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Centers for Disease Control and Prevention |
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Protect Your Family from Rabies | CDC Features |
Rabies is a dangerous virus that anyone can get if they handle or get bitten by an animal that has the disease. Protect yourself and your family from rabies: stay away from wild animals and be sure pets are vaccinated every year.
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| pets | 0.336825 |
| Early symptoms | 0.297205 |
| useful barrier | 0.279987 |
| unusual animal behavior | 0.358047 |
| wild animals | 0.765322 |
| unfamiliar domestic animals | 0.369443 |
| similar risks | 0.281188 |
| direct supervision | 0.28457 |
| rabies testing | 0.452783 |
| direct bat contact | 0.342956 |
| rabid animal | 0.309115 |
| animal control | 0.44071 |
| Animal care | 0.294274 |
| family members | 0.355268 |
| domestic animals | 0.496876 |
| camp sites | 0.28043 |
| animal rabies cases | 0.567868 |
| rabies shots | 0.463475 |
| occupied spaces | 0.28023 |
| unwanted animals | 0.302249 |
| camp attendees | 0.282654 |
| natural setting | 0.283679 |
| Family pets | 0.292198 |
| potential exposures | 0.349398 |
| best ways | 0.29365 |
|
| rabid wild animals | 0.401132 |
| camp official | 0.28204 |
| rabies-suspect animal | 0.297916 |
| bats | 0.375266 |
| regular basis | 0.286777 |
| camp situations | 0.277212 |
| rabies vaccinations | 0.46306 |
| close contact | 0.28782 |
| potential exposure | 0.282492 |
| dead bats | 0.311207 |
| higher risk | 0.286521 |
| life-threatening situations | 0.28008 |
| dead wild animals | 0.37363 |
| dangerous virus | 0.293823 |
| wildlife conservation agencies | 0.349567 |
| rabies | 0.935109 |
| Contact animal control | 0.366057 |
| people | 0.360318 |
| following link | 0.279969 |
| stray animals | 0.354887 |
| main animals | 0.310414 |
| healthcare provider | 0.286688 |
| risk | 0.290059 |
| ferrets indoors | 0.288856 |
|
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Centers for Disease Control and Prevention |
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Autism: New Training for HealthProfessionals | CDC Features |
April is Autism Awareness Month. Learn about CDC's new training to help health practitioners identify autism and provide quality care. |
| real-life scenarios | 0.423976 |
| hearing test | 0.440306 |
| CDC’s training | 0.53495 |
| appropriate alternatives | 0.43356 |
| Applied Behavior Analysis | 0.528076 |
| following topics | 0.422653 |
| ACT CE course | 0.78183 |
| early services | 0.435963 |
| Act Early. | 0.637282 |
| comprehensive teaching tool | 0.542942 |
| instructor-support materials | 0.432578 |
| regular basis | 0.427073 |
| case-based format | 0.437248 |
| Developmental Behavioral Pediatrician | 0.624675 |
| early care | 0.466581 |
| CNE credits | 0.441268 |
| early warning signs | 0.703584 |
| autism spectrum disorders | 0.610184 |
| ACT in-classroom training | 0.606982 |
| autism spectrum disorder | 0.617782 |
| hearing problems | 0.440183 |
| online continuing education | 0.550797 |
| in-classroom training | 0.678973 |
| developmental disabilities | 0.438904 |
|
| solid foundation | 0.43172 |
| Dr. Georgina Peacock | 0.559145 |
| ACT curriculum | 0.562075 |
| appropriate action | 0.438995 |
| ABA Therapy | 0.431732 |
| pediatric trainees | 0.445355 |
| self-study ACT CE | 0.799434 |
| quality care | 0.468755 |
| early identification | 0.43638 |
| gut feeling | 0.620022 |
| downloadable curriculum | 0.44289 |
| learner participation | 0.429958 |
| resident training programs | 0.567665 |
| Western Reserve University | 0.534711 |
| free resources | 0.519671 |
| primary care practitioners | 0.785357 |
| developmental-behavioral pediatrics training | 0.576711 |
| right track | 0.438857 |
| developmental delay | 0.4445 |
| Developmental/Behavioral Pediatrician | 0.497519 |
| Assistant Professor | 0.425283 |
| Autism Case Training | 0.985892 |
| early developmental milestones | 0.565723 |
|
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Centers for Disease Control and Prevention |
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Evidence-based health: necessary but not sufficient [letter |
As public health practitioners from the National Asthma Control Program (NACP) of the Centers for Disease Control and Prevention, we read the essay “From Evidence-Based Medicine to Evidence-Based Health: the Example of Asthma” (1) with great interest. |
| evidence-based clinical medicine | 0.736814 |
| clinical management | 0.529545 |
| demonstration projects | 0.628022 |
| successful asthma interventions | 0.88622 |
| public health practitioners | 0.709166 |
| population-level asthma surveillance | 0.823247 |
| organized research effort | 0.621807 |
| clinical teams | 0.532331 |
| key demonstration projects | 0.613005 |
| health services research | 0.66814 |
| multicomponent interventions | 0.623077 |
| sufficient evidence | 0.522387 |
| asthma self-management support | 0.866016 |
| Disease Control | 0.721709 |
| change elements | 0.537002 |
| community-level interventions | 0.623245 |
| convincing insurers | 0.523853 |
| public’s health | 0.634988 |
| Environmental Health | 0.547742 |
| asthma | 0.980021 |
| community health interventions | 0.751461 |
| Evidence-Based Medicine | 0.612434 |
| cost-effective ways | 0.522312 |
| Community Preventive Services | 0.640074 |
| public health response | 0.690884 |
|
| clinical case studies | 0.625977 |
| evidence-based practice | 0.593589 |
| community health services | 0.679855 |
| National Asthma Control | 0.891986 |
| recent article | 0.528234 |
| asthma triggers | 0.711048 |
| Expert Panel Report | 0.642462 |
| disparately high prevalence | 0.633207 |
| community resources | 0.528341 |
| state asthma programs | 0.822942 |
| asthma prevalence | 0.729222 |
| public health | 0.764931 |
| evidence-based treatments | 0.577207 |
| program implementation questions | 0.618393 |
| evidence-based health | 0.818578 |
| clinical guidelines | 0.526545 |
| case studies | 0.632496 |
| research dollars | 0.52555 |
| behavioral interventions | 0.604466 |
| racial/ethnic minorities | 0.522382 |
| systematic review | 0.524317 |
| Public Health Service | 0.655345 |
| vastly disproportionate funding | 0.617741 |
| new medications | 0.525745 |
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Centers for Disease Control and Prevention |
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Results from the 2010 NSDUH: Summary of National Findings, SAMHSA, CBHSQ |
Results from the 2010 NSDUH: Summary of National Findings, Substance Abuse and Mental Health Reports from SAMHSA's Center for Behavioral Health Statistics and Quality |
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Centers for Disease Control and Prevention |
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Preventing Chronic Disease - CDC: Volume 10, 2013: 12_0073ee |
Volume 10 — February 14, 2013. |
| Disease Control | 0.360502 |
| Parent-Reported Medication Rates | 0.738052 |
| Public Health Service | 0.654567 |
| affiliated institutions | 0.35763 |
|
| Human Services | 0.364011 |
| Prev Chronic Dis | 0.929461 |
| Attention-Deficit/Hyperactivity Disorder | 0.472464 |
| Demographic Variation | 0.449163 |
|
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| 9508 |
Centers for Disease Control and Prevention |
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Food Safety Epidemiology Capacity in State Health Departments — 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. |
| foodborne diseases | 0.590391 |
| adequate epidemiology capacity | 0.541272 |
| local foodborne disease | 0.588332 |
| foodborne disease programs | 0.552552 |
| foodborne disease epidemiology | 0.708588 |
| enteric illness | 0.530015 |
| epidemiology capacity assessment | 0.630942 |
| state health departments | 0.517938 |
| state | 0.571348 |
| current epidemiology capacity | 0.533386 |
| core capacity | 0.498652 |
| foodborne epidemiologists | 0.548094 |
| foodborne disease outbreaks | 0.663665 |
| foodborne disease outbreak | 0.632411 |
| program capacity | 0.53014 |
| epidemiology capacity | 0.64337 |
| Matthew L. Boulton | 0.503674 |
| epidemiology degree | 0.507328 |
| Foodborne Outbreak Response | 0.55844 |
| Foodborne Outbreak Reporting | 0.567651 |
| Territorial Epidemiologists | 0.511995 |
| foodborne disease investigations | 0.550284 |
| Disease Outbreak Response | 0.522853 |
| foodborne outbreaks | 0.584701 |
| United States | 0.498908 |
|
| overall foodborne disease | 0.541787 |
| food safety epidemiology | 0.600499 |
| states | 0.749896 |
| foodborne pathogens | 0.54787 |
| formal epidemiology training | 0.509335 |
| lead foodborne disease | 0.57448 |
| safety epidemiology capacity | 0.631646 |
| national epidemiology workforce | 0.501015 |
| local health departments | 0.564771 |
| foodborne disease epidemiologists | 0.659594 |
| public health | 0.520085 |
| E. coli | 0.504749 |
| national foodborne disease | 0.555085 |
| foodborne investigations | 0.515529 |
| national food safety | 0.51739 |
| foodborne outbreak | 0.592402 |
| adequate epidemiology expertise | 0.609318 |
| foodborne diseases program | 0.539708 |
| foodborne disease | 0.903486 |
| food safety capacity | 0.501788 |
| local level | 0.51107 |
| disease epidemiology capacity | 0.582405 |
| foodborne safety staff | 0.653902 |
| foodborne outbreak investigations | 0.562615 |
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Centers for Disease Control and Prevention |
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Preventing Chronic Disease - CDC: Volume 10, 2013: 13_0120 |
Volumen 10 — el 05 de septiembre de 2013. |
| Elizabeth Dodson | 0.325662 |
| Aushra Shatchkute | 0.324507 |
| Elizabeth Baker | 0.324416 |
| An Evaluation | 0.323198 |
| Gunter Diem | 0.328623 |
| internacionales wesley s | 0.340623 |
| Jacobs JA | 0.323917 |
| Shannon M | 0.323774 |
| International Practitioners | 0.323295 |
| Julie A | 0.323346 |
| Gibbert WS | 0.323061 |
|
| Dodson E | 0.323236 |
| Wayne Giles | 0.323108 |
| Diem G | 0.324754 |
| salud pública | 0.954592 |
| profesionales médicos | 0.32374 |
| Keating SM | 0.32511 |
| Kathleen N | 0.323447 |
| Vilius Grabauskas | 0.323298 |
| Chronic Dis | 0.324658 |
| Impact Among US | 0.340242 |
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Global Health - Global Health Security - Why It Matters |
null |
| safer environments | 0.431697 |
| infectious disease threats | 0.676905 |
| fewer failed states | 0.537095 |
| cross-cutting global health | 0.600649 |
| viable trading partners | 0.528854 |
| familiar microbes | 0.439372 |
| public health crises | 0.565312 |
| GHS initiative | 0.44516 |
| health systems | 0.477094 |
| World Health Organization | 0.600919 |
| real-time disease tracking | 0.545445 |
| Healthier countries | 0.4335 |
| laboratory accident | 0.440934 |
| Pandemic influenza | 0.438472 |
| new microbes | 0.447739 |
| medical product supply | 0.576548 |
| accurate data sharing | 0.521105 |
| security capacity | 0.440656 |
| Health Security agenda | 0.592839 |
| highest levels | 0.428796 |
| available antibiotics | 0.428737 |
| dangerous new threats | 0.635041 |
| greater global health | 0.621971 |
| International Health Regulations | 0.597796 |
| drug resistance | 0.429359 |
|
| drug-resistant illnesses | 0.4583 |
| resistant germs | 0.442395 |
| global health security | 0.958429 |
| global economy | 0.442795 |
| new global solutions | 0.588311 |
| economic burden worldwide | 0.523601 |
| emergency operations centers | 0.525738 |
| U.S. hospitals | 0.432928 |
| Pandemic disease threats | 0.654192 |
| member state | 0.43605 |
| stable economies | 0.429705 |
| disease threats | 0.841062 |
| especially heavy toll | 0.519145 |
| security activities | 0.431745 |
| better lab systems | 0.530218 |
| global disease threats | 0.713932 |
| global health programs—like | 0.591618 |
| child health | 0.461762 |
| nationwide surveillance systems | 0.522906 |
| national economies | 0.434086 |
| member states | 0.43929 |
| respiratory syndrome coronavirus | 0.584188 |
| avoidable epidemics | 0.448847 |
| Substantial investments | 0.430812 |
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Safe and Healthy Travel to an International Mass Gathering | CDC Features |
International events draw huge crowds and come with unique risks to travelers. Whether they are planned years in advance (Olympics) or happen more spontaneously (Nelson Mandela’s funeral), mass gatherings are associated with crowding at venues, poor hygiene from temporary food and sanitation facilities, and challenging security situations. The risk of infectious diseases increases because of crowded conditions and the influx of attendees from around the world. |
| large number | 0.559874 |
| CDC’s Travelers | 0.583778 |
| CDC guidance | 0.576705 |
| financial difficulties | 0.542331 |
| medical history | 0.541695 |
| health information | 0.543124 |
| adequate time | 0.560154 |
| Zika prevention page | 0.713039 |
| pregnant women | 0.587439 |
| Nelson Mandela | 0.575699 |
| local resources | 0.571424 |
| pregnant partners | 0.579815 |
| time frame | 0.55298 |
| infectious diseases increases | 0.711889 |
| adequate vaccinations | 0.554632 |
| travel warnings | 0.571457 |
| temporary food | 0.567915 |
| medical conditions | 0.539566 |
| travel alerts | 0.569345 |
| primary care provider | 0.660914 |
| crowd crush | 0.563529 |
| Zika Travel Information | 0.742542 |
| international mass gathering | 0.675411 |
| travel plans | 0.697076 |
|
| sex partners | 0.565671 |
| specific destinations | 0.666555 |
| customized recommendations | 0.538982 |
| planned activities | 0.543261 |
| firm footing | 0.550136 |
| CDC recommendations | 0.580059 |
| security situations | 0.56938 |
| travel medicine provider | 0.911154 |
| mass gatherings | 0.571448 |
| mass gathering | 0.706567 |
| birth defects | 0.555135 |
| good idea | 0.541219 |
| unique risks | 0.569584 |
| travel notices | 0.562916 |
| specific location | 0.565091 |
| infected person | 0.56058 |
| safe journey | 0.546386 |
| huge crowds | 0.575908 |
| Traveler Enrollment Program | 0.661986 |
| poor hygiene | 0.562045 |
| specific purpose | 0.564968 |
| sanitation facilities | 0.574036 |
| International events | 0.573091 |
| departure date | 0.556044 |
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Disparities in Who Receives Weight-Loss Advice From a Health Care Provider: Does Income Make a Difference? |
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. |
| income | 0.245199 |
| weight-loss advice | 0.947833 |
| care provider advice | 0.224394 |
| health insurance | 0.299571 |
| health care provider | 0.76202 |
| higher odds | 0.38398 |
| insurance status | 0.239116 |
| health status | 0.254397 |
|
| health insurance status | 0.227083 |
| respondents | 0.203934 |
| racial/ethnic minority | 0.205848 |
| obese adults | 0.211571 |
| weight-loss advice aligns | 0.212531 |
| health care providers | 0.27705 |
| multivariate logistic regression | 0.216561 |
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