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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
6462	Centers for Disease Control and Prevention	Html	en	Obesity in K-8 Students - New York City, 2006-07 to 2010-11 School Years	Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov.	school neighborhood poverty 0.58273 grade children 0.549821 public health interventions 0.620418 neighborhood poverty level 0.561983 Asian/Pacific Islander children 0.608985 obesity prevention programs 0.564438 postal code area 0.562182 public health office 0.591633 City public school 0.585763 education public schools 0.550968 obesity prevalence trends 0.594882 New York City 0.96021 public school students 0.59091 children 0.67889 school 0.652973 shows obesity prevalence 0.599487 school postal code 0.60941 obesity prevalence 0.691896 child obesity 0.548554 poverty level 0.585933 obesity reduction 0.549943 body mass index 0.569503 York City Dept 0.613604 age groups 0.577588 pediatric obesity 0.563653	public school children 0.60315 York City fitness 0.557308 federal poverty level 0.567968 K–8 public school 0.575406 United States 0.559483 age group 0.582415 public school data 0.56175 obese children 0.553035 school type 0.548094 group child care 0.557457 public school 0.648072 public school population 0.571083 Asian/Pacific Islander 0.678625 white children 0.557586 school postal codes 0.550181 district public health 0.549462 Obesity prevalence estimates 0.58522 largest decrease 0.553839 school borough 0.581458 physical education teachers 0.570859 physical activity 0.574964 York City Department 0.60924 childhood obesity 0.585227 free lunch status 0.65201	CLICK HERE
8015	Centers for Disease Control and Prevention	Html	en	Why Our Global Work Matters - CDC Global Health	null	Global Work Matters 0.628451		CLICK HERE
9451	Centers for Disease Control and Prevention	Html	es	Mejora del rendimiento del sistema de salud pública por medio de asociaciones multiorganizacionales.	null	Scutchfield FD 0.359078 múltiples organizaciones 0.347442 salud pública 0.933435	Mays GP 0.360711 Estados Unidos 0.420296 altos costos 0.347513	CLICK HERE
10969	Centers for Disease Control and Prevention	Html	en	MERS-Laboratory Testing for MERS-CoV	CDC Coronavirus: Coronaviruses are common throughout the world. They can infect people and animals. Five different coronaviruses can infect people and make them sick. They usually cause mild to moderate upper-respiratory illness.	investigational purposes 0.661456 active infection 0.726152 circumstances additional specimens 0.662152 CDC 0.843775 FDA-cleared/approved tests 0.560801 additional confirmatory testing 0.616652 stool specimens 0.561091 public health investigators 0.632961 current case definition 0.644236 MERS-CoV outbreak 0.560701 MERS symptoms 0.575269 rRT-PCR assay 0.715309 travel industry partners 0.67345 secondary antibody 0.640045 Serology testing 0.582449 CDC investigators 0.604616 serology tests 0.801317 specific confirmatory test 0.629213 ELISA results 0.569197 IFA results 0.576045 single negative result 0.653775 active MERS-CoV infection 0.874032 virus-infected cells 0.658375 Real-time reverse-transcription polymerase 0.653533 IFA assay 0.636395	MERS-CoV serology tests 0.734997 specific antibodies 0.826761 MERS disease 0.578686 single positive target 0.645902 positive rRT-PCR result 0.664331 ELISA 0.584465 different laboratory tests 0.704199 negative rRT-PCR tests 0.691043 United States 0.642599 public health scientists 0.832736 diagnostic purposes 0.650633 lab tests 0.578256 immunofluorescence assay 0.592508 public health 0.898539 specific genomic targets 0.64778 microneutralization assay 0.776213 molecular tests 0.77192 negative rRT-PCR test 0.678434 MERS-CoV serology results 0.707824 MERS-CoV infection 0.99837 local public health 0.67812 previous infection 0.725597 enzyme-linked immunosorbent assay 0.696018 clinical sample 0.727559	CLICK HERE
11710	Centers for Disease Control and Prevention	Html	en	Alcohol Involvement in Opioid Pain Reliever andBenzodiazepine Drug Abuse-Related Emergency Department Visits andDrug-Related Deaths - United States, 2010	Christopher M. Jones, PharmD1, Leonard J. Paulozzi, MD2, Karin A.	DAWN ME data 0.547161 benzodiazepine deaths 0.57232 OPR drug 0.545762 abuse–related ED visits 0.787552 United States 0.623523 OPR abuse–related ED 0.591904 Drug Administration 0.544138 ED visits 0.991544 alcohol consumption 0.603555 benzodiazepine ED visits 0.655949 national ED visits 0.621294 benzodiazepine visits 0.57281 prescription drug abuse 0.579913 alcohol involvement 0.702533 prescription drugs 0.548071 single-drug class deaths 0.602889 drug abuse-related ED 0.620951 Excessive alcohol consumption 0.601837 alcohol overdose 0.569821 OPR ED visits 0.633684 benzodiazepine drug-related deaths 0.61956 benzodiazepine single-drug class 0.548036 Drug Abuse Warning 0.552709 alcohol 0.85075	single-drug class ED 0.590821 alcohol-related visits 0.561645 illicit drugs 0.544487 hospital ED visits 0.622648 benzodiazepines 0.668043 drugs 0.610099 OPRs 0.610711 alcohol increases 0.584314 Christopher M. Jones 0.573296 class ED visits 0.623767 DAWN ED 0.615133 problematic alcohol 0.569219 drug related deaths 0.580656 single drug-class deaths 0.571183 abuse-related ED visits 0.656696 alcohol consumption level 0.584622 pharmaceutical overdose deaths 0.571044 drug abuse–related ED 0.687137 OPR deaths 0.593359 OPR visits 0.578234 drug-related deaths 0.783779 ED visit data 0.579513 benzodiazepine-related deaths 0.556675	CLICK HERE
11878	Centers for Disease Control and Prevention	Html	en	Influenza Outbreak in a Vaccinated Population - USS Ardent,February 2014	Theodore L. Aquino, DO1, Gary T. Brice, PhD2, Sherry Hayes, MPH3, Christopher A.	Center San Diego 0.358092 Preventive Medicine Unit 0.432131 Ardent crew member 0.406064 influenza vaccination policy 0.525361 San Diego County 0.346564 nasal swab specimens 0.999545 seasonal influenza vaccination 0.517233 San Diego 0.849812 independent duty corpsman 0.436884 ILI cases 0.442786 influenza A. Ultimately 0.563326 ILI case 0.426458 influenza vaccine 0.627407 ILI symptoms 0.758156 outbreak response 0.361913 Public Health Services 0.439824 rapid influenza testing 0.776649 U.S. Navy minesweeper 0.380544 local naval health 0.342019 immediate influenza testing 0.538563 U.S. Navy 0.485998 Health Research Center 0.667209 ship outbreak 0.361256 hemisphere influenza season 0.518432	influenza 0.781739 Diego Public Health 0.447259 Naval Health Research 0.545673 influenza outbreaks 0.447659 USS Ardent sailor 0.374397 H3N2 influenza outbreak 0.644008 shipboard medical provider 0.339197 Theodore L. Aquino 0.444398 crew members 0.985698 USS Ardent 0.79934 ILI patients 0.565675 higher-level Navy authorities 0.351446 initial rapid influenza 0.561949 influenza season 0.55381 USS Ardent crew 0.505646 San Diego Public 0.447276 ILI patient 0.504075 rapid influenza tests 0.533109 outbreak isolate 0.371021 influenza epidemics 0.450791 Ardent crew members 0.51484 Influenza A virus 0.463483 outbreak information 0.361849 Base San Diego 0.340838	CLICK HERE
12545	Centers for Disease Control and Prevention	Video	en	CDC: Theresa's Story, Let's Stop HIV Together	In this digital story, Theresa discusses learning about her HIV diagnosis and how her diagnosis has changed her life. Her daughter, Crystal, discusses the importance of supporting friends and family who are HIV positive. Let's Stop HIV Together is a national HIV awareness and anti-stigma campaign produced by the Centers for Disease Control and Prevention (CDC). It features stories of individuals living with HIV and the people who support them. Join the conversation on Facebook at www.facebook.com/ActAgainstAIDS. Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html This video can also be viewed at http://streaming.cdc.gov/vod.php?id=3fee3ed417ee28e72d10704798ef7c3420131125085910390	CDC 0.701155 Theresa 0.718023	YouTube 0.672781	CLICK HERE
13458	Centers for Disease Control and Prevention	Html	en	Notes from the Field: Large Outbreak of Botulism Associatedwith a Church Potluck Meal - Ohio, 2015	Carolyn L. McCarty, PhD1,2; Kristina Angelo, DO2,3; Karlyn D. Beer, PhD2,3; Katie Cibulskas-White1; Kim Quinn, MS1; Sietske de Fijter, MS1; Rick Bokanyi, PhD1; Eric St.	Public Health Laboratory 0.689015 potluck foods 0.669413 botulism outbreaks 0.694154 botulinum neurotoxin type 0.879953 Strategic National Stockpile 0.828895 probable case definition 0.690782 largest botulism outbreak 0.794451 Eric St. Germain 0.685566 health department notification 0.733083 Brendan R. Jackson 0.682599 home-canned potatoes 0.664682 Botulism Associated 0.748909 Barbara E. Mahon 0.687543 improperly home-canned potatoes 0.661473 Fairfield Department 0.787466 Fairfield Medical Center 0.845785 Agam K. Rao 0.690849 potato salad 0.910573 Zoonotic Infectious Diseases 0.775891 Ohio Department 0.707645 potluck meal 0.950196 public health emergency 0.731173 5Fairfield Medical Center 0.661602 early hospital discharge 0.646328	laboratory-confirmed botulism 0.7212 homemade potato salad 0.697702 public health 0.78893 botulinum toxin 0.645972 National Center 0.645219 County Public Health 0.688906 Carolyn L. McCarty 0.838655 Karlyn D. Beer 0.693374 confirmed case status 0.689131 church potluck meal 0.94684 emergency department 0.74768 botulinum antitoxin 0.739973 established home-canning guidelines 0.65476 similar clinical features 0.671833 Public Health Preparedness 0.687264 2Epidemic Intelligence Service 0.651181 Columbus metropolitan area 0.666215 C. botulinum spores 0.71966 case definition 0.709483 Kara Jacobs Slifka 0.679564 botulism 0.803631 potluck food 0.684429 Clostridium botulinum type 0.726801	CLICK HERE
13527	Centers for Disease Control and Prevention	Html	en	Publications, Data, & Statistics | Contact Lenses | CDC	CDC - Protect Your Eyes: Healthy and Safe Contact Lens Cleaning and Use. Millions of people use contact lenses every day but lens cleaning practices can lead to eye infections. Hands should be washed before handling contact lenses and contacts should be properly cleaned, disinfected, and stored to ensure eye health and safety. Following your eye doctor’s recommendations and a few simple steps can lead to healthy daily contact lens use.	pediatric contact lens 0.356152 Lam DY 0.312681 wear contact lens 0.341539 contact lens users 0.337717 contact lens risk 0.337329 Chalmers RL 0.472701 Cont Lens Anterior 0.733085 extended-wear contact lens 0.334071 Kinoshita BT 0.28361 Stapleton F. Contact 0.352929 lens materials 0.306259 Beach MJ 0.291389 Acanthamoeba keratitis 0.351261 Lens Anterior Eye. 0.733067 Study Group 0.28165 contact lenses 0.417087 contact lens case 0.34969 risk factors 0.342736 F. Contact lens 0.350097 Stapleton F. 0.391309 Contact lens wearer 0.333375 microbial keratitis 0.312297 contact lens storage 0.335809 multiple contact lens 0.331789 contact lens hygiene 0.310353	soft contact lens 0.381679 contact lens wearers 0.385076 contact lens postmarket 0.323913 disposable contact lens 0.321349 United States 0.288696 cosmetic contact lenses 0.296543 Eye Contact Lens. 0.810076 lens replacement 0.292958 contact lens wear 0.510764 safe lens wear 0.298044 silicone hydrogel 0.317271 contact lens assessment 0.347294 silicone hydrogel lenses 0.298831 corneal infiltrative events 0.294927 disposable contact lenses 0.305594 lens storage cases 0.289235 lens case biofilm 0.287012 lens storage case 0.328768 contact lens compliance 0.354469 contact lens solution 0.409927 lens case contamination 0.328777 contact lens cases 0.340368 contact lens solutions 0.331318 Optom Vis Sci. 0.900611	CLICK HERE
13689	Centers for Disease Control and Prevention	Html	en	The Contribution of Age and Weight to Blood Pressure Levels Among Blacks and Whites Receiving Care in Community-Based Primary Care Practices	Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention.	demographic characteristics 0.261544 Johns Hopkins University 0.43375 whites 0.317622 Maryland primary care 0.286114 BP cuff 0.413377 diastolic blood pressure 0.329178 BMI category 0.589024 cross-sectional study 0.288839 older ages 0.271133 Johns Hopkins 0.633602 high BP 0.385121 clinical research committee 0.255793 Hopkins Bloomberg School 0.432581 blood pressure 0.42108 risk factors 0.256504 medical record data 0.283226 body mass index 0.499749 patients 0.351683 Johns Hopkins Medicine 0.30055 weight loss 0.321408 Hopkins University School 0.428403 uncontrolled BP 0.441693 primary care provider 0.26328 diastolic BP 0.882298 higher BP 0.578148	diabetes status 0.255211 African American 0.260187 electronic medical record 0.576453 Public Health 0.277562 Johns Hopkins Bloomberg 0.437921 United States 0.249812 age group 0.282893 association 0.28701 3-minute rest period 0.252269 institutional review board 0.250867 BP 0.972711 Johns Hopkins Community 0.293474 adult patients 0.289558 non-Hispanic blacks 0.366432 health care 0.250799 BMI 0.749115 higher BP levels 0.527789 elevated weight category 0.296527 race 0.417766 elevated BP 0.446452 BP measurement devices 0.485419 elevated blood pressure 0.281231 poorer BP control 0.515435 systolic BP 0.85729	CLICK HERE