POSHAN District Nutrition Profile_Munger_BiharPOSHAN
POSHAN District Nutrition Profiles (DNPs) draw on diverse sources of data to compile a set of indicators on the state of nutrition and its cross-sectoral determinants. The profiles are intended to be conversation-starters at the district level and to enable discussions about why undernutrition levels are high, and which factors, at multiple levels, might need to be addressed to improve nutrition.
PLEASE NOTE that POSHAN is regularly tracking data sources as they are released and updating the profiles accordingly.
POSHAN District Nutrition Profile_Munger_BiharPOSHAN
POSHAN District Nutrition Profiles (DNPs) draw on diverse sources of data to compile a set of indicators on the state of nutrition and its cross-sectoral determinants. The profiles are intended to be conversation-starters at the district level and to enable discussions about why undernutrition levels are high, and which factors, at multiple levels, might need to be addressed to improve nutrition.
PLEASE NOTE that POSHAN is regularly tracking data sources as they are released and updating the profiles accordingly.
Summary of Telemedicine study in Serbia / Sažetak studije o Telemedicini u Sr...NALED Serbia
Studija o potencijalima primene telemedicine u Srbiji i njenim benefitima za građane i lokalne samouprave.
Study on the potentials of implementation of telemedicine in Serbia and its benefits for the citizens and local governments.
Improving nutrition in Himachal Pradesh: Trends in outcomes, determinants and...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Predictive analysis WHO's life expectancy dataset using Tableau data visualis...Tarun Swarup
Performed predictive analysis on global Life expectancy dataset (WHO) to analyze the vital factors affecting human health and other societal risks demographically.
Designed a visual dashboard to identify intrinsic patterns in different factors and extract valuable insights to predict life expectancy accordingly.
▪ Infant Death Rate almost reduced by 40% in the last two decades.
▪ Overall adult mortality rate turned down by almost 17% in the previous years.
Improving nutrition in Karnataka:Trends in outcomes, determinants and interve...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Improving nutrition in Tripura:Trends in outcomes, determinants and intervent...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
IHME's Dr. Lozano discusses how the quality of maternal mortality data was improved in Mexico, leading to better estimates to more reliably measure progress.
For more information please visit www.healthmetricsandevaluation.org
Improving nutrition in Maharashtra:Trends in outcomes, determinants and inter...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Improving nutrition in Sikkim:Trends in outcomes, determinants and interventi...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
POSHAN District Nutrition Profile_Saharsa_BiharPOSHAN
POSHAN District Nutrition Profiles (DNPs) draw on diverse sources of data to compile a set of indicators on the state of nutrition and its cross-sectoral determinants. The profiles are intended to be conversation-starters at the district level and to enable discussions about why undernutrition levels are high, and which factors, at multiple levels, might need to be addressed to improve nutrition.
PLEASE NOTE that POSHAN is regularly tracking data sources as they are released and updating the profiles accordingly.
Improving nutrition in Andaman & Nicobar Islands: Trends in outcomes, determi...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Summary of Telemedicine study in Serbia / Sažetak studije o Telemedicini u Sr...NALED Serbia
Studija o potencijalima primene telemedicine u Srbiji i njenim benefitima za građane i lokalne samouprave.
Study on the potentials of implementation of telemedicine in Serbia and its benefits for the citizens and local governments.
Improving nutrition in Himachal Pradesh: Trends in outcomes, determinants and...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Predictive analysis WHO's life expectancy dataset using Tableau data visualis...Tarun Swarup
Performed predictive analysis on global Life expectancy dataset (WHO) to analyze the vital factors affecting human health and other societal risks demographically.
Designed a visual dashboard to identify intrinsic patterns in different factors and extract valuable insights to predict life expectancy accordingly.
▪ Infant Death Rate almost reduced by 40% in the last two decades.
▪ Overall adult mortality rate turned down by almost 17% in the previous years.
Improving nutrition in Karnataka:Trends in outcomes, determinants and interve...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Improving nutrition in Tripura:Trends in outcomes, determinants and intervent...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
IHME's Dr. Lozano discusses how the quality of maternal mortality data was improved in Mexico, leading to better estimates to more reliably measure progress.
For more information please visit www.healthmetricsandevaluation.org
Improving nutrition in Maharashtra:Trends in outcomes, determinants and inter...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Improving nutrition in Sikkim:Trends in outcomes, determinants and interventi...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
POSHAN District Nutrition Profile_Saharsa_BiharPOSHAN
POSHAN District Nutrition Profiles (DNPs) draw on diverse sources of data to compile a set of indicators on the state of nutrition and its cross-sectoral determinants. The profiles are intended to be conversation-starters at the district level and to enable discussions about why undernutrition levels are high, and which factors, at multiple levels, might need to be addressed to improve nutrition.
PLEASE NOTE that POSHAN is regularly tracking data sources as they are released and updating the profiles accordingly.
Improving nutrition in Andaman & Nicobar Islands: Trends in outcomes, determi...POSHAN
This slide deck is an evolving work in progress, with updates being made frequently. If you want to use or cite this, please email us at IFPRI-POSHAN@cgiar.org to receive the most updated version
Vital statistics is accumulated data gathered on live births, deaths, migration, fetal deaths, marriages and divorces. The most common way of collecting information on these events is through civil registration, an administrative system used by governments to record vital events which occur in their populations.
Vital statistics is accumulated data gathered on live births, deaths, migration, fetal deaths, marriages and divorces. The most common way of collecting information on these events is through civil registration, an administrative system used by governments to record vital events which occur in their populations.
Data Driven Decision Making in Ministry of Health and Family WelfareData Portal India
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Population Studies / Demography IntroductionMuteeullah
Presentation and Assignment on Population / Demography including mortality, fertility and their measure, population census, vital registration, demography survey, House hold survey, population composition, errors in demographic data, demographic measures.................By Muteeullah Channa University of Sindh
GHME 2013 Conference
Session: Measuring child mortality and causes of death
Date: June 18 2013
Presenter: Celia Szwarcwald
Institution:
National School of Public Health
Institute of Scientific and Technologic Information
Oswaldo Cruz Foundation
Rashmi Kukreja - Data visualization PresentationHFG Project
Dr. Rashmi Kukreja also presented to the consortium on Indices on Family Planning using data visualization, based on the result of a new HFG report by Avenir Health: Understanding District-level Variation in Fertility Rates in High-focus Indian States.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
1. The Global Summit on CRVS
Civil Registration System,
Sample Registration System
&
Annual Health Survey :
Issues and Policy Uses
DR. R. C. SETHI
FORMER ADDITIONAL REGISTRAR GENERAL, INDIA
Office of the Registrar General, India
18-19th
April 2013
2. OVERVIEW
Civil Registration System- Status, Challenges
and Initiatives
Sample Registration System, 2011- Key
Results
Annual Health Survey, 2009-2011- Highlights
of the baseline survey
3. Civil Registration System
• Comprehensive and complete CRS has multi-faceted
implications on socio-economic development of a country.
• A complete & up to date CRS can provide:
Reliable Statistics on fertility & mortality at all level of
aggregations
Almost on a real time basis which is not possible from any
sample survey.
Key for evidence based planning and has no parallels
• The levels of registration reflects the quality of
governance.
4. Civil Registration System (CRS)- Scenario
• Registration of Births and Deaths in India is mandatory
with the enactment of Registration of Births and Death
Act (RBD Act), 1969.
• Registration of Births and Deaths falls under the
Concurrent list of the Constitution.
• Registrar General, India unifies and coordinates the
activities of the States.
• States are responsible for implementation of RBD Act.
• National Population Policy mandates cent percent
registration.
5. • LOR (Birth) – India: 62.5% to 81.3 % ( + 18.8 %)
• LOR (Death)– India 55.0% to 66.9% ( + 11.9%)
• 13 States/UTs have achieved 100% registration
of births.
• 6 States/UTs have achieved 100% registration of
deaths.
• Some of the major States remains the main
concern.
Registration Scenario in India during last 5 years
6. Level of Registration of Births and Deaths, 2000-2009
Still every 5th
birth & every 3rd
death goes un-registered.
7. Issues
Utility of birth and death certificate- Enhancing the utility
and awareness among the general public, a cause of
concern.
States/UTs are functioning at different level of efficiency-
reflects the governance.
Flow of registered vital events- a bottleneck in monitoring.
Under reporting of domiciliary infant deaths & still births
and misclassification of maternal deaths in better
performing States- how to estimate IMR & MMR?
Utility of data gets diminished on account of delayed
reporting by the States.
8. Initiatives to re-vitalise the system
To enhance the utility, MOHFW has linked the delivery of
services with registration e.g. cash incentive under JSY etc.
Provision for incentive to the States and to grass-root
workers Anganwadi/ASHA for registration and delivery.
Ministry of Health has made registration as one of the focus
areas under National Rural Health Mission (NRHM)/ NHM.
To cover all institutional events, a database of Medical
Institutions is being prepared.
Provisions of the Act are being simplified for better
implementation.
Linking CRS at sub-district level to update NPR.
Collaboration with various partners for further
strengthening of the system.
9. Introduced in early 1970s to provide cause-specific
mortality profile.
Restricted to urban areas, that too few selected
hospitals.
At various stages of implementation across different
States.
Coding is as per ICD-10.
Covers about 19% of the total registered deaths only.
Garbage codes(R00-R99) are to the tune of 14%.
Medical Certification of Causes of Death (MCCD)
10. Time Series on Medically Certified Deaths vis-a-vis Total Registered Deaths Reported
for the Period 1986-2007
ORGI has expanded the scope under MCCD to all Institutions
including individual practitioners and the coverage , extended
to rural areas as well.
11. Sample Registration System
Genesis
Initiated in 1969-70 for want of complete registration from CRS.
Objectives
Provide reliable annual estimates of birth, death and infant mortality rates
at the State and National levels separately for rural and urban areas.
Also provides Child Mortality Rate (CMR), Total Fertility Rate (TFR), Sex
Ratio at Birth and 0-4 age, Institutional deliveries, Medical Attention before
death, etc.
Under 5 mortality rate also generated from 2008 annually.
Features
•One of the largest demographic household sample survey in the world
Sample size determination based on IMR
Permissible level of RSE: 10% (bigger states)
1.3 million households and about 7 million population
Only panel survey with dual recording
Panel revised once in 10 years based on the latest available Census frame
12. • Of the 8 MDGs, IMR, U5MR and MMR are generated by SRS.
Goal
No.
Goals Indicators
Targets
by 2015
4
Reduce infant mortality Infant Mortality Rate (IMR) 28
Reduce child mortality Under 5 Mortality Rate (U5MR) 42
5 Improve maternal health Maternal Mortality Ratio (MMR) 109
MILLENNIUM DEVELOPMENT GOALS(MDG)
13. • MMRatio measures number of women aged 15-49 years dying
due to maternal causes per 1,00,000 live births.
• Decline in MMR estimates in 2007-09 over 2004-06:
At the country level, it has declined to 212 from 254 (a fall of about
17%)
It varies between 81 in the State of Kerala to 390 in Assam ( a variability
of 5 times).
• MDG target of 109 have been achieved by 3 States viz. Kerala,
Tamil Nadu & Maharashtra.
• 4 States viz. Andhra Pradesh, West Bengal, Gujarat and
Haryana are in closer proximity to achieving the MDG target.
MMR ESTIMATES 2007-09
14. TREND IN MMRatio- India
(2004-06)
2009
2007-09 SRS
212
56 000
(2007-09)
15. Region MMR Life time
risk
% share of
female Popln.
% to total
maternal deaths
EAG states 308 1.1% 48.0 61.6
Southern
states
127 0.3% 21.0 11.4
Other states 149 0.4% 31.0 27.0
India 212 0.6% 100 100
LEVELS OF MMRATIO BY REGIONS, 2007-09
½ of the female population of EAG States contributes about
2/3rd
of Maternal Deaths.
16. Total Fertility Rate (TFR) BY RESIDENCE, 1990-
2011
TFR for the country declined by 1.4 points (down by
more than a child), rural TFR also by 1.4 points and
urban TFR by 0.9 point over last 21 years.
18. “To yield a comprehensive,
representative and reliable dataset on
core vital indicators including
composite ones like IMR, MMR and
TFR along with their co-variates
(process and outcome indicators) at
the district level and map changes
therein on an annual basis.”
OBJECTIVE OF AHS
20. o
AHS States constitute:
• 48 percent of country’s Population
• 59 percent of Births
• 70 percent of Infant Deaths
• 75 percent of Under 5 Deaths
• 62 percent of Maternal Deaths
o
Enable direct monitoring of UN Millennium
Development Goals on Child Mortality and Maternal
Health at the district(s) level.
o
Help in identifying high focus districts meriting
special attention in view of stark inter-district
variations in these States.
WHY AHS ?
21. • Panel Survey on the pattern of SRS.
• Coverage- All the 284 districts of 8 EAG States and Assam.
• Sample Size- IMR as the decisive indicator with 10%RSE.
• Sample Units- 20,694 statistically selected sample unit
(Census Enumeration Blocks in urban areas and Villages or a
part thereof in rural areas).
• Sample Population- About 20.1 million.
• Sample Households - 4.1 million households.
• Sample Units per district- 73.
• Sample Population per district - About 71 thousand.
• Sample households per district - About 14.5 thousand.
The Largest Sample Survey in the World
KEY FEATURES
22. •In all, 161 indicators are available from AHS baseline:
Fertility- 13 Sex Ratio- 3
Marriage- 5 Mortality- 7
Mother & Child Care- 63
Ante Natal Care: 11 Delivery Care: 8
Post Natal Care: 5 Janani Suraksha Yojana (JSY): 3
Immunization: 8 Vitamin A & Iron Supplements: 2
Birth Weight: 2 Childhood Disease: 6
Birth Registration: 2 Breastfeeding & Supplementation: 12
Awareness in Mothers: 4
Abortion- 6 Family Planning Practices- 15
Disability- 1 Morbidity- 19
Personal Habits:adults-4 Housing & HH Characteristics- 13
Others- 12
INDICATORS UNDER AHS
24. Clinical, Anthropometric & Bio-Chemical Component
• CAB component of the AHS would provide
district level data on the prevalence of the
following in a selected sub-samples of
households across all the AHS districts.
under and over nutrition,
anaemia,
hypertension,
fasting glucose levels, and
household availability of iodised salt
25. POLICY IMPLICATIONS
Policy needs particularly in respect of reliable and timely data
have undergone a paradigm shift since last 50 years.
State level estimates are used for both central as well as state
level planning. Also for pop. Proj., life tables, IMR, MMR, HDI
etc.
SRS was therefore designed as a stop-gap arrangement to
bridge the data gap at national and state levels in view of an
deficient CRS.
Non availability of district level estimates thwarted the need
for sub-state level planning despite the recognition of the
facts that state averages mask the reality.
26. AHS conclusively proved the above hypothesis and stressed
the importance of identifying the hotspots (districts
requiring special attention).
Availability of such a rich and comprehensive dataset would
help in accessing the impact of various health interventions
including those under NRHM/ NHM – JSY, SRB.
Estimates of IMR at district level and MMR for a group of
districts would enable tracking of MDGs at below state level.
District level estimates would provide requisite inputs for
better planning of health programmes and pave the way for
evidence based intervention strategies.
Results of CAB on such a large sample would be available
for the first time, could be used for appropriate
interventions, examining cause & effect relationship etc.
POLICY IMPLICATIONS
27. There is no substitute for a complete
Civil Registration System
Bulk of the above information particularly fertility and
mortality indicators cross-classified by standard auxiliary
variables can be made available for all the districts if there
was a complete and up to date CRVS.
Universal coverage under CRS will yield meaningful
information on sex-ratio at birth and still birth rate, which
would help in mapping the effectiveness of PNDT Act.
For causes of death, this perhaps (MCCD) is the only
solution.
The list is endless………
POLICY IMPLICATIONS