Data from the 2011 Ethiopia Demographic and Health Survey
Data from the 2011 Ethiopia Demographic and Health Survey
Data from the 2011 Ethiopia Demographic and Health Survey
In low- and middle-income middle-income countries, reliable and disaggregated disability data on prevalence, participation and barriers are often unavailable. This study aimed to estimate disability prevalence, determine associated socio-demographic factors and compare access in the community betwee...n people with and without disability in Dehradun district of Uttarakhand, India, using the Rapid Assessment of Disability survey.
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For the 24th consecutive year, PAHO has published the report Health Situation in the Americas: Core Indicators featuring the latest information on key indicators for the Region of the Americas. This 2018 edition includes data on the 82 core indicators for the countries, territories, and sub regions ...of the Americas, grouped into the following categories: demographic-socioeconomic, health status, risk factors, service coverage, and health systems. Information is also presented on 22 indicators of the Sustainable Development Goals (SDGs).
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This document presents the findings of the National Census of Persons with Disabilities in Rwanda. The preliminary result of this census has been used to produce a summary analysis of tables and figures. It shall be possible to derive basic socio-demographic indicators as well as to obtain the estim...ate of persons with disability in Rwanda, all of which shall serve as a reference to the categorization activity planned to be done in the near future by a medical committee from the Ministry of Health. The data of this report relate to (1) Persons with disability size for various administrative units (Districts and Provinces), (2) Distribution of Persons with disabilities by sex, age, marital status and type of disabilities.
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DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delive...ry, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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DHS Further Analysis Reports No. 88 - This further analysis examines levels, trends, and determinants of neonatal mortality in Rwanda, using data from the 2000, 2005, and 2010 Rwanda Demographic and Health Surveys (RDHS).
DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ...the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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Neonatal mortality is a major challenge in reducing child mortality rates in Nepal. Despite efforts by the Government of Nepal, data from the last three demographic and health surveys show a rise in the contribution of neonatal deaths to infant and child mortality. The Government of Nepal has implem...ented community-based programs that were piloted and then scaled up based on lessons learned. These programs include, but are not limited to ensuring safe motherhood, birth preparedness package, community-based newborn care package, and integrated management of childhood illnesses. Despite the implementation of such programs on a larger scale, their effective coverage is yet to be achieved. Health system challenges included an inadequate policy environment, funding gaps, inadequate procurement, and insufficient supplies of commodities, while human resource management has been found to be impeding service delivery. Such bottlenecks at policy, institutional and service delivery level need to be addressed incorporating health information in decision-making as well as working in partnership with communities to facilitate the utilization of available services.
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Accessed on 31.01.2020
The Senegal Continuous Survey is designed to provide yearly data for monitoring the population and health situation in Senegal through both a Demographic and Health Survey and Service Provision Assessment. The 4th phase of the five-year Continuous Survey was implemented in... 2016.
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Accessed on 03.03.2020
The country recognizes the importance of family planning as they focus on achieving a demographic dividend. In order to improve the service delivery and supply chain, Senegal is strengthening its data management and reporting. Domestic resource mobilization for family plannin...g remains a key challenges for Senegal.
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The Burkina Faso Demographic and Health and Multiple Cluster Indicator Survey 2010 (DHS-MICS), or Enquête Démographique et de Santé et à Indicateurs Multiples du Burkina Faso 2010, was conducted by the Institut National de la Statistique et de la Démographie (INSD) of the Ministry of Economy a...nd Plan (MOEP) in collaboration with the Ministry of Health (MOH), with technical assistance from ICF International. Data for this nationally representative survey were collected from 14,424 households, and complete interviews were conducted with 17,087 women aged 15−49 and 7,307 men aged 15–59. The fieldwork took place from May 2010 to January 2011. The summary statistics presented below were taken from the 2010 Burkina Faso DHS-MICS (INSD and ICF International 2012), with exceptions as noted.
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Interactive Map
You’ve probably noticed that the map has been evolving along with the virus. Now, it sports new layers of data—including a close-up section on the US, with details on testing, hospitalizations, and country-level demographic data.
The map provides “more nuance on what’s h...appening to support decision-making.
For example, the new details can help prepare hospitals to better anticipate staffing and resource shortages
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Massoda Tonye et al. Malar J (2018) 17:156
https://doi.org/10.1186/s12936-018-2284-7
Background: In 2011, the demographic and health survey (DHS) in Cameroon was combined with the multiple indicator
cluster survey. Malaria parasitological data were collected, but the survey period did not overl...ap with the high
malaria transmission season. A malaria indicator survey (MIS) was also conducted during the same year, within the
malaria peak transmission season. This study compares estimates of the geographical distribution of malaria parasite
risk and of the effects of interventions obtained from the DHS and MIS survey data.
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This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delivery, and timely postnatal care (PNC).This s...tudy uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12regions.We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use.We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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Because of the limited access to more powerful diagnostic tools, there is a paucity of data regarding the burden of fungal infections in Burkina Faso. The aim of this study was to estimate the incidence and prevalence of serious fungal infections in this sub-Saharan country. We primarily used the na...tional demographic data and performed a PubMed search to retrieve all published papers on fungal infections from Burkina Faso and its surrounding West African countries. Considering the prevalence of HIV infection (0.8% of the population) and a 3.4% incidence of cryptococcosis in hospitals, it is estimated that 459 patients per year develop cryptococcosis. For pneumocystosis, it is suggested that 1013 new cases occur every year. Taking into account the local TB frequency (population prevalence at 0.052%), we estimate the prevalence of chronic pulmonary aspergillosis at 1120 cases. Severe forms of asthma with fungal sensitization and allergic bronchopulmonary aspergillosis are estimated to affect 7429 and 5628 cases, respectively. Vulvovaginal candidiasis may affect 179,000 women, and almost 1,000,000 children may suffer from tinea capitis. Globally, we estimate that roughly 1.4 million people in Burkina Faso (7.51% of the population) suffer from a serious fungal infection. These data should be used to drive future epidemiological studies, diagnostic approaches, and therapeutic strategies.
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Contains data from World Health Organization's data portal covering the following categories:
Mortality and global health estimates, Sustainable development goals, Millennium Development Goals (MDGs), Health systems, Malaria, Tuberculosis, Child health, Infectious diseases, Neglected Tropical Disea...ses, World Health Statistics, Health financing, Tobacco, Substance use and mental health, Injuries and violence, HIV/AIDS and other STIs, Public health and environment, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Health inequality monitor, Health Equity Monitor, Child malnutrition, TOBACCO, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, 0, Insecticide resistance, Oral health, Universal Health Coverage, Global Observatory for eHealth (GOe)
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Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards ...UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country’s UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios.
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We combine data on Chinese development projects with data from Demographic and Health Surveys to study the impact of Chinese aid on household welfare in sub-Saharan Africa. We use a novel methodology to test the effect of Chinese aid on three important development outcomes: education, health, and nu...trition. For each outcome, we use difference-in-difference estimations to compare household areas near Chinese project sites to control areas located farther away, before and after receiving Chinese aid. This empirical strategy rules out many confounding factors that can bias measuring the impact of Chinese aid on our outcome variables. First, we find that Chinese projects significantly improve education and child mortality in treatment areas, but do not significantly affect nutrition. Second, social sector projects have a larger effect on outcomes than economic projects. Third, we do not find significant effects for projects that ended more than five years before the post-treatment survey wave. Our results are robust to a host of robustness checks.
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