The German Centre for Infection Research (DZIF) contracted PPMI to carry out an external evaluation of the Global AMR R&D Hub. The Hub was established in 2018 as a key actor aiming to improve coordination and collaboration in the global antimicrobial resistance (AMR) R&D field in response to a G20 Call to Action on AMR. The main objective of the evaluation was to assess the Hub’s performance in its initial years of operation between 2018-2021.
The evaluation analysed the Hub’s activities and outputs focusing on five evaluation criteria: relevance, governance, effectiveness, efficiency and cost-effectiveness, and impact and sustainability. The evidence informing was collected and analysed using qualitative and quantitative methods, including an extensive desk research and literature review, interview and survey programmes, cost-effectiveness analysis and uptake analytics for the Hub’s Dynamic Dashboard and other communication platforms. A case study was prepared to analyse the impact of COVID-19 on the Hub’s capacity to achieve planned outcomes. Finally, the evaluation informed the development of conclusions and recommendations on potential areas where the Hub’s performance could be improved in the future.
The evaluation concluded that the Hub achieved a considerable progress towards its objectives during the first three years of operation. Despite the outbreak of a global COVID-19 pandemic, the Hub successfully established a data platform called Dynamic Dashboard that effectively provides near real-time information on the investments, pipeline, and incentives in the global AMR R&D field. The scope and volume of data presented by the Dynamic Dashboard so far has not been achieved by any other initiative in the global AMR R&D field, particularly in terms of its cross-cutting focus on all the One Health sectors, including human, animal, plant and environmental health. While its short-term visibility and impact will depend on continuous updates to the data provided by the Dynamic Dashboard, its long-term impact and sustainability could most likely be achieved through increased focus on data analyses and associated communication and collaboration efforts.