I defined a new validation rule for "Total number of yellow fever cases"
Left side was a sum of all yellow fever cases (OPD, IP discharge, deaths) dis-aggregated by three age groups each (Total of nine data elements). Right side was defined as a constant (1.0). "Skip for missing values" was unchecked for both sides. Operator was >=. Period type was set to monthly (Same as the data collection frequency). Other options (Sequential sample count, etc) were left blank. I run the validation rule analysis and get violations basically everywhere Organisation unit Period Importance Left side descriptionValue OperatorValueRight side descriptionDetailsce Foo OrgunitSeptember 2013MediumTotal yellow fever cases0.0>=1.0Zero ... (many more here) What I do not understand is why this rule is being tripped. For this data element, (Yellow fever) we are not recording zeros, and the values therefore should always be NULL, unless there happens to be a value entered greater than zero. Maybe again, this is a misunderstanding on my part of how the validation rule analysis handles blank values. In this case, I would expect that if "Skip for missing values" is not checked, that the NULLS would be handled effectively as zeros, so that when the multiple data elements are summed up, the left hand side is zero. It seems that is not the case, or else I am missing something. This use case is quite common for disease surveillance, whereby data elements will typically be NULL (or perhaps zero), but most likely null, since the values are almost always zero, and it does not make sense to record anything other than non-zeros here. What am I missing? Regards, Jason
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