205a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss7205a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In 2020, approximately 71,000 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 2020. 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.</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>NVDRS collects data regarding violent deaths obtained from death certificates, coroner and medical examiner records, and law enforcement reports. This report includes data collected for violent deaths that occurred in 2020. 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 (35 California counties, representing 71% of its population, and four Texas counties, representing 39% 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 2020, NVDRS collected information on 64,388 fatal incidents involving 66,017 deaths that occurred in 48 states (46 states collecting statewide data, 35 California counties, and four Texas counties), and the District of Columbia. In addition, information was collected for 729 fatal incidents involving 790 deaths in Puerto Rico. Data for Puerto Rico were analyzed separately. Of the 66,017 deaths, the majority (58.4%) were suicides, followed by homicides (31.3%), deaths of undetermined intent (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 deaths (<1.0%). The term \"legal intervention\" is a classification incorporated into the International Classification of Diseases, Tenth Revision, and does not denote the lawfulness or legality of the circumstances surrounding a death caused by law enforcement.Demographic patterns and circumstances varied by manner of death. The suicide rate was higher for males than for females. Across all age groups, the suicide rate was highest among adults aged ≥85 years. In addition, non-Hispanic American Indian or Alaska Native (AI/AN) persons had the highest suicide rates among all racial and ethnic groups. Among both males and females, the most common method of injury for suicide was a firearm. Among all suicide victims, when circumstances were known, suicide was most often preceded by a mental","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"72 5","pages":"1-38"},"PeriodicalIF":24.9,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9923219","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}
Kyle R Ryff, Aidsa Rivera, Dania M Rodriguez, Gilberto A Santiago, Freddy A Medina, Esther M Ellis, Jomil Torres, Ann Pobutsky, Jorge Munoz-Jordan, Gabriela Paz-Bailey, Laura E Adams
<p><strong>Problem/condition: </strong>Dengue is one of the most common vectorborne flaviviral infections globally, with frequent outbreaks in tropical regions. In 2019 and 2020, the Pan American Health Organization reported approximately 5.5 million dengue cases from the Americas, the highest number on record. In the United States, local dengue virus (DENV) transmission has been reported from all U.S. territories, which are characterized by tropical climates that are highly suitable for Aedes species of mosquitoes, the vector that transmits dengue. Dengue is endemic in the U.S. territories of American Samoa, Puerto Rico, and the U.S. Virgin Islands (USVI). Dengue risk in Guam and the Commonwealth of the Northern Mariana Islands is considered sporadic or uncertain. Despite all U.S. territories reporting local dengue transmission, epidemiologic trends over time have not been well described.</p><p><strong>Reporting period: </strong>2010-2020.</p><p><strong>Description of system: </strong>State and territorial health departments report dengue cases to CDC through ArboNET, the national arboviral surveillance system, which was developed in 2000 to monitor West Nile virus infections. Dengue became nationally notifiable in ArboNET in 2010. Dengue cases reported to ArboNET are categorized using the 2015 Council of State and Territorial Epidemiologists case definition. In addition, DENV serotyping is performed at CDC's Dengue Branch Laboratory in a subset of specimens to support identification of circulating DENV serotypes.</p><p><strong>Results: </strong>During 2010-2020, a total of 30,903 dengue cases were reported from four U.S. territories to ArboNET. Puerto Rico reported the highest number of dengue cases (29,862 [96.6%]), followed by American Samoa (660 [2.1%]), USVI (353 [1.1%]), and Guam (28 [0.1%]). However, annual incidence rates were highest in American Samoa with 10.2 cases per 1,000 population in 2017, followed by Puerto Rico with 2.9 in 2010 and USVI with 1.6 in 2013. Approximately one half (50.6%) of cases occurred among persons aged <20 years. The proportion of persons with dengue who were hospitalized was high in three of the four territories: 45.5% in American Samoa, 32.6% in Puerto Rico, and 32.1% in Guam. In Puerto Rico and USVI, approximately 2% of reported cases were categorized as severe dengue. Of all dengue-associated deaths, 68 (0.2%) were reported from Puerto Rico; no deaths were reported from the other territories. During 2010-2020, DENV-1 and DENV-4 were the predominant serotypes in Puerto Rico and USVI.</p><p><strong>Interpretation: </strong>U.S. territories experienced a high prevalence of dengue during 2010-2020, with approximately 30,000 cases reported, and a high incidence during outbreak years. Children and adolescents aged <20 years were disproportionately affected, highlighting the need for interventions tailored for this population. Ongoing education about dengue clinical management for health care providers in U.S. t
问题/状况:登革热是全球最常见的媒介传播的黄病毒感染之一，经常在热带地区暴发。2019年和2020年，泛美卫生组织报告了美洲约550万例登革热病例，这是有记录以来的最高数字。在美国，所有美国领土都报告了当地登革热病毒(DENV)传播，这些领土的特点是热带气候，非常适合传播登革热的媒介伊蚊。登革热是美国属地美属萨摩亚、波多黎各和美属维尔京群岛(USVI)的地方病。关岛和北马里亚纳群岛联邦的登革热风险被认为是零星的或不确定的。尽管所有美国领土都报告了当地登革热传播，但长期以来的流行趋势尚未得到很好的描述。报告期:2010-2020年。系统描述:州和地区卫生部门通过国家虫媒病毒监测系统ArboNET向疾病预防控制中心报告登革热病例，该系统是2000年为监测西尼罗河病毒感染而开发的。登革热于2010年在ArboNET中成为全国必须报告的疾病。报告给ArboNET的登革热病例使用2015年州和地区流行病学家委员会的病例定义进行分类。此外，在疾控中心登革热分科实验室对一部分标本进行登革热病毒血清分型，以支持对流行登革热病毒血清型的识别。结果:2010-2020年期间，美国4个领土共报告了30,903例登革热病例。波多黎各报告的登革热病例数最多(29,862例[96.6%])，其次是美属萨摩亚(660例[2.1%])、美属维尔京群岛(353例[1.1%])和关岛(28例[0.1%])。然而，年发病率最高的是美属萨摩亚，2017年每1000人中有10.2例病例，其次是波多黎各，2010年为2.9例，美属维尔京群岛2013年为1.6例。解释:美国领土在2010-2020年期间经历了登革热的高流行，报告了大约30,000例病例，并且在爆发年份发病率很高。公共卫生行动:免疫做法咨询委员会建议对既往有登革热感染证据并生活在登革热流行地区的9-16岁儿童接种登卡夏疫苗。登革热疫苗的建议为公共卫生专业人员和卫生保健提供者提供了一种新的干预措施，以预防四个地区疾病负担最高的年龄组的疾病和住院(Paz Bailey G, Adams L, Wong JM，等)。登革热疫苗:免疫做法咨询委员会的建议，美国，2021年。MMWR提案Rep 2021;70[No. 7]RR-6])。美属萨摩亚、波多黎各和美属维尔京群岛都被认为是流行地区，居住在这些地区的人有资格接种新的登革热疫苗。在那些有既往登革热感染实验室证据的司法管辖区，9-16岁的人可以接种登革热疫苗，从而降低出现症状性疾病、住院或严重登革热的风险。这些地区的卫生保健提供者应熟悉接种疫苗的资格标准和建议，以减轻有症状疾病最高风险人群的登革热负担。对卫生保健提供者进行关于登革热病例识别和管理的教育，可以改善患者的预后，并改善登革热病例的监测和报告。
{"title":"Epidemiologic Trends of Dengue in U.S. Territories, 2010-2020.","authors":"Kyle R Ryff, Aidsa Rivera, Dania M Rodriguez, Gilberto A Santiago, Freddy A Medina, Esther M Ellis, Jomil Torres, Ann Pobutsky, Jorge Munoz-Jordan, Gabriela Paz-Bailey, Laura E Adams","doi":"10.15585/mmwr.ss7204a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss7204a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Dengue is one of the most common vectorborne flaviviral infections globally, with frequent outbreaks in tropical regions. In 2019 and 2020, the Pan American Health Organization reported approximately 5.5 million dengue cases from the Americas, the highest number on record. In the United States, local dengue virus (DENV) transmission has been reported from all U.S. territories, which are characterized by tropical climates that are highly suitable for Aedes species of mosquitoes, the vector that transmits dengue. Dengue is endemic in the U.S. territories of American Samoa, Puerto Rico, and the U.S. Virgin Islands (USVI). Dengue risk in Guam and the Commonwealth of the Northern Mariana Islands is considered sporadic or uncertain. Despite all U.S. territories reporting local dengue transmission, epidemiologic trends over time have not been well described.</p><p><strong>Reporting period: </strong>2010-2020.</p><p><strong>Description of system: </strong>State and territorial health departments report dengue cases to CDC through ArboNET, the national arboviral surveillance system, which was developed in 2000 to monitor West Nile virus infections. Dengue became nationally notifiable in ArboNET in 2010. Dengue cases reported to ArboNET are categorized using the 2015 Council of State and Territorial Epidemiologists case definition. In addition, DENV serotyping is performed at CDC's Dengue Branch Laboratory in a subset of specimens to support identification of circulating DENV serotypes.</p><p><strong>Results: </strong>During 2010-2020, a total of 30,903 dengue cases were reported from four U.S. territories to ArboNET. Puerto Rico reported the highest number of dengue cases (29,862 [96.6%]), followed by American Samoa (660 [2.1%]), USVI (353 [1.1%]), and Guam (28 [0.1%]). However, annual incidence rates were highest in American Samoa with 10.2 cases per 1,000 population in 2017, followed by Puerto Rico with 2.9 in 2010 and USVI with 1.6 in 2013. Approximately one half (50.6%) of cases occurred among persons aged <20 years. The proportion of persons with dengue who were hospitalized was high in three of the four territories: 45.5% in American Samoa, 32.6% in Puerto Rico, and 32.1% in Guam. In Puerto Rico and USVI, approximately 2% of reported cases were categorized as severe dengue. Of all dengue-associated deaths, 68 (0.2%) were reported from Puerto Rico; no deaths were reported from the other territories. During 2010-2020, DENV-1 and DENV-4 were the predominant serotypes in Puerto Rico and USVI.</p><p><strong>Interpretation: </strong>U.S. territories experienced a high prevalence of dengue during 2010-2020, with approximately 30,000 cases reported, and a high incidence during outbreak years. Children and adolescents aged <20 years were disproportionately affected, highlighting the need for interventions tailored for this population. Ongoing education about dengue clinical management for health care providers in U.S. t","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"72 4","pages":"1-12"},"PeriodicalIF":24.9,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9520400","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}
Kathryn Miele, Shin Y Kim, Rachelle Jones, Juneka H Rembert, Elisha M Wachman, Hira Shrestha, Michelle L Henninger, Teresa M Kimes, Patrick D Schneider, Vaseekaran Sivaloganathan, Katherine A Sward, Vikrant G Deshmukh, Pilar M Sanjuan, Jessie R Maxwell, Neil S Seligman, Sarah Caveglia, Judette M Louis, Tanner Wright, Carolyne Cody Bennett, Caitlin Green, Nisha George, Lucas Gosdin, Emmy L Tran, Dana Meaney-Delman, Suzanne M Gilboa
<p><strong>Problem: </strong>Medication for opioid use disorder (MOUD) is recommended for persons with opioid use disorder (OUD) during pregnancy. However, knowledge gaps exist about best practices for management of OUD during pregnancy and these data are needed to guide clinical care.</p><p><strong>Period covered: </strong>2014-2021.</p><p><strong>Description of the system: </strong>Established in 2019, the Maternal and Infant Network to Understand Outcomes Associated with Medication for Opioid Use Disorder During Pregnancy (MAT-LINK) is a surveillance network of seven clinical sites in the United States. Boston Medical Center, Kaiser Permanente Northwest, The Ohio State University, and the University of Utah were the initial clinical sites in 2019. In 2021, three clinical sites were added to the network (the University of New Mexico, the University of Rochester, and the University of South Florida). Persons receiving care at the seven clinical sites are diverse in terms of geography, urbanicity, race and ethnicity, insurance coverage, and type of MOUD received. The goal of MAT-LINK is to capture demographic and clinical information about persons with OUD during pregnancy to better understand the effect of MOUD on outcomes and, ultimately, provide information for clinical care and public health interventions for this population. MAT-LINK maintains strict confidentiality through robust information technology architecture. MAT-LINK surveillance methods, population characteristics, and evaluation findings are described in this inaugural surveillance report. This report is the first to describe the system, presenting detailed information on funding, structure, data elements, and methods as well as findings from a surveillance evaluation. The findings presented in this report are limited to selected demographic characteristics of pregnant persons overall and by MOUD treatment status. Clinical and outcome data are not included because data collection and cleaning have not been completed; initial analyses of clinical and outcome data will begin in 2023.</p><p><strong>Results: </strong>The MAT-LINK surveillance network gathered data on 5,541 reported pregnancies with a known pregnancy outcome during 2014-2021 among persons with OUD from seven clinical sites. The mean maternal age was 29.7 (SD = ±5.1) years. By race and ethnicity, 86.3% of pregnant persons were identified as White, 25.4% as Hispanic or Latino, and 5.8% as Black or African American. Among pregnant persons, 81.6% had public insurance, and 84.4% lived in urban areas. Compared with persons not receiving MOUD during pregnancy, those receiving MOUD during pregnancy were more likely to be older and White and to have public insurance. The evaluation of the surveillance system found that the initial four clinical sites were not representative of demographics of the South or Southwest regions of the United States and had low representation from certain racial and ethnic groups compared with the ov
{"title":"Medication for Opioid Use Disorder During Pregnancy - Maternal and Infant Network to Understand Outcomes Associated with Use of Medication for Opioid Use Disorder During Pregnancy (MAT-LINK), 2014-2021.","authors":"Kathryn Miele, Shin Y Kim, Rachelle Jones, Juneka H Rembert, Elisha M Wachman, Hira Shrestha, Michelle L Henninger, Teresa M Kimes, Patrick D Schneider, Vaseekaran Sivaloganathan, Katherine A Sward, Vikrant G Deshmukh, Pilar M Sanjuan, Jessie R Maxwell, Neil S Seligman, Sarah Caveglia, Judette M Louis, Tanner Wright, Carolyne Cody Bennett, Caitlin Green, Nisha George, Lucas Gosdin, Emmy L Tran, Dana Meaney-Delman, Suzanne M Gilboa","doi":"10.15585/mmwr.ss7203a1","DOIUrl":"10.15585/mmwr.ss7203a1","url":null,"abstract":"<p><strong>Problem: </strong>Medication for opioid use disorder (MOUD) is recommended for persons with opioid use disorder (OUD) during pregnancy. However, knowledge gaps exist about best practices for management of OUD during pregnancy and these data are needed to guide clinical care.</p><p><strong>Period covered: </strong>2014-2021.</p><p><strong>Description of the system: </strong>Established in 2019, the Maternal and Infant Network to Understand Outcomes Associated with Medication for Opioid Use Disorder During Pregnancy (MAT-LINK) is a surveillance network of seven clinical sites in the United States. Boston Medical Center, Kaiser Permanente Northwest, The Ohio State University, and the University of Utah were the initial clinical sites in 2019. In 2021, three clinical sites were added to the network (the University of New Mexico, the University of Rochester, and the University of South Florida). Persons receiving care at the seven clinical sites are diverse in terms of geography, urbanicity, race and ethnicity, insurance coverage, and type of MOUD received. The goal of MAT-LINK is to capture demographic and clinical information about persons with OUD during pregnancy to better understand the effect of MOUD on outcomes and, ultimately, provide information for clinical care and public health interventions for this population. MAT-LINK maintains strict confidentiality through robust information technology architecture. MAT-LINK surveillance methods, population characteristics, and evaluation findings are described in this inaugural surveillance report. This report is the first to describe the system, presenting detailed information on funding, structure, data elements, and methods as well as findings from a surveillance evaluation. The findings presented in this report are limited to selected demographic characteristics of pregnant persons overall and by MOUD treatment status. Clinical and outcome data are not included because data collection and cleaning have not been completed; initial analyses of clinical and outcome data will begin in 2023.</p><p><strong>Results: </strong>The MAT-LINK surveillance network gathered data on 5,541 reported pregnancies with a known pregnancy outcome during 2014-2021 among persons with OUD from seven clinical sites. The mean maternal age was 29.7 (SD = ±5.1) years. By race and ethnicity, 86.3% of pregnant persons were identified as White, 25.4% as Hispanic or Latino, and 5.8% as Black or African American. Among pregnant persons, 81.6% had public insurance, and 84.4% lived in urban areas. Compared with persons not receiving MOUD during pregnancy, those receiving MOUD during pregnancy were more likely to be older and White and to have public insurance. The evaluation of the surveillance system found that the initial four clinical sites were not representative of demographics of the South or Southwest regions of the United States and had low representation from certain racial and ethnic groups compared with the ov","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"72 3","pages":"1-14"},"PeriodicalIF":37.3,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154076/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10297375","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}
Kelly A Shaw, Deborah A Bilder, Dedria McArthur, Ashley Robinson Williams, Esther Amoakohene, Amanda V Bakian, Maureen S Durkin, Robert T Fitzgerald, Sarah M Furnier, Michelle M Hughes, Elise T Pas, Angelica Salinas, Zachary Warren, Susan Williams, Amy Esler, Andrea Grzybowski, Christine M Ladd-Acosta, Mary Patrick, Walter Zahorodny, Katie K Green, Jennifer Hall-Lande, Maya Lopez, Kristen Clancy Mancilla, Ruby H N Nguyen, Karen Pierce, Yvette D Schwenk, Josephine Shenouda, Kate Sidwell, Alison Vehorn, Monica DiRienzo, Johanna Gutierrez, Libby Hallas, Allison Hudson, Margaret H Spivey, Sydney Pettygrove, Anita Washington, Matthew J Maenner
<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years. In 2020, a total of 11 sites (located in Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) conducted surveillance of ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2020. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in an evaluation, 2) a special education classification of autism (eligibility), or 3) an ASD International Classification of Diseases (ICD) code (revisions 9 or 10). Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had a documented qualified professional's statement indicating a suspicion of ASD. This report focuses on children aged 4 years in 2020 compared with children aged 8 years in 2020.</p><p><strong>Results: </strong>For 2020, ASD prevalence among children aged 4 years varied across sites, from 12.7 per 1,000 children in Utah to 46.4 in California. The overall prevalence was 21.5 and was higher among boys than girls at every site. Compared with non-Hispanic White children, ASD prevalence was 1.8 times as high among Hispanic, 1.6 times as high among non-Hispanic Black, 1.4 times as high among Asian or Pacific Islander, and 1.2 times as high among multiracial children. Among the 58.3% of children aged 4 years with ASD and information on intellectual ability, 48.5% had an IQ score of ≤70 on their most recent IQ test or an examiner's statement of intellectual disability. Among children with a documented developmental evaluation, 78.0% were evaluated by age 36 months. Children aged 4 years had a higher cumulative incidence of ASD diagnosis or eligibility by age 48 months compared with children aged 8 years at all sites; risk ratios ranged from 1.3 in New Jersey and Utah to 2.0 in Tennessee. In the 6 months before the March 2020 COVID-19 pandemic declaration by the World Health Organization, there were 1,593 more evaluations and 1.89 more ASD identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. After the COVID-19 pandemic declaration, this pattern reversed: in the 6 months after pandemic onset, there were 217 fewer evaluations and 0.26 fewer identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. Patterns of evaluation and identification varied among sites, but there was not recovery to pre-COVID-19 pandemic levels by the end of 2020 at most sites or overall. For 2020
{"title":"Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.","authors":"Kelly A Shaw, Deborah A Bilder, Dedria McArthur, Ashley Robinson Williams, Esther Amoakohene, Amanda V Bakian, Maureen S Durkin, Robert T Fitzgerald, Sarah M Furnier, Michelle M Hughes, Elise T Pas, Angelica Salinas, Zachary Warren, Susan Williams, Amy Esler, Andrea Grzybowski, Christine M Ladd-Acosta, Mary Patrick, Walter Zahorodny, Katie K Green, Jennifer Hall-Lande, Maya Lopez, Kristen Clancy Mancilla, Ruby H N Nguyen, Karen Pierce, Yvette D Schwenk, Josephine Shenouda, Kate Sidwell, Alison Vehorn, Monica DiRienzo, Johanna Gutierrez, Libby Hallas, Allison Hudson, Margaret H Spivey, Sydney Pettygrove, Anita Washington, Matthew J Maenner","doi":"10.15585/mmwr.ss7201a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss7201a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years. In 2020, a total of 11 sites (located in Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) conducted surveillance of ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2020. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in an evaluation, 2) a special education classification of autism (eligibility), or 3) an ASD International Classification of Diseases (ICD) code (revisions 9 or 10). Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had a documented qualified professional's statement indicating a suspicion of ASD. This report focuses on children aged 4 years in 2020 compared with children aged 8 years in 2020.</p><p><strong>Results: </strong>For 2020, ASD prevalence among children aged 4 years varied across sites, from 12.7 per 1,000 children in Utah to 46.4 in California. The overall prevalence was 21.5 and was higher among boys than girls at every site. Compared with non-Hispanic White children, ASD prevalence was 1.8 times as high among Hispanic, 1.6 times as high among non-Hispanic Black, 1.4 times as high among Asian or Pacific Islander, and 1.2 times as high among multiracial children. Among the 58.3% of children aged 4 years with ASD and information on intellectual ability, 48.5% had an IQ score of ≤70 on their most recent IQ test or an examiner's statement of intellectual disability. Among children with a documented developmental evaluation, 78.0% were evaluated by age 36 months. Children aged 4 years had a higher cumulative incidence of ASD diagnosis or eligibility by age 48 months compared with children aged 8 years at all sites; risk ratios ranged from 1.3 in New Jersey and Utah to 2.0 in Tennessee. In the 6 months before the March 2020 COVID-19 pandemic declaration by the World Health Organization, there were 1,593 more evaluations and 1.89 more ASD identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. After the COVID-19 pandemic declaration, this pattern reversed: in the 6 months after pandemic onset, there were 217 fewer evaluations and 0.26 fewer identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. Patterns of evaluation and identification varied among sites, but there was not recovery to pre-COVID-19 pandemic levels by the end of 2020 at most sites or overall. For 2020","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"72 1","pages":"1-15"},"PeriodicalIF":24.9,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9265452","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}
Matthew J Maenner, Zachary Warren, Ashley Robinson Williams, Esther Amoakohene, Amanda V Bakian, Deborah A Bilder, Maureen S Durkin, Robert T Fitzgerald, Sarah M Furnier, Michelle M Hughes, Christine M Ladd-Acosta, Dedria McArthur, Elise T Pas, Angelica Salinas, Alison Vehorn, Susan Williams, Amy Esler, Andrea Grzybowski, Jennifer Hall-Lande, Ruby H N Nguyen, Karen Pierce, Walter Zahorodny, Allison Hudson, Libby Hallas, Kristen Clancy Mancilla, Mary Patrick, Josephine Shenouda, Kate Sidwell, Monica DiRienzo, Johanna Gutierrez, Margaret H Spivey, Maya Lopez, Sydney Pettygrove, Yvette D Schwenk, Anita Washington, Kelly A Shaw
<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years. In 2020, there were 11 ADDM Network sites across the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. A child met the case definition if their record documented 1) an ASD diagnostic statement in an evaluation, 2) a classification of ASD in special education, or 3) an ASD International Classification of Diseases (ICD) code.</p><p><strong>Results: </strong>For 2020, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 23.1 in Maryland to 44.9 in California. The overall ASD prevalence was 27.6 per 1,000 (one in 36) children aged 8 years and was 3.8 times as prevalent among boys as among girls (43.0 versus 11.4). Overall, ASD prevalence was lower among non-Hispanic White children (24.3) and children of two or more races (22.9) than among non-Hispanic Black or African American (Black), Hispanic, and non-Hispanic Asian or Pacific Islander (A/PI) children (29.3, 31.6, and 33.4 respectively). ASD prevalence among non-Hispanic American Indian or Alaska Native (AI/AN) children (26.5) was similar to that of other racial and ethnic groups. ASD prevalence was associated with lower household income at three sites, with no association at the other sites.Across sites, the ASD prevalence per 1,000 children aged 8 years based exclusively on documented ASD diagnostic statements was 20.6 (range = 17.1 in Wisconsin to 35.4 in California). Of the 6,245 children who met the ASD case definition, 74.7% had a documented diagnostic statement of ASD, 65.2% had a documented ASD special education classification, 71.6% had a documented ASD ICD code, and 37.4% had all three types of ASD indicators. The median age of earliest known ASD diagnosis was 49 months and ranged from 36 months in California to 59 months in Minnesota.Among the 4,165 (66.7%) children with ASD with information on cognitive ability, 37.9% were classified as having an intellectual disability. Intellectual disability was present among 50.8% of Black, 41.5% of A/PI, 37.8% of two or more races, 34.9% of Hispanic, 34.8% of AI/AN, and 31.8% of White children with ASD. Overall, children with intellectual disability had earlier median ages of ASD diagnosis (43 months) than those without intellectual disability (53 months).</p><p><strong>Interpretation: </strong>For 2020, one in 36 children aged 8 years (approximately 4% of boys and 1% of girls) was estimated to have ASD. These estimates are
{"title":"Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.","authors":"Matthew J Maenner, Zachary Warren, Ashley Robinson Williams, Esther Amoakohene, Amanda V Bakian, Deborah A Bilder, Maureen S Durkin, Robert T Fitzgerald, Sarah M Furnier, Michelle M Hughes, Christine M Ladd-Acosta, Dedria McArthur, Elise T Pas, Angelica Salinas, Alison Vehorn, Susan Williams, Amy Esler, Andrea Grzybowski, Jennifer Hall-Lande, Ruby H N Nguyen, Karen Pierce, Walter Zahorodny, Allison Hudson, Libby Hallas, Kristen Clancy Mancilla, Mary Patrick, Josephine Shenouda, Kate Sidwell, Monica DiRienzo, Johanna Gutierrez, Margaret H Spivey, Maya Lopez, Sydney Pettygrove, Yvette D Schwenk, Anita Washington, Kelly A Shaw","doi":"10.15585/mmwr.ss7202a1","DOIUrl":"10.15585/mmwr.ss7202a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2020.</p><p><strong>Description of system: </strong>The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years. In 2020, there were 11 ADDM Network sites across the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. A child met the case definition if their record documented 1) an ASD diagnostic statement in an evaluation, 2) a classification of ASD in special education, or 3) an ASD International Classification of Diseases (ICD) code.</p><p><strong>Results: </strong>For 2020, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 23.1 in Maryland to 44.9 in California. The overall ASD prevalence was 27.6 per 1,000 (one in 36) children aged 8 years and was 3.8 times as prevalent among boys as among girls (43.0 versus 11.4). Overall, ASD prevalence was lower among non-Hispanic White children (24.3) and children of two or more races (22.9) than among non-Hispanic Black or African American (Black), Hispanic, and non-Hispanic Asian or Pacific Islander (A/PI) children (29.3, 31.6, and 33.4 respectively). ASD prevalence among non-Hispanic American Indian or Alaska Native (AI/AN) children (26.5) was similar to that of other racial and ethnic groups. ASD prevalence was associated with lower household income at three sites, with no association at the other sites.Across sites, the ASD prevalence per 1,000 children aged 8 years based exclusively on documented ASD diagnostic statements was 20.6 (range = 17.1 in Wisconsin to 35.4 in California). Of the 6,245 children who met the ASD case definition, 74.7% had a documented diagnostic statement of ASD, 65.2% had a documented ASD special education classification, 71.6% had a documented ASD ICD code, and 37.4% had all three types of ASD indicators. The median age of earliest known ASD diagnosis was 49 months and ranged from 36 months in California to 59 months in Minnesota.Among the 4,165 (66.7%) children with ASD with information on cognitive ability, 37.9% were classified as having an intellectual disability. Intellectual disability was present among 50.8% of Black, 41.5% of A/PI, 37.8% of two or more races, 34.9% of Hispanic, 34.8% of AI/AN, and 31.8% of White children with ASD. Overall, children with intellectual disability had earlier median ages of ASD diagnosis (43 months) than those without intellectual disability (53 months).</p><p><strong>Interpretation: </strong>For 2020, one in 36 children aged 8 years (approximately 4% of boys and 1% of girls) was estimated to have ASD. These estimates are ","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"72 2","pages":"1-14"},"PeriodicalIF":24.9,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9265448","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}
Katherine Kortsmit, Antoinette T Nguyen, Michele G Mandel, Elizabeth Clark, Lisa M Hollier, Jessica Rodenhizer, Maura K Whiteman
<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>2020.</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 2020, a total of 49 reporting areas voluntarily provided aggregate abortion data to CDC. Of these, 48 reporting areas provided data each year during 2011-2020. 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 2019 were assessed as part of CDC's Pregnancy Mortality Surveillance System (PMSS).</p><p><strong>Results: </strong>A total of 620,327 abortions for 2020 were reported to CDC from 49 reporting areas. Among 48 reporting areas with data each year during 2011-2020, in 2020, a total of 615,911 abortions were reported, the abortion rate was 11.2 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 198 abortions per 1,000 live births. From 2019 to 2020, the total number of abortions decreased 2% (from 625,346 total abortions), the abortion rate decreased 2% (from 11.4 abortions per 1,000 women aged 15-44 years), and the abortion ratio increased 2% (from 195 abortions per 1,000 live births). From 2011 to 2020, the total number of reported abortions decreased 15% (from 727,554), the abortion rate decreased 18% (from 13.7 abortions per 1,000 women aged 15-44 years), and the abortion ratio decreased 9% (from 217 abortions per 1,000 live births).In 2020, women in their 20s accounted for more than half of abortions (57.2%). Women aged 20-24 and 25-29 years accounted for the highest percentages of abortions (27.9% and 29.3%, respectively) and had the highest abortion rates (19.2 and 19.0 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 3.7%, respectively) and had the lowest abortion rates (0.4 and 2.6 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 25-39 years.Abortion rates decreased from 2011 to 2020 among all age groups. The decrease in abortion rate was highest among adolescents compared with any other age group. From 2019 to 2020, abortion rates decreased or did not change for all age groups. Abortion ratios decreased from 2011 to 2020 for all age groups, except adolescents aged 15-19 years and women aged 25-29 years for whom abortion ratios increased. The decrease in abortion ratio was highest among women aged ≥40 years compared with any other age group. From 2019 to
{"title":"Abortion Surveillance - United States, 2020.","authors":"Katherine Kortsmit, Antoinette T Nguyen, Michele G Mandel, Elizabeth Clark, Lisa M Hollier, Jessica Rodenhizer, Maura K Whiteman","doi":"10.15585/mmwr.ss7110a1","DOIUrl":"10.15585/mmwr.ss7110a1","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>2020.</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 2020, a total of 49 reporting areas voluntarily provided aggregate abortion data to CDC. Of these, 48 reporting areas provided data each year during 2011-2020. 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 2019 were assessed as part of CDC's Pregnancy Mortality Surveillance System (PMSS).</p><p><strong>Results: </strong>A total of 620,327 abortions for 2020 were reported to CDC from 49 reporting areas. Among 48 reporting areas with data each year during 2011-2020, in 2020, a total of 615,911 abortions were reported, the abortion rate was 11.2 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 198 abortions per 1,000 live births. From 2019 to 2020, the total number of abortions decreased 2% (from 625,346 total abortions), the abortion rate decreased 2% (from 11.4 abortions per 1,000 women aged 15-44 years), and the abortion ratio increased 2% (from 195 abortions per 1,000 live births). From 2011 to 2020, the total number of reported abortions decreased 15% (from 727,554), the abortion rate decreased 18% (from 13.7 abortions per 1,000 women aged 15-44 years), and the abortion ratio decreased 9% (from 217 abortions per 1,000 live births).In 2020, women in their 20s accounted for more than half of abortions (57.2%). Women aged 20-24 and 25-29 years accounted for the highest percentages of abortions (27.9% and 29.3%, respectively) and had the highest abortion rates (19.2 and 19.0 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 3.7%, respectively) and had the lowest abortion rates (0.4 and 2.6 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 25-39 years.Abortion rates decreased from 2011 to 2020 among all age groups. The decrease in abortion rate was highest among adolescents compared with any other age group. From 2019 to 2020, abortion rates decreased or did not change for all age groups. Abortion ratios decreased from 2011 to 2020 for all age groups, except adolescents aged 15-19 years and women aged 25-29 years for whom abortion ratios increased. The decrease in abortion ratio was highest among women aged ≥40 years compared with any other age group. From 2019 to","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"71 10","pages":"1-27"},"PeriodicalIF":37.3,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10465302","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}
Angela B Snyder, Sangeetha Lakshmanan, Mary M Hulihan, Susan T Paulukonis, Mei Zhou, Sophia S Horiuchi, Karon Abe, Shammara N Pope, Laura A Schieve
<p><strong>Problem/condition: </strong>Sickle cell disease (SCD), an inherited blood disorder affecting an estimated 100,000 persons in the United States, is associated with multiple complications and reduced life expectancy. Complications of SCD can include anemia, debilitating acute and chronic pain, infection, acute chest syndrome, stroke, and progressive organ damage, including decreased cognitive function and renal failure. Early diagnosis, screenings and preventive interventions, and access to specialist health care can decrease illness and death. Population-based public health surveillance is critical to understanding the course and outcomes of SCD as well as the health care use, unmet health care needs, and gaps in essential services of the population affected by SCD.</p><p><strong>Period covered: </strong>2004-2018.</p><p><strong>Description of the program: </strong>In 2015, CDC established the Sickle Cell Data Collection (SCDC) program to characterize the epidemiology of SCD in two states (California and Georgia). Previously, surveillance for SCD was conducted by two short-term projects: Registry and Surveillance System for Hemoglobinopathies (RuSH), which was conducted during 2010-2012 and included 2004-2008 data, and Public Health Research, Epidemiology, and Surveillance for Hemoglobinopathies (PHRESH), which was conducted during 2012-2014 and included 2004-2008 data. Both California and Georgia participated in RuSH and PHRESH, which guided the development of the SCDC methods and case definitions. SCDC is a population-based tracking system that uses comprehensive data linkages in state health systems. These linkages serve to synthesize and disseminate population-based, longitudinal data for persons identified with SCD from multiple sources using selected International Classification of Diseases, Ninth Revision, Clinical Modification, and Tenth Revision codes and laboratory results confirmed through state newborn screening (NBS) programs or clinic case reporting. Administrative and clinical data sources include state Medicaid and Children's Health Insurance Program databases, death certificates, NBS programs, hospital discharge and emergency department records, and clinical records or case reports. Data from multiple sources and years are linked and deduplicated so that states can analyze and report on SCD population prevalence, demographic characteristics, health care access and use, and health outcomes. The SCD case definition is based on an algorithm that classifies cases with laboratory confirmation as confirmed cases and those with a reported clinical diagnosis or three or more diagnostic codes over a 5-year period from an administrative data source as probable cases. In 2019, nine states (Alabama, California, Georgia, Indiana, Michigan, Minnesota, North Carolina, Tennessee, and Virginia) were funded as part of an SCDC capacity-building initiative. The newly funded states developed strategies for SCD case identification and data l
{"title":"Surveillance for Sickle Cell Disease - Sickle Cell Data Collection Program, Two States, 2004-2018.","authors":"Angela B Snyder, Sangeetha Lakshmanan, Mary M Hulihan, Susan T Paulukonis, Mei Zhou, Sophia S Horiuchi, Karon Abe, Shammara N Pope, Laura A Schieve","doi":"10.15585/mmwr.ss7109a1","DOIUrl":"10.15585/mmwr.ss7109a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Sickle cell disease (SCD), an inherited blood disorder affecting an estimated 100,000 persons in the United States, is associated with multiple complications and reduced life expectancy. Complications of SCD can include anemia, debilitating acute and chronic pain, infection, acute chest syndrome, stroke, and progressive organ damage, including decreased cognitive function and renal failure. Early diagnosis, screenings and preventive interventions, and access to specialist health care can decrease illness and death. Population-based public health surveillance is critical to understanding the course and outcomes of SCD as well as the health care use, unmet health care needs, and gaps in essential services of the population affected by SCD.</p><p><strong>Period covered: </strong>2004-2018.</p><p><strong>Description of the program: </strong>In 2015, CDC established the Sickle Cell Data Collection (SCDC) program to characterize the epidemiology of SCD in two states (California and Georgia). Previously, surveillance for SCD was conducted by two short-term projects: Registry and Surveillance System for Hemoglobinopathies (RuSH), which was conducted during 2010-2012 and included 2004-2008 data, and Public Health Research, Epidemiology, and Surveillance for Hemoglobinopathies (PHRESH), which was conducted during 2012-2014 and included 2004-2008 data. Both California and Georgia participated in RuSH and PHRESH, which guided the development of the SCDC methods and case definitions. SCDC is a population-based tracking system that uses comprehensive data linkages in state health systems. These linkages serve to synthesize and disseminate population-based, longitudinal data for persons identified with SCD from multiple sources using selected International Classification of Diseases, Ninth Revision, Clinical Modification, and Tenth Revision codes and laboratory results confirmed through state newborn screening (NBS) programs or clinic case reporting. Administrative and clinical data sources include state Medicaid and Children's Health Insurance Program databases, death certificates, NBS programs, hospital discharge and emergency department records, and clinical records or case reports. Data from multiple sources and years are linked and deduplicated so that states can analyze and report on SCD population prevalence, demographic characteristics, health care access and use, and health outcomes. The SCD case definition is based on an algorithm that classifies cases with laboratory confirmation as confirmed cases and those with a reported clinical diagnosis or three or more diagnostic codes over a 5-year period from an administrative data source as probable cases. In 2019, nine states (Alabama, California, Georgia, Indiana, Michigan, Minnesota, North Carolina, Tennessee, and Virginia) were funded as part of an SCDC capacity-building initiative. The newly funded states developed strategies for SCD case identification and data l","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"71 9","pages":"1-18"},"PeriodicalIF":24.9,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552568/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10464772","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}
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