Planning of CMAM services

Estimation of incidence from prevalence is a hazardous exercise. Personally, I suggest to increase prevalence by 60% . This figure comes from the abstract below suggesting an average duration of untreated SAM of 7.5 mo. The idea is as follows:

In stable conditions, with many hypothesis met,

Incidence = prevalence /average duration of disease

In this case, disease duration in year is 7.5/12

incidence = prevalence *12/7.5 = prevalence x 1.6

I heard that some NGOs use a higher correcting factor, up to 2 or even higher. It is quite possible indeed that the Garenne et al study overestimated SAM duration as it is based on study of 6 month intervals, censoring short episodes. In any case, a major challenge is to take into account the effect of seasonal vairations of SAM. The same prevalence will be associated with different incidences if it takes place just before or just after the hungry season. Important to triangulate your estimate with other informations re. food supply / harvest and so on. Indeed with Claudine Prudhon we are currently exploring this issue.

Garenne M, Willie D, Maire B, Fontaine O, Eeckels R, Briend A, Van den Broeck J. Incidence and duration of severe wasting in two African populations. Pub Health Nutr, 2009.

OBJECTIVE: The present study aimed to compare two situations of endemic malnutrition among <5-year-old African children and to estimate the incidence, the duration and the case fatality of severe wasting episodes. DESIGN: Secondary analysis of longitudinal studies, conducted several years ago, which allowed incidence and duration to be calculated from transition rates. The first site was Niakhar in Senegal, an area under demographic surveillance, where we followed a cohort of children in 1983-5. The second site was Bwamanda in the Democratic Republic of Congo, where we followed a cohort of children in 1989-92. Both studies enrolled about 5,000 children, who were followed by routine visits and systematic anthropometric assessment, every 6 months in the first case and every 3 months in the second case. RESULTS: Niakhar had less stunting, more wasting and higher death rates than Bwamanda. Differences in cause-specific mortality included more diarrhoeal diseases, more marasmus, but less malaria and severe anaemia in Niakhar. Severe wasting had a higher incidence, a higher prevalence and a more marked age profile in Niakhar. However, despite the differences, the estimated mean durations of episodes of severe wasting, calculated by multi-state life table, were similar in the two studies (7.5 months). Noteworthy were the differences in the prevalence and incidence of severe wasting depending on the anthropometric indicator (weight-for-height Z-score <or=-3.0 or mid upper-arm circumference <110 mm) and the reference system (National Center for Health Statistics 1977, Centers for Disease Control and Prevention 2000 or Multicentre Growth Reference Study 2006). CONCLUSIONS: Severe wasting appeared as one of the leading cause of death among under-fives: it had a high incidence (about 2 % per child-semester), long duration of episodes and high case fatality rates (6 to 12 %).

Following my previous post, I received the following comment from Hedwige de Coninck (Fanta 2). With her persmission, I reproduce it below. I think these are interesting considerations and illustrate the difficulty of the issue.

I read with interest your answer to the ENN question on SAM incidence, and before exposing this discussion on ENN:

Quote:

You very clearly defined incidence based on evidence, but I think that people want to hear your opinion on calculating case load, to go one step further than incidence, thus give advice on how to calculate case load. I have learned that this is not an easy step for many.

A suggestion could be:

For estimating SAM case load for planning purposes, for a 12-month period we base the estimations on:

case load = prevalence (take prevalent cases at start of program) + incidence (add new cases expected over 12-month period, based on),

and

incidence = prevalence / duration of illness (with duration of illness estimated at 7.5 months or 7.5/12)

thus we suggest to use:

case load= prevalence + incidence, or

case load= prevalence + prevalence x 1,6.

Next step should account for e.g., expected coverage

Example of planning for treatment of SAM for the year 2010 in a population of children 10,000:

- If the estimated SAM prevalence rate from a survey done in December 2009 is 1.2 percent

On January 1, 2010, there are 120 kids with SAM

- The number of new cases that will be expected to develop during the year, or 12-month incidence = prevalence/duration of disease= prevalence x 12/7.5

Incident cases are then expected to be 1.2 x 1.6 = 1.92 or 192 kids

- Then for a 12-month program we plan to treat the prevalent cases of 120 kids and add the incident cases over 12-month period of 192 kids, and plan for treating 312 kids

-- if coverage is 100% including, e.g., multiple other caveats on seasonality vs stability, on precision of the prevalence estimate, on indicators used for prevalence vs admission or a combination of several

Usually the case load is a number higher then prevalence x3, and to account for a coverage lower than 80% we often end up using prevalence x2.

It still remains a rough estimate, but at least one learns about prevalent and incident cases and the other assumptions to take into account.

The discrepancy between the incidence and the prevalence can be attributed to the classification of the SAM cases and the MAM cases in the survey reports, as the cases are reported in the surveys as MAM based on the classification of 70-80% median (the surveys here are the tools which can speak on the prevalence), while the admission criteria for the feeding centers for the SAM is less than 75% median according to the new WHO gross chart (the admission criteria here is the tool for indicating the incidence ) , there is 5% of the cases in the prevalence considered as MAM cases (70-75%) while they are at the treatment level appearing as SAM cases which makes the figures doubled or troubled, unifying the measurements tools of the prevalence expression and the admission criteria will make the planning for the supplies requirements easier.
New classification for the SAM and MAM in the surveys according to the admission criteria is required.

Indeed, as mentioned in the previous post, it is important when estimating CMAM needs to use anthrometric surveys using the same SAM definition as used for admission for treatment. In this regard, there may be a problem when WFH is used to estimate SAM prevalence in areas where CMAM programmes use MUAC as admission criteria.

To avoid this problem, WHO now recommends to measure MUAC (along with weight and height) in anthropometric surveys in areas where a CMAM programme uses mUAC as admission criteria. And also the same WFH definition of SAM for surveys and admission criteria (WFH < -3). See: http://www.who.int/nutrition/publications/severemalnutrition/9789241598163/en/index.html