The level of performance and extent of outreach workers’ activities provides an indication of a program’s ability to find and recruit SAM cases which is an important contributing factor to good coverage. The level of performance of outreach workers can be assessed through different proxy indicators. An example of this is a three category performance classification such as:

  • Poor: Zero, one, or two outreach visits in the previous 6 months

  • OK: Three or four outreach visits in the previous 6 months

  • Good: Five or more outreach visits in the previous 6 months

This example indicator uses frequency of outreach visits in a given period of time as proxy measure of performance. The assumption here is that the more frequent outreach visits are made by outreach workers, the greater the chance that all or nearly all of prevalent and incident SAM cases are found and referred to the program. Hence, this can be thought of as an indicator of temporal coverage.

It is also important to assess the geographical extent of outreach workers’ activities. An even or nearly even spatial spread of outreach visits indicates that outreach activities such as community sensitisation and mobilisation and active and adaptive case finding are happening across all or nearly all of the villages of the program area.

Data requirements

Data on outreach workers’ activities is not part of the program monitoring database. For more established programs, separate reporting and monitoring systems are in place for the community outreach and mobilisation component of the program which may involve the use of a specific database for community outreach activities and regular reporting formats for outreach workers. If available, the spatial and temporal data on outreach workers’ activities can be extracted from the database or collected from the monthly reporting formats of outreach workers.

Analysis of data

Assessment of both the temporal (how often) and geographical (where) dimensions of outreach workers’ activities can done via tabulation using lists and tables. Table 1 is an example of how the tabulation approach can be performed.

Table 1: Dates of outreach visits against a complete list of villages

From FANTA technical reference page 30

Table 1 is a good example of how the tabular approach is useful in analysing spatial data over time. The rows in Table 1 are the locations or villages (spatial data) while the columns for time in months. Empty cells are months when no outreach visit was made to a village. These represent coverage failures at particular times at particular places or locations.

Additional dimensions of analysis can be performed based on the information provided in Table 1. In Table 2 the numbers of visit to each village are tallied and used to classify levels of success achieved over the entire reporting period stratified by outreach team.

Table 2: Mean number of outreach visits and classification of levels of success by team

From FANTA technical reference page 30


From Table 1 and Table 2, it can be seen that the program has both poor spatial and temporal coverage of outreach activities. The data also indicates that of the two outreach teams, Team B is not performing its outreach activities well and would require remedial action from the managers of the program.

Analysis of outreach workers’ activities using lists and tables is complementary to mapping of outreach workers’ activities. Maps allow simple spatial analysis while tables allow more complicated analysis.

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