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NCIRD | DBD Bulletin Fall 2011 | Preventable Diseases Network | CDC |
Division of Bacterial Diseases Bulletin Fall |
| training course | 0.722529 |
| ongoing support | 0.713911 |
| Haemophilus influenzae type | 0.828738 |
| new vaccines | 0.758629 |
| sentinel site visits | 0.796395 |
| RDB’s Streptococcus | 0.739895 |
| Western Pacific Region | 0.800279 |
| pneumococcal vaccines | 0.759373 |
| Vaccine Preventable Diseases | 0.837755 |
| rotavirus vaccines | 0.844508 |
| S. pneumoniae | 0.72052 |
| Mongolia national laboratory | 0.803416 |
| Global Meningitis Laboratory | 0.87971 |
| Bacterial Vaccine-Preventable Diseases | 0.844859 |
| Kenya RRL | 0.716877 |
| Global Reference Laboratory | 0.83957 |
| vaccine introduction | 0.729391 |
| surveillance data | 0.722367 |
| DBD laboratories | 0.77801 |
| Neisseria meningitidis | 0.732511 |
| laboratory IB-VPD posters | 0.80434 |
| countries | 0.715248 |
| vaccine impact post | 0.805854 |
| Streptococcus pneumoniae | 0.763305 |
| regional reference labs | 0.795708 |
|
| continuous power supply | 0.781024 |
| GRL works | 0.762149 |
| inadequate specimen handling | 0.785533 |
| high quality data | 0.792565 |
| quality control/quality assurance | 0.775079 |
| GRL activities | 0.769821 |
| DBD staff members | 0.867764 |
| Respiratory Diseases Branch | 0.802813 |
| surveillance capacity | 0.717328 |
| Bacterial Diseases | 0.732497 |
| IB-VPD network activities | 0.80492 |
| technical support | 0.726601 |
| site visits | 0.900471 |
| various training workshops | 0.808846 |
| GAVI CEO Seth | 0.819305 |
| GAVI Alliance | 0.83269 |
| global standard operating | 0.783733 |
| pentavalent vaccine | 0.71434 |
| Streptococcus Laboratory | 0.81947 |
| laboratory-based surveillance network | 0.854484 |
| regional offices | 0.801251 |
| bacterial disease surveillance | 0.819614 |
| new conjugate vaccines | 0.892495 |
| limited supply chains | 0.782386 |
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Prevent Infections During Pregnancy | CDC Features |
If you're pregnant or planning a pregnancy, there are simple steps you can take to protect your unborn baby or newborn from infections that cause serious health problems. |
| pregnant hispanic women | 0.63043 |
| health care provider | 0.5346 |
| Zika virus | 0.515289 |
| mung bean sprouts | 0.375998 |
| pregnant women | 0.938531 |
| CMV infection | 0.620649 |
| pregnant woman | 0.51073 |
| hot dogs | 0.386918 |
| possibly contaminated food | 0.490822 |
| queso fresco | 0.369305 |
| sex partner | 0.377105 |
| strep test | 0.532603 |
| oral sex | 0.376625 |
| pregnancy | 0.560951 |
| soft cheeses | 0.536613 |
| unpasteurized) milk. | 0.377724 |
| queso blanco | 0.360848 |
| health problems | 0.386632 |
| congenital CMV infection | 0.59569 |
| listeriosis | 0.637139 |
| Aedes albopictus mosquito | 0.371896 |
| queso panela | 0.362079 |
| Zika Travel Information | 0.413168 |
| infected Aedes aegypti | 0.374729 |
|
| special travel considerations | 0.36898 |
| deli meats | 0.386189 |
| lunch meat packages | 0.365893 |
| Hispanic-style soft cheeses | 0.530071 |
| lunch meats | 0.383642 |
| cuajada en terrón | 0.36836 |
| Zika virus infection | 0.413439 |
| lightly cooked sprouts | 0.375407 |
| Zika | 0.567518 |
| group b strep | 0.836765 |
| deadly Listeria food | 0.405712 |
| possible listeriosis | 0.407184 |
| muscle aches | 0.396556 |
| Zika travel notices | 0.40322 |
| queso ranchero | 0.362484 |
| Regular hand washing | 0.395772 |
| sex | 0.428428 |
| commonly recommended step | 0.394722 |
| nonessential travel | 0.374082 |
| birth defects | 0.369014 |
| commercial cottage cheese | 0.371361 |
| sex toys | 0.381802 |
| healthcare provider | 0.443027 |
| up-to-date travel recommendations | 0.365184 |
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August 07, 2009: States Where Persons Infected with the Outbreak Strain of E. coli O157:H7 Live, United States, by State | E. coli CDC |
Get the latest CDC information on the recent infections from fresh spinach, and find out what you can do to protect yourself and your family. |
| O157 | 0.383198 |
| North Carolina | 0.382606 |
| Oregon | 0.314192 |
| CDC | 0.319667 |
| United States | 0.557321 |
| confirmatory test results | 0.45535 |
| Maine | 0.314594 |
| Oklahoma | 0.314226 |
| South Carolina | 0.380667 |
| advanced DNA test | 0.456505 |
| number | 0.315099 |
| Friday | 0.315096 |
| Eating Raw Refrigerated | 0.477308 |
| Colorado | 0.314947 |
| Massachusetts | 0.314663 |
| Missouri | 0.314531 |
| ill persons | 0.3892 |
| E. coli | 0.946913 |
| outbreak strain | 0.806668 |
| Arizona | 0.315016 |
| H7 Live | 0.695115 |
| Outbreak Investigations | 0.474332 |
|
| Nevada | 0.314337 |
| New York | 0.381847 |
| Montana | 0.314497 |
| Prepackaged Cookie Dough | 0.487509 |
| Kentucky | 0.314698 |
| Minnesota | 0.314566 |
| California | 0.314982 |
| Delaware | 0.314878 |
| particular DNA fingerprint | 0.465324 |
| New Jersey | 0.382283 |
| Pennsylvania | 0.314157 |
| persons | 0.389878 |
| Iowa | 0.314801 |
| Illinois | 0.314739 |
| Texas | 0.314074 |
| New Hampshire | 0.382521 |
| Connecticut | 0.314912 |
| Ohio | 0.314254 |
| Georgia | 0.314843 |
| Maryland | 0.314635 |
| Multistate Outbreak | 0.483101 |
| Idaho | 0.314774 |
|
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CDC reports uneven declines in coronary heart disease by state and race/ethnicity - Press Release: October 13, 2011 |
CDC reports uneven declines in coronary heart disease by state and race/ethnicity |
| Mortality Weekly Report | 0.371985 |
| M.D. | 0.225245 |
| heart disease prevalence | 0.485126 |
| high blood cholesterol | 0.358046 |
| number | 0.241102 |
| high cholesterol | 0.281558 |
| Disease Control | 0.309208 |
| Hearts visit http://millionhearts.hhs.gov/about–mh.shtml | 0.329442 |
| decline | 0.23043 |
| Hearts national initiative | 0.340568 |
| lower respiratory diseases | 0.343493 |
| Jing Fang | 0.275536 |
| Americans | 0.317727 |
| patients | 0.226411 |
| health providers | 0.276008 |
| high risk populations | 0.356725 |
| state coronary heart | 0.402842 |
| phone survey | 0.287025 |
| MMWR report | 0.278508 |
| coronary heart disease. | 0.425235 |
| heart attack | 0.313187 |
| Factor Surveillance | 0.282043 |
| highest levels | 0.276901 |
| HUMAN SERVICES | 0.272122 |
| geographic differences | 0.273766 |
|
| heart attacks | 0.335346 |
| high blood pressure | 0.471637 |
| United States | 0.361728 |
| African Americans | 0.299731 |
| percent | 0.32442 |
| certain groups | 0.269511 |
| American Indians/Alaskan Natives | 0.478553 |
| West Virginia | 0.278373 |
| U.S. DEPARTMENT | 0.272201 |
| CDC′s Division | 0.272052 |
| cardiovascular disease | 0.29839 |
| higher risk | 0.270602 |
| CDC′s Behavioral Risk | 0.357926 |
| strokes | 0.227812 |
| Stroke Prevention | 0.270768 |
| clinical care | 0.275168 |
| uncontrolled high blood | 0.460951 |
| highest rates | 0.278057 |
| people | 0.25708 |
| Southern states | 0.277948 |
| chest pain | 0.284803 |
| Thomas R. Frieden | 0.346506 |
| older adults | 0.34341 |
| new report | 0.298019 |
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Integrating a multimode design into a national random-digit-dialed telephone survey. |
null |
| landline telephone methods | 0.4743 |
| landline telephone noncoverage | 0.463941 |
| cellular telephone modes | 0.4109 |
| landline RDD surveys | 0.472189 |
| cellular telephone interview | 0.395868 |
| landline telephone surveys | 0.553268 |
| cellular telephone numbers | 0.535435 |
| Survey Cellular Telephone | 0.434728 |
| RDD telephone surveys | 0.520964 |
| cellular telephones | 0.618556 |
| cellular telephone coverage | 0.415525 |
| health telephone survey | 0.458589 |
| RDD landline frames | 0.510585 |
| multimode design | 0.445817 |
| cellular telephone proportion | 0.389671 |
| current RDD landline | 0.482726 |
| landline telephone survey | 0.809527 |
| landline RDD survey | 0.573783 |
| landline telephones | 0.427617 |
| cellular telephone respondents | 0.428019 |
| cellular telephone frames | 0.392274 |
| physical health measurements | 0.455195 |
| risk factor surveillance | 0.467439 |
| BRFSS data collection | 0.447372 |
|
| RDD telephone sampling | 0.4332 |
| Public Opinion | 0.459711 |
| mail follow-up survey | 0.472061 |
| cellular telephone survey | 0.434142 |
| traditional RDD landline | 0.532335 |
| self-reported data | 0.452897 |
| telephone survey mode | 0.47445 |
| RDD landline telephone | 0.914099 |
| American Statistical Association | 0.426886 |
| landline BRFSS data | 0.491074 |
| landline RDD telephone | 0.548014 |
| public health | 0.407587 |
| cellular telephone interviews | 0.451935 |
| landline telephone–based RDD | 0.479964 |
| lack landline telephones | 0.425069 |
| cellular telephone–only households | 0.520936 |
| response rates | 0.466067 |
| health | 0.48052 |
| ongoing landline telephone | 0.430948 |
| monthly landline | 0.417122 |
| landline telephone BRFSS | 0.549365 |
| data collection | 0.806802 |
| sample telephone numbers | 0.398414 |
| behavioral risk factor | 0.468262 |
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Global Health - South Africa - CDC's Global Disease Detection Programs in South Africa |
The South Africa Regional Global Disease Detection Centre (SARGDDC) builds global health security by enhancing capacity in South Africa to detect and respond to infectious disease threats through surveillance, workforce development, and public health research and response. |
| Global Disease Detection | 0.568526 |
| control influenza | 0.491548 |
| infectious disease threats | 0.563693 |
| supervised work experience | 0.51046 |
| Influenza Reference Laboratory | 0.587331 |
| Disease Control | 0.46022 |
| Africa’s capacity | 0.478534 |
| IHR capacity building | 0.560689 |
| zoonotic disease surveillance | 0.605847 |
| South Africa Field | 0.601397 |
| enhanced surveillance | 0.505887 |
| Health Program | 0.707939 |
| National Health Laboratory | 0.616159 |
| infectious disease outbreaks | 0.537066 |
| evidence-based policy decisions | 0.499999 |
| public health expertise | 0.562106 |
| wide variety | 0.524805 |
| neurologic disease surveillance | 0.60384 |
| early warning systems | 0.495532 |
| synergistic program components | 0.543134 |
| laboratory systems | 0.438781 |
| CDC’s Division | 0.451736 |
| CDC core expertise | 0.552432 |
| South Africa | 0.902481 |
| laboratory surveillance | 0.495402 |
|
| Biological Engagement Program | 0.574112 |
| global health security | 0.611455 |
| Health spectrum | 0.453749 |
| strong regional partners | 0.503249 |
| Epidemiology Training Program | 0.620299 |
| Emerging Infections Program | 0.585679 |
| rapid response activities | 0.508682 |
| public health threats | 0.588496 |
| surveillance systems | 0.516127 |
| public health capacities | 0.59386 |
| public health | 0.822228 |
| South Africa Regional | 0.612266 |
| infection control practices | 0.512809 |
| National Institute | 0.44029 |
| National Influenza Center | 0.59155 |
| public health importance | 0.589496 |
| South Africa NDoH | 0.585674 |
| sentinel surveillance | 0.488755 |
| Influenza Program | 0.713281 |
| South African government | 0.518661 |
| public health capacity | 0.663811 |
| South Africa National | 0.602216 |
| NICD | 0.442427 |
| 2-year training program | 0.573109 |
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Global Health - Chad |
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| Content source | 0.422709 |
| HHS | 0.297574 |
| list Skip | 0.74332 |
| endorsement | 0.291872 |
| CDC | 0.271556 |
| non-federal site | 0.4688 |
|
| Notice | 0.270187 |
| sponsors | 0.241885 |
| page options Skip | 0.947337 |
| information | 0.241652 |
| employees | 0.242118 |
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Protect Your Hearing, Promote Hearing Health | CDC Features |
October is National Protect Your Hearing Month. Find out if noise at your workplace is affecting your hearing and learn how to prevent noise-induced hearing loss. Monitor noise levels and protect your hearing.
|
| noise exposure level | 0.649933 |
| HPD performance | 0.471644 |
| occupational hearing loss | 0.790496 |
| hearing protectors | 0.614063 |
| Monitor noise levels | 0.668869 |
| loud noise | 0.604447 |
| hazardous noise exposure | 0.664411 |
| hearing disorders | 0.64489 |
| overall level | 0.464075 |
| sound level meter | 0.614636 |
| cardiovascular health risks | 0.510729 |
| National Protect | 0.519452 |
| noise level increases | 0.649956 |
| Hearing Loss Prevention | 0.805206 |
| quick screening methods | 0.507537 |
| common work-related illnesses | 0.523693 |
| work-related hearing loss | 0.66815 |
| NIOSH HPD Well-Fitâ„¢ | 0.542382 |
| U.S. workers | 0.472818 |
| complete noise survey | 0.643449 |
| regular science blogs | 0.498455 |
| noise-induced hearing loss | 0.805652 |
| hearing loss | 0.990057 |
| noise exposure | 0.779866 |
| noise levels | 0.78741 |
|
| Protector Device Compendium | 0.496822 |
| United States | 0.465899 |
| dangerous noise exposures | 0.627276 |
| Loss Prevention programs | 0.510683 |
| Endocrine disrupters | 0.459861 |
| Audiometric evaluation | 0.461304 |
| constant noise | 0.586958 |
| abrupt starts | 0.45944 |
| noise | 0.816586 |
| Ototoxic chemicals | 0.459844 |
| level meter app | 0.518956 |
| loss prevention program | 0.595252 |
| Certain biological factors | 0.498411 |
| comprehensive searchable database | 0.499162 |
| noise exposures | 0.653366 |
| smartphone sound level | 0.620669 |
| HPD Well-FitTM | 0.472106 |
| NIOSH Science Blog | 0.539326 |
| level meter apps | 0.51859 |
| sound measurement apps | 0.513997 |
| Impulsiveness – noises | 0.464425 |
| hearing protection devices | 0.662702 |
| NIOSH Hearing Loss | 0.706491 |
| high economic price | 0.513723 |
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Association Between the Built Environment in SchoolNeighborhoods With Physical Activity Among New York City Children,2012 |
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. |
| total enrollment zone | 0.583397 |
| physical activity behaviors | 0.598012 |
| public transportation density | 0.809798 |
| obesity prevention programs | 0.623115 |
| New York City | 0.630188 |
| land use mix | 0.592554 |
| public school students | 0.576211 |
| model | 0.624947 |
| between-school variation | 0.789814 |
| residential population density | 0.671009 |
| national average | 0.579073 |
| retail floor area | 0.660161 |
| body mass index | 0.630351 |
| total crime | 0.76833 |
| Sallis JF | 0.570503 |
| park access | 0.664323 |
| light PA frequency | 0.573917 |
| school neighborhood | 0.616443 |
| light PA duration | 0.567661 |
| enrollment zone | 0.717083 |
| behavioral intention | 0.584766 |
| heavy duration | 0.577508 |
| environment characteristics | 0.765116 |
| habit strength | 0.603486 |
| Total crime index | 0.616872 |
|
| students | 0.623074 |
| medium PA frequency | 0.573024 |
| Teachers College Columbia | 0.584897 |
| College Columbia University | 0.583894 |
| motor vehicle theft | 0.612548 |
| heavy PA frequency | 0.5732 |
| public health | 0.57076 |
| neighborhood school environment | 0.572739 |
| New York | 0.710262 |
| total land area | 0.60143 |
| enrollment zone area | 0.581079 |
| school neighborhoods | 0.572357 |
| Response options | 0.595282 |
| English language learners | 0.595827 |
| neighborhood-level built environment | 0.568347 |
| physical activity | 0.958854 |
| PA | 0.722815 |
| psychosocial factors | 0.834152 |
| intersection density | 0.578823 |
| light physical activity | 0.571628 |
| floor area density | 0.640071 |
| PA behaviors | 0.618824 |
| mean physical activity | 0.567821 |
| PA frequency | 0.622031 |
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Fire Fighter Fatality Investigation Report F2007-02 |
Career Fire Fighter Injured during Rapid Fire Progression in an Abandoned Structure Dies Six Days Later ? Georgia |
| experienced fire fighters | 0.615136 |
| self-contained breathing apparatus | 0.683915 |
| officer | 0.743441 |
| service time test | 0.61813 |
| new fire fighters | 0.617809 |
| Engine 16Â’s crew | 0.596479 |
| battalion | 0.600228 |
| fighters | 0.932537 |
| flow performance test | 0.609855 |
| single story duplex | 0.622712 |
| personal alert safety | 0.676034 |
| chief training officer | 0.602163 |
| dark black smoke | 0.661696 |
| initial size-up | 0.625659 |
| NIOSH Task Number | 0.597363 |
| SCBA | 0.694193 |
| 33-year old victim | 0.610845 |
| E16 acting officer | 0.61521 |
| gas flow test | 0.642548 |
| team members | 0.646782 |
| incident commander | 0.655831 |
| SCBA post-incident test | 0.622309 |
| SCBA status investigation | 0.602266 |
| heavy black smoke | 0.612405 |
|
| PASS device | 0.649114 |
| 33-year-old male career | 0.605361 |
| occupational health specialists | 0.59865 |
| NIOSH SCBA | 0.629516 |
| NIOSH SCBA Certification | 0.621162 |
| crew | 0.644382 |
| engine | 0.705507 |
| Incident Safety Officer | 0.680801 |
| victim | 0.790895 |
| Fighter Fatality Investigation | 0.651322 |
| rapid intervention team | 0.637803 |
| interior conditions | 0.613569 |
| engine company officer | 0.601775 |
| incident command | 0.635298 |
| black smoke | 0.701686 |
| structure | 0.754992 |
| static pressure test | 0.640388 |
| air flow performance | 0.639944 |
| command post | 0.670344 |
| incident structure | 0.605476 |
| NIOSH investigators | 0.624055 |
| company officer | 0.632625 |
| disoriented fire fighters | 0.627025 |
| positive pressure test | 0.610186 |
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