The National Institute for Transforming India (NITI) Aayog has developed the Composite Water Management Index (CWMI) to enable effective water management in Indian states in the face of extreme water stress. The Index and this associated report are
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expected to: (1) establish a clear baseline and benchmark for state-level performance on key water indicators; (2) uncover and explain how states have progressed on water issues over time, including identifying high-performers and under-performers, thereby inculcating a culture of constructive competition among states; and, (3) identify areas for deeper engagement and investment on the part of the states. Eventually, NITI Aayog plans to develop the index into a composite, national-level data management platform for all water resources in India.
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The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect
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data for monitoring progress on health programs and policies in Rwanda. This publication illustrates the profile of Kigali City
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The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect
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data for monitoring progress on health programs and policies in Rwanda. This publication illustrates the profile of Southern province
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This report covers research conducted on HIV stigma and discrimination using the Stigma Index in the Papua New Guinea provinces of Western Highlands and Chimbu*. When Igat Hope began the project the aim was to conduct interviews in all regions of PNG. However, due to funding constraints and organis
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ational capacities, the Stigma Index has only been applied in one region, that is, the Highlands Region. In future, the hope is to gather comparable data from other regions in PNG. Despite the fact that the overall project aims have not yet been achieved, the data contained in this report provides useful information that can be considered as work continues in PNG on HIV-related stigma and discrimination and human rights.
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The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect
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data for monitoring progress on health programs and policies in Rwanda. This publication illustrates the profile of Eastern Province.
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he National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect
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data for monitoring progress on health programs and policies in Rwanda. This publication illustrates the profile of Northern Province.
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Senegal’s substantial and sustained progress against malaria is an inspiring public health success story, and a source of potential lessons for other countries on the path to elimination. This case study describes three major success factors—(1) outstanding leadership and partner engagement, (2)
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the achievement and maintenance of high intervention coverage levels, and (3) a thriving data culture—and explores several exciting new opportunities to consolidate and expand upon Senegal’s two decades of impact.
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The government of Rwanda conducted the 2010 Rwanda Demographic and Health Survey (RDHS) to gather up-to-date information for monitoring progress on healthcare programs and policies in Rwanda, including the Economic Development and Poverty Reduction Strategy (EDPRS), the Millennium Development Goals
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(MDGs),
and Vision 2020. The 2010 RDHS is a follow-up to the 1992, 2000, 2005, and 2007-08 RDHS surveys. Each survey provides data on background characteristics of the respondents, demographic and health indicators, household health expenditures, and domestic violence. The target groups in these surveys were women age 15-49 and men age 15-59
who were randomly selected from households across the country. Information about children age 5 and under also was collected, including the weight and height of the children.
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This Case Study explores flood forecasting systems from the perspective of its position within the flood warning process. A method for classifying the different approaches taken in flood forecasting is introduced before the elements of a present-day flood forecasting system are discussed in detail.
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Finally, the state of the art in developing flood forecasting systems is addressed including how to deal with specific challenges posed.
The target group of this case study are decision makers in disaster risk management and/or water management. The case study should help to understand some hydrologic basics of the flood forecast and assist in the administration and implementation of an appropriate flood warning system in a specific environment, to find the best solution for a region.
Best solutions depend mainly on quality and availability of data, the areas and/or points of interest, catchment properties, cross border catchments, and financial capabilities with special consideration of flood forecast.
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Children malnutrition eradication in developing countries is a real challenge, especially among
vulnerable population. There are so many effort towards women (who are the main care providers)
socio-economic situation in order to improve their children nutrition. This article aims to identify the
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impact of mothers’ activities on child nutrition and care. Interviews were used to collect data from
mothers of children less than 5 years old. Pearson correlation test and regression models were
performed to highlight relation and to identify the main factors that affect child nutrition and care. The
nutritional statuses of children show a high prevalence of underweight (38.46%), emaciation (25.17%)
and stunting (23.77%). Statistic results show that a child whose mother has food processing as main
activity has 2,322 more times to not suffer from emaciation malnutrition compared to a child whose
mother has trade as main activity. A child whose mother has high revenue has 1.463 more times to
not be suffering from stunting malnutrition compared to a child whose mother has lower revenue. A
child whose father has fishing as main activity has 8,4 more chance to not be suffering from stunting
malnutrition compared to a child whose father has another activity as main activity. A child whose
father is present in the household has 8.11 more chance to not suffer from stunting malnutrition
compared to a child whose father is absent. A child from mother who has food processing as main
activity is 2,464 more times preserved from fever compared to a child from mother whose main activity
is trade. Moreover child position, child feeding with porridge, child nursing are correlated with mother
activity. This situation is justified by the fact that mother need money to improve child nutrition and
health but they are also confronted to the fact that those activity that provide significant money are
sometime time consuming and not permit to take care of children in term of feeding practices, hygiene
control etc. Therefore it is important that intervention towards women take in consideration those
factors (money and time) but also the family in the whole.
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This is only the cover of the book. Download the whole Toolkit at: www.cdc.gov/reproductivehealth/Refugee/
Understanding the reproductive health needs of conflict-affected women will enable organizations to implement and enhance programs and services to improve the health of women and their fam
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ilies. The Reproductive Health Assessment Toolkit (RHA) for Conflict-Affected Women provides user-friendly tools to quantitatively assess the reproductive health needs of conflict-affected women aged 15–49 years. The RHA Toolkit enables field staff to collect data to inform program planning, monitoring, evaluation, and advocacy. It promotes using the collected data to enhance services and improve the reproductive health of women and their families.
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West: Drada & Nagar Haveli, Daman & Diu, Goa, Gujarat, Maharashtra
South: Andhra Pradesh & Telangana, Karnataka, Kerala, Puducherry, Tamil Nadu
This technical document consists of epidemiological profiles (fact-sheets) for States and districts based on information available from multiple
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data sources including the HIV Sentinel Surveillance (HSS) and the Integrated Biological and Behavioural Surveillance (IBBS). Given the need for focussed prevention efforts in low/high prevalence and vulnerable States/districts, the information presented will be useful for policy makers, program planners at national/State/ district level, researchers, and academicians in identification of areas for priority attention and also to derive meaningful conclusions for programme planning, implementation, monitoring and scale-up. This document will be a quick reference for the HIV/AIDS situation in a State/district, risk and safe behaviour of the high risk groups, their level of knowledge about STIs and HIV/AIDS, experience of violence, HIV testing and ART awareness and exposure to HIV/AIDS prevention.
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Northern: Chandigarh, Delhi, Haryana, Himachal Pradesh, Jammu & Kashmir, Punjab, Rajasthan, and Uttarakhand
Central: Chhattisgarh, Madhya Pradesh and Uttar Pradesh
Eastern: Andaman & Nicobar, Bihar, Jharkhand, Odisha and West Bengal
This technical document consists of epidemiological
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profiles (fact-sheets) for States and districts based on information available from multiple data sources including the HIV Sentinel Surveillance (HSS) and the Integrated Biological and Behavioural Surveillance (IBBS). Given the need for focussed prevention efforts in low/high prevalence and vulnerable States/districts, the information presented will be useful for policy makers, program planners at national/State/ district level, researchers, and academicians in identification of areas for priority attention and also to derive meaningful conclusions for programme planning, implementation, monitoring and scale-up. This document will be a quick reference for the HIV/AIDS situation in a State/district, risk and safe behaviour of the high risk groups, their level of knowledge about STIs and HIV/AIDS, experience of violence, HIV testing and ART awareness and exposure to HIV/AIDS prevention.
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Further analysis of the 1996, 2001, and 2006 Demographic and Health Surveys Data
Analysis of microfilaria prevalence data from 430 communities
AN ANALYSIS OF UNICEF MICS 3 SURVEY DATA FROM BANGLADESH, LAO PDR, MONGOLIA AND THAILAND
Joint data assessment by the Central Statistical Organization and UNDP
The report shows that the National Statistical System of Myanmar has some work ahead of it in terms of preparing for the m
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onitoring of the SDG indicators. Only 44 of the SDG indicators are currently produced and readily available at the national level. However, the good news is that many (97) of the missing indicators can be computed from existing data sources – often with little effort - and don’t require any additional data collection. The report concludes that Myanmar is in a decent position to start monitoring the SDGs, and should start as soon as possible in putting its existing data to full use for the SDGs.
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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 f
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rom the 2000, 2005, and 2010 Rwanda Demographic and Health Surveys (RDHS).
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This third edition of the landscape analysis provides regional and country-specific data. This report illustrates the complexities in surveillance of influenza and other respiratory viruses and high
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lights differences in the countries’ preparedness capacities through charts, infographics, tables, and brief narratives.
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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, enab
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ling, and need factors potentially associated with use of antenatal care (ANC), health facility delivery, 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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