Oftentimes when we do coverage surveys, we do them for the purpose of a large scale effectiveness evaluation, right? For evaluating a health program, understanding whether it did or didn't have an impact. And this course will be useful to you, whether or not you are measuring coverage for an evaluation. But we do want to make a point of talking about how coverage should be used in effectiveness evaluations of health programs. So why do we measure coverage in evaluations? Increases in coverage of effective interventions. So interventions that have proven effectiveness against known causes of mortality and morbidity should lead to improved health outcomes, right? So if you have an effective intervention, it goes to more of the population in need, you should improve health outcomes. And so coverage is an important precursor to health outcomes. It is also more specific than impact measures like all-cause mortality or undernutrition. So often, it can be challenging to measure the specific health outcome of interest for an evaluation or a program evaluation. So let's say we're evaluating a program that we expect to impact on malaria mortality. It is very difficult to measure cause specific mortality, especially at scale. And so, often we measure all-cause mortality instead, and lots of things can affect all-cause mortality besides our program of interest. So measures of intervention coverage. For example, measures if it's a bed net program, measures of bed net ownership or bed net use, are going to help us attribute changes in mortality to the program or not, right? Depending on whether we see changes in coverage. Coverage also tends to be faster and somewhat cheaper to measure than impact. And what I mean by that is, measuring mortality and changes in mortality often requires very large sample sizes. Coverage indicators, generally, although not always, require smaller sample sizes. So they're a little bit less expensive. And then sometimes it takes a while to see population level changes in impact, especially nutritional status because that tends to be a bit of a lagged indicator. But also even mortality, it can take a while for changes in intervention coverage to translate into measurable changes in mortality. And so often you can do an immediate coverage survey and see sort of changes in coverage before you are able to do a mortality survey. And see those changes reflected in the mortality level. And finally, even though coverage is not a measure of impact, we can use coverage to model changes in impact. So again, if we know the change in the coverage level, we know the effectiveness of the intervention, we know the population in need. We can model what changes in coverage might lead to in terms of changes in health status or nutritional status. One tool that does this is the Live Saved Tool or LiST. So you could use that. There are other tools out there that could also be used. So digging further into this question of why is coverage important for programs to achieve impact and for evaluations of program impact. This slide shows the step-wise approach to program evaluation. So, kind of what needs to happen in order for a program to achieve impact. So at the very bottom you have the inputs. So basically is the program design. Is the program focused on the right interventions for the context in which it is implemented? Are the policies in place, the necessary policies in place? Are the necessary resources and inputs in place for the program to be implemented? If all of those things are there, then are the program activities being implemented? So is the program being implemented as planned, with sufficient strength, with sufficient quality to achieve the expected impact? If the program is being implemented with sufficient strength and quality, are the services being used by the population, right? You can have good quality services and nobody comes to use them. So the next question is, are services being used? If those things are true, if the program is being implemented with good quality and services are being used by the population, we would then expect to see a change in coverage in outcome level. So do the women and children who need interventions receive them? So we would expect to see a change in intervention coverage. And if we see a change in intervention coverage, we would then expect to see a population level change in impact. So intervention measures of intervention coverage help us to understand that this outcome level of the step-wise approach to evaluation. And if you are not getting population level changes in coverage, you would not expect to see an impact, a program impact. So it might not even make sense to spend a lot of money, for example, to measure mortality or to measure whatever your indicator of impact is. So now that we've talked about why coverage is important and why we want to measure it or use measures of coverage in our evaluations, we'll talk about some sources of coverage data.
