Work

Response to “Global trends in antimicrobial use in food-producing animals: 2020 to 2030”

Year: 2024

Type: article

Abstract: We write to draw attention to errors and concerns in the paper by Ranya Mulchandani et al., "Global trends in antimicrobial use in food-producing animals: 2020 to 2030", published earlier in 2023.We agree that in the absence of universal data collection and reporting, development of reliable and accurate models to estimate global antimicrobial usage (AMU) is necessary.Model outputs can inform policy decisions, communication materials, and mitigation measures for antimicrobial resistance at both the country and the international level.However, we believe the model developed by the authors and used to produce the results described in their paper is neither reliable nor accurate and therefore inappropriate for these purposes.We have serious concerns about the underlying assumptions on which the model is based, the paucity and suitability of input data and the conclusions drawn.We discuss each of these issues in turn, then demonstrate the inaccuracies of model estimates of antimicrobial usage at the country level.We have focussed on Australia, however are concerned that these errors may not be unique to the Australian context.We do acknowledge that data limitations were outlined by the authors in the paper, however our concern is that valid conclusions could not be made with the limited data available, and this paper could do nothing more than validate the model, rather than use it to call-out the purported 5 highest users of antimicrobials.Furthermore, we emphasise that papers like this disregard antimicrobial stewardship efforts which are independent to usage levels such as education and prescribing guidelines, and are therefore damaging to global efforts to improve antimicrobial usage monitoring and reporting in animals.Input data used for this model are sparse.Actual AMU data were available from only 42 countries, which is less than 20% of the countries and territories for which results are presented, and accounts for a greater biomass, therefore likely uses more antimicrobials than other countries.Most of these countries are in Europe, and therefore are not statistically independent due to similarities in socioeconomic factors, climate, farming systems, animal disease incidence and regulatory systems, in comparison to countries elsewhere in the world.This limits external validity, which is the essential basis for predicting usage in countries for which input data was not available.Consider that antimicrobial use in 54 African nations has been estimated using data from a single African country (Cameroon) and use throughout Latin America has been estimated using data from only a single country from that region, Chile.Data from 32 European countries contributed to these estimates.A similar problem arises for livestock species-specific estimates, which are based on data from even fewer countries, around

Source: PLOS Global Public Health

DOI: 10.1371/journal.pgph.0003133

Authors: Samantha Ellis, Jo Coombe, Stephen Page, Jay Gomboso, Rachel Iglesias, Mark Schipp