| 5921 |
Centers for Disease Control and Prevention |
Html |
en |
Propane sultone - NIOSH Pocket Guide to Chemical Hazards |
null |
| 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 |
| 5972 |
Centers for Disease Control and Prevention |
Html |
en |
Aluminum (soluble salts and alkyls, as Al) - NIOSH Pocket Guide to Chemical Hazards |
null |
| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
|
| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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CLICK HERE |
| 6760 |
Centers for Disease Control and Prevention |
Html |
en |
Global Health - South Africa - CDC's Epidemiology and Strategic Programs |
CDC partners in South Africa with government and parastatal agencies, private institutions, universities and non-governmental organizations to improve the country’s public health foundation, to prevent transmission of HIV, to provide care and treatment for those who are already infected with HIV, and to strengthen laboratory capacity.
|
| Annual Program Results | 0.686004 |
| HIV micro-epidemics analysis | 0.683135 |
| strategic information | 0.673929 |
| evidence-based program improvement | 0.661474 |
| surveillance strategic plan | 0.773268 |
| better understanding | 0.566518 |
| HIV epidemic | 0.589652 |
| Co-coordinated Site Monitoring | 0.672963 |
| HIV prevention | 0.589002 |
| tuberculosis programs | 0.5774 |
| Align PEPFAR | 0.553448 |
| information cooperative agreements | 0.652 |
| submission support | 0.554738 |
| strategic plan | 0.813168 |
| program planning | 0.566657 |
| AIDS Relief | 0.548454 |
| health information systems | 0.716013 |
| epidemiologic methods | 0.618259 |
| national M&E | 0.563342 |
| Provide expert | 0.553888 |
| PEPFAR SA Team | 0.675056 |
| surveillance activities | 0.604334 |
| program planners | 0.580561 |
| operational research | 0.948793 |
|
| surveillance systems | 0.668373 |
| UNAIDS country spectrum | 0.69062 |
| program initiatives | 0.559068 |
| Emergency Plan | 0.566303 |
| indicator results | 0.545709 |
| SI strategic plan | 0.696475 |
| expert technical assistance | 0.936523 |
| national surveys | 0.570783 |
| routine data | 0.583842 |
| treatment programs | 0.574123 |
| dynamic nature | 0.566237 |
| epidemiologic analysis | 0.597293 |
| data quality assessment | 0.710882 |
| non-federal site | 0.55685 |
| policy makers | 0.566846 |
| technical expertise | 0.587508 |
| public health science | 0.693739 |
| CDC South Africa | 0.724873 |
| data entry | 0.576171 |
| NDoH systems | 0.553298 |
| country-specific technical assistance | 0.693304 |
| data sharing | 0.58352 |
| operational research methods | 0.720977 |
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| 10923 |
Centers for Disease Control and Prevention |
Html |
en |
Workers Without Paid Sick Leave May Skip Cancer Screening Tests |
Lack of paid sick leave can prevent people from getting the health care services they need. |
| data | 0.408891 |
| Berkowitz | 0.408525 |
| National Health Interview | 0.548273 |
| office | 0.40747 |
| family member | 0.446695 |
| significant difference | 0.440976 |
| health care benefits | 0.515143 |
| percentage | 0.40788 |
| Colorectal cancer screening | 0.480522 |
| professional workers | 0.446235 |
| low-paying jobs | 0.437366 |
| Soman | 0.407484 |
| Pap test | 0.471497 |
| health care services | 0.467438 |
| BMC Public Health | 0.471571 |
| Health Interview Survey | 0.54824 |
| cervical cancer | 0.477224 |
| medical care-seeking | 0.437935 |
| lack | 0.42725 |
| fecal occult blood | 0.478478 |
| person | 0.414751 |
| small difference | 0.440365 |
| Peipins | 0.410418 |
| job | 0.447136 |
| managers | 0.408159 |
|
| women | 0.439269 |
| White MC | 0.440091 |
| study | 0.425302 |
| cancer screening | 0.564495 |
| United States | 0.482615 |
| Working women | 0.43923 |
| adults | 0.408866 |
| sick leave | 0.971316 |
| medical needs | 0.446247 |
| mammogram | 0.410155 |
| workers | 0.529453 |
| colonoscopy | 0.409639 |
| Breast cancer screening | 0.475384 |
| production jobs | 0.4424 |
| smaller companies | 0.443591 |
| medical care | 0.43871 |
| doctor | 0.407475 |
| paid sick leave | 0.630734 |
| Cervical cancer screening | 0.475811 |
| major influence | 0.438675 |
| responses | 0.408385 |
| 91.9 | 0.407626 |
| clinic | 0.407467 |
| time workers | 0.45142 |
|
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| 11505 |
Centers for Disease Control and Prevention |
Html |
en |
NCIRD | DBD Bulletin Fall 2013 | On Call for Diphtheria, MERS | CDC |
Division of Bacterial Diseases Bulletin Fall |
| Haiti | 0.451003 |
| request | 0.441128 |
| death | 0.446194 |
| United States | 0.918548 |
| close collaboration | 0.641928 |
| patient interviews | 0.640514 |
| outbreak investigation | 0.65033 |
| epidemiologic | 0.468138 |
| example | 0.444084 |
| visits | 0.44271 |
| local health ministries | 0.849833 |
| physicians | 0.444972 |
| pockets | 0.461991 |
| village leader | 0.639735 |
| children | 0.446155 |
| U.S. cases | 0.676235 |
| illness | 0.445862 |
| historical reasons | 0.706334 |
| Laos country office | 0.933105 |
| increasingly rare disease | 0.916784 |
| World Health Organization | 0.851272 |
|
| issue | 0.442782 |
| unique challenges | 0.666541 |
| countries | 0.481521 |
| major cause | 0.679584 |
| MVPDB staff | 0.647628 |
| people | 0.444033 |
| benefit | 0.441549 |
| Huoaphang Province | 0.638956 |
| global public health | 0.878557 |
| scientists | 0.444759 |
| light | 0.444129 |
| CDC’s diphtheria | 0.986945 |
| Content | 0.449982 |
| activities | 0.443841 |
| surveillance group | 0.645577 |
| district | 0.440395 |
| laboratory support | 0.652224 |
| page | 0.449919 |
| inadequately immunized populations | 0.967046 |
| sporadic outbreaks—cases | 0.689207 |
| large areas | 0.656746 |
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| 11770 |
Centers for Disease Control and Prevention |
Html |
en |
Smoking in Pregnancy: A Possible Risk for ADHD | CDC Features |
Learn and share during ADHD Awareness Month. |
| ADHD | 0.947815 |
| oppositional defiant disorder | 0.359197 |
| prenatal smoking | 0.413503 |
| United States | 0.211402 |
| previous Surgeon General | 0.32916 |
| free quit plan | 0.322803 |
| negative effects | 0.314858 |
| 50th anniversary | 0.204612 |
| small sample sizes | 0.336519 |
| prenatal exposure | 0.690573 |
| developmental outcomes | 0.327499 |
| specific neurobehavioral disorders | 0.421096 |
| free quit coaching | 0.323053 |
|
| public health approach | 0.320676 |
| Disease Control | 0.203943 |
| children | 0.372022 |
| smoking | 0.806589 |
| maternal smoking | 0.524428 |
| behavioral outcomes | 0.201865 |
| common neurobehavioral disorders | 0.449001 |
| anxiety disorders | 0.358351 |
| disruptive behavioral disorders | 0.373223 |
| Surgeon General | 0.586828 |
| behavioral disorders | 0.504404 |
| research studies | 0.346766 |
| neurobehavioral disorders | 0.83559 |
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| 12000 |
Centers for Disease Control and Prevention |
Html |
en |
A Toolkit for Long-Term Care Employers: Increasing Influenza Vaccination among Healthcare Personnel in Long-term Care Settings |
A Toolkit for Long-Term Care Employers: Increasing Influenza Vaccination among Health Care Personnel in Long-term Care Settings - CDC |
| access | 0.265808 |
| agency | 0.266495 |
| importance | 0.289778 |
| resources | 0.267182 |
| long-term care facility | 0.837589 |
| comprehensive toolkit | 0.657659 |
| influenza vaccination | 0.947061 |
| corporation owners | 0.575508 |
|
| email feedback | 0.575122 |
| input | 0.28862 |
| number | 0.267354 |
| employer | 0.305756 |
| workforce | 0.312487 |
| employees | 0.26366 |
| workers | 0.264691 |
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| 13469 |
Centers for Disease Control and Prevention |
Html |
en |
Alcohol-Impaired Driving Among Adults - United States,2012 |
Amy Jewett, MPH1; Ruth A. Shults, PhD1; Tanima Banerjee, MS2; Gwen Bergen, PhD1. |
| sobriety checkpoints | 0.363529 |
| binge drinking | 0.43727 |
| g/dL BAC laws | 0.369971 |
| higher alcohol-impaired driving | 0.429914 |
| alcohol-impaired driving episodes | 0.763102 |
| health risk data | 0.337774 |
| secondary law states | 0.341901 |
| BRFSS survey | 0.367432 |
| alcohol-impaired driving crashes | 0.494175 |
| annual episodes | 0.343988 |
| alcohol-impaired driving question | 0.431955 |
| alcohol-impaired drivers | 0.462402 |
| Midwest U.S. Census | 0.371445 |
| alcohol-impaired driving | 0.912086 |
| state seat belt | 0.355185 |
| seat belt laws | 0.380157 |
| BRFSS survey respondents | 0.341943 |
| alcohol-impaired driving episode | 0.434789 |
| U.S. Census region | 0.457375 |
| alcohol-impaired driving rates | 0.525132 |
| binge drinking episodes | 0.370941 |
| persons | 0.34514 |
| secondary seat belt | 0.376941 |
| U.S. adult population | 0.337847 |
| Behavioral Risk Factor | 0.339026 |
|
| national rate | 0.338774 |
| United States | 0.358049 |
| primary seat belt | 0.407234 |
| Ruth A. Shults | 0.341384 |
| ignition interlocks | 0.340462 |
| alcoholic beverages | 0.356547 |
| states | 0.397693 |
| blood alcohol concentration | 0.339935 |
| consistent seat belt | 0.349879 |
| random-digit–dialed telephone survey | 0.33893 |
| adult population | 0.352871 |
| crash fatalities | 0.343178 |
| alcohol-impaired driving rate | 0.4664 |
| young men | 0.360677 |
| respective weighted population | 0.338189 |
| Amy Jewett | 0.341008 |
| alcohol ignition interlocks | 0.337823 |
| seat belt | 0.594218 |
| self-reported alcohol-impaired driving | 0.428387 |
| Alcohol-impaired driving prevalence | 0.441709 |
| reported episodes | 0.370296 |
| annual number | 0.337956 |
| enforcement seat belt | 0.354584 |
| annual alcohol-impaired driving | 0.522329 |
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| 14404 |
Centers for Disease Control and Prevention |
Html |
en |
Notes from the Field | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| rabies virus variant | 0.521926 |
| canine rabies | 0.506555 |
| IBCM program | 0.483751 |
| Ethiopian Public Health | 0.419795 |
| health centers | 0.400939 |
| animal health facilities | 0.467197 |
| rabies risk assessments | 0.500731 |
| regional quarantine facilities | 0.354892 |
| rabies laboratory | 0.413512 |
| Zoonotic Infectious Diseases | 0.447672 |
| additional public health | 0.423724 |
| animal health workers | 0.878516 |
| national animal rabies | 0.528034 |
| low dog-bite reporting | 0.360259 |
| dog bites | 0.361627 |
| Emerging Zoonotic Infectious | 0.44179 |
| human rabies deaths | 0.534489 |
| additional animal health | 0.449472 |
| health posts | 0.357266 |
| human health sectors | 0.440241 |
| Human health care | 0.471188 |
| community rabies exposures | 0.500318 |
| rabies vaccines | 0.423006 |
| Rabies diagnostic testing | 0.490507 |
|
| animal health agencies | 0.446369 |
| traditional healers | 0.354677 |
| regional animal disease | 0.395595 |
| cold-chain capacity | 0.435103 |
| Annual rabies-associated livestock | 0.36079 |
| animal rabies assessments | 0.540665 |
| animal health providers | 0.474268 |
| canine rabies vaccine | 0.477407 |
| Health’s Tool | 0.353723 |
| bite detection rates | 0.358588 |
| quarantine facilities | 0.356241 |
| decrease unnecessary PEP | 0.423327 |
| suspected rabid animals | 0.387739 |
| Amhara Region | 0.460654 |
| program supervisors | 0.376163 |
| animal disease surveillance | 0.401321 |
| Ohio State University | 0.351735 |
| rabies | 0.605558 |
| integrated bite-case management | 0.354292 |
| rabid dogs | 0.457968 |
| zoonotic diseases | 0.371605 |
| animal health | 0.910509 |
| IBCM pilot program | 0.499054 |
| veterinary services | 0.346872 |
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| 14451 |
Centers for Disease Control and Prevention |
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Arthritis Across America | CDC Features |
Doctor-diagnosed arthritis is widespread throughout the United States, according to a new study that looks at where arthritis is most common. Physical activity and self-management education can improve the quality of life of those adults with arthritis. |
| findings | 0.321814 |
| 20th edition | 0.430352 |
| MB | 0.32118 |
| physical activity programs | 0.506357 |
| doctor-diagnosed arthritis | 0.820475 |
| limitations | 0.320917 |
| new study | 0.4361 |
| Kentucky | 0.321443 |
| Lu | 0.32141 |
| Download map | 0.4137 |
| quality | 0.34594 |
| Arth Rheum | 0.430917 |
| U.S. counties | 0.416114 |
| arthritis | 0.970795 |
| U.S. county—all | 0.429267 |
| highest levels | 0.420911 |
| community centers | 0.414815 |
| Boring MA | 0.498971 |
| Experts | 0.32197 |
| United States | 0.660399 |
| local Ys | 0.421008 |
| self-reported doctor-diagnosed arthritis | 0.728398 |
| Tennessee | 0.321421 |
| adults | 0.438172 |
| Hootman JM | 0.424606 |
|
| Alabama | 0.321455 |
| CDC analysis | 0.410887 |
| life | 0.345916 |
| Helmick CG | 0.50213 |
| bike | 0.322212 |
| West Virginia | 0.422451 |
| prevalence | 0.380265 |
| arthritis symptoms | 0.657875 |
| effective ways | 0.421077 |
| KA | 0.322846 |
| Holt JB | 0.411061 |
| public health professionals | 0.521634 |
| County Level | 0.407223 |
| MMWR | 0.323357 |
| separate ten-minute sessions | 0.52723 |
| Barbour KE | 0.523638 |
| CDC researchers | 0.437691 |
| self-management education classes | 0.526966 |
| people | 0.359306 |
| physical activity | 0.656844 |
| Michigan | 0.321432 |
| self-management education | 0.703084 |
| common arthritis | 0.656917 |
| arthritis-attributable activity | 0.408665 |
|
CLICK HERE |