31/10/20

A one health framework to estimate the cost of antimicrobial resistance

Morel CM, Alm RA, Årdal C, Bandera A, Bruno GM, Carrara E, Colombo GL, de Kraker MEA, Essack S, Frost I, Gonzalez-Zorn B, Goossens H, Guardabassi L, Harbarth S, Jørgensen PS, Kanj SS, Kostyanev T, Laxminarayan R, Leonard F, Hara GL, Mendelson M, Mikulska M, Mutters NT, Outterson K, Baňo JR, Tacconelli E, Scudeller L; GAP-ON€ network.

Antimicrob Resist Infect Control. 2020 Nov 26;9(1):187. doi: 10.1186/s13756-020-00822-6., 11/2020.

Objectives/purpose: The  costs attributable to antimicrobial resistance (AMR) remain theoretical  and largely unspecified. Current figures fail to capture the full  health and economic burden caused by AMR across human, animal, and  environmental health; historically many studies have considered only  direct costs associated with human infection from a hospital  perspective, primarily from high-income countries. The Global  Antimicrobial Resistance Platform for ONE-Burden Estimates (GAP-ON€)  network has developed a framework to help guide AMR costing exercises in  any part of the world as a first step towards more comprehensive  analyses for comparing AMR interventions at the local level as well as  more harmonized analyses for quantifying the full economic burden  attributable to AMR at the global level.


Methods: GAP-ON€  (funded under the JPIAMR 8th call (Virtual Research Institute) is  composed of 19 international networks and institutions active in the  field of AMR. For this project, the Network operated by means of Delphi  rounds, teleconferences and face-to-face meetings. The resulting costing  framework takes a bottom-up approach to incorporate all relevant costs  imposed by an AMR bacterial microbe in a patient, in an animal, or in  the environment up through to the societal level.


Results: The  framework itemizes the epidemiological data as well as the direct and  indirect cost components needed to build a realistic cost picture for  AMR. While the framework lists a large number of relevant pathogens for  which this framework could be used to explore the costs, the framework  is sufficiently generic to facilitate the costing of other resistant  pathogens, including those of other aetiologies.


Conclusion: In  order to conduct cost-effectiveness analyses to choose amongst  different AMR-related interventions at local level, the costing of AMR  should be done according to local epidemiological priorities and local  health service norms. Yet the use of a common framework across settings  allows for the results of such studies to contribute to cumulative  estimates that can serve as the basis of broader policy decisions at the  international level such as how to steer R&D funding and how to  prioritize AMR amongst other issues. Indeed, it is only by building a  realistic cost picture that we can make informed decisions on how best  to tackle major health threats.


Keywords: Antimicrobial resistance; Cost; One health.