 Let's go ahead and register a new event. We will click on the green icon that says register event. The first thing we have to do is enter a reporting date. This is different than numerical data entry where we were selecting a period. Now we actually select the date in which the event took place. In this case, this could be when you actually performed the survey. Once we select a report date, some of the other values appear. We can see that there are not many data elements present when we select the reporting date to start. The CERA survey uses a set of rules in order to determine which sections we should enter data into. In this example, if the facility does not offer any family planning services, then there's no need to continue with the remainder of the family planning services section. If I select no, then we can see there is no change. If I select yes, however, the related variables in that family planning section appear and we can now enter data against these different data elements. We can use this type of logic to implement rules to show and hide data depending on our inputs in event programs. Let's go through and enter some data for this form. This would be based off a survey that's collected in the field. There is a mixture of yes and no questions, drop-down items and numerical fields. This is all definable within DHIS2. Let's go back to the top. On the right-hand side, we have some indicators. These indicators calculate the percentage of staff that are trained in certain areas. We can see that these are calculated on the fly. At the top, I have my denominator for these indicator values. When I go through the survey, I enter the numerator for these particular indicators. This is dependent on how I answer certain questions within the survey. If no staff have been trained in a certain area, then it will not ask us the follow-up question as to how many staff have been trained. If I enter another data value and scroll back up, we can see the indicator is calculating as I enter these data values. We can also perform data validation like we do with numerical-based data entry. Here, if I reduce the total number of staff to be less than any of the staff that are trained in this facility, some warnings will appear. We can see now, because the total number of staff are less than the number of staff that have been trained in a certain area, some warnings appear. These warnings let us know that the total number of staff in this facility should be greater than or equal to the number of staff that have been trained in a certain area. If I go ahead and change this value, the validation warnings will be removed. We can use these warnings to stop submission of program data sets. So for example, if I did have these validation warnings, I could stop the user from submitting this particular program data set until they fix this data value, either within the numerator or the denominator for these particular indicators. We can see now that event capture allows us to enter data about individual events. We can also build in rules, indicators, and validation warnings within these event programs. These allow us to show and hide inputs based on certain logical rules that are defined by that health program. In this example, if they do not offer any family planning services, then none of the other variables related to family planning services should be filled in. We can see that if I deselect yes from the question does this facility offer family planning services, a warning appears that tells us it will blank out all of the other data values that are associated with this section. Because if the facility does not offer any family planning services, then none of the other questions apply in this particular facility.