MMWR supplements最新文献

{"title":"Interpersonal Violence Victimization Among High School Students - Youth Risk Behavior Survey, United States, 2019.","authors":"Kathleen C Basile, Heather B Clayton, Sarah DeGue, John W Gilford, Kevin J Vagi, Nicolas A Suarez, Marissa L Zwald, Richard Lowry","doi":"10.15585/mmwr.su6901a4","DOIUrl":"10.15585/mmwr.su6901a4","url":null,"abstract":"<p><p>Adolescent interpersonal violence victimization is an adverse childhood experience and a serious public health problem for youths, their families, and communities. Violence victimization includes dating violence, sexual violence, and bullying. Youth Risk Behavior Survey data for 2019 were used to examine physical and sexual dating violence; sexual violence by anyone; and bullying victimization, whether on school property or electronic, of U.S. high school students by sex, race/ethnicity, and sexual identity. In addition, this report explores frequency of dating violence and frequency of sexual violence among students who reported these forms of victimization and presents composites of dating violence and bullying. Findings reveal that 8.2% of students reported physical dating violence; 8.2% reported sexual dating violence; 10.8% reported sexual violence by anyone, of which 50% of cases were by a perpetrator other than a dating partner; 19.5% reported bullying on school property; and 15.7% reported electronic bullying victimization during the previous 12 months. Approximately one in eight students reported any dating violence, and one in four reported any bullying victimization. Female students; lesbian, gay, and bisexual students; and students not sure of their sexual identity reported the highest prevalence estimates across all five violence victimization types, any and both forms of dating violence, and any bullying victimization. Non-Hispanic white students reported the highest prevalence of bullying victimization. Among students experiencing physical or sexual dating violence or sexual violence by anyone, the most common frequency reported was one time during the previous year; higher frequency was more prevalent among male students compared with female students. These findings provide a contextual understanding of the prevalence of interpersonal violence of U.S. high school students, highlighting those with highest prevalence. Findings can be used by public health professionals to guide prevention efforts with youths in schools and communities.</p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"69 1","pages":"28-37"},"PeriodicalIF":0.0,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38291749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescription Opioid Misuse and Use of Alcohol and Other Substances Among High School Students - Youth Risk Behavior Survey, United States, 2019.","authors":"Christopher M Jones,&nbsp;Heather B Clayton,&nbsp;Nicholas P Deputy,&nbsp;Douglas R Roehler,&nbsp;Jean Y Ko,&nbsp;Marissa B Esser,&nbsp;Kathryn A Brookmeyer,&nbsp;Marci Feldman Hertz","doi":"10.15585/mmwr.su6901a5","DOIUrl":"https://doi.org/10.15585/mmwr.su6901a5","url":null,"abstract":"<p><p>Adolescence is an important period of risk for substance use initiation and substance use-related adverse outcomes. To examine youth substance use trends and patterns, CDC analyzed data from the 2009-2019 Youth Risk Behavior Survey. This report presents estimated prevalence of current (i.e., previous 30-days) marijuana use, prescription opioid misuse, alcohol use, and binge drinking and lifetime prevalence of marijuana, synthetic marijuana, cocaine, methamphetamine, heroin, injection drug use, and prescription opioid misuse among U.S. high school students. Logistic regression and Joinpoint analyses were used to assess 2009-2019 trends. Prevalence of current and lifetime substance use by demographics, frequency of use, and prevalence of co-occurrence of selected substances among students reporting current prescription opioid misuse are estimated using 2019 data. Multivariable logistic regression analysis was used to determine demographic and substance use correlates of current prescription opioid misuse. Current alcohol, lifetime cocaine, methamphetamine, heroin, and injection drug use decreased during 2009-2019. Lifetime use of synthetic marijuana (also called synthetic cannabinoids) decreased during 2015-2019. Lifetime marijuana use increased during 2009-2013 and then decreased during 2013-2019. In 2019, 29.2% reported current alcohol use, 21.7% current marijuana use, 13.7% current binge drinking, and 7.2% current prescription opioid misuse. Substance use varied by sex, race/ethnicity, grade, and sexual minority status (lesbian, gay, or bisexual). Use of other substances, particularly current use of alcohol (59.4%) and marijuana (43.5%), was common among students currently misusing prescription opioids. Findings highlight opportunities for expanding evidence-based prevention policies, programs, and practices that aim to reduce risk factors and strengthen protective factors related to youth substance use, in conjunction with ongoing initiatives for combating the opioid crisis.</p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"69 1","pages":"38-46"},"PeriodicalIF":0.0,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440199/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38291752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Suicidal Ideation and Behaviors Among High School Students - Youth Risk Behavior Survey, United States, 2019.","authors":"Asha Z Ivey-Stephenson,&nbsp;Zewditu Demissie,&nbsp;Alexander E Crosby,&nbsp;Deborah M Stone,&nbsp;Elizabeth Gaylor,&nbsp;Natalie Wilkins,&nbsp;Richard Lowry,&nbsp;Margaret Brown","doi":"10.15585/mmwr.su6901a6","DOIUrl":"https://doi.org/10.15585/mmwr.su6901a6","url":null,"abstract":"<p><p>Suicide is the second leading cause of death among high school-aged youths 14-18 years after unintentional injuries. This report summarizes data regarding suicidal ideation (i.e., seriously considered suicide) and behaviors (i.e., made a suicide plan, attempted suicide, and made a suicide attempt requiring medical treatment) from CDC's 2019 Youth Risk Behavior Survey. Results are reported overall and by sex, grade, race/ethnicity, sexual identity, and sex of sexual contacts, overall and within sex groups. Trends in suicide attempts during 2009-2019 are also reported by sex, race/ethnicity, and grade. During 2009-2019, prevalence of suicide attempts increased overall and among female, non-Hispanic white, non-Hispanic black, and 12th-grade students. Data from 2019 reflect substantial differences by demographics regarding suicidal ideation and behaviors. For example, during 2019, a total of 18.8% of students reported having seriously considered suicide, with prevalence estimates highest among females (24.1%); white non-Hispanic students (19.1%); students who reported having sex with persons of the same sex or with both sexes (54.2%); and students who identified as lesbian, gay, or bisexual (46.8%). Among all students, 8.9% reported having attempted suicide, with prevalence estimates highest among females (11.0%); black non-Hispanic students (11.8%); students who reported having sex with persons of the same sex or with both sexes (30.3%); and students who identified as lesbian, gay, or bisexual (23.4%). Comprehensive suicide prevention can address these differences and reduce prevalence of suicidal ideation and behaviors by implementing programs, practices, and policies that prevent suicide (e.g., parenting programs), supporting persons currently at risk (e.g., psychotherapy), preventing reattempts (e.g., emergency department follow-up), and attending to persons who have lost a friend or loved one to suicide.</p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"69 1","pages":"47-55"},"PeriodicalIF":0.0,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38291754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transportation Risk Behaviors Among High School Students - Youth Risk Behavior Survey, United States, 2019.","authors":"Merissa A Yellman,&nbsp;Leah Bryan,&nbsp;Erin K Sauber-Schatz,&nbsp;Nancy Brener","doi":"10.15585/mmwr.su6901a9","DOIUrl":"https://doi.org/10.15585/mmwr.su6901a9","url":null,"abstract":"<p><p>Motor-vehicle crashes are a leading cause of death and nonfatal injury among U.S. adolescents, resulting in approximately 2,500 deaths and 300,000 nonfatal injuries each year. Risk for motor-vehicle crashes and resulting injuries and deaths varies, depending on such behaviors as seat belt use or impaired or distracted driving. Improved understanding of adolescents' transportation risk behaviors can guide prevention efforts. Therefore, data from the 2019 Youth Risk Behavior Survey were analyzed to determine prevalence of transportation risk behaviors, including not always wearing a seat belt, riding with a driver who had been drinking alcohol (riding with a drinking driver), driving after drinking alcohol, and texting or e-mailing while driving. Differences by student characteristics (age, sex, race/ethnicity, academic grades in school, and sexual identity) were calculated. Multivariable analyses controlling for student characteristics examined associations between risk behaviors. Approximately 43.1% of U.S. high school students did not always wear a seat belt and 16.7% rode with a drinking driver during the 30 days before the survey. Approximately 59.9% of students had driven a car during the 30 days before the survey. Among students who drove, 5.4% had driven after drinking alcohol and 39.0% had texted or e-mailed while driving. Prevalence of not always wearing a seat belt was higher among students who were younger, black, or had lower grades. Riding with a drinking driver was higher among Hispanic students or students with lower grades. Driving after drinking alcohol was higher among students who were older, male, Hispanic, or had lower grades. Texting while driving was higher among older students or white students. Few differences existed by sexual identity. Multivariable analyses revealed that students engaging in one transportation risk behavior were more likely to engage in other transportation risk behaviors. Traffic safety and public health professionals can use these findings to reduce transportation risk behaviors by selecting, implementing, and contextualizing the most appropriate and effective strategies for specific populations and for the environment.</p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"69 1","pages":"77-83"},"PeriodicalIF":0.0,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38291753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infection Prevention and Control for Ebola in Health Care Settings - West Africa and United States.","authors":"Jeffrey C Hageman,&nbsp;Carmen Hazim,&nbsp;Katie Wilson,&nbsp;Paul Malpiedi,&nbsp;Neil Gupta,&nbsp;Sarah Bennett,&nbsp;Amy Kolwaite,&nbsp;Abbigail Tumpey,&nbsp;Kristin Brinsley-Rainisch,&nbsp;Bryan Christensen,&nbsp;Carolyn Gould,&nbsp;Angela Fisher,&nbsp;Michael Jhung,&nbsp;Douglas Hamilton,&nbsp;Kerri Moran,&nbsp;Lisa Delaney,&nbsp;Chad Dowell,&nbsp;Michael Bell,&nbsp;Arjun Srinivasan,&nbsp;Melissa Schaefer,&nbsp;Ryan Fagan,&nbsp;Nedghie Adrien,&nbsp;Nora Chea,&nbsp;Benjamin J Park","doi":"10.15585/mmwr.su6503a8","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a8","url":null,"abstract":"<p><p>The 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa underscores the need for health care infection prevention and control (IPC) practices to be implemented properly and consistently to interrupt transmission of pathogens in health care settings to patients and health care workers. Training and assessing IPC practices in general health care facilities not designated as Ebola treatment units or centers became a priority for CDC as the number of Ebola virus transmissions among health care workers in West Africa began to affect the West African health care system and increasingly more persons became infected. CDC and partners developed policies, procedures, and training materials tailored to the affected countries. Safety training courses were also provided to U.S. health care workers intending to work with Ebola patients in West Africa. As the Ebola epidemic continued in West Africa, the possibility that patients with Ebola could be identified and treated in the United States became more realistic. In response, CDC, other federal components (e.g., Office of the Assistant Secretary for Preparedness and Response) and public health partners focused on health care worker training and preparedness for U.S. health care facilities. CDC used the input from these partners to develop guidelines on IPC for hospitalized patients with known or suspected Ebola, which was updated based on feedback from partners who provided care for Ebola patients in the United States. Strengthening and sustaining IPC helps health care systems be better prepared to prevent and respond to current and future infectious disease threats.The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"50-6"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34647993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Identification and Prevention of the Spread of Ebola in High-Risk African Countries.","authors":"Lucy Breakwell,&nbsp;A Russell Gerber,&nbsp;Ashley L Greiner,&nbsp;Deborah L Hastings,&nbsp;Kelsey Mirkovic,&nbsp;Magdalena M Paczkowski,&nbsp;Sekou Sidibe,&nbsp;James Banaski,&nbsp;Chastity L Walker,&nbsp;Jennifer C Brooks,&nbsp;Victor M Caceres,&nbsp;Ray R Arthur,&nbsp;Frederick J Angulo","doi":"10.15585/mmwr.su6503a4","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a4","url":null,"abstract":"<p><p>In the late summer of 2014, it became apparent that improved preparedness was needed for Ebola virus disease (Ebola) in at-risk countries surrounding the three highly affected West African countries (Guinea, Sierra Leone, and Liberia). The World Health Organization (WHO) identified 14 nearby African countries as high priority to receive technical assistance for Ebola preparedness; two additional African countries were identified at high risk for Ebola introduction because of travel and trade connections. To enhance the capacity of these countries to rapidly detect and contain Ebola, CDC established the High-Risk Countries Team (HRCT) to work with ministries of health, CDC country offices, WHO, and other international organizations. From August 2014 until the team was deactivated in May 2015, a total of 128 team members supported 15 countries in Ebola response and preparedness. In four instances during 2014, Ebola was introduced from a heavily affected country to a previously unaffected country, and CDC rapidly deployed personnel to help contain Ebola. The first introduction, in Nigeria, resulted in 20 cases and was contained within three generations of transmission; the second and third introductions, in Senegal and Mali, respectively, resulted in no further transmission; the fourth, also in Mali, resulted in seven cases and was contained within two generations of transmission. Preparedness activities included training, developing guidelines, assessing Ebola preparedness, facilitating Emergency Operations Center establishment in seven countries, and developing a standardized protocol for contact tracing. CDC's Field Epidemiology Training Program Branch also partnered with the HRCT to provide surveillance training to 188 field epidemiologists in Côte d'Ivoire, Guinea-Bissau, Mali, and Senegal to support Ebola preparedness. Imported cases of Ebola were successfully contained, and all 15 priority countries now have a stronger capacity to rapidly detect and contain Ebola.The activities summarized in this report would not have been possible without collaboration with many U.S and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"21-7"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34710637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling in Real Time During the Ebola Response.","authors":"Martin I Meltzer,&nbsp;Scott Santibanez,&nbsp;Leah S Fischer,&nbsp;Toby L Merlin,&nbsp;Bishwa B Adhikari,&nbsp;Charisma Y Atkins,&nbsp;Caresse Campbell,&nbsp;Isaac Chun-Hai Fung,&nbsp;Manoj Gambhir,&nbsp;Thomas Gift,&nbsp;Bradford Greening,&nbsp;Weidong Gu,&nbsp;Evin U Jacobson,&nbsp;Emily B Kahn,&nbsp;Cristina Carias,&nbsp;Lina Nerlander,&nbsp;Gabriel Rainisch,&nbsp;Manjunath Shankar,&nbsp;Karen Wong,&nbsp;Michael L Washington","doi":"10.15585/mmwr.su6503a12","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a12","url":null,"abstract":"<p><p>To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"85-9"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34643688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory Response to Ebola - West Africa and United States.","authors":"Tara K Sealy,&nbsp;Bobbie R Erickson,&nbsp;Céline H Taboy,&nbsp;Ute Ströher,&nbsp;Jonathan S Towner,&nbsp;Sharon E Andrews,&nbsp;Laura E Rose,&nbsp;Elizabeth Weirich,&nbsp;Luis Lowe,&nbsp;John D Klena,&nbsp;Christina F Spiropoulou,&nbsp;Mark A Rayfield,&nbsp;Brian H Bird","doi":"10.15585/mmwr.su6503a7","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a7","url":null,"abstract":"<p><p>The 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa highlighted the need to maintain organized laboratory systems or networks that can be effectively reorganized to implement new diagnostic strategies and laboratory services in response to large-scale events. Although previous Ebola outbreaks enabled establishment of critical laboratory practice safeguards and diagnostic procedures, this Ebola outbreak in West Africa highlighted the need for planning and preparedness activities that are better adapted to emerging pathogens or to pathogens that have attracted little commercial interest. The crisis underscored the need for better mechanisms to streamline development and evaluation of new diagnostic assays, transfer of material and specimens between countries and organizations, and improved processes for rapidly deploying health workers with specific laboratory expertise. The challenges and events of the outbreak forced laboratorians to examine not only the comprehensive capacities of existing national laboratory systems to recognize and respond to events, but also their sustainability over time and the mechanisms that need to be pre-established to ensure effective response. Critical to this assessment was the recognition of how response activities (i.e., infrastructure support, logistics, and workforce supplementation) can be used or repurposed to support the strengthening of national laboratory systems during the postevent transition to capacity building and recovery. This report compares CDC's domestic and international laboratory response engagements and lessons learned that can improve future responses in support of the International Health Regulations and Global Health Security Agenda initiatives.The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"44-9"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34647485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foreword.","authors":"Thomas R Frieden","doi":"10.15585/mmwr.su6503a1","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a1","url":null,"abstract":"<p><p>The 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa required a massive international response by many partners to assist the affected countries and tested the world's readiness to respond to global health emergencies. The epidemic demonstrated the importance of improving readiness in at-risk countries and remaining prepared for Ebola and other health threats. The devastation caused by Ebola in Guinea, Liberia, and Sierra Leone is well recognized; what is less widely recognized is that in these countries more people probably died because of Ebola than from Ebola. The epidemic shut most health care systems and derailed programs to prevent and treat malaria, tuberculosis, vaccine-preventable diseases, and other conditions (1,2). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34548394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDC's Response to the 2014-2016 Ebola Epidemic - Guinea, Liberia, and Sierra Leone.","authors":"Benjamin A Dahl,&nbsp;Michael H Kinzer,&nbsp;Pratima L Raghunathan,&nbsp;Athalia Christie,&nbsp;Kevin M De Cock,&nbsp;Frank Mahoney,&nbsp;Sarah D Bennett,&nbsp;Sara Hersey,&nbsp;Oliver W Morgan","doi":"10.15585/mmwr.su6503a3","DOIUrl":"https://doi.org/10.15585/mmwr.su6503a3","url":null,"abstract":"<p><p>CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa was the largest in the agency's history and occurred in a geographic area where CDC had little operational presence. Approximately 1,450 CDC responders were deployed to Guinea, Liberia, and Sierra Leone since the start of the response in July 2014 to the end of the response at the end of March 2016, including 455 persons with repeat deployments. The responses undertaken in each country shared some similarities but also required unique strategies specific to individual country needs. The size and duration of the response challenged CDC in several ways, particularly with regard to staffing. The lessons learned from this epidemic will strengthen CDC's ability to respond to future public health emergencies. These lessons include the importance of ongoing partnerships with ministries of health in resource-limited countries and regions, a cadre of trained CDC staff who are ready to be deployed, and development of ongoing working relationships with U.S. government agencies and other multilateral and nongovernment organizations that deploy for international public health emergencies. CDC's establishment of a Global Rapid Response Team in June 2015 is anticipated to meet some of these challenges. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). </p>","PeriodicalId":37858,"journal":{"name":"MMWR supplements","volume":"65 3","pages":"12-20"},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34647120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}