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2015-16 Demographic and Health Survey and Malaria Indicator Survey
The Namibia Population-based HIV Impact Assessment (NAMPHIA) 2017 | The Ministry of Health and Services is leading the NAMPHIA survey in collaboration with the Namibia Statistics Agency (NSA) and the Namibia Institute of Pathology (NIP). The survey is supported by the United States President’s Eme...rgency Plan for AIDS Relief (PEPFAR), through the U.S. Centers for Disease Control and Prevention (CDC). | The goal of NAMPHIA is to examine the current distribution of the HIV epidemic and assess the impact of Namibia’s prevention, care and treatment response across all 14 regions of Namibia.
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The Namibia Population-based HIV Impact Assessment (NAMPHIA) 2017 | The Ministry of Health and Services is leading the NAMPHIA survey in collaboration with the Namibia Statistics Agency (NSA) and the Namibia Institute of Pathology (NIP). The survey is supported by the United States President’s Eme...rgency Plan for AIDS Relief (PEPFAR), through the U.S. Centers for Disease Control and Prevention (CDC). | The goal of NAMPHIA is to examine the current distribution of the HIV epidemic and assess the impact of Namibia’s prevention, care and treatment response across all 14 regions of Namibia.
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FAST FACTS FROM THE 2013-14 ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY
The Namibia Population-based HIV Impact Assessment (NAMPHIA) 2017 | The Ministry of Health and Services is leading the NAMPHIA survey in collaboration with the Namibia Statistics Agency (NSA) and the Namibia Institute of Pathology (NIP). The survey is supported by the United States President’s Eme...rgency Plan for AIDS Relief (PEPFAR), through the U.S. Centers for Disease Control and Prevention (CDC). | The goal of NAMPHIA is to examine the current distribution of the HIV epidemic and assess the impact of Namibia’s prevention, care and treatment response across all 14 regions of Namibia.
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The 2007 Rwanda Service Provision Assessment (RSPA) was a national representative survey conducted in 538 health facilities throughout Rwanda. The survey covered hospitals, health centers, dispensaries and
health posts, including all public facilities such as government and government-assisted heal...th facilities. The 2007 RSPA used interviews with health service providers and clients and observations of provider client consultations to obtain information on the capacity of facilities to provide quality services and the existence of functioning systems to support quality services. The areas addressed were the overall facility
infrastructure, maternal and child health, reproductive health, tuberculosis, malaria services; and services for sexually transmitted infections and HIV/AIDS. The objective was to assess the strengths and
weaknesses of the infrastructure and systems supporting these services, and to assess the adherence to standards in the delivery of services.
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Info-graphic on Fast Facts from the 2014-15 Rwanda Demographic and Health Survey.
The primary objectives of the 2017 TMIS are to measure the level of ownership and use of mosquito nets; assess coverage of intermittent preventive treatment for pregnant women; identify treatment practices, including the use of specific antimalarial medications to treat malaria among c...hildren age 6-59 months; measure the prevalence of malaria and anemia among children age 6-59 months; and assess knowledge, attitudes, and practices among adults with malaria.
This table provides estimates of key indicators for the country as a whole and for each of the 31 geographic regions in Tanzania. A comprehensive analysis of the 2017 TMIS data will be presented in a final report.
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Policy brief based on the 2007 Rwanda Service Provision Assessment (RSPA) survey. The 2007 RSPA survey describes how the formal health sector in Rwanda provides services for family planning, maternal health, child health, malaria, HIV/AIDS, and other communicable diseases.
Nigeria is Africa’s most populous nation and accounts for nearly one quarter of the continent’s maternal, newborn and child deaths. In the spirit of the global Countdown to 2015 for Maternal, Newborn and Child Health and the Nigerian Saving One Million Lives Initiative, these state data profiles... have been designed to prompt and inform policy and programme action.
Without data there can be no accountability. Without accountability we risk making no progress for Nigeria’s women and children. The data included in these profiles come mainly from large-scale, periodic household surveys. Continued efforts are needed to strengthen civil registration, vital statistics and health management information systems, as well as the institutional capacity to gather and use these data.
Updated from 2011, these data profiles can be used to compare progress in different areas, identify opportunities to address specific coverage gaps, and monitor implementation.
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Background: Disbursements of development assistance for health (DAH) have risen substantially during the past several decades. More recently, the international community's attention has turned to other international challenges, introducing uncertainty about the future of disbursements for DAH.
Meth...ods: We collected audited budget statements, annual reports, and project-level records from the main international agencies that disbursed DAH from 1990 to the end of 2015. We standardised and combined records to provide a comprehensive set of annual disbursements. We tracked each dollar of DAH back to the source and forward to the recipient. We removed transfers between agencies to avoid double-counting and adjusted for inflation. We classified assistance into nine primary health focus areas: HIV/AIDS, tuberculosis, malaria, maternal health, newborn and child health, other infectious diseases, non-communicable diseases, Ebola, and sector-wide approaches and health system strengthening. For our statistical analysis, we grouped these health focus areas into two categories: MDG-related focus areas (HIV/AIDS, tuberculosis, malaria, child and newborn health, and maternal health) and non-MDG-related focus areas (other infectious diseases, non-communicable diseases, sector-wide approaches, and other). We used linear regression to test for structural shifts in disbursement patterns at the onset of the Millennium Development Goals (MDGs; ie, from 2000) and the global financial crisis (impact estimated to occur in 2010). We built on past trends and associations with an ensemble model to estimate DAH through the end of 2040.
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