Identifying Driver of Inequity & Target Population
In this step, you will want to identify the main driver of inequality for the analysis from the following:
- Areas of residence
- Wealth quintiles
To determine your driver of inequity, refer back to your frontiers analysis. Where differences in survival and stunting most pronounced between different wealth quintiles, different regions, or urban and rural locations?
Second, you need to identify what your ultimate objective and/or area of interest is: Is it overall child mortality and nutrition? Are you interested specifically on neonatal mortality or maternal health? Is your area of focus limited to the immunization programme? Are you only interested in malaria? The EQUIST tool is built in a flexible way to help identify priority populations using different criteria which adapt to your ultimate goal. If you are interested in overall child health and nutrition identifying the groups with high under-5 mortality rates or absolute numbers may be the best approach. However if your area of interest is the immunization programme, you may want to use coverage of immunization as the main criterion for prioritizing target populations. Using this, you will be able to identify the target population.
In addition to the analysis performed under the situation analysis, under this tab user can further analyze and assess the driver of inequity using the equi-plot visualization. The Analysis by option allows changing the indicator; the equi-plot will refresh to show the data based on selected indicator.
In the second tab, the user can select the driver of inequity in the dropdown and then select the deprived population with the help of indicator charts and map available. The following screen will appear:
Select the target population for the selected driver of inequity. You may want to select the regions with the worst health indicators. To decide this, use the map on the right and toggle with the “Analysis by” function above the map to select various indicators by sector and theme.
As you do this, the map will change to indicate the areas with the lowest and highest values for that particular indicator. If you choose “moderate & severe underweight (proportion U5 children with weight for age <-2SD), the map will show percentages accordingly.
From this, you may want to select the regions for the target population with the highest rates of child stunting. You can do this by either selecting the regions on the map directly or deselecting the region names under “select target population”.
Make sure to click save after you are complete with the target population selection.