1. Flag all monthly values that look suspicious

There are many suspicious data in almost all Districts & I have tried to group the suspicious months as below (also see the attachment)

FINAL_20Vacciland_20case_20study_20data.xlsx

• Greatly exaggerated report data found in: District 3 (all 12 months), in District 4 (May, Dec & Nov), in District 6 (Nov.), in District 10 (Jan, Feb, Apr, May & Nov), in District 12 (Apr), in District 13 (Jan, Feb & Apr), in District 14 (in all months expet Jun, July & Dec), in District 15 (Jan, Apr, Aug, Sep & Oct)
• Over reported data found in: District 1 (Jan, Apr, Nov & Dec), in District 6 (Dec), in District 9 (Nov), in District 10 (July, Aug, Oct & Dec), in District 11 (Jan, Feb, Mar, Apr & May)
• Undr reported data found in: District 1 (Sep), in District 8 (Sep), in District 12 (Sep), in District 13 (Mar & Jun)
• Unlikely very low reported in District 13 November month

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?

• Coverage of MR1 is relatively good & consistent at national & most subnational level.
• Higher number of unvaccinated in 2015 & minimum gap in between surviving infants & unvaccinated children shown in 2016. This might be happened due to decreasing of denominator number in 2016.
• Suboptimal coverage of MR1 throughout all the 7 years in 2 subnational areas (Nemo & Westtan)
• Overachievement of MR1 coverage shown in 2 subnational areas (Grandtown & Remo), it might be due to migration of people to urban areas, or over reporting of unvaccinated children or can be due to low denominator value.

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 there is no significant MR1 coverage gap between coverage evaluation survey data & administrative data coverage in 2013.
• However, my view is changed at subnational level, because of wide difference (up to 24%) of MR1 observed between survey & administrative coverages in most subnational areas in 2013.
• Under reporting or lower denominator value shown in Nemo, Chello and Westan (Grandtan is between 5% CI)
• Over reporting or higher denominator value shown in Alu, Grandtown, and Remo

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

• More than 25% of the cases occurred in 1-4 age groups, it tells that there were more unimmunized children in previous 3 years &/or due to the effect cumulative number of unimmunized children.
• High percentage of measles cases shown in above 19-year age groups, which might be associated with either they were unimmunized or were not exposed to measles case in previous years.

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

• Coverage of MR1 is better at national level & in some subnational areas, but in some subnational areas coverage is sub-optimal.
• Data quality is not in good condition, because most subnational areas either under reported or over reported MR1
• There were high number cumulative unvaccinated people in the country & which resulted the occurrence of measles outbreak & needs supplementary vaccination.

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

• Plan and implement additional immunization sessions for catch up especially in underserved communities.
• Strengthen active and passive surveillance system
• Improve data quality through proper training and supervision/monitoring.
• Strengthen immunization system to achieve higher & equitable coverages in all sub-national areas

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.

• Vacciland should be apply critical review of immunization data at all level of the system .
• Tracing mechanism of unimmunized people & taking action at a regular manner should be Strengthen.
• Improve the capacity of service providers on data quality & use.