Mmwr Surveillance Summaries最新文献

{"title":"Abortion Surveillance - United States, 2018.","authors":"Katherine Kortsmit, Tara C Jatlaoui, Michele G Mandel, Jennifer A Reeves, Titilope Oduyebo, Emily Petersen, Maura K Whiteman","doi":"10.15585/mmwr.ss6907a1","DOIUrl":"10.15585/mmwr.ss6907a1","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>2018.</p><p><strong>Description of system: </strong>Each year, CDC requests abortion data from the central health agencies for 50 states, the District of Columbia, and New York City. For 2018, 49 reporting areas voluntarily provided aggregate abortion data to CDC. Of these, 48 reporting areas provided data each year during 2009-2018. 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 2017 were assessed as part of CDC's Pregnancy Mortality Surveillance System (PMSS).</p><p><strong>Results: </strong>A total of 619,591 abortions for 2018 were reported to CDC from 49 reporting areas. Among 48 reporting areas with data each year during 2009-2018, in 2018, a total of 614,820 abortions were reported, the abortion rate was 11.3 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 189 abortions per 1,000 live births. From 2017 to 2018, the total number of abortions and abortion rate increased 1% (from 609,095 total abortions and from 11.2 abortions per 1,000 women aged 15-44 years, respectively), and the abortion ratio increased 2% (from 185 abortions per 1,000 live births). From 2009 to 2018, the total number of reported abortions, abortion rate, and abortion ratio decreased 22% (from 786,621), 24% (from 14.9 abortions per 1,000 women aged 15-44 years), and 16% (from 224 abortions per 1,000 live births), respectively. In 2018, women in their 20s accounted for more than half of abortions (57.7%). In 2018 and during 2009-2018, women aged 20-24 and 25-29 years accounted for the highest percentages of abortions; in 2018, they accounted for 28.3% and 29.4% of abortions, respectively, and had the highest abortion rates (19.1 and 18.5 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 2.6 per 1,000 women aged <15 and ≥40 years, respectively). However, abortion ratios in 2018 and throughout 2009-2018 were highest among adolescents (aged ≤19 years) and lowest among women aged 25-39 years. Abortion rates decreased from 2009 to 2018 for all women, regardless of age. The decrease in abortion rate was highest among adolescents compared with women in any other age group. From 2009 to 2013, the abortion rates decreased for all age groups and from 2014 to 2018, the abortion rates decreased for all age groups, except for women aged 30-34 years and those aged ≥40 years. In addition, from 2017 to 2018, abortion rates did not change or decreased a","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 7","pages":"1-29"},"PeriodicalIF":24.9,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713711/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38304143","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":"Investigations of Possible Multistate Outbreaks of Salmonella, Shiga Toxin-Producing Escherichia coli, and Listeria monocytogenes Infections - United States, 2016.","authors":"Katherine E Marshall, Thai-An Nguyen, Michael Ablan, Megin C Nichols, Misha P Robyn, Preethi Sundararaman, Laura Whitlock, Matthew E Wise, Michael A Jhung","doi":"10.15585/mmwr.ss6906a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6906a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Salmonella, Shiga toxin-producing Escherichia coli (STEC), and Listeria monocytogenes are the leading causes of multistate foodborne disease outbreaks in the United States. Responding to multistate outbreaks quickly and effectively and applying lessons learned about outbreak sources, modes of transmission, and risk factors for infection can prevent additional outbreak-associated illnesses and save lives. This report summarizes the investigations of multistate outbreaks and possible outbreaks of Salmonella, STEC, and L. monocytogenes infections coordinated by CDC during the 2016 reporting period.</p><p><strong>Period covered: </strong>2016. An investigation was considered to have occurred in 2016 if it began during 2016 and ended on or before March 31, 2017, or if it began before January 1, 2016, and ended during March 31, 2016-March 31, 2017.</p><p><strong>Description of system: </strong>CDC maintains a database of investigations of possible multistate foodborne and animal-contact outbreaks caused by Salmonella, STEC, and L. monocytogenes. Data were collected by local, state, and federal investigators during the detection, investigation and response, and control phases of the outbreak investigations. Additional data sources used for this report included PulseNet, the national molecular subtyping network based on isolates uploaded by local, state, and federal laboratories, and the Foodborne Disease Outbreak Surveillance System (FDOSS), which collects information from state, local, and territorial health departments and federal agencies about single-state and multistate foodborne disease outbreaks in the United States. Multistate outbreaks reported to FDOSS were linked using a unique outbreak identifier to obtain food category information when a confirmed or suspected food source was identified. Food categories were determined and assigned in FDOSS according to a classification scheme developed by CDC, the Food and Drug Administration (FDA), and the U.S. Department of Agriculture Food Safety and Inspection Service (FSIS) in the Interagency Food Safety Analytics Collaboration. A possible multistate outbreak was determined by expert judgment to be an outbreak if supporting data (e.g., temporal, geographic, demographic, dietary, travel, or food history) suggested a common source. A solved outbreak was an outbreak for which a specific kind of food or animal was implicated (i.e., confirmed or suspected) as the source. Outbreak-level variables included number of illnesses, hospitalizations, cases of hemolytic uremic syndrome (HUS), and deaths; the number of states with illnesses; date of isolation for the earliest and last cases; demographic data describing patients associated with a possible outbreak (e.g., age, sex, and state of residence); the types of data collected (i.e., epidemiologic, traceback, or laboratory); the outbreak source, mode of transmission, and exposure location; the name or brand of the source; ","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 6","pages":"1-14"},"PeriodicalIF":24.9,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38699168","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":"Evaluation of CDC's Hemophilia Surveillance Program - Universal Data Collection (1998-2011) and Community Counts (2011-2019), United States.","authors":"Laura A Schieve, Vanessa R Byams, Brandi Dupervil, Meredith A Oakley, Connie H Miller, J Michael Soucie, Karon Abe, Christopher J Bean, W Craig Hooper","doi":"10.15585/mmwr.ss6905a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6905a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Hemophilia is an X-linked genetic disorder that primarily affects males and results in deficiencies in blood-clotting proteins. Hemophilia A is a deficiency in factor VIII, and hemophilia B is a deficiency in factor IX. Approximately one in 5,000 males are born with hemophilia, and hemophilia A is about four times as common as hemophilia B. Both disorders are characterized by spontaneous internal bleeding and excessive bleeding after injuries or surgery. Hemophilia can lead to repeated bleeding into the joints and associated chronic joint disease, neurologic damage, damage to other organ systems, and death. Although no precise national U.S. prevalence estimates for hemophilia exist because of the difficulty identifying cases among persons who receive care from various types of health care providers, two previous state-based studies estimated hemophilia prevalence at 13.4 and 19.4 per 100,000 males. In addition, these studies showed that 67% and 82% of persons with hemophilia received care in a federally funded hemophilia treatment center (HTC), and 86% and 94% of those with the most severe cases of hemophilia (i.e., those with the lowest levels of clotting factor activity in the circulating blood) received care in a federally funded HTC. As of January 2020, the United States had 144 HTCs.</p><p><strong>Period covered: </strong>1998-2019.</p><p><strong>Description of the system: </strong>Surveillance for hemophilia, which is a complex, chronic condition, is challenging because of its low prevalence, the difficulty in ascertaining cases uniformly, and the challenges in routinely characterizing and tracking associated health complications. Over time, two systems involving many stakeholders have been used to conduct ongoing hemophilia surveillance. During 1998-2011, CDC and the HTCs collaborated to establish the Universal Data Collection (UDC) surveillance system. The purposes of the UDC surveillance system were to monitor human immunodeficiency virus (HIV) and bloodborne viral hepatitis in persons with hemophilia, thereby tracking blood safety, and to track the prevalence of and trends in complications associated with hemophilia. HTC staff collected clinical data and blood specimens from UDC participants and submitted them to CDC. CDC tested specimens for viral hepatitis and HIV. In 2011, the UDC surveillance system was replaced by a new hemophilia surveillance system called Community Counts. CDC and the HTCs established Community Counts to expand laboratory testing and the collection of clinical data to better identify and track emerging health issues in persons with hemophilia.</p><p><strong>Results: </strong>This report is the first comprehensive summary of CDC's hemophilia surveillance program, which comprises both UDC and Community Counts. Data generated from these surveillance systems have been used in the development of public health and clinical guidelines and practices to improve the safety of U.S. blo","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 5","pages":"1-18"},"PeriodicalIF":24.9,"publicationDate":"2020-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38340672","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":"Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016.","authors":"Matthew J Maenner,&nbsp;Kelly A Shaw,&nbsp;Jon Baio,&nbsp;Anita Washington,&nbsp;Mary Patrick,&nbsp;Monica DiRienzo,&nbsp;Deborah L Christensen,&nbsp;Lisa D Wiggins,&nbsp;Sydney Pettygrove,&nbsp;Jennifer G Andrews,&nbsp;Maya Lopez,&nbsp;Allison Hudson,&nbsp;Thaer Baroud,&nbsp;Yvette Schwenk,&nbsp;Tiffany White,&nbsp;Cordelia Robinson Rosenberg,&nbsp;Li-Ching Lee,&nbsp;Rebecca A Harrington,&nbsp;Margaret Huston,&nbsp;Amy Hewitt,&nbsp;Amy Esler,&nbsp;Jennifer Hall-Lande,&nbsp;Jenny N Poynter,&nbsp;Libby Hallas-Muchow,&nbsp;John N Constantino,&nbsp;Robert T Fitzgerald,&nbsp;Walter Zahorodny,&nbsp;Josephine Shenouda,&nbsp;Julie L Daniels,&nbsp;Zachary Warren,&nbsp;Alison Vehorn,&nbsp;Angelica Salinas,&nbsp;Maureen S Durkin,&nbsp;Patricia M Dietz","doi":"10.15585/mmwr.ss6904a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6904a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2016.</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 whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.</p><p><strong>Results: </strong>For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (39% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively) [corrected]. Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months).</p><p><strong>Interpretation: </strong>The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children.</p><p><strong>Public health action: </strong>These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.</p>","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 4","pages":"1-12"},"PeriodicalIF":24.9,"publicationDate":"2020-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7119644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37772201","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":"Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Six Sites, United States, 2016.","authors":"Kelly A Shaw,&nbsp;Matthew J Maenner,&nbsp;Jon Baio,&nbsp;Anita Washington,&nbsp;Deborah L Christensen,&nbsp;Lisa D Wiggins,&nbsp;Sydney Pettygrove,&nbsp;Jennifer G Andrews,&nbsp;Tiffany White,&nbsp;Cordelia Robinson Rosenberg,&nbsp;John N Constantino,&nbsp;Robert T Fitzgerald,&nbsp;Walter Zahorodny,&nbsp;Josephine Shenouda,&nbsp;Julie L Daniels,&nbsp;Angelica Salinas,&nbsp;Maureen S Durkin,&nbsp;Patricia M Dietz","doi":"10.15585/mmwr.ss6903a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6903a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Autism spectrum disorder (ASD).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Period covered: &lt;/strong&gt;2016.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of system: &lt;/strong&gt;The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network, a subset of the overall ADDM Network, is an active surveillance program that estimates ASD prevalence and monitors early identification of ASD among children aged 4 years. Children included in surveillance year 2016 were born in 2012 and had a parent or guardian who lived in the surveillance area in Arizona, Colorado, Missouri, New Jersey, North Carolina, or Wisconsin, at any time during 2016. Children were identified from records of community sources including general pediatric health clinics, special education programs, and early intervention programs. Data from comprehensive evaluations performed by community professionals were abstracted and reviewed by trained clinicians using a standardized ASD surveillance case definition with criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In 2016, the overall ASD prevalence was 15.6 per 1,000 (one in 64) children aged 4 years for Early ADDM Network sites. Prevalence varied from 8.8 per 1,000 in Missouri to 25.3 per 1,000 in New Jersey. At every site, prevalence was higher among boys than among girls, with an overall male-to-female prevalence ratio of 3.5 (95% confidence interval [CI] = 3.1-4.1). Prevalence of ASD between non-Hispanic white (white) and non-Hispanic black (black) children was similar at each site (overall prevalence ratio: 0.9; 95% CI = 0.8-1.1). The prevalence of ASD using DSM-5 criteria was lower than the prevalence using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria at one of four sites that used criteria from both editions. Among sites where ≥60% of children aged 4 years had information about intellectual disability (intelligence quotient ≤70 or examiner's statement of intellectual disability documented in an evaluation), 53% of children with ASD had co-occurring intellectual disability. Of all children aged 4 years with ASD, 84% had a first evaluation at age ≤36 months and 71% of children who met the surveillance case definition had a previous ASD diagnosis from a community provider. Median age at first evaluation and diagnosis for this age group was 26 months and 33 months, respectively. Cumulative incidence of autism diagnoses received by age 48 months was higher for children aged 4 years than for those aged 8 years identified in Early ADDM Network surveillance areas in 2016.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;In 2016, the overall prevalence of ASD in the Early ADDM Network using DSM-5 criteria (15.6 per 1,000 children aged 4 years) was higher than the 2014 estimate using DSM-5 criteria (14.1 per 1,000). Children born in 2012 had a higher cumulative incidence of ASD diagnoses by age 48 months compared w","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 3","pages":"1-11"},"PeriodicalIF":24.9,"publicationDate":"2020-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7119643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37773267","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":"National Toxic Substances Incidents Program - Nine States, 2010-2014.","authors":"Natalia Melnikova,&nbsp;Jennifer Wu,&nbsp;Patricia Ruiz,&nbsp;Maureen F Orr","doi":"10.15585/mmwr.ss6902a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6902a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Every year in the United States, thousands of toxic substance incidents harm workers, first responders, and the public with the potential for catastrophic consequences. Surveillance data enable public health and safety professionals to understand the patterns and causes of these incidents, which can improve prevention efforts and preparation for future incidents.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Period covered: &lt;/strong&gt;2010-2014.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of system: &lt;/strong&gt;In 2010, the Agency for Toxic Substances and Disease Registry (ATSDR) initiated the National Toxic Substance Incidents Program (NTSIP), and it was retired in 2014. Nine state health departments participated in NTSIP surveillance: California, Louisiana, North Carolina, New York, Missouri, Oregon, Tennessee, Utah, and Wisconsin. The states conducted surveillance on acute toxic substance incidents, defined as an uncontrolled or illegal acute (lasting &lt;72 hours) release of any toxic substance including chemical, biologic, radiologic, and medical materials. Surveillance focused on associated morbidity and mortality and public health actions. This report presents an overview of NTSIP and summarizes incidents and injuries from the nine participating states during 2010-2014.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;During 2010-2014, participating state health departments reported 22,342 incidents, of which 13,529 (60.6%) met the case definition for acute toxic substance incidents, and included 6,635 injuries among 5,134 injured persons, of whom 190 died. A trend analysis of the three states participating the entire time showed a decrease in the number of incidents with injuries. NTSIP incidents were 1.8 times more likely and injured persons were 10 times more likely to be associated with fixed facilities than transportation. Natural gas, carbon monoxide, ammonia, and chemicals used in illegal methamphetamine production were the most frequent substances in fixed-facility incidents. Sodium and potassium hydroxide, hydrochloric acid, natural gas, and sulfuric acid were the most frequent substances in transportation-related incidents. Carbon monoxide was the most frequent substance in incidents with a large number of injured persons, and chemicals used in illegal methamphetamine production were the most frequent substance in incidents involving decontamination. Incidents most frequently occurred during normal business days (Monday through Friday) and hours (6:00 a.m.-5:59 p.m.) and warmer months (March-August). The transportation and warehousing industry sector had the largest number of incidents (4,476); however, most injured persons were injured in their private residences (1,141) or in the industry sectors of manufacturing (668), educational services (606), and real estate rental and leasing (425). The most frequently injured persons were members of the public (43.6%), including students. Injured first responders, particularly police, frequently were not wearing any chemic","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 2","pages":"1-10"},"PeriodicalIF":24.9,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093087/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37754483","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":"Opioid Prescribing Behaviors - Prescription Behavior Surveillance System, 11 States, 2010-2016.","authors":"Gail K Strickler,&nbsp;Peter W Kreiner,&nbsp;John F Halpin,&nbsp;Erin Doyle,&nbsp;Leonard J Paulozzi","doi":"10.15585/mmwr.ss6901a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6901a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In 2017, a total of 70,237 persons in the United States died from a drug overdose, and 67.8% of these deaths involved an opioid. Historically, the opioid overdose epidemic in the United States has been closely associated with a parallel increase in opioid prescribing and with widespread misuse of these medications. National and state policy makers have introduced multiple measures to attempt to assess and control the opioid overdose epidemic since 2010, including improvements in surveillance systems.</p><p><strong>Period covered: </strong>2010-2016 DESCRIPTION OF SYSTEM: The Prescription Behavior Surveillance System (PBSS) was created in 2011. Its goal was to track rates of prescribing of controlled substances and possible misuse of such drugs using data from selected state prescription drug monitoring programs (PDMP). PBSS data measure prescribing behaviors for prescription opioids using multiple measures calculated from PDMP data including 1) opioid prescribing, 2) average daily opioid dosage, 3) proportion of patients with daily opioid dosages ≥90 morphine milligram equivalents, 4) overlapping opioid prescriptions, 5) overlapping opioid and benzodiazepine prescriptions, and 6) multiple-provider episodes. For this analysis, PBSS data were available for 2010-2016 from 11 states representing approximately 38.0% of the U.S.</p><p><strong>Population: </strong>Average quarterly percent changes (AQPC) in the rates of opioid prescribing and possible opioid misuse measures were calculated for each state.</p><p><strong>Results and interpretation: </strong>Opioid prescribing rates declined in all 11 states during 2010-2016 (range: 14.9% to 33.0%). Daily dosage declined least (AQPC: -0.4%) in Idaho and Maine, and most (AQPC: -1.6%) in Florida. The percentage of patients with high daily dosage had AQPCs ranging from -0.4% in Idaho to -2.3% in Louisiana. Multiple-provider episode rates declined by at least 62% in the seven states with available data. Variations in trends across the 11 states might reflect differences in state policies and possible differential effects of similar policies.</p><p><strong>Public health actions: </strong>Use of PDMP data from individual states enables a more detailed examination of trends in opioid prescribing behaviors and indicators of possible misuse than is feasible with national commercially available prescription data. Comparison of opioid prescribing trends among states can be used to monitor the temporal association of national or state policy interventions and might help public health policymakers recognize changes in the use or possible misuse of controlled prescription drugs over time and allow for prompt intervention through amended or new opioid-related policies.</p>","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"69 1","pages":"1-14"},"PeriodicalIF":24.9,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37594191","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":"Population-Based Active Surveillance for Culture-Confirmed Candidemia — Four Sites, United States, 2012–2016","authors":"Mitsuru Toda, Sabrina R. Williams, Elizabeth L Berkow, M. Farley, L. Harrison, Lindsay Bonner, Kaytlynn Marceaux, R. Hollick, Alexia Y. Zhang, W. Schaffner, S. Lockhart, Brendan R. Jackson, S. Vallabhaneni","doi":"10.15585/mmwr.ss6808a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6808a1","url":null,"abstract":"Problem/Condition Candidemia is a bloodstream infection (BSI) caused by yeasts in the genus Candida. Candidemia is one of the most common health care–associated BSIs in the United States, with all-cause in-hospital mortality of up to 30%. Period Covered 2012–2016. Description of System CDC’s Emerging Infections Program (EIP), a collaboration among CDC, state health departments, and academic partners that was established in 1995, was used to conduct active, population-based laboratory surveillance for candidemia in 22 counties in four states (Georgia, Maryland, Oregon, and Tennessee) with a combined population of approximately 8 million persons. Laboratories serving the catchment areas were recruited to report candidemia cases to the local EIP program staff. A case was defined as a blood culture that was positive for a Candida species collected from a surveillance area resident during 2012–2016. Isolates were sent to CDC for species confirmation and antifungal susceptibility testing. Any subsequent blood cultures with Candida within 30 days of the initial positive culture in the same patient were considered part of the same case. Trained surveillance officers collected clinical information from the medical chart for all cases, and isolates were sent to CDC for species confirmation and antifungal susceptibility testing. Results Across all sites and surveillance years (2012–2016), 3,492 cases of candidemia were identified. The crude candidemia incidence averaged across sites and years during 2012–2016 was 8.7 per 100,000 population; important differences in incidence were found by site, age group, sex, and race. The crude annual incidence was the highest in Maryland (14.1 per 100,000 population) and lowest in Oregon (4.0 per 100,000 population). The crude annual incidence of candidemia was highest among adults aged ≥65 years (25.5 per 100,000 population) followed by infants aged &lt;1 year (15.8). The crude annual incidence was higher among males (9.4) than among females (8.0) and was approximately 2 times greater among blacks than among nonblacks (13.7 versus 5.8). Ninety-six percent of cases occurred in patients who were hospitalized at the time of or during the week after having a positive culture. One third of cases occurred in patients who had undergone a surgical procedure in the 90 days before the candidemia diagnosis, 77% occurred in patients who had received systemic antibiotics in the 14 days before the diagnosis, and 73% occurred in patients who had had a central venous catheter (CVC) in place within 2 days before the diagnosis. Ten percent were in patients who had used injection drugs in the past 12 months. The median time from admission to candidemia diagnosis was 5 days (interquartile range [IQR]: 0–16 days). Among 2,662 cases that were treated in adults aged &gt;18 years, 34% were treated with fluconazole alone, 30% with echinocandins alone, and 34% with both. The all-cause, in-hospital case-fatality ratio was 25% for any time after admissi","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"20 1","pages":"1 - 15"},"PeriodicalIF":24.9,"publicationDate":"2019-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81683118","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":"Surveillance for Coccidioidomycosis — United States, 2011–2017","authors":"Kaitlin Benedict, O. McCotter, Shane Brady, K. Komatsu, Gail L. Sondermeyer Cooksey, Alyssa Nguyen, Seemalata Jain, D. Vugia, Brendan R. Jackson","doi":"10.15585/mmwr.ss6807a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6807a1","url":null,"abstract":"Problem/Condition Coccidioidomycosis (Valley fever) is an infection caused by the environmental fungus Coccidioides spp., which typically causes respiratory illness but also can lead to disseminated disease. This fungus typically lives in soils in warm, arid regions, including the southwestern United States. Reporting Period 2011–2017. Description of System Coccidioidomycosis has been nationally notifiable since 1995 and is reportable in 26 states and the District of Columbia (DC), where laboratories and physicians notify local and state public health departments about possible coccidioidomycosis cases. Health department staff determine which cases qualify as confirmed cases according to the definition established by Council of State and Territorial Epidemiologists and voluntarily submit basic case information to CDC through the National Notifiable Diseases Surveillance System. Results During 2011–2017, a total of 95,371 coccidioidomycosis cases from 26 states and DC were reported to CDC. The number of cases decreased from 2011 (22,634 cases) to 2014 (8,232 cases) and subsequently increased to 14,364 cases in 2017; >95% of cases were reported from Arizona and California. Reported incidence in Arizona decreased from 261 per 100,000 persons in 2011 to 101 in 2017, whereas California incidence increased from 15.7 to 18.2, and other state incidence rates stayed relatively constant. Patient demographic characteristics were largely consistent with previous years, with an overall predominance among males and among adults aged >60 years in Arizona and adults aged 40–59 years in California. Interpretation Coccidioidomycosis remains an important national public health problem with a well-established geographic focus. The reasons for the changing trends in reported cases are unclear but might include environmental factors (e.g., temperature and precipitation), surveillance artifacts, land use changes, and changes in the population at risk for the infection. Public Health Action Health care providers should consider a diagnosis of coccidioidomycosis in patients who live or work in or have traveled to areas with known geographic risk for Coccidioides and be aware that those areas might be broader than previously recognized. Coccidioidomycosis surveillance provides important information about the epidemiology of the disease but is incomplete both in terms of geographic coverage and data availability. Expanding surveillance to additional states could help identify emerging areas that pose a risk for locally acquired infections. In Arizona and California, where most cases occur, collecting systematic enhanced data, such as more detailed patient characteristics and disease severity, could help clarify the reasons behind the recent changes in incidence and identify additional opportunities for focused prevention and educational efforts.","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"31 1","pages":"1 - 15"},"PeriodicalIF":24.9,"publicationDate":"2019-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78704000","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":"Babesiosis Surveillance - United States, 2011-2015.","authors":"Elizabeth B Gray,&nbsp;Barbara L Herwaldt","doi":"10.15585/mmwr.ss6806a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6806a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Babesiosis is caused by parasites of the genus Babesia, which are transmitted in nature by the bite of an infected tick. Babesiosis can be life threatening, particularly for persons who are asplenic, immunocompromised, or elderly.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Period covered: &lt;/strong&gt;2011-2015.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of system: &lt;/strong&gt;CDC has conducted surveillance for babesiosis in the United States since January 2011, when babesiosis became a nationally notifiable condition. Health departments in states in which babesiosis is reportable voluntarily notify CDC of cases through the National Notifiable Diseases Surveillance System (NNDSS) and submit supplemental case information by using a babesiosis-specific case report form (CRF). As of 2015, babesiosis was a reportable condition in 33 states compared with 22 states in 2011.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;For the 2011-2015 surveillance period, CDC was notified of 7,612 cases of babesiosis (6,277 confirmed [82.5%] and 1,335 probable [17.5%]). Case counts varied from year to year (1,126 cases for 2011, 909 for 2012, 1,761 for 2013, 1,742 for 2014, and 2,074 for 2015). Cases were reported among residents of 27 states. However, 7,194 cases (94.5%) occurred among residents of seven states with well-documented foci of tickborne transmission (i.e., Connecticut, Massachusetts, Minnesota, New Jersey, New York, Rhode Island, and Wisconsin). Maine (152 cases) and New Hampshire (149 cases) were the only other states that reported &gt;100 cases for the 5-year period, and both states also reported increasing numbers of cases over time. The median age of the 7,173 patients with available information was 63 years (range: &lt;1-99 years; interquartile range: 51-73 years); 4,156 (57.9%) were aged ≥60 years, and 15 (&lt;1%) were aged &lt;1 year. The proportion of patients with symptom onset during June-August was &gt;70% for each of the 5 surveillance years. Approximately half (3,004 of 6,404 [46.9%]) of the patients with available data were hospitalized at least overnight. Hospitalization rates ranged from 16.0% among patients aged 10-19 years (16 of 100) to 72.6% among those aged ≥80 years (552 of 760). Hospitalizations were reported significantly more often among patients who were asplenic than among patients who were not (106 of 126 [84.1%] versus 643 of 1,396 [46.1%]). Fifty-one cases of babesiosis among recipients of blood transfusions were classified by the reporting health department as transfusion associated. The median intervals from the earliest date associated with each case of babesiosis to the initial report via NNDSS and submission of supplemental CRF data to CDC were approximately 3 months and 1 year, respectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;For the first 5 years of babesiosis surveillance, the reported cases occurred most frequently during June-August in the Northeast and upper Midwest. Maine and New Hampshire reported increasing numbers of cases over time, which suggest","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"68 6","pages":"1-11"},"PeriodicalIF":24.9,"publicationDate":"2019-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37012717","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}