| 969 |
Centers for Disease Control and Prevention |
Html |
en |
Prevalence of Influenza-Like Illness and Seasonal andPandemic H1N1 Influenza Vaccination Coverage Among Workers - UnitedStates, 2009-10 Influenza Season |
Sara E. Luckhaupt, MD1, Geoffrey M. Calvert, MD1, Jia Li, MS1, Marie Sweeney, PhD1, Tammy A. |
| influenza vaccination coverage | 0.826807 |
| pH1N1 influenza vaccine | 0.522467 |
| ILI | 0.592492 |
| novel influenza | 0.480178 |
| comprehensive influenza prevention | 0.472145 |
| highest prevalence | 0.441804 |
| influenza vaccination programs | 0.586747 |
| influenza-like illness | 0.440068 |
| industry groups | 0.416081 |
| pH1N1 influenza vaccination | 0.742176 |
| seasonal influenza vaccination | 0.555707 |
| highest pH1N1 vaccination | 0.454197 |
| vaccination coverage | 0.955325 |
| prevalence | 0.524357 |
| occupation groups | 0.48491 |
| pandemic H1N1 influenza | 0.485615 |
| relatively low prevalence | 0.421578 |
| vaccination status | 0.531495 |
| ILI prevalence | 0.506541 |
| social services | 0.451643 |
| workplace influenza vaccination | 0.529266 |
| significantly higher APRs | 0.418775 |
| seasonal influenza vaccine | 0.556226 |
| similar pH1N1 vaccination | 0.451292 |
|
| workers | 0.468421 |
| Food preparation | 0.444925 |
| sickle cell anemia | 0.474147 |
| relatively low vaccination | 0.446794 |
| influenza vaccine | 0.585161 |
| influenza season | 0.557209 |
| ILI symptoms | 0.424137 |
| personal protective equipment | 0.489896 |
| seasonal influenza | 0.61592 |
| influenza pandemic | 0.543131 |
| chronic medical conditions | 0.467321 |
| pandemic influenza virus | 0.520982 |
| groups | 0.525348 |
| relatively high prevalence | 0.524283 |
| vaccination coverage data | 0.471011 |
| influenza vaccination | 0.853136 |
| chronic illness | 0.455466 |
| food services | 0.437625 |
| pandemic influenza infection | 0.527803 |
| high prevalence rates | 0.516832 |
| risk | 0.417882 |
| pH1N1 vaccination coverage | 0.675528 |
| unemployed adults | 0.505484 |
|
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| 6690 |
Centers for Disease Control and Prevention |
Html |
en |
Community-Based Opioid Overdose Prevention Programs Providing Naloxone - United States, 2010 |
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. |
| higher overdose risk | 0.299614 |
| opioid drug overdose | 0.463048 |
| high drug overdose | 0.302579 |
| untreated opioid overdoses | 0.243015 |
| drug overdose | 0.836519 |
| drug overdose reversals | 0.317747 |
| opioid-related drug overdose | 0.311802 |
| overdose prevention activities | 0.308078 |
| prescription opioid analgesics | 0.313197 |
| opioid overdose education | 0.423906 |
| Naloxone Overdose Prevention | 0.346473 |
| overdose risk | 0.320878 |
| age-adjusted drug overdose | 0.317171 |
| overdose prevention training | 0.32075 |
| opioid prescribing guidelines | 0.246575 |
| opioid antagonist naloxone | 0.313117 |
| local opioid overdose | 0.500531 |
| community-based opioid overdose | 0.514457 |
| substance abuse treatment | 0.2334 |
| overdose risk factors | 0.312725 |
| naloxone distribution | 0.303828 |
| noninjection opioid users | 0.253618 |
| opioid overdose prevention | 0.992111 |
| overdose prevention services | 0.394003 |
| opioid overdose reversals | 0.38679 |
|
| United States | 0.254981 |
| overdose reversals | 0.54568 |
| overdose prevention programs | 0.479367 |
| overdose death rates | 0.611837 |
| local overdose prevention | 0.300665 |
| opioid overdoses | 0.251765 |
| high overdose mortality | 0.299348 |
| overdose prevention program | 0.490321 |
| drug overdose deaths | 0.684491 |
| overdose prevention interventions | 0.31792 |
| Harm Reduction Coalition | 0.245327 |
| drug overdose death | 0.646641 |
| opioid analgesic prescriptions | 0.24508 |
| unreported overdose reversals | 0.312431 |
| potential overdose witnesses | 0.283004 |
| unintentional drug overdose | 0.386474 |
| overdose rescue kit | 0.288925 |
| highest drug overdose | 0.314459 |
| prescription opioid medications | 0.236009 |
| naloxone | 0.451716 |
| drug overdose prevention | 0.370348 |
| abuse treatment programs | 0.22229 |
| opioid overdose programs | 0.431742 |
| opioid overdose mortality | 0.42065 |
|
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| 6868 |
Centers for Disease Control and Prevention |
Html |
en |
Avian Influenza A (H5N1) Human Infection in Hong Kong |
Avian Influenza A (H5N1) Human Infection in Hong Kong - CDC |
| human influenza | 0.300556 |
| important public health | 0.254239 |
| avian influenza | 0.672399 |
| Pandemic preparedness plans | 0.252126 |
| Hong Kong | 0.426179 |
| HPAI H5N1 | 0.795845 |
| Strategic National Stockpile | 0.264002 |
| CHP DH | 0.209499 |
| highly pathogenic influenza | 0.368134 |
| new confirmed case | 0.278545 |
| live poultry market | 0.259763 |
| novel influenza viruses | 0.391289 |
| pathogenic avian influenza | 0.443978 |
| H5N1 virus strains | 0.418437 |
| close contact | 0.258719 |
|
| Hong Kong SAR | 0.252785 |
| laboratory testing techniques | 0.239065 |
| limited human-to-human transmission | 0.251481 |
| HPAI H5N1 viruses | 0.6021 |
| HPAI H5N1 infection | 0.480528 |
| World Health Organization | 0.272144 |
| influenza pandemic | 0.312461 |
| Communicable Diseases Watch | 0.268106 |
| endemic infection | 0.233487 |
| broadly protective vaccine | 0.241384 |
| influenza surveillance | 0.276573 |
| regular human infections | 0.280684 |
| U.S. Government CDC | 0.263899 |
| CDC avian flu | 0.29718 |
| human infection | 0.445907 |
|
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| 7635 |
Centers for Disease Control and Prevention |
Html |
en |
Global Health - Kenya - Improving Emergency Preparedness & Response |
Improving Emergency Preparedness & Response
CDC-Kenya strengthens public health capacity to rapidly identify and contain infectious disease threats as well as respond to natural and man-made disasters.
|
| international concern | 0.638805 |
| communication systems | 0.64474 |
| international spread | 0.646049 |
| ) Unit. | 0.646981 |
| Laboratory Training Program | 0.719253 |
| large-scale trauma | 0.632817 |
| control strategies | 0.633915 |
| comprehensive outbreak surveillance | 0.779066 |
| global regulations | 0.629008 |
| African Union Mission | 0.716087 |
| dangerous outbreaks | 0.678091 |
| increasingly globalized world | 0.753604 |
| humanitarian disasters | 0.634614 |
| World Health Organization | 0.778024 |
| CDC-Kenya | 0.665648 |
| public health emergencies | 0.815567 |
| Kenya Medical Research | 0.737357 |
| open reporting | 0.626823 |
| public health risks | 0.775281 |
| measure severe outcomes | 0.699534 |
| acute febrile illness | 0.710788 |
| public health response | 0.804047 |
| response efforts | 0.628942 |
| diagnostic support | 0.707882 |
| International Health Regulations | 0.786548 |
|
| outbreaks | 0.680682 |
| Health approach | 0.64611 |
| world more secure | 0.630027 |
| East Africa region | 0.726017 |
| U.S. government partners | 0.721517 |
| emergency medical services | 0.760823 |
| outbreak responses | 0.664199 |
| international borders | 0.63768 |
| non-governmental organizations | 0.639035 |
| public health threats | 0.786816 |
| technical assistance | 0.736533 |
| Rift Valley Fever | 0.704989 |
| public health | 0.928956 |
| disease threats | 0.639716 |
| integrated Zoonotic Disease | 0.748513 |
| future outbreaks | 0.664702 |
| Effective response | 0.660202 |
| international travel | 0.6435 |
| outbreak control plans | 0.794022 |
| emergency medical response | 0.778627 |
| environmental health experts | 0.741814 |
| zoonotic diseases | 0.72721 |
| refugee camps | 0.746333 |
| improved risk communication | 0.759144 |
|
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| 9375 |
Centers for Disease Control and Prevention |
Html |
es |
Intervención de mapeo como guía para el desarrollo de un programa contra la diabetes de apoyo entre compañeros en la zona rural de Alabama |
CDC - Wide Page example description goes here |
| Halanych JH | 0.455825 |
| Hayes M | 0.411781 |
| rural alabama | 0.458526 |
| Wright MA | 0.424646 |
| Appel SJ | 0.476276 |
| Martin MY | 0.430916 |
| Cherrington A | 0.422779 |
|
| salud pública | 0.754982 |
| estrategia promisoria | 0.408684 |
| Chronic Dis | 0.45994 |
| support intervention | 0.574749 |
| asesores pares | 0.966311 |
| Cordón negro | 0.909181 |
|
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| 9842 |
Centers for Disease Control and Prevention |
Html |
null |
Tratamiento - Medicamentos antivirales |
Acerca de los medicamentos antivirales para el público en general - CDC |
|
|
CLICK HERE |
| 10951 |
Centers for Disease Control and Prevention |
Html |
en |
Ovarian Cancer Prevention |
There is no known way to prevent ovarian cancer. But there are few things that may lower a woman's chance of getting ovarian cancer. |
| cervix | 0.292945 |
| risk factors | 0.448414 |
| everybody | 0.273135 |
| ovaries | 0.259616 |
| ovarian cancer | 0.966389 |
| hysterectomy | 0.282126 |
| modestly reduced risk | 0.744152 |
| Breastfeeding. | 0.256919 |
| ovarian cancer— | 0.671032 |
| Talk | 0.255164 |
| birth control pills | 0.775032 |
|
| known way | 0.540616 |
| tubal ligation | 0.56538 |
| lower chance | 0.572975 |
| doctor | 0.25504 |
| uterus | 0.293913 |
| risks | 0.262465 |
| tubes | 0.265817 |
| things | 0.32393 |
| studies | 0.256839 |
| operation | 0.259286 |
|
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| 10963 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Defining Powerhouse Fruits and Vegetables: A Nutrient Density Approach - CDC |
National nutrition guidelines emphasize consumption of powerhouse fruits and vegetables (PFV), foods most strongly associated with reduced chronic disease risk; yet efforts to define PFV are lacking. This study developed and validated a classification scheme defining PFV as foods providing, on average, 10% or more daily value per 100 kcal of 17 qualifying nutrients. Of 47 foods studied, 41 satisfied the powerhouse criterion and were more nutrient-dense than were non-PFV, providing preliminary evidence of the validity of the classification scheme. The proposed classification scheme is offered as a tool for nutrition education and dietary guidance. |
| powerhouse group | 0.557659 |
| classification scheme | 0.93064 |
| food guide pyramid | 0.353391 |
| energy density | 0.316666 |
| Agricultural Research Service | 0.45585 |
| powerhouse criterion | 0.409219 |
| foods | 0.481509 |
| food phytochemicals | 0.326259 |
| Guidelines Advisory Committee | 0.433275 |
| green leafy | 0.458925 |
| World Cancer Research | 0.338737 |
| nutrient density differences | 0.566394 |
| nutrient requirements | 0.402561 |
| cruciferous items | 0.395802 |
| nutrient density | 0.931876 |
| National nutrition guidelines | 0.380042 |
| score/energy density | 0.313882 |
| nutrient desirability | 0.409028 |
| nutrient adequacy score/energy | 0.497379 |
| percent daily values | 0.468988 |
| good sources | 0.341103 |
| nutrients | 0.696695 |
| chronic disease risk | 0.625274 |
| powerhouse message | 0.321561 |
|
| nutrient density scores | 0.766605 |
| powerhouse fruits | 0.394343 |
| nutrient content | 0.426371 |
| percent DVs | 0.373948 |
| heart disease | 0.338784 |
| nutrient adequacy score | 0.595397 |
| PFV | 0.55298 |
| beneficial nutrients PFV | 0.506278 |
| William Paterson University | 0.331223 |
| particular nutrient | 0.422201 |
| nutrient-dense items | 0.37291 |
| National Academies Press | 0.333183 |
| public health importance | 0.350795 |
| national nutrient database | 0.453347 |
| daily energy needs | 0.34222 |
| nutrient quality | 0.406228 |
| food | 0.457573 |
| Dietary Guidelines | 0.372266 |
| nutrient density score | 0.608729 |
| cruciferous food groups | 0.392848 |
| kcal/d diet | 0.354261 |
| Dietary Guidelines Advisory | 0.341581 |
| nutrient-dense foods | 0.340851 |
|
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| 11941 |
Centers for Disease Control and Prevention |
Html |
en |
Considerations for Discharging Persons Under Investigation (PUI) for Ebola Virus Disease (Ebola) |
null |
| concur | 0.350384 |
| Ebola virus infection | 0.707898 |
| fever | 0.340672 |
| example | 0.336112 |
| Ebola virus | 0.805055 |
| 21-day period | 0.495838 |
| antipyretics | 0.368098 |
| state health departments | 0.627222 |
| clinical laboratory results | 0.646274 |
| place | 0.333019 |
| vomiting | 0.349676 |
| illness | 0.340424 |
| RT-PCR test result | 0.650826 |
|
| PUI | 0.925111 |
| alternative diagnosis | 0.48904 |
| onset | 0.344963 |
| Ebola virus exposures | 0.709764 |
| medical care | 0.476669 |
| diarrhea | 0.349156 |
| blood | 0.332166 |
| symptoms | 0.419414 |
| EVD | 0.441549 |
| clinical judgment | 0.519993 |
| medical team | 0.509063 |
| active monitoring | 0.614075 |
| alternative explanation | 0.493886 |
|
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| 16048 |
Centers for Disease Control and Prevention |
Html |
en |
GIS Exchange|Map Details - Diabetes Hospitalizations and Access to Health Care Services |
GIS Exchange |
| additional challenge | 0.284948 |
| Diabetes hospital morbidity | 0.396464 |
| Public Health District | 0.424094 |
| Waycross Public Health | 0.443511 |
| Arc Map | 0.20656 |
| GIS Exchange http://www.cdc.gov/dhdsp/maps/gisx/mapgallery/GA_Waycross.html | 0.259107 |
| diabetes resources | 0.418764 |
| Services Administration | 0.204878 |
| diabetes patients | 0.420739 |
| Health Resources | 0.230103 |
| Diabetes Educators | 0.31446 |
| census tract level | 0.298472 |
| health care resources | 0.441349 |
|
| poverty level | 0.396781 |
| health care services | 0.941623 |
| type ii diabetes | 0.500445 |
| general areas | 0.298579 |
| Georgia Hospital Discharge | 0.280252 |
| additional resources | 0.285623 |
| Diabetes Self-Management Education | 0.401392 |
| Health Care Centers | 0.313852 |
| Map Gallery | 0.221913 |
| Poverty Level Hospitalized | 0.299524 |
| census tract | 0.393165 |
| American Diabetes Association | 0.392092 |
| Georgia Department | 0.266124 |
|
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