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Centers for Disease Control and Prevention |
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Antimicrobial Resistance Posing Growing Health Threat - Press Release: April 7, 2011 |
Antimicrobial Resistance Posing Growing Health Threat |
| key goals | 0.361187 |
| sexually transmitted infection | 0.412816 |
| economic burden | 0.362961 |
| Plasmodium falciparum | 0.371136 |
| antimicrobial resistance efforts | 0.565023 |
| antimalarial drugs | 0.37737 |
| CDC Director Thomas | 0.45435 |
| recommended antibiotic | 0.378207 |
| antimicrobial resistance | 0.95461 |
| urgent action | 0.373884 |
| important resource | 0.369329 |
| health care providers | 0.515035 |
| entire health care | 0.443572 |
| health care professionals | 0.440082 |
| societal costs | 0.364126 |
| World Health Organization | 0.446951 |
| longer hospital stays | 0.411764 |
| health care costs | 0.447816 |
| infection prevention techniques | 0.403149 |
| drug-resistant infections | 0.404925 |
| health care facilities | 0.434016 |
| health care settings | 0.526858 |
| past couple | 0.368449 |
| antibiotics | 0.425326 |
| malaria parasites | 0.363513 |
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| action plan | 0.455118 |
| United States | 0.422319 |
| methicillin-resistant Staphylococcus aureus | 0.422082 |
| Sporadic cases | 0.367156 |
| Drug Administration | 0.361371 |
| Southeast Asia | 0.364842 |
| new drug-resistant pathogens | 0.457351 |
| antimicrobial drugs | 0.475737 |
| antibiotic resistance | 0.585651 |
| pressing resistance issues | 0.508813 |
| Resistant infections | 0.381491 |
| global problem | 0.364848 |
| Drug-resistant Klebsiella pneumoniae | 0.455886 |
| CDC advocates | 0.38541 |
| Antimicrobial resistance—when germs | 0.511247 |
| health care | 0.761012 |
| latest available data | 0.41358 |
| pandemic H1N1 flu | 0.418042 |
| R. Frieden | 0.370266 |
| increased costs | 0.364404 |
| effective drugs | 0.377479 |
| health partners | 0.433842 |
| health action plan | 0.442266 |
| worst infections | 0.387809 |
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Centers for Disease Control and Prevention |
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Welding fumes - NIOSH Pocket Guide to Chemical Hazards |
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| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
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| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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| 7484 |
Centers for Disease Control and Prevention |
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Clean Water for Health Program - Water-related Research |
The Health Studies Branch (HSB) leads CDC’s Clean Water for Heath Program (CWH), focuses on drinking water sources that are not regulated by the Safe Drinking Water Act. CWH conducts activities in three areas: water-related exposure and outcome research, the Private Well Initiative, and technical assistance and outbreak response. |
| population health risks | 0.662013 |
| past investigations | 0.289762 |
| toxic chemicals | 0.355984 |
| non-infectious contaminants | 0.655257 |
| research findings | 0.289287 |
| drinking water sources | 0.629992 |
| Health Studies Branch | 0.65727 |
| international partners | 0.281665 |
| public health risks | 0.804847 |
| surface water | 0.300654 |
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| hazardous exposures | 0.388627 |
| private wells | 0.299961 |
| small systems | 0.29088 |
| impact human health | 0.589151 |
| non-infectious agents | 0.447221 |
| health risks | 0.941045 |
| drinking water | 0.914115 |
| investigations focus | 0.290278 |
| Drinking Water contaminants | 0.796079 |
| Common water contaminants | 0.722517 |
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Centers for Disease Control and Prevention |
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Women's Health - Health Communication |
Gateway to Health Communication and Social Marketing Practice - Women's Health |
| certain diseases | 0.415425 |
| treatment | 0.236131 |
| woman | 0.78344 |
| regular screenings | 0.452979 |
| specific disease | 0.429268 |
| impact her health | 0.477602 |
| lifestyle choices | 0.878896 |
| regular exercise | 0.448477 |
| poor health | 0.422928 |
| healthier lifestyle choices | 0.84109 |
| healthy body weight | 0.761983 |
| example | 0.252406 |
| lung cancer | 0.441099 |
| heart disease | 0.817253 |
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| simple measures | 0.428251 |
| smoking | 0.254242 |
| early detection | 0.772288 |
| diseases | 0.479225 |
| second-hand smoke | 0.470645 |
| cervical cancer | 0.451148 |
| stroke | 0.263629 |
| steps | 0.222454 |
| factors | 0.362228 |
| nutritious diet | 0.48303 |
| family history | 0.503547 |
| Women’s Health | 0.387883 |
| risk | 0.914539 |
| conditions | 0.235647 |
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Centers for Disease Control and Prevention |
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Preventing Chronic Disease | The Importance of NaturalExperiments in Diabetes Prevention and Control and the Need forBetter Health Policy Research - CDC |
Diabetes has steadily increased in prevalence, becoming one of the nation’s most challenging public health threats. Prevalence among adults is now more than 10%, and diabetes is the leading cause of nontraumatic lower-extremity amputation, end-stage kidney disease, and blindness; it more than doubles the risk of heart disease, stroke, and disability. |
| diabetes prevention | 0.750646 |
| health insurance | 0.541647 |
| health plans | 0.629438 |
| population-level health policies | 0.597713 |
| territorial health departments | 0.584623 |
| risk factor control | 0.576557 |
| health care benefits | 0.601472 |
| Disease Control | 0.752012 |
| national public health | 0.61576 |
| health behaviors | 0.54992 |
| health systems | 0.796226 |
| NEXT-D research teams | 0.557497 |
| clinical best practices | 0.649186 |
| better health policy | 0.609835 |
| nontraumatic lower-extremity amputation | 0.541547 |
| Affordable Care Act | 0.543844 |
| rigorous health policy | 0.714591 |
| end-stage kidney disease | 0.55945 |
| natural experiments | 0.791595 |
| policy-level approaches | 0.770716 |
| policy effects | 0.535765 |
| health effects | 0.549064 |
| diabetes prevention programs | 0.700292 |
| Health policy studies | 0.632909 |
| NEXT-D studies | 0.641133 |
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| health information technology | 0.582265 |
| major public health | 0.596403 |
| primary prevention strategies | 0.566584 |
| diabetes care quality | 0.695647 |
| diabetes prevalence | 0.662825 |
| Popul Health Metr | 0.57989 |
| health policy research | 0.853655 |
| diabetes incidence demand | 0.709502 |
| public health threats | 0.635309 |
| multicenter research network | 0.5513 |
| public health | 0.913436 |
| CDC-funded Diabetes Prevention | 0.697535 |
| evidence base | 0.540949 |
| public policy decision | 0.537861 |
| diabetes health research | 0.757363 |
| diabetes complications | 0.649196 |
| clinical trial evidence | 0.559366 |
| Public Health Service | 0.592455 |
| public health priority | 0.63409 |
| diabetes risk factors | 0.678755 |
| preventive services | 0.547073 |
| diabetes | 0.972154 |
| NEXT-D natural experiments | 0.555972 |
| Diabetes Translation | 0.604296 |
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Centers for Disease Control and Prevention |
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Asthma - BRFSS 2008 - Prevalence Tables and Maps |
BRFSS 2008 - Prevalence Tables and Maps |
| CDCasthma | 0.468765 |
| Twitter | 0.531587 |
| asthma | 0.725431 |
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| control | 0.462721 |
| live healthier lives | 0.999719 |
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Centers for Disease Control and Prevention |
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Staying Safe Around Damanged Buildings Damaged'PSAs for Disasters |
The Centers for Disease Control and Prevention (CDC) provides Public Service Announcements (PSAs) to help share life-saving information during natural disasters and severe weather. English and Spanish PSAs are in a variety of formats including text, audio, and video. |
| Water | 0.523589 |
| Carbon Monoxide Poisoning | 0.593614 |
| Kreyòk Ayisyen | 0.528926 |
| DME Batteries | 0.539967 |
| Generator Safety | 0.526936 |
| Cold Weather | 0.576627 |
| Apre yon Katastwòf | 0.519098 |
| Sanitize Food Cans | 0.511536 |
| Loved Ones | 0.536427 |
| Mold Cleaning | 0.518854 |
| Haitian Creole | 0.56641 |
| yon Katastwòf Natirèl | 0.519261 |
| disasters | 0.511449 |
| Kid | 0.536966 |
| Pet Kit | 0.551677 |
| Cans Swollen | 0.536185 |
| Pet Microchip | 0.528772 |
| Kids | 0.51815 |
| Heat | 0.518704 |
| Chain Saw Injuries | 0.522181 |
| Canned Drinks | 0.521924 |
| Cell Phone | 0.524477 |
| Renal Diet | 0.536439 |
| Preparedness Tip | 0.963606 |
|
| Hypothermia | 0.516852 |
| Evacuation Centers | 0.513584 |
| Supply Recheck | 0.536853 |
| Carbon Monoxide | 0.600726 |
| Spanish [Español] | 0.522848 |
| Food – Perishables | 0.52187 |
| Food – Canned | 0.520647 |
| Food – Cans | 0.532221 |
| Early Treatment | 0.533557 |
| Extreme Heat | 0.513166 |
| Safety | 0.527094 |
| Stay | 0.513724 |
| Food | 0.537248 |
| Flood Water | 0.521592 |
| Disaster Preparedness | 0.583267 |
| Older Adults | 0.512552 |
| Emergency Wound Care | 0.514803 |
| Dialysis Kit | 0.533621 |
| Public Service Announcements | 0.516163 |
| Educational Materials | 0.511783 |
| Power Outage Spanish | 0.512924 |
| Worker Safety | 0.512329 |
| severe weather | 0.511548 |
| Power Line | 0.524657 |
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Centers for Disease Control and Prevention |
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Acute Flaccid Myelitis | For Clinicians |
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| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
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| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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| 12178 |
Centers for Disease Control and Prevention |
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Global Invasive Bacterial Vaccine-Preventable DiseasesSurveillance - 2008-2014 |
Jillian Murray, MSPH1,2, Mary Agócs, MD1, Fatima Serhan, PhD1, Simarjit Singh, MScIT1, Maria Deloria-Knoll, PhD2, Katherine O'Brien, MD2, Jason M. Mwenda, MD3, Richard Mihigo, MD3, Lucia Oliveira, DSc4, Nadia Teleb, MD, PhD5, Hinda Ahmed, PhD5, Annemarie Wasley, PhD6, Dovile Videbaek, MSc6, Pushpa Wijesinghe, MD7, Arun Bhadra Thapa, MSPH7, Kimberly Fox, MD8, Fem Julia Paladin, PhD8, Rana Hajjeh, MD9, Stephanie Schwartz, MSc9, Chris Van Beneden, MD9, Terri Hyde, MD10, Claire Broome, MD11, Thomas Cherian, MD1 (Author affiliations at end of text). |
| H. influenzae | 0.753737 |
| sentinel hospital sites | 0.843809 |
| Haemophilus influenzae type | 0.743793 |
| childhood immunization programs | 0.743643 |
| Johns Hopkins University | 0.796655 |
| data | 0.937626 |
| chain reaction testing | 0.802806 |
| technical advisory group | 0.819051 |
| web-based data management | 0.746801 |
| Haemophilus influenzae | 0.757409 |
| data tracking hospitalizations | 0.747945 |
| Strategic Advisory Group | 0.88576 |
| PCV impact monitoring | 0.824466 |
| sentinel hospital surveillance | 0.824852 |
| S. pneumoniae | 0.813923 |
| consistent pneumonia case | 0.75523 |
| regional surveillance networks | 0.815369 |
| global reference laboratories | 0.814309 |
| surveillance | 0.951516 |
| vaccine impact | 0.762398 |
| polymerase chain reaction | 0.804874 |
| sentinel hospitals | 0.759687 |
| global surveillance feedback | 0.796382 |
| reference laboratories | 0.883384 |
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| World Health Organization | 0.819025 |
| data postvaccine introduction | 0.748184 |
| baseline surveillance capacity | 0.777913 |
| meningitis | 0.759966 |
| PCV impact | 0.94285 |
| baseline surveillance data | 0.817104 |
| pneumonia syndromic surveillance | 0.860919 |
| countries | 0.769356 |
| well-characterized clinical data | 0.754353 |
| off-site laboratory data | 0.752717 |
| surveillance platform | 0.748403 |
| new vaccines surveillance | 0.794183 |
| conduct population-based surveillance | 0.794753 |
| bacterial meningitis cases | 0.753516 |
| global IB-VPD surveillance | 0.816737 |
| pediatric pneumonia | 0.754927 |
| IB-VPD surveillance network | 0.904892 |
| Regional Office | 0.825347 |
| external quality assessment | 0.787502 |
| Gavi-eligible countries | 0.762337 |
| laboratory data | 0.754069 |
| in-patient pediatric pneumonia | 0.753841 |
| advisory group | 0.889403 |
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Centers for Disease Control and Prevention |
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Naegleria fowleri - Sources of Infection - Case-report Data and Graphs |
Graphs and data related to Naegleria fowleri epidemiology. Education and information about the brain eating ameba Naegleria fowleri that causes encephalitis and death including frequently asked questions, biology, sources of infection, diagnosis, treatment, prevention and control, and other publications and pertinent information for the public and medical professionals. |
| exposure unknown | 0.638256 |
| pond | 0.431925 |
| general public | 0.571051 |
| CDC | 0.478363 |
| example | 0.429435 |
| natural structures | 0.571563 |
| water (N=1) | 0.70036 |
| PAM cases | 0.70105 |
| play venues/water playgrounds | 0.728773 |
| state | 0.428059 |
| artificial whitewater rivers | 0.718908 |
| median age | 0.614594 |
| N=132 | 0.432412 |
|
| swimming pools | 0.579465 |
| local public health | 0.702312 |
| chlorine | 0.440355 |
| hot tubs/spas | 0.571507 |
| therapeutic purpose | 0.578465 |
| partners | 0.427952 |
| probable water exposures | 0.725816 |
| aquatic venues | 0.913231 |
| well-operated aquatic venues | 0.757505 |
| illness onset | 0.57754 |
| reservoir | 0.433958 |
| male | 0.431492 |
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