| 6742 |
Centers for Disease Control and Prevention |
Html |
en |
Global Health - Kenya - Where We Work |
In Kenya, the CDC is addressing the region's toughest health problems at their source, directly working with vulnerable families and communities in local hospitals, clinics, and laboratories. |
| Kibera | 0.520997 |
| CDC | 0.827011 |
| endorsement | 0.493304 |
| largest informal settlements | 0.9511 |
| offices | 0.460552 |
| large PEPFAR | 0.756244 |
| malaria | 0.484726 |
| CDC-Kenya office | 0.720028 |
| infectious disease threats | 0.963271 |
| major locations | 0.769349 |
| lifecycle | 0.482646 |
| Content source | 0.72811 |
| HHS | 0.499704 |
| bench research | 0.767824 |
| Nairobi | 0.609507 |
| operations | 0.466486 |
| world | 0.461064 |
| largest office | 0.742097 |
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| Notice | 0.468934 |
| HIV/AIDS program | 0.782107 |
| sponsors | 0.458665 |
| showcases | 0.466908 |
| place | 0.460259 |
| policy | 0.463383 |
| vulnerable families | 0.834646 |
| work | 0.554109 |
| tuberculosis | 0.486843 |
| tropical diseases | 0.769474 |
| programmatic oversight | 0.792598 |
| local clinics | 0.806492 |
| Kisumu | 0.682942 |
| practice change | 0.764513 |
| non-federal site | 0.776595 |
| region | 0.471403 |
| employees | 0.458775 |
| office locations | 0.708357 |
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| 6777 |
Centers for Disease Control and Prevention |
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Evaluation of the Healthy Schools Program: Part I. Interim progress. |
The objective of this study was to evaluate interim progress in schools receiving hands-on training from the Healthy Schools Program, the nation’s largest school-based program aimed at preventing childhood obesity. |
| physical education | 0.72886 |
| health education | 0.363142 |
| HSP website | 0.384067 |
| program targets schools | 0.494572 |
| school districts | 0.446364 |
| Wood Johnson Foundation | 0.44241 |
| obesity prevention | 0.352089 |
| overall HSP participants | 0.402673 |
| relevant school personnel | 0.35291 |
| HSP relationship managers | 0.441882 |
| 4-year program targets | 0.412873 |
| HSP Inventory | 0.517025 |
| HSP | 0.617899 |
| school meals | 0.378652 |
| income elementary schools | 0.35133 |
| Hunger-Free Kids Act | 0.449759 |
| HSP program | 0.404818 |
| American Heart Association | 0.386288 |
| after-school programs | 0.355279 |
| schools | 0.908577 |
| HSP Framework | 0.385476 |
| school representatives | 0.504303 |
| managers contact schools | 0.385378 |
| competitive foods | 0.54341 |
|
| United States | 0.351442 |
| public school districts | 0.358347 |
| school progress | 0.34891 |
| significant changes | 0.349461 |
| school employee wellness | 0.714051 |
| Robert Wood Johnson | 0.444083 |
| school meals areas | 0.360195 |
| technical assistance | 0.357542 |
| Schools complete training | 0.387797 |
| HSP participants | 0.419726 |
| school nutrition programs | 0.369834 |
| federally funded school | 0.352648 |
| content areas | 0.570899 |
| school wellness council | 0.367242 |
| Healthy Schools Program | 0.55784 |
| elementary schools | 0.355646 |
| school wellness efforts | 0.367524 |
| school wellness policy | 0.392784 |
| physical activity | 0.825963 |
| follow-up inventories | 0.460422 |
| childhood obesity | 0.491032 |
| relationship managers | 0.476688 |
| physical education programs | 0.356222 |
| WIC Reauthorization Act | 0.382948 |
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| 8003 |
Centers for Disease Control and Prevention |
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Science Clips - Monday, January 28, 2013 |
null |
| smoke-free laws | 0.624708 |
| hepatitis C. Looking | 0.73019 |
| independent risk factor | 0.694094 |
| New York City | 0.711341 |
| CDC laboratorians | 0.726958 |
| important articles | 0.629102 |
| ongoing burden | 0.619452 |
| CDC Science Clips | 0.823511 |
| 2009-2010 H1N1 pandemic | 0.706458 |
| school-level implementation | 0.619852 |
| Librarian | 0.607937 |
| forward looking articles | 0.69923 |
| Current influenza prevention | 0.723849 |
| Barbara Landreth | 0.610743 |
| Science Clips Production | 0.71945 |
| non-pharmaceutical interventions | 0.620558 |
| high-risk group | 0.616317 |
| response teams | 0.610737 |
| DHHS | 0.614972 |
| life expectancy | 0.622813 |
| Haiti earthquake | 0.607973 |
| preparedness plans | 0.608797 |
| state level | 0.622213 |
| Chronic Disease Self-Management | 0.736695 |
| treatment strategies | 0.610045 |
|
| Lancet notes reasons | 0.693668 |
| MC Farrelly | 0.625692 |
| Web Developer | 0.693273 |
| public health priorities | 0.713021 |
| CDC journal | 0.757942 |
| timely commentary | 0.607799 |
| Rickettsia spp | 0.612716 |
| retrospective cohort study | 0.701238 |
| cautious optimism | 0.614784 |
| individual benefit | 0.610775 |
| CY Kato | 0.61384 |
| public health | 0.807657 |
| Science Clips | 0.924246 |
| chronic diseases | 0.629239 |
| state tobacco control | 0.716874 |
| KB Enfield | 0.608669 |
| public health literature | 0.691609 |
| B. Thacker CDC | 0.797895 |
| EIS alumnus SG | 0.713837 |
| prominent role | 0.60994 |
| youth smoking | 0.612682 |
| John Iskander | 0.730238 |
| New England Journal | 0.732069 |
| Science Clips features | 0.76289 |
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| 8640 |
Centers for Disease Control and Prevention |
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en |
PanFlu Storybook - Finding A Cure, Sadie Afraid of His Horses-Janis |
Finding A Cure, One of the most important challenges, for health communicators today, is helping the public to understand that a flu shot will not be readily available when the next pandemic strikes. Once the virus is identified, it will take several months to produce a vaccine. In 1918, in desperation, people tried a variety of methods to cure the sick —some practical and effective, others questionable and even amusing. |
| Sadie Afraid | 0.567346 |
| 1918 flu pandemic | 0.581589 |
| cousin Edgar | 0.412807 |
| sweet grass | 0.485277 |
| Poor Elk–Red Cloud | 0.575992 |
| cousin Nancy | 0.460837 |
| flat cedar | 0.492088 |
| Red Cloud | 0.979346 |
| Pine Ridge | 0.719573 |
| Pine Ridge Indian | 0.514573 |
| white kerosene | 0.425634 |
| members | 0.40611 |
| Sadie′s father | 0.511983 |
| Sadie′s brother Paul | 0.484543 |
| influential Sioux leaders | 0.514871 |
| husband Joe Hand | 0.503965 |
| Denver Broncos football | 0.481386 |
| flat cedar tea | 0.476757 |
| Red Cloud family | 0.884258 |
| Alice Red Cloud | 0.579235 |
| Jack Red Cloud | 0.604758 |
| Sadie′s grandmother | 0.476898 |
| five–day journey | 0.413714 |
| personal items | 0.5024 |
| cousin depart | 0.421631 |
|
| Spud Pickin | 0.416474 |
| Sadie′s sister | 0.416746 |
| Young Man Afraid | 0.536132 |
| grandmother Sadie | 0.641509 |
| Nancy | 0.504139 |
| Nancy′s family | 0.451972 |
| Sallie Black Bear | 0.509768 |
| Sadie′s siblings Zona | 0.536892 |
| bad sickness | 0.502386 |
| economic venture | 0.408012 |
| real bad sickness | 0.498968 |
| Alliance | 0.419217 |
| parents Lucy | 0.409981 |
| Susie Red Cloud–Hand | 0.533545 |
| elderly grandmother′s wagon | 0.503617 |
| South Dakota | 0.535679 |
| wagon box | 0.418302 |
| Sadie | 0.667503 |
| Short Bull | 0.421446 |
| home | 0.437662 |
| Frank Afraid | 0.439841 |
| oldest children | 0.410184 |
| drizzling rain | 0.40577 |
| Edgar Red Cloud | 0.580469 |
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| 10051 |
Centers for Disease Control and Prevention |
Html |
en |
CDC Global Health - Stories - People on the Move: Reaching Mobile Workers in the Dominican Republic |
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| construction workers | 0.768191 |
| early results | 0.592353 |
| Ministry | 0.556196 |
| national surveillance | 0.582414 |
| so-called mobile workers | 0.705322 |
| truck drivers | 0.599232 |
| farm | 0.532751 |
| street vendors | 0.595941 |
| lay health educators | 0.680902 |
| health emergencies | 0.598444 |
| data shows | 0.597975 |
| seasonal work | 0.607569 |
| testing | 0.532724 |
| public health officials | 0.705149 |
| construction sites | 0.595429 |
| farms | 0.534662 |
| intimate knowledge | 0.593229 |
| highest priorities | 0.588825 |
| larger effort | 0.585311 |
| pregnant mothers | 0.584922 |
| precise size | 0.598042 |
| new cases | 0.586045 |
| impressive results | 0.605947 |
| HIV/AIDs | 0.554601 |
| condoms | 0.519402 |
|
| mobile populations | 0.588513 |
| general population | 0.604071 |
| local community | 0.593826 |
| HHS | 0.519811 |
| promotores | 0.531678 |
| sexually transmitted infections | 0.655258 |
| mobile population | 0.606673 |
| CDC’s country | 0.637036 |
| adult HIV | 0.61406 |
| sugar cane plantations | 0.693907 |
| prevention methods | 0.588969 |
| health care workers | 0.680568 |
| social stigma | 0.593767 |
| additional benefits | 0.589167 |
| counseling | 0.532724 |
| hard-to-find population | 0.6261 |
| mobile health units | 0.685596 |
| people | 0.602777 |
| transient workers | 0.603288 |
| laborers | 0.521092 |
| small group interventions | 0.666233 |
| non-governmental agencies | 0.59664 |
| non-federal site | 0.592186 |
| Dominican Republic | 0.949453 |
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| 10319 |
Centers for Disease Control and Prevention |
Html |
en |
HAN Archive - 00001 - Terrorist Activity Response |
Health Alert Network (HAN). Provided by the Centers for Disease Control and Prevention (CDC). |
| local laboratory directors | 0.819992 |
| public information officers | 0.803282 |
| unusual occurrence | 0.684104 |
| CDC | 0.664533 |
| access | 0.436626 |
| illnesses | 0.442377 |
| dispatch centers | 0.63928 |
| http://emergency.cdc.gov/ | 0.436505 |
| unusual disease occurrence | 0.90462 |
| numbers | 0.439683 |
| HAN coordinators | 0.643594 |
| hospital emergency departments | 0.832335 |
| units | 0.438674 |
| assistance | 0.437837 |
| international organizations | 0.614004 |
| Health Alert Network | 0.94491 |
| segments | 0.445649 |
| enhances health decisions | 0.828331 |
| Prevention | 0.435932 |
| critical health issues | 0.816258 |
| credible information | 0.635264 |
| Disease Control | 0.62159 |
| possible unusual disease | 0.90057 |
|
| clinician organizations | 0.6327 |
| e-mail | 0.436731 |
| Tuesday | 0.440111 |
| state | 0.485324 |
| surveillance | 0.437183 |
| situation | 0.443079 |
| PM EDT | 0.74463 |
| emergency response | 0.639582 |
| emergency number | 0.631483 |
| website | 0.436592 |
| healthalert | 0.436696 |
| healthy living | 0.614998 |
| patterns | 0.440631 |
| local health officers | 0.833783 |
| message | 0.436546 |
| alert status | 0.672391 |
| people | 0.435847 |
| local public health | 0.861038 |
| biological agents | 0.649329 |
| strong partnerships | 0.616067 |
| current events | 0.652 |
| chemical | 0.440485 |
| cdc.gov | 0.436661 |
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CLICK HERE |
| 11576 |
Centers for Disease Control and Prevention |
Html |
en |
NER - Peer-Reviewed Biomonitoring Articles | (PCBs), and Organochlorine Pesticides |
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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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CLICK HERE |
| 12954 |
Centers for Disease Control and Prevention |
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en |
Invasive Cancer Incidence and Survival - United States,2011 |
S. Jane Henley, MSPH1, Simple D. Singh, MD1, Jessica King, MPH1, Reda Wilson, MPH1, Mary Elizabeth O'Neil, MPH1, A. |
| S. Jane Henley | 0.436997 |
| female breast cancer | 0.417507 |
| data | 0.462502 |
| skin cancer prevention | 0.412248 |
| melanoma incidence rates | 0.419902 |
| high cancer incidence | 0.483708 |
| invasive cancers | 0.451353 |
| relative survival rate | 0.441842 |
| lung cancer | 0.439808 |
| Central Cancer Registry | 0.443584 |
| U.S. Cancer Statistics | 0.441334 |
| cancer incidence rates | 0.797113 |
| white persons | 0.415513 |
| cancer control programs | 0.429143 |
| 5-year relative survival | 0.650422 |
| colorectal cancer | 0.48419 |
| state-specific cancer incidence | 0.463685 |
| cancer diagnosis | 0.454271 |
| annual incidence | 0.468862 |
| persons | 0.510427 |
| cancer survivors | 0.461452 |
| cancers | 0.47476 |
| relative survival rates | 0.448827 |
| cervical cancer incidence | 0.519944 |
| Puerto Rico | 0.52545 |
|
| common cancer sites | 0.414762 |
| cancer prevention | 0.42361 |
| regional cancer registry | 0.412603 |
| United States | 0.546876 |
| cancer registry data | 0.453289 |
| site-specific cancer incidence | 0.469328 |
| cancer incidence rate | 0.468334 |
| cancer registries | 0.483454 |
| population-based cancer registries | 0.429544 |
| Annual incidence rates | 0.435672 |
| cell skin cancers | 0.411863 |
| National Cancer Institute | 0.444694 |
| annual incidence rate | 0.432445 |
| cancer surveillance data | 0.427429 |
| Healthy People | 0.456105 |
| colorectal cancer incidence | 0.46885 |
| black persons | 0.444654 |
| cancer survival rates | 0.460136 |
| USCS publication criteria | 0.448879 |
| central cancer registries | 0.42389 |
| breast cancer | 0.436804 |
| national cancer objectives | 0.414974 |
| age-adjusted annual incidence | 0.420147 |
| prostate cancer | 0.441407 |
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| 13302 |
Centers for Disease Control and Prevention |
Video |
en |
Lisa: My Experience with BRCA Counseling and Testing |
Lisa, age 40, talks about how her family history led her to get genetic counseling and testing for BRCA gene mutations. She describes the genetic testing experience, and how it helped her understand her family history and manage her risk for breast cancer.
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://www.cdc.gov/cancer/videos/breast/BringYourBrave/Lisa/MyExperienceCT/MyExperienceCT_lowRes.mp4 |
| Experience | 0.660934 |
| BRCA Counseling | 0.907396 |
|
| YouTube | 0.883609 |
| Lisa | 0.818773 |
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CLICK HERE |
| 14380 |
Centers for Disease Control and Prevention |
Html |
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Products - Data Briefs - Number 241 - April 2016 |
Increase in Suicide in the United States, 1999–2014 |
| female age-adjusted rate | 0.20531 |
| suicide mortality | 0.304241 |
| important public health | 0.210648 |
| Margaret Warner | 0.202208 |
| United States | 0.324464 |
| Access data table | 0.504436 |
| age group | 0.281252 |
| second-highest suicide rate | 0.3121 |
| age-adjusted death rates | 0.254059 |
| Associate Director | 0.217753 |
| suicide rates | 0.938196 |
| age-adjusted suicide rate | 0.56591 |
| percent increase | 0.590549 |
| Data Brief No. | 0.212761 |
| Sally C. Curtin | 0.296785 |
| suicide rate | 0.630688 |
| codes U03 | 0.386954 |
| lowest suicide rate | 0.310685 |
| age-adjusted rate | 0.233645 |
| second-largest percent increase | 0.309259 |
| National Center | 0.231387 |
| Suicide deaths | 0.371296 |
| female suicide rates | 0.316832 |
| females | 0.385745 |
|
| common suicide method | 0.361697 |
| Percent increases | 0.210256 |
| suffocation | 0.223266 |
| nchs data brief | 0.313181 |
| annual percent increase | 0.303101 |
| rate ratios | 0.262924 |
| National Vital Statistics | 0.768232 |
| males | 0.354894 |
| age groups | 0.581205 |
| Suicide numbers | 0.237808 |
| cause-of-death codes U03 | 0.269651 |
| male age-adjusted rate | 0.205345 |
| generally declining mortality | 0.203084 |
| multiple cause-of-death mortality | 0.201367 |
| International Statistical Classification | 0.638908 |
| Related Health Problems | 0.623388 |
| suicides | 0.261405 |
| largest percent increase | 0.30681 |
| suicide methods | 0.265392 |
| average annual percent | 0.299942 |
| Holly Hedegaard | 0.205521 |
| frequent suicide method | 0.322463 |
| small number | 0.204659 |
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CLICK HERE |