Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger

Abstract

IntroductionReliable prospective estimates of annual severe acute malnutrition (SAM) caseloads for treatment are needed for policy decisions and planning of quality services in the context of competing public health priorities and limited resources. This paper compares the reliability of SAM caseloads of children 6–59 months of age in Niger estimated from prevalence at the start of the year and counted from incidence at the end of the year.MethodsSecondary data from two health districts for 2012 and the country overall for 2013 were used to calculate annual caseload of SAM. Prevalence and coverage were extracted from survey reports, and incidence from weekly surveillance systems.ResultsThe prospective caseload estimate derived from prevalence and duration of illness underestimated the true burden. Similar incidence was derived from two weekly surveillance systems, but differed from that obtained from the monthly system. Incidence conversion factors were two to five times higher than recommended.DiscussionObtaining reliable prospective caseloads was challenging because prevalence is unsuitable for estimating incidence of SAM. Different SAM indicators identified different SAM populations, and duration of illness, expected contact coverage and population figures were inaccurate. The quality of primary data measurement, recording and reporting affected incidence numbers from surveillance. Coverage estimated in population surveys was rarely available, and coverage obtained by comparing admissions with prospective caseload estimates was unrealistic or impractical.ConclusionsCaseload estimates derived from prevalence are unreliable and should be used with caution. Policy and service decisions that depend on these numbers may weaken performance of service delivery. Niger may improve SAM surveillance by simplifying and improving primary data collection and methods using innovative information technologies for single data entry at the first contact with the health system. Lessons may be relevant for countries with a high burden of SAM, including for targeted emergency responses.

Acute malnutrition recovery energy requirements based on mid-upper arm circumference: Secondary analysis of feeding program data from 5 countries, Combined Protocol for Acute Malnutrition Study (ComPAS) Stage 1

“…Acute malnutrition (AM) is divided into Severe Acute Malnutrition (SAM) and Moderate Acute Malnutrition (MAM), with SAM defined as a MUAC <115mm, weight-for-height zscores below -3 of the median WHO growth standards or by the presence of nutritional oedema, and MAM defined as MUAC 115 to <125mm or weight-for-height z-scores of between <-2 and �-3. Globally, at any one time, it is estimated that more than 50 million children under the age of five suffer from acute malnutrition (AM) [1], likely translating to over 100 million incident cases of SAM each year [2][3][4][5]. SAM accounts for approximately 516,000 deaths annually, MAM for 359,000 [6,7].…”

Improving estimates of the burden of severe acute malnutrition and predictions of caseload for programs treating severe acute malnutrition: experiences from Nigeria

“…Reports from SAM treatment programs suggest that the use of K = 1.6 has led to programs underestimating caseload in some West African settings. Recent work indicates that a single value of K for use globally may not be useful (see Table 1 ) [ 6 , 14 – 16 ].…”

“…Recent work indicates that a single value of K for use globally may not be useful (see Table 1 ) [ 6 , 14 – 16 ].…”

Using cross-sectional surveys to estimate the number of severely malnourished children needing to be enrolled in specific treatment programmes

“…It is plausible that J lies somewhere between these values, consistent with other studies. One study ( 16 ) found a range for the incidence conversion factor J of 4·3–9·5 and another study ( 17 ) found a pooled incidence conversion factor J of 4·82, with a wide range among the three African countries.…”