GHDx: Mauritania Dataset Records https://ghdx.healthdata.org/geography/508/feed?field_keywords_tid=&field_type_tid=All&field_time_value%5Bmin%5D&field_time_value%5Bmax%5D en WHO Global Health Observatory - Population Living in Trachoma Endemic Areas https://ghdx.healthdata.org/record/who-global-health-observatory-population-living-trachoma-endemic-areas <div class="field field-name-field-alt-title field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even">Population in areas that warrant treatment with antibiotics, facial cleanliness and environmental improvement for elimination of trachoma as a public health problem</div> </div> </div><div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2005 - present</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/survey" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Survey</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/world-health-organization-who" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">World Health Organization (WHO)</a></div> </div> </div> Wed, 20 Mar 2024 15:43:57 -0700 GHDx 260507 at https://ghdx.healthdata.org WHO Africa Region Bacterial Antimicrobial Resistance Burden Estimates 2019 https://ghdx.healthdata.org/record/ihme-data/who-region-africa-amr-2019 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2019 - December, 2019</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>Researchers at IHME and the University of Oxford estimated deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) associated with and attributable to bacterial antimicrobial resistance (AMR) in 88 pathogen-drug combinations for the WHO Region of Africa and for 35 countries in 2019. Data gathered to inform these estimates included multiple cause of death data, hospital discharges, minimally invasive tissue sampling, systematic literature reviews, and microbiology lab results from hospitals and national and multi-national surveillance systems, totaling 343 million individual records or isolates and 11,361 study-location-years collected. These data informed 8 modelling components which were combined with results from GBD 2019 to estimate AMR burden. Estimates were produced for two counterfactual scenarios: no infection and drug-susceptible infection.</p> </div> </div> </div> Wed, 20 Dec 2023 12:17:08 -0800 GHDx 539882 at https://ghdx.healthdata.org Mauritania Multiple Indicator Cluster Survey 2015 https://ghdx.healthdata.org/record/mauritania-multiple-indicator-cluster-survey-2015 <div class="field field-name-field-alt-title field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even">Enquête par Grappes à Indicateurs Multiples (MICS) 2015</div> </div> </div><div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">July, 2015 - November, 2015</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/survey" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Survey</a>: </span> Cross-sectional - Household - Individual - Interview - Nationally representative - Subnationally representative - Urban-rural representative </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/united-nations-childrens-fund-unicef" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">United Nations Children&#039;s Fund (UNICEF)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>The Mauritania Multiple Indicator Cluster Survey 2015 is part of MICS5, an international survey initiative to monitor the situation of children and women. Topics commonly covered in MICS include immunization, education, child and maternal health, family planning and knowledge of HIV/AIDS. MICS also provides data for tracking progress toward Millennium Development Goals (MDGs), particularly those related to health, education and mortality. For the 2015 Mauritania MICS, 14,342 women ages 15-49, and 4,691 men ages 15-49 were successfully interviewed from 11,765 households. Additionally, 10,663 questionnaires for children under five were completed.</p> </div> </div> </div> Tue, 12 Sep 2023 13:27:22 -0700 GHDx 267343 at https://ghdx.healthdata.org Sub-Saharan Africa MenAfriVac Coverage Estimates 2010-2021 https://ghdx.healthdata.org/record/ihme-data/sub-saharan-africa-menafrivac-estimates-2010-2021 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2010 - December, 2021</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset provides estimates of vaccination coverage for meningococcal serogroup A conjugate vaccine (MenAfriVac®) for 24 countries in the meningitis belt of sub-Saharan Africa between 2010 and 2021. Indicators include mean and 95% uncertainty intervals for the estimated coverage for children aged 1 to 5 and children and young adults aged 1 to 29. These estimates include coverage from both mass vaccination campaigns and routine immunization delivery. The estimation process primarily utilized survey report data and country-reported administrative vaccine coverage data.</p> </div> </div> </div> Thu, 16 Mar 2023 09:26:56 -0700 GHDx 508638 at https://ghdx.healthdata.org Africa Exclusive Breastfeeding Prevalence Geospatial Estimates 2000-2017 https://ghdx.healthdata.org/record/ihme-data/africa-exclusive-breastfeeding-prevalence-geospatial-estimates-2000-2017 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2000 - December, 2017</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a>: </span> Subnationally representative </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>Estimates were produced for exclusive breastfeeding (EBF) prevalence among infants under 6 months of age at the 5x5 km-level in 49 countries in Africa between 2000-2017. These estimates were produced using data extracted from 188 household surveys that had complete records of questions relating to infant feeding and geographical information. The surveys include the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), and country‐specific and other multinational surveys.</p> <p>This dataset includes the following:</p> <ul> <li>GeoTIFF raster files for pixel-level estimates of EBF prevalence</li> <li>CSV files of aggregated estimates for each country at the zero, first, and second administrative divisions</li> <li>Code files used to generate the estimates</li> </ul> </div> </div> </div> Fri, 23 Sep 2022 09:04:32 -0700 GHDx 400957 at https://ghdx.healthdata.org Low- and Middle-Income Country Neonatal, Infant, and Under-5 Mortality Geospatial Estimates 2000-2017 https://ghdx.healthdata.org/record/ihme-data/lmic-under5-mortality-rate-geospatial-estimates-2000-2017 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2000 - December, 2017</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>Annual estimates were produced for mortality probability and death counts in three age groups – neonates (0-28 days old), infants (under-1 year old), and under-5 (0-5 years old) – at the 5x5 km-level in 99 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using data on child mortality and geographical locations from censuses and several household survey series. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.</p> <p>This dataset includes the following:</p> <ul> <li>GeoTIFF raster files for pixel-level estimates of mortality probability and death counts in 3 age bins</li> <li>CSV files of aggregated mortality probability and death count estimates for each country at the zero, first, and second administrative divisions, by age group</li> <li>Code files used to generate the estimates</li> </ul> </div> </div> </div> Fri, 23 Sep 2022 09:04:32 -0700 GHDx 413180 at https://ghdx.healthdata.org Africa Under-5 Lower Respiratory Infection Incidence, Prevalence, and Mortality Geospatial Estimates 2000-2017 https://ghdx.healthdata.org/record/ihme-data/africa-under-5-lri-incidence-prevalence-mortality-geospatial-estimates-2000-2017 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2000 - December, 2017</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a>: </span> Subnationally representative </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>Estimates were produced for lower respiratory infection (LRI) incidence, prevalence, and mortality among children under 5 at the 5x5 km-level in 52 countries in Africa between 2000-2017. These estimates were produced using data extracted from 191 household surveys that had questions about the prevalence of cough with difficulty breathing among children under 5, and allowed for subnational geolocation. The surveys include the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), World Bank, and other country‐specific surveys. Collectively, they provided 56,628 total data points, corresponding to 53,592 survey clusters and 3,036 subnational polygon boundaries.</p> <p>This dataset includes the following:</p> <ul> <li>GeoTIFF raster files for pixel-level estimates of LRI incidence, prevalence, and mortality</li> <li>CSV files of aggregated estimates for each country at the zero, first, and second administrative divisions</li> <li>Code files used to generate the estimates</li> </ul> </div> </div> </div> Fri, 23 Sep 2022 09:04:32 -0700 GHDx 417555 at https://ghdx.healthdata.org