Filter
3320
Text search:
Sex
workers
Featured
325
1001
Language
3240
77
55
47
32
25
16
10
6
5
5
4
4
4
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Document type
2030
469
373
160
138
59
48
19
8
5
5
2
Countries / Regions
139
124
122
93
93
83
76
69
69
67
66
66
64
63
60
53
41
40
39
37
36
34
34
32
30
26
25
22
21
20
19
19
18
18
17
17
16
15
12
11
11
11
10
10
10
10
10
10
10
9
9
8
8
7
7
7
6
6
6
6
6
6
6
6
5
5
5
4
4
4
4
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Authors & Publishers
372
149
139
119
104
71
58
46
42
39
37
31
28
27
25
23
22
21
21
19
19
19
19
19
15
15
14
14
14
13
13
13
13
13
11
11
11
11
11
10
10
10
10
10
10
10
9
9
9
9
9
9
8
8
8
8
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Publication Years
1
858
2113
334
12
1
1
Category
1461
208
192
171
163
110
10
1
Toolboxes
427
218
211
159
120
88
88
79
68
61
53
46
44
39
31
24
24
19
19
17
11
9
9
8
2
2
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 data for monitoring progress on health programs and policies in Rwanda. This publication ill
...
ustrates the profile of Kigali City
more
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 data for monitoring progress on health programs and policies in Rwanda. This publication illu
...
strates the profile of Northern Province.
more
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 data for monitoring progress on health programs and policies in Rwanda. This publication ill
...
ustrates the profile of Southern province
more
Rwanda’s fourth health sector strategic plan (HSSP4) is meant to provide the health sector with a Strategic Plan that will highlight its commitments and priorities for the coming 6 years. It will be fully integrated in the overall economic development plan of the Government. HSSP4 will fulfill the
...
country’s commitment expressed in the national constitution, National Strategy for Transformation (NST) and the aspirations of the Health Sector Policy 2015. The strategies herein adhere to the Universal Health Coverage (UHC) principles towards realisation of the Sustainable Development Goals (SDGs). HSSP4 therefore lays a foundation for Vision 2050 (“The Rwanda We Want”), which will transform Rwanda into a high-income country by 2050. HSSP4 anticipates the epidemiological transition of the country, the increase in population and life expectancy and the expected increase of the health needs of the elderly, notably in Non Communicable Diseases (NCDs). HSSP4 also anticipates a decrease in external financial inflows, hence it is imperative to build secure / resilient health systems.
more
Save the Children in collaboration with the Bhubaneswar Municipal Corporation (BMC) and the state National Health Mission (NHM) undertook this study in the urban slums of Bhubaneswar city to generate learnings for designing a city-specific public health approach to improve MNH services for the urban
...
poor.
more
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine | The aim of this study was to explore the risk factors for stillbirth and neonatal death and change in perinatal outcomes after the introduction of helping Babies Breathe Quality Improvement Cycle in Nepal.
According to the Report, cascading and interlinked crises are putting the 2030 Agenda for Sustainable Development in grave danger, along with humanity’s very own survival. The Report highlights the severity and magnitude of the challenges before us. The confluence of crises, dominated by COVID-19,
...
climate change, and conflicts, are creating spin-off impacts on food and nutrition, health, education, the environment, and peace and security, and affecting all the Sustainable Development Goals (SDGs). The Report details the reversal of years of progress in eradicating poverty and hunger, improving health and education, providing basic services, and much more. It also points out areas that need urgent action in order to rescue the SDGs and deliver meaningful progress for people and the planet by 2030.
more
The report examines some of the underlying causes of domestic violence and the impact on children of being exposed to violence in the home.
Zero Draft for Consultation, 3rd Version, November 2015
This manual summarizes the methodology used to develop WHODAS 2.0 and the findings obtained when the schedule was applied to certain areas of general health, including mental and neurological disorders.
The manual will be useful to any researcher or clinician wishing to use WHODAS 2.0 in their prac
...
tice. It includes the seven versions of WHODAS 2.0, which differ in length and intended mode of administration. It also provides general population norms; these allow WHODAS 2.0 values for certain subpopulations to be compared with those for the general population.
more
A two-week mission was conducted by WASH and quality UHC technical experts from WHO headquarters and supported by the WHO Ethiopia Country Office (WASH and health systems teams) in July 2016, to understand how change in WASH services and quality improvements have been implemented in Ethiopia at nati
...
onal, sub-national and facility levels; to document existing activities; and through the “joint lens” of quality UHC and WASH, to identify and seek to address key bottlenecks in specific areas including leadership, policy/financing, monitoring and evaluation, evidence application and facility improvements. Ethiopia has implemented a number of innovative and successful interventions.
more
Census Report Volume 4-E
As no census has been undertaken in over 30 years, many aspects of the demographic situation in the country were unknown. For instance, before the Census it was thought that the country had a population of about 60 million, but the 2014 Census showed that the population ... (including an estimate for under-enumeration) was 51,486,253 persons, around 8.5 million less than the previous estimate.
In the 1983 census, 35,307,913 persons were recorded. Therefore between 1983 and 2014, the population increased by 46 per cent. With an average annual population growth rate of 0.89 per cent between 2003 and 2014, Myanmar is one of the slowest growing countries in Southeast Asia. more
As no census has been undertaken in over 30 years, many aspects of the demographic situation in the country were unknown. For instance, before the Census it was thought that the country had a population of about 60 million, but the 2014 Census showed that the population ... (including an estimate for under-enumeration) was 51,486,253 persons, around 8.5 million less than the previous estimate.
In the 1983 census, 35,307,913 persons were recorded. Therefore between 1983 and 2014, the population increased by 46 per cent. With an average annual population growth rate of 0.89 per cent between 2003 and 2014, Myanmar is one of the slowest growing countries in Southeast Asia. more
Census Report Volume 4-L
Myanmar’s 2014 Census enumerated 4.5 million people aged 60 and over and by 2050 Myanmar is projected to have 13 million people in this age group.
Myanmar’s population has aged between 1973 and 2014; while the total population increased at an annual rate of 1. ... 4 per cent, the population aged 60 and over increased annually by 2.4 per cent. Within the older population, the oldest age group, those over 80 years old, has been growing much faster than those aged 60-79. In 2014, the urban population was slightly older than the rural population. This is the result of a more rapid decline in urban fertility, offset by net migration to urban areas by youth and young adults. more
Myanmar’s 2014 Census enumerated 4.5 million people aged 60 and over and by 2050 Myanmar is projected to have 13 million people in this age group.
Myanmar’s population has aged between 1973 and 2014; while the total population increased at an annual rate of 1. ... 4 per cent, the population aged 60 and over increased annually by 2.4 per cent. Within the older population, the oldest age group, those over 80 years old, has been growing much faster than those aged 60-79. In 2014, the urban population was slightly older than the rural population. This is the result of a more rapid decline in urban fertility, offset by net migration to urban areas by youth and young adults. more
In April and May 2015, Nepal was hit by two major earthquakes killing around 9,000 people and leaving many thousands more injured and homeless.
To optimize the speed and volume of critical humanitarian assistance, the HCT has developed this Plan to:
1. Reach a common understanding of earth ... quake risk to ensure early action is taken when required.
2. Establish a minimum level of earthquake preparedness across clusters.
3. Build the basis for a joint HCT response strategy to meet the needs of affected people in the first 6 weeks to 3 months of a response.
4. Define considerations for detailed contingency planning on the basis of the worst-case scenario, especially around access and logistics. more
To optimize the speed and volume of critical humanitarian assistance, the HCT has developed this Plan to:
1. Reach a common understanding of earth ... quake risk to ensure early action is taken when required.
2. Establish a minimum level of earthquake preparedness across clusters.
3. Build the basis for a joint HCT response strategy to meet the needs of affected people in the first 6 weeks to 3 months of a response.
4. Define considerations for detailed contingency planning on the basis of the worst-case scenario, especially around access and logistics. more
This is the Technical Annex for the BRACED report: Measuring changes in household resilience as a result of BRACED activities in Myanmar.
Policy Brief, Updated in March 2017
