Part 1. Data analysis

Before you head into the meeting with the Minister, you want to make sure your data are solid. Most of the cases occurred in the capital, Grandtown, where reported coverage is high. You want to ensure that the data for Grandtown don’t contain any mistakes, so you requested this table with reported doses of MR1 for last year.

Task 1. Flag all the suspicious values. (Outliers, repetitions, etc.) (spend max 15 minutes)

•District-wise administrative coverage data for Jan and Feb looks suspicious and repetitive for all districts, except district 13

•Repetitive data seen for district 1 in the months of November and December

•Repetitive data seen for districts 14 in the months of April-May and Oct-Nov

•Monthly coverage data looks suspicious for district 3 in the months of April, May and November

•Monthly coverage data looks suspicious for district 4 in the month of May

•Monthly coverage data looks suspicious for district 13 in the month of Nov

•Annual coverage data calculated using population as denominator looks suspicious for districts 1, 3, 4, 10, 11, 12, 14 and 15 as coverage is exceeding above 100%

•Data validation not done to ensure corrections in coverage data

Task 2. Review the national and subnational coverage for MR1. Your data manager produces the following tables. What can you conclude from the administrative data?

•Reported MR1 coverage over the period 2011-2017 remains >=90%. However, this data cannot be validated as 3/8 districts have excessive outlier data

•Excessive outlier MR1 coverage data exceeding above 100% seen in Alu, Grandtown and Remo over different time periods. This indicates poor data quality

When we review the bar chart of national and sub-national coverage of MR1 doses and surviving infants, MR1 doses administered are less than the surviving infants over the period of 2011-2017

Task 3. Review coverage evaluation survey data. You remember that in 2013, there was a coverage evaluation survey. You pull up the data for that. Does this change your view about coverage at national level? For any of the regions?

At national level, the administrative coverage is close to the survey data
Significant difference observed in reported coverage and estimated through DHS 2013 coverage evaluation survey for the Grandtan, Grandtown, Remo and Alu regions.

Task 4. Review the chart with the age distribution of measles cases. Does that tell you anything additional about coverage?

•Of the total 625 confirmed measles cases in 2018 (YTD), the majority of cases (26%) have been reported from the age group of 1-4 years, followed by 22% cases reported in the age group of 30+ years.

•At the same time, there has been a decline in the percentage of confirmed measles cases reported in years 2014-2017, indicating good coverage through SIAs or immunization intensification.

Part 2. Brief the Minister

Task 5. Brief the Minister (spend max 1/2 hour on this section). Summarize the situation in three bullet points.

•Every region of vacciland, maintaining >80% of administrative coverage. But figures need to be revaluated based on coverage evaluation survey data

•Measles immunity is low in age groups of 1-4 years and above 30 years. Percentage of cases below 10 year constitutes for 49% (mostly school going) and this age group is important in terms of mortality and morbidity associated with measles.

•Emphasis on data strengthening as administrative coverage reporting found either over-reported or under-reported and sometime repetition of the same data is observed in the number of districts

•Address the data reporting issues as MR1 coverage is not syncing with surviving infant figures in some of the regions

Task 6. Brief the Minister. Propose three actions to respond to the outbreak.

•Conduct a nation-wide measles SIA activity to cover the age group with low immunity levels and the susceptible cohort focused in high-risk areas

•Ensure stakeholder engagement and high quality monitoring

•Focus on data cleaning and capture and analyze cleaned data to get real picture of vacciland, all immunization coverage.

Task 7. Formulate recommendations. List your top 3-5 recommendations specific to data strengthening you would prioritize as the EPI and surveillance teams in Vacciland

•Intensification of measles immunization activities through conduct of supplementary immunization activities

•Strengthen surveillance (laboratory capacity, outbreak investigations, and monitoring and evaluation systems) with a focus on case identification and

Regularly analyze coverage reports to identify any errors and ensure high quality data quality as part of routine immunization strengthening