Background: As a complement to the provider potential calculations, and to assuage Foundation concerns that the calculation does not account for the need in a provider’s area of influence, all platforms will also measure, but not report on, the universe of need in a provider’s area of influence. In the future, we may assess the need being met by the provider by taking the ratio of a provider’s total yearly insertions by the need in the area. This calculation will determine the number of potential IUD users in a provider’s catchment area, given available data on population size, unmet need and IUD specific CPR.
Programmatic Utility: As demonstrated by Nepal, this calculation can be used to guide IPC workers regarding how many contacts they should make in a provider’s catchment area or area of influence in order to reach a point where demand is self-propagating. In the case of Nepal, they concluded that they would reach approximately 10% of the universe of need in each catchment area, and used this figure to calculate how many contacts an IPC agent should have weekly, as well as how many agents should be assigned to an area. The utility of this is dependent upon the size of the catchment area (described below) as well as the nature of the IPC program. The data may also be used to motivate providers regarding potential demand in their areas.
Method of Measurement: The method of measurement described below different from that proposed by R&M for the product specific universe of need calculations. The major reason for the difference is that the R&M calculation occurs at the national level, and reflects an aspiration to reach replacement fertility. The calculation presented here reflects an aspiration to be locally sensitive, and with as specific of data as possible.
Data required:
- Recent DHS or national reproductive health survey
- Recent Census or administrative data on population
- Location of provider’s facility
Calculation explanation
- Define the catchment area for the private provider
- The catchment area, or area of influence, should be defined as the lowest level administrative area containing the provider for which there is reliable population size data.
- *Determine if it is appropriate to calculate unmet need among unmarried women in your context, and if data on contraceptive use and unmet need for unmarried women is available.
- Acquire the population data for the administrative areas for all providers in the network.
- Where possible, acquire the population of women of reproductive age.
- If not available, determine the proportion of women of reproductive age at the national level, from DHS data. Multiply (population*proportion WRA) to get the number of WRA in the administrative area.
- In the example, DHS data is available only by region, not by sub-region such as zone or district. However, it is likely that population data is locally available at the district level.
- Examine the DHS for the lowest level at which statistics are reported. This may be national, regional, or urban/rural. In the example provided, it is at the region.
- Create and populate a spreadsheet with the following columns:
- Provider name/unique ID
- Provider location (district)
- Provider location (region)
- Population WRA (district)
- Proportion of WRA married (region)
- Unmet need for MWRA (region)
- CPRIUD for MWRA (region)
- * Unmet need for unmarried WRA (national)
- *CPRIUD for unmarried WRA (national)
- If the IUD specific CPR is less than 2%, consider using 2% as the target
- Calculation:
- Unmet need for IUDs among married women of reproductive age (MWRA)
- Population WRA * Proportion of WRA married * Unmet need * CPRIUD
- *Unmet need for IUDs among unmarried WRA
- Population WRA * (1-Proportion of WRA married) * Unmet need for unmarried WRA* CPRIUD for unmarried WRA
- Total unmet need in district = Unmet need for MWRA + Unmet need for unmarried WRA
Calculation Example- Assume Tigray region contains 4 districts with PSI providers
- Given the low number of sexually active unmarried women, assume it is not appropriate in this context [A]
- Population of districts is fictitious (for example purposes only)
- IUD specific CPR is set to 2%, because it is 0% as per DHS [B]
- Sources of other data is indicated in the attached tables
- In this example, the number of married women of reproductive age in District D who may have an unmet need for an IUD is 115.
Provider Name
Provider ID
Provider district
Region
Population WRA (district)
Proportion WRA married [C]
Unmet need for MWRA [D]
CPR IUD[B]
Unmet need for IUD
Abebe
125
A
Tigray
25000
58.1
22
2
63.91
Hafiza
20
B
Tigray
100000
58.1
22
2
255.64
Haile
15
C
Tigray
50000
58.1
22
2
127.82
Getachew
231
D
Tigray
45000
58.1
22
2
115.038
- Unmet need for IUDs among married women of reproductive age (MWRA)
- To the number of potential IUD users, a platform can add a target number of method switchers. Using data on the contraceptive prevalence of other methods, the same method can be followed to calculate the number of current users of injectables or OCs in a district.
- Calculation of population of married women OC users in district
- Population WRA * Proportion WRA married * CPROC = # of married women using OCs
- Calculation of population of married women OC users who could switch methods
- Target proportion of switchers is decided by platform
- # of women using OCs * target proportion of switchers = # of potential method switchers (who are married)
- Similar calculations can be done for unmarried women, and for injectable users
- Population WRA * (1-Proportion WRA married) * CPROC = # of unmarried women using OCs
- Population WRA * Proportion WRA married * CPRInj = # of married women using injectables
- Population WRA * (1-Proportion WRA married) * CPRInj = # of unmarried women using injectables
- Calculation of population of married women OC users in district
Calculation Example Tables: DHS Ethiopia
