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Other Types of Data

Watch as Svea Closser reviews the various types of surveillance data the polio eradication project collects (Step 3.9).
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SVEA CLOSSER: So as we’ve discussed, people working on polio eradication use a large variety of different types of data in making decisions. They use data from their surveillance system, they use programmatic data from their campaigns, and they use other kinds of data to understand their social mobilization efforts. But this isn’t even all. Depending on the challenge that polio eradication is are up against, they may use other types of information as well. So take a minute and think about what other kinds of information you might want to know about. For example, in a context you know well, what other sorts of information might be important if you were trying to eradicate polio?
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The answers to this question are almost as numerous as the number of contexts in the world. But we’ll share a couple examples here of different kinds of data that have been used in polio eradication. This example is from Yemen. And we touched on this earlier. But this is, again, looking at how accessible a given district is. So we have a map here of Yemen with inaccessible districts marked in red and accessible districts marked in green. The utility of this is fairly obvious if districts are inaccessible, it’s going to be difficult to reach children with door to door vaccination campaigns. And therefore, you’re going to have to come up with a different strategy to interrupt polio transmission in those areas.
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So what we just shared was a pretty basic use of data. Here’s an example of a very complex use of data. This example is from Nigeria where each vaccination team was actually tracked as they went about their door to door vaccination campaign. And what you have here is a map from Kano State in Nigeria showing some of the tracks of the vaccination teams. So this slide, which also came from polio eradication, shows that tracking vaccination teams led to a decrease in missed settlements over time. So we have a bar graph here. And it shows you that in September 2013, there were around 3,000 missed children.
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But by the next year as tracking kept going on, more and more children were covered by campaigns. But I want to ask a question of you. And there is no right answer to this question. Do you think this kind of data collection, tracking vaccinators as they go around their work, is ethical?
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Here’s another example of yet another kind of data that’s been used in polio eradication. This is a slide from Yemen, and it’s looking at refugees and migrants. There is a bar graph that shows the number of migrants to Yemen and between 2016 and 2019. There’s is a pie chart that shows what countries these arrivals were coming from. And there’s a table that shows the origin country of different numbers of migrants. So think for a minute about why this is important and useful. You would need to know where people are coming from. If you’re concerned about the spread of polio.
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So particularly if these people are coming from places where polio is being transmitted, that’s going to increase the risk people in Yemen. On the flip side, if these people contract polio in Yemen, they might bring it back to where they came from. So you’d want to be coordinating between countries to control polio in this scenario. Here’s another way that data was used in Yemen to try to think about controlling polio. And this is two different maps of the country with different visualizations of where displaced people were living. This is a little different than the previous slide, because rather than showing what country they came from, this is showing where displaced people are living.
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The caption here also mentions that many of these displaced people are living in someone else’s house, maybe with relatives. So think for a moment about what steps you might take based on this information. There’s a lot of potential answers to this question. One potential answer might be in areas with a lot of displaced people, you would do a lot of effort working with vaccination teams to make sure they asked questions about children who were visiting living in the house to make sure that everyone got covered. So overall, the polio program uses data from a huge variety of sources.
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And what’s important here is not that you remember the details of each source I just went over, but that there are many, many sources of data and polio eradication and that this is a strength in many ways. They have a huge amount of different ways of thinking about the strengths and weaknesses of their program, the reasons that children are getting covered or not covered, the reasons that polio transmission might be continuing or not continuing. There’s a lot of information for them to work with. There are also situations in which having so much data can be a bit overwhelming, that time and energy can be spent focusing on data analysis rather than programmatic improvements.
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So there’s a plus and minus to having so much data. Of course, it’s wonderful to have all this information at your fingertips. But it’s only useful if it’s useful. It’s only useful if it’s done to make more than PowerPoint slides and actually improve service provision to kids.

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

In the video, the lecturer points out that the polio program uses data from a huge variety of sources, far greater than just those discussed in the video.

Why is this huge variety of sources of data a strength? Might there be any downsides to so much data?

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

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