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Social Mobilization Data

In this section, Svea Closser shares examples of social mobilization data and how we might use it for decision making. (Step 3.8)

Svea Closser, MPH, PhD
Bloomberg School of Public Health, Johns Hopkins University, USA

In 2004 in Kano, Nigeria, for almost 3/4 of the children that were recorded as missed, the reason was categorized as “religious objections”. However, when new categories for the reasons that children weren’t vaccinated were added in 2006 and 2007, this went from 75% down to approximately 10%. This led to the realization that religion wasn’t really the risk factor. The campaign got inaccurate data because there weren’t enough categories, so religion was getting selected as sort of a “catch-all” category.

As a result of this case study, we can see that asking the right questions is incredibly important. Otherwise, the data you collect can lead you astray.

Think about this situation. Based on the information that you’ve learned so far in this lecture, and on your own experience, what could have been some additional categories that might have been added that would help identify what was really going on? What might help draw out the ideas that were falling under the “religious objection” category?

Please take a moment to share your ideas in the discussion.

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Collecting and Using Data for Disease Control and Global Health Decision-Making

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