WEEK 3 ASSIGNMENT

Step 2. Analyse reporting timeliness and completeness

Refer to tabs 1 and 2, reporting completeness and timeliness, and answer the following questions:

Are the data complete?

If not, which regions have completeness issues?

Response:

Data is not complete.

As per the reports submitted in 2014 the following regions are having completeness issues

1.Centre

2.Far North

3.North

4.North West

5.West

6.South West

 

What is the implication of that for interpretation of the data?

Response:

1.Coverage can’t be assessed.

2.Planning and target delivery of immunizations sessions get hampered

3.Vaccine management including the logistics are deranged

4.VPDs surveillance gets affected

 

Are the data sent in a timely way?

If not, which regions have timeliness issues?

Response:

Data is not being sent timely by all the regions except for occasionally in-between.

 

Is timeliness improving or getting worse over time?

Response:

Getting worse over time

 

What kind of indicators or visualization did you use to analyse completeness and timeliness?

Response:

 

1.For Analysing Completeness the indicator is defined as the number of district reports that were received, divided by the expected number of reports during the same period (such as last calendar year or last month).

2.Timeliness is defined as the fraction of expected reports that were received on time, or before a cut-off date that is set in the national or district-level reporting policy.

 

Step 3. Scan for outliers and other inconsistences

Refer to tabs 3 and 4, with monthly administered doses for Penta 1 and 3, and OPV3.

Can you find any obvious outliers (monthly values that seem too high or too low compared to the average). For which region(s)?

Response:

Yes the Obvious Outliers are;(along with month)

1.Penta1

Far North; Jun14

South;Nov14

2.Penta3

Centre; April14,14August and Jun14

North West; Dec14

South; April14,Jun14

Southwest; Jan14

3. OPV3

Far North; Nov14, Dec14

North West; Dec14

West; Dec13 and Dec14

South; Dec13 and April14

 

Can you spot any major differences in numerator data for doses that are normally given at the same time, and that should be somewhat consistent?

Can you spot any other possible mistakes?

Response:

Yes.For example OPV3 in the months of Nov13 and Dec13 are higher than Penta3 for corresponding months.For region “East” there is inconsistency for all the months.

 

What could be some other reasons for differences between different vaccines, apart from data quality issues?

Response:

1.Vaccine Stock Outs

2.Vaccine Hesitancy

What kind of indicators or visualization did you use to help you spot outliers and consistency between doses?

Time Series Analysis

Step 4. Analyse coverage trends.

Refer to tab 5, coverage.

Are the coverage estimates by region consistent, or are there obvious problems with the data?

There was a big drop in coverage last year: what caused this drop?

Response:

1.Coverage estimates for the regions of North,North West,South and South West are not consistent and point towards the deficiencies of data quality.

2.May be earlier there was overreporting of numerator and or target population was underestimated which when corrected later on led to correction.

3.Secondly there is increasing survival of infants also contributing to drop in coverage calculation as the denominator figures have changed.

Step 5. Compare your denominator to the UN Population estimate.

Refer to Tab 6

Which denominator estimate seems more plausible and why?

Response:

1.UNDP Denominator estimate seems to be more plausible as there is jump of more than 30000 from 2013 to 2014 which is unexplainable from the trends mentioned here.

2.Country figures are having data collation issues also as there is repetition of figures of 2008 and 2009.