As we move forward, I will kind of remind you of where we are in the overall idea of the structure of evaluations and our fundamentals class. We talk about the six questions that need to answer that not only for your evaluation but also for the program implemented. And this course is going to be focusing on question five, which is the expected impact of the program occurring and why or why not? So the idea is impacts really the bottom line for everybody. You don't measure it in all evaluations but in terms of people's thinking about why are we doing this? It's all related to impact. That's going to if you kind of think of the left, it's going to impact, it's going to change something in terms of help the population. It's going to change the health status of a population whether that's mother's children are men or adolescents. And that change is going to be related to mortality and morbidity, nutritional status, fertility, lots of other outcomes. In this class we're going to in this particular course, we're going to try to go through and look at how you can measure and model these different impact measures quiz. Why is impact important? The idea is it's the bottom line for all health programs. Even if you have an evaluation that is or you have a program that's, let's say, focusing on increasing drug supply, some intermediate outcome. Still, the key is you're doing that because you're going to have an impact at population health. Whether it's morbidity, mortality and fertility, it's not always necessary to measure impact and evaluation. Because in fact, if you have coverage levels or other intermediate outcomes and if you know that there's a known efficacy of the intervention and delivery is straightforward routine in modern. You can usually use that as a good proxy of what the impact would be. So in this class, in this course, we're going to be talking about the kind of the major categories of impact is mortality. We're going to talk about under five maternal neonatal. There's going to be some breaks around that and pregnancy outcomes. Where you're looking at still bursts preterm birth, small for gestational age, birth, fertility, which focuses on modern contraceptive use, absolute fertility contraceptive prevalence, right? And unmet need for contraception. Nutritional status, which is primarily people think about growth in Children wasting, stunning. But also it can be BMI and pregnant women. There's lots of different nutritional status that kind of cover the whole a train and finally, morbidity, which is in some ways a strangely enough it more difficult to measure. But looking at incidents of different diseases or long lasting outcomes, health outcomes. So, what I want to do now is give you a quick example I mentioned earlier that one of the ideas is that sometimes you do studies that you had in fact don't need to measure mortality. That you could simply measure changing coverage and it would be sufficient. Here's an example. Just ask this question for you, why are immunization coverage levels often accepted as proxy for impact? The idea here is that if you look at it, we have very good data on the efficacy of vaccines. If you think about measles vaccine, it's been around for 60 years. There's lots of studies showing efficacy. It's effective in the US. It's effective in Democratic Republic of Congo. We have good information on that. We know about heard effects. We know how big of an impact it can have. Now if you can measure the coverage of measles vaccines and the Democratic Republic of Congo went from 50 of all children between the ages of 12 and 24 months to 80%. Most people would be perfectly happy to accept that as in fact, you did have an impact on under five mortality among those kills. One of the reasons that's true is because it's a simple mechanism in terms of delivery people either get a vaccine or not. It's not got a quality issue. Or if you talk about treating other diseases, pneumonia or diarrhoea, there's a quality aspect that in fact doesn't really come into play with vaccines. So that many times you can have studies where what you're going to measure as your impact is going to be a proxy. And this is often used in modeling of if you have good coverage intervention and known if efficacy of the intervention that often is used to estimate impact our project. Okay, so the idea is for most programs demonstrating impact is something the evaluators should do. The key is it's often very difficult and you're going to have to have different approaches to estimating the impact of the program. In this course, that's going to be the primary focus is saying, how can we measure, what are the different types of impact measures? How could they be measured? How can they be modeled and you as an evaluator, how you kind of assume those trade offs between spending lots of money and time and effort to measure? Perhaps not very accurately impact versus perhaps modeling impact and it's all going to depend on of course the situation you're in and what data are available. So the risk of course is really going to be focusing on that aspect of how one in an evaluation is able to estimate the impact the program has a population health