Menu ENN Search

UNICEF global SAM management update (2012)

Summary of report1

Thanks to Saul Guerrero, ACF-UK, for preparing this summary.

Location: Global

What we know: Mapping of global SAM management requires baseline and consistent data.

What this article adds: A web-based data collection and reporting system for SAM management at national level was developed by UNICEF and Valid International to address existing inconsistences in data reporting to strengthen mapping. The 2012 mapping reports on number of countries providing updates, national reporting services, estimated burden of SAM, SAM admissions, quality of SAM treatment, and integration into health services. Recommendations include integration of the UNICEF annual supply forecasting tool into the current online system, and improvement of the quality of performance indicator reporting and trend analysis.

The management of severe acute malnutrition (SAM) is critical for child survival and is a key component of the Scaling Up Nutrition framework for addressing undernutrition. UNICEF is a leading organisation in the scaled-up implementation of community-based management of acute malnutrition (CMAM), providing technical support, capacity building and therapeutic supplies for Ministries of Health and non-governmental organisation (NGO) partners. Monitoring and evaluation of service provision is a significant component of UNICEF’s work.

An initial mapping of countries supported by UNICEF in the area of CMAM was first presented in the ‘Global Mapping Review’ (2010 using 2009 data), followed by the 2011 ‘Global SAM Treatment Update’ in 2011. In order to build on previous efforts to gather baseline data related to SAM management at the national level, in 2012 UNICEF worked with Valid International to gather updated information through a web-based data collection and reporting system.

With a view to address previously noted inconsistencies with data reporting, UNICEF’s Nutrition in Emergencies unit undertook a standardisation process for the three main areas where discrepancies were identified, specifically incidence, burden of SAM and SAM treatment coverage. A range of technical experts, United Nations (UN) agencies, and field staff were consulted and the formulas used for the 2012 update are presented in Box 1. The original questionnaire was also refined based on feedback from previous years. The web-based platform enabled data quality checks at data entry, and guidance for each question was expanded. The main findings of the 2012 update are outlined below:

Number of countries implementing services

National reporting rates

Estimated burden of SAM

SAM admissions

Table 1: Reported annual admissions for SAM treatment by UNICEF region (2009-2012)
Region 2009 2011 2012

ESARO

414,412 806,919 890,414
WCARO 488,366 488,366 1,235,302
ROSA 29,116 207,215 258,366
MENA 64,124 126,647 217,935
TACRO 0 21,660 28,882
EAPRO 5,600 12,671 31,813
Total 1,001,618 1,961,772 2,662,712

EASRO Eastern and Southern Africa Regional Office, WCARO West and Central Africa Office, ROSA South Asia Regional Office, MENA Middle East and Northern Africa Regional Office, TACRO Americas and Caribbean Regional Office EAPRO East Asia and the Pacific Regional Office

Quality of SAM treatment

The three globally agreed performance indicators (recovered, defaulted and died) are routinely collected at a decentralised level to assess quality of SAM treatment. In order to give a more accurate picture of performance indicator rates in 2012, countries were asked to provide raw numbers for death, defaulting and recovery which were then used to calculate performance statistics, as opposed to reporting percentages as in previous rounds of data collection. With a focus on recovery and defaulting:

Challenges were presented with reporting data as raw numbers, with over 42% of the countries (25 countries) unable to report either defaulter or reporting figures. Efforts are required to support countries in the collection/ collation of these performance indicators.

Integration into Health Services

Integration of SAM management into national health systems has expanded the geographical coverage of SAM treatment as some ministries of health have adopted SAM management as part of the essential health package (not all countries are aiming for nationwide scale-up).

Some aspects of integration of SAM treatment into health systems were found to be strong with many countries reporting:

At the same time, many countries reported areas where there was less integration, such as:

The analysis found no obvious correlation between integration indicators and the levels of treatment or geographic coverage or number of admissions attained by countries. Nevertheless, it is clear that more needs to be done to advocate for an enhanced commitment by governments to SAM management.

Recommendations

Integration of the UNICEF annual supply forecasting tool into the current online system.

Whilst harmonised in terms of timing, the supply forecasting exercise and 2012 Global SAM Update are currently two separate data collection processes.

Improvement of the quality of performance indicator reporting and trend analysis.

UNICEF and partners are continuing to work with countries to improve SAM reporting using a variety of techniques (national web-based platforms, SMS systems, HMIS integrated reporting etc).

Integration of coverage survey data.

UNICEF will work with partners to strengthen capacity of some countries to undertake coverage surveys.

Development of additional modules for micronutrients and infant and young child feeding.

Creating additional data modules is crucial to building UNICEF’s global data management system from a harmonised perspective and lessening the burden of multiple information requests to countries at different times.

 

Box 1: Key definitions

Incidence of SAM
An estimate of the incidence of SAM can be calculated as follows:

Incidence = Prevalence/average duration of disease

A common estimate of the average duration of an untreated SAM episode is 7.5 months (Garenne et al. 2009). Using this to estimate incidence over one year (i.e., 12 months) yields:

Incidence = Prevalence × 12/7.5 = Prevalence × 1.6

1.6 is therefore the incidence correction factor for the calculation of incidence from a given prevalence.

Burden of malnutrition
The burden of SAM is defined as an estimation of the total number of SAM cases in a population over a specific period (i.e. prevalent cases + incident cases in the year).

Burden = Population 6-59m x [Prevalence + (Prevalence x 1.6)]
Or simplified to: Burden = Population 6-59m x Prevalence x 2.6

To clarify further:
- Prevalent cases = prevalent SAM x population 6-59m
- Incident cases = prevalent SAM X population 6-59m x 1.6 (where 1.6 is a correction factor which gives incidence as factor of prevalence)

Treatment Coverage
SAM treatment coverage is defined as the proportion of children with SAM who receive therapeutic care. For UNICEF’s 2012 data, this was calculated as follows:

SAM Treatment coverage = Admissions / Population 6-59m x [Prevalence + (Prevalence x 1.6)]

Geographical Coverage
The working definition for geographical coverage used by UNICEF in its 2012 Global SAM Management Update is as follows:

SAM Geographical Coverage = Healthcare facilities delivering treatment for SAM/ total number of healthcare facilities

Show footnotes

More like this

FEX: The state of global SAM management coverage 2012

Summary of report1 Thanks to Saul Guerrero, ACF-UK, for preparing this article. Location: Global What we know: Geographical coverage and treatment coverage are needed to...

en-net: Caseload calculations and nutrition indicators

We are currently calculating people in need (PiN) as per the humanitarian needs overview (HNO). The two most recent large scale national nutrition surveys indicated GAM rates...

en-net: Calculating caseloads-cmam=SAM/or MAM- need for clarification-part of the formula

From a document found in CMAM Forum on how to calaculate the SAM/ or MAM, The formula is: Case load = N × P × K × C N= total population of the under-fives in the catchment...

FEX: Improving estimates of numbers of children with severe acute malnutrition using cohort and survey data

Summary of Research Isanaka S, Boundy EO, Graise RF, Myatt M and Briend A. (2016). Improving Estimates of Numbers of Children With Severe Acute Malnutrition Using Cohort and...

FEX: Estimating the burden of wasting during COVID-19 based on empirical experiences in the Sahel

View this article as a pdf Lisez cet article en français ici By Saidou Magagi, Sumra Kureishy, Jessica Bourdaire and Katrien Ghoos Saidou Magagi is a monitoring,...

FEX: UNICEF Global reporting update: SAM treatment in UNICEF supported countries

A child being screened for malnutrition in a UNICEF supported programme By UNICEF Nutrition in Emergencies Unit and Valid International Following the CMAM mapping exercises...

en-net: Planning of CMAM services

The number of the children who need CMAM services is based on the prevalence data from nutrition surveys that indicate the numbers of children with SAM/MAM at a given time. For...

en-net: Caseload calculations (incidence rate)

I'm currently training some folks on how to calculate expected CMAM caseload using the (prevalence + incidence) * coverage equation. I'm having difficulty explaining to my team...

en-net: Estimating caseload for Targeted Suplementary Fedding programme (TSFP)

For estimating SAM caseload, detailed explanation was given by André Briend with a formula as follow: expected caseload of SAM over 12 month = Prevalence + prevalence...

FEX: Putting Child Kwashiorkor on the Map

Jose Luis Alvarez, Nicky Dent, Lauren Browne, Mark Myatt and André Briend Putting Kwashiorkor on the Map started as a call for sharing data to give an idea of...

FEX: Assessing the differences in the scale of nutrition response efforts to El Niño in Ethiopia

By Getinet Babu, Alexandra Rutishauser-Perera and Claudine Prudhon View this article as a pdf Getinet Babu is a humanitarian nutritionist with over 12 years' extensive...

en-net: Monthly program coverage calculation for TFP / SFP

In order to track program coverage for a TFP (for example) on a monthly basis, I would use Mark M.s Indirect Method = No. of children attending SCs and OTPs / (Estimated prev'...

FEX: Scale-up of IMAM services in Afghanistan

By Ahmad Nawid Qarizada, Piyali Mustaphi, Jecinter Akinyi Oketch and Shafiqullah Safi View this article as a pdf Lisez cet article en français ici Ahmad Nawid...

FEX: Integration of CMAM into routine health services in Nepal

By Regine Kopplow Regine is a former CMAM Advisor with Concern Nepal. She is a nutritionist with a background in rural development. She has worked in the field of nutrition...

FEX: UNICEF call for data sharing for incidence analysis

UNICEF has issued a request to organisations to share data to inform an analysis of the incidence of severe acute malnutrition (SAM) at country level. This analysis aims to...

FEX: Invited commentary: improving estimates of severe acute malnutrition requires more data

Summary of commentary1 Authors of an invited commentary on a recent paper by Isanaka et al (2016), that described development of an updated incidence-correction factor for...

FEX: SAM and MAM programming in East and West Africa: An insight into continuum of service provision for acute malnutrition treatment

View this article as a pdf By Rebecca Brown, Kate Sadler, Tanya Khara, Marie McGrath and Jeremy Shoham Rebecca Brown is an experienced public health nutritionist engaged as...

FEX: Global CMAM mapping in UNICEF supported countries

Summary of review1 A recent review commissioned by UNICEF set out to develop a global map on the status of Communitybased Management of Acute Malnutrition (CMAM) with a focus...

FEX: Scaling-up of care for children with acute malnutrition during emergency nutrition response in South Sudan between 2014 and 2018

View this article as a pdf Lisez cet article en français ici By Dina Aburmishan, Vilma Tyler, Lucas Alamprese, Priscilla Bayo Nicholas, Marie Darline Raphael, Joseph...

FEX: Community management of acute malnutrition in Mozambique

By Edna Germack Possolo, Yara Lívia Novele Ngovene and Maaike Arts Edna Germack Possolo is Chief of the Nutrition Department of the Ministry of Health, Republic of Mozambique...

Close

Reference this page

Saul Guerrero (). UNICEF global SAM management update (2012). Field Exchange 47, April 2014. p52. www.ennonline.net/fex/47/unicef

(ENN_4493)

Close

Download to a citation manager

The below files can be imported into your preferred reference management tool, most tools will allow you to manually import the RIS file. Endnote may required a specific filter file to be used.