A technical guidance note has been finalised recently setting out to respond to common challenges encountered when measuring the coverage of SAM and MAM treatment programmes during a SQUEAC assessment. Since 2014, the CMN's coverage experts have supported a number of CMAM programmes to measure bot MAM and SAM coverage :
- Hagadera camp in Dadaab in Kenya (SQUEAC report)
- Twic country in South Sudan (OTP report, SFP report)
- Panyijiar county in South Sudan (SQUEAC report)
- Aweil West in South Sudan (to be published)
|CHALLENGES||OTP and SFP programmes have different barriers and boosters to access||Prior coverage estimates may be different for OTP and SFP programmes||Active and adaptive case finding techniques may not work well when used to find MAM cases|
|ADAPTATIONS||Data should be collected and analysed separately for each programme. |
In the SAM and MAM programmes are fully integrated, data can be collected by the same staff on the same day. But they should still be collected separately.
If the programmes are not fully integrated then data will need to be collected by separate staff on separate days.
In both cases, the data should be analysed separately. Therefore two lists of Barriers, Boosters and Questions should be formulated.
|A single prior is unlikely to be appropriate for both programmes. |
If the two prior estimates are very different from each other, then a common weak prior can be used.
However it will usually be more efficient to use two priors.
|Use house-to-house and door-to-door sampling.
In small communities this should be an exhaustive sample of the whole community.
In larger communities an exhaustive sample of a number of segments or blocks in the community may be used
A short case study has also been finalised based on the CMN's experience of using smartphones to collect survey data during a SQUEAC in Burkina Faso in September 2015. The SQUEAC took place in the District Sanitaire of Gourcy which is supported by Helen Keller International - view the final report here. During the assessment, the data collection team used smartphones and the ONA platform to collect information from carers of SAM cases and recovering cases (239 children in total). Forms and questionnaires were designed using excel before being uploaded to the software which was previously installed on the smartphones. Depending on the data that was entered, the software automatically issued instructions to the data collectors. Geolocation data was also automatically added to the data collection form. The results of the trial were very encouraging. The process was simple to understand for both the M&E manager and the data collectors. Reports were generated as soon as data was uploaded enabling survey supervisors to quickly assess data quality and the mapping of sample points. In conclusion, the experience indicated that the use of smartphones to collect and analyse simple datasets arising from coverage surveys is feasible and should be considered in other programme M&E activities.