# Caseload calculations and nutrition indicators

This question was posted the Assessment and Surveillance forum area and has 2 replies.

### Grace Maclean

Nutrition Specialist Irish Aid RRI

Normal user

11 Sep 2019, 15:02

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 close to 15%.

1) How is the incidence factor determined in this case?

2) The two indicators used to assess GAM prevalence in the most recent national survey are MUAC and WHZ scores. In 20% of the surveyed localities, MUAC is higher than WHZ scores while in the remainder, WHZ scores are higher. Which indicator should technically be used in describing/ reporting on the national GAM prevalence?

Grateful if you would share experiences on these two questions.

### Mark Myatt

Epidemiologist at Brixton Health

Frequent user

11 Sep 2019, 16:27

WRT your questions (1) ... This has been a subject of much activity. I think, unless you have a good reason to do otherwise, you should use the "standard" correction factor of *K* = 1.6. This will almost certainly be wrong but you will be able to calibrate this to improve local need estimates over time using something like the method outlined in this article

If you have the required data you could use this method to calibrate K and use that instead of the "standard" *K* = 1.6.

WRT your question (2) ... GAM is usually defined using WHZ but you are looking to estimate person in need of intervention ("burden") and you may want to work with intervention admission criteria.

I hope this is of some use.

### Mbaye Diop

CLM

Normal user

14 Sep 2019, 14:34

For a year, it is generally considered that the correction factor for the incidence of SAM is 2.6 (note: the figure 2.6 comes from the article by Garenne et al 2009 evoking a common estimate of the average duration of one untreated SAM episode at 7.5 months. Therefore 12 months / 7.5 = 1.6 The total burden of SAM is calculated as follows: population 6-59m x [prevalence + (prevalence x incidence)]; if the incidence is 1.6, the calculation becomes: population 6-59m x [prevalence + (prevalence x 1.6)] that can be simplified to population 6-59m x prevalence x 2.6.

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