Vaccine wastage through a new lens: improving estimates through analytics

Wastage rates of vaccines are an inevitable part of immunization supply chains. With the increasing cost of vaccines and resource constraints, however, minimizing wastage has become a critical priority for immunization programs globally, perhaps at the risk of coverage. Reported or calculated wastage rates using only health service delivery data are often inaccurate and, when aggregated from different levels of the supply chain, lose their nuance and the ability to provide true insight. In a unique approach, our analysis, which utilizes a combination of service delivery and supply chain data from two districts in Mozambique to calculate wastage rates, proves both feasible and applicable. This illustrative analysis show wastage rates at the district level are comparable to global standards, yet markedly different, at times with a wide range, when disaggregated at the facility level. This analysis also shows the link between lower volumes of monthly administration and higher wastage rates. With improved data and information systems now available, immunization programs have the opportunity to calculate accurate and tailored wastage rates, using them to identify sites requiring strengthening of service provision, program implementation, or reporting quality data, and thereby improving the accuracy of forecasts and re-supply decisions for the facility level. We take this opportunity also to suggest an update to the language used for vaccine ‘wastage rate’ as it no longer reflects the nuanced realities of vaccine management and inadvertently casts a negative light on essential operational processes and can hinder the provision of immunization services.

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Publication Details

Journal
Vaccine Insights
Published
2025-10-03
DOI
https://doi.org/10.18609/vac.2025.038
Citations
1
Primary Topic
Vaccine Coverage and Hesitancy
Type
article
Field-Weighted Citation Impact
2.17
Controls
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article

Vaccine wastage through a new lens: improving estimates through analytics

Wendy Prosser, Laila Akhlaghi
1 citations
Vaccine Insights
Vaccine Coverage and Hesitancy
2.17
article

Vaccine wastage through a new lens: improving estimates through analytics

Wendy Prosser, Laila Akhlaghi
article en
1 citations

Abstract

Wastage rates of vaccines are an inevitable part of immunization supply chains. With the increasing cost of vaccines and resource constraints, however, minimizing wastage has become a critical priority for immunization programs globally, perhaps at the risk of coverage. Reported or calculated wastage rates using only health service delivery data are often inaccurate and, when aggregated from different levels of the supply chain, lose their nuance and the ability to provide true insight. In a unique approach, our analysis, which utilizes a combination of service delivery and supply chain data from two districts in Mozambique to calculate wastage rates, proves both feasible and applicable. This illustrative analysis show wastage rates at the district level are comparable to global standards, yet markedly different, at times with a wide range, when disaggregated at the facility level. This analysis also shows the link between lower volumes of monthly administration and higher wastage rates. With improved data and information systems now available, immunization programs have the opportunity to calculate accurate and tailored wastage rates, using them to identify sites requiring strengthening of service provision, program implementation, or reporting quality data, and thereby improving the accuracy of forecasts and re-supply decisions for the facility level. We take this opportunity also to suggest an update to the language used for vaccine ‘wastage rate’ as it no longer reflects the nuanced realities of vaccine management and inadvertently casts a negative light on essential operational processes and can hinder the provision of immunization services.

Vaccine InsightsVol. 4(7)
Virginia Hospital Center (US), Seattle University (US)
Openalex Percentile: Top 9%
Vaccine Coverage and Hesitancy
2.17
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