Keeping it simple in a data-sparse environment: The case of donor breastmilk demand and supply in South Africa

Abstract

Donor breastmilk could potentially save thousands of neonatal lives and save millions of Rands in treatment costs annually. A facility location-allocation model will be used to develop a strategic national network expansion plan based on an existing breastmilk banking service model. The disaggregate demand and supply data required by this location-allocation model do not exist as-is in South Africa. This is often the case when developing OR models for developing countries. This paper thus discusses a simple methodology whereby the input data for the location-allocation model are prepared and not the location-allocation model itself. The methodology combines demographic data, health statistics and insights from literature and subject experts to determine that in 2011 almost 90 000 premature infants without access to Mother s-own-Milk would have required more than 1.7 million bottles of pasteurised donor breastmilk to protect them from fatal infections during the first 14 days of life. Simultaneously, 160 000 bottles of unpasteurised donor breastmilk could be sourced from potential donors. The disaggregate estimates show that supply and demand are geographically disparate and that at most 43% of demand could be covered with the given demand. This has implications for the model development, specifically in accounting for equitable distribution.