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• These children are people not constrained to families
• We will define operational areas as schools based on community-level polygons that are provided by the Eswatini team.
  • Operational areas will have two types of distributions points within them, school, or health facility (1 or 2 of each per community). The list of students/children will be the same at all of these distribution points within a community. We want users within a community to be able to see the entire register list for that community, regardless of whether the child was registered at a school site or a health facility site. Tasks and entities will not differ based on distribution point type. Tbd, see below, if we handle these distribution points as locations or as attributes of the child.
• We will manage classrooms as an attribute to the school We do not need to collect the classroom attribute; if any classroom data collected, it will be free text, not used for analysis.
• Children who are registered ad-hoc will not be linked to a location. No longer relevant since Workflow 0 not being done. Children registered ad hoc will be associated with the school operational area community they are registered in, and the distribution point of their registration (could be school or community).
• Schools will have either 1 or 2 Drug Distribution task per eligible, depending on the child's age (from the registration attributes) whether that school requires one or two rounds of dosing (will be pre-defined and based on endemicity)

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There are two main templates that will inform these workflows. The Web UI reporting and plan template contains the details of the plan and activity as well as requirements for web based dashboards. The Data collection data dictionary Data Collection Data Dictionary defines the forms and data needed for register child and drug distribution workflow.

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• We need to define what are the key values we need to build in tables in Superset
• Disaggregation would be by any other items from data dictionary mentioned like gender, classroom, precise age, dose given, drugs taken etc.

On app indicators to be defined. See Data collection data dictionary

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