Antimicrobial use data collection in animal agriculture

Abstract

Antimicrobial drug use can contribute to the emergence of antimicrobial drug‐resistant organisms; therefore, judicious use of this important category of drugs is critical in both human and animal medicine to slow the development and spread of resistance. The US Food and Drug Administration (FDA) Center for Veterinary Medicine (CVM) is committed to advancing efforts to implement good antimicrobial stewardship practices in veterinary settings as part of our mission to protect human and animal health. In order to understand the drivers of resistance in veterinary settings and assess the impact of interventions designed to slow the development and spread of resistance, it is vital to have access to scientifically sound data on antimicrobial use and resistance. In 2016, FDA awarded funds in the form of cooperative agreements to support pilot projects for the collection of farm‐level antimicrobial use data in animal agriculture. These funded data collection efforts are intended to provide needed information on antimicrobial use practices in various animal production settings and to inform the development of long‐term strategies for collecting and reporting such data in a sustainable and nationally representative manner. Data were collected from records of participating dairy and feedlot cattle operations, swine companies, and broiler and turkey companies. Information from the first 2 years of the pilot projects is presented in this special issue, along with discussions related to challenges of collecting and reporting antimicrobial use data.

Comparison of different biomass methodologies to adjust sales data on veterinary antimicrobials in the USA

“…It has been recognized that antimicrobial sales data can be used to assess trends and broad shifts in the amounts of antimicrobials sold for use in animals annually. 32 In our study, between 2016 and 2018, the cattle-specific unadjusted total and medically important antimicrobial sales were the highest compared with sales of remaining major food animals; however, when the biomass adjustment was applied, the highest sales of total and medically important antimicrobials were for turkeys. As demonstrated, biomass-adjusted sales and unadjusted sales led to different types of insights into antimicrobial sales for use in the US food animal production.…”

“…for what indications, doses or durations); consequently, management of antimicrobial resistance and antimicrobial stewardship efforts cannot be informed by the sales data alone. 30 , 32 Sales data are affected by the composition of the population under study, and they do not reflect important aspects of the actual antimicrobial use, such as the availability of different drugs, with different potencies, for different diseases and species. 28 , 33 Thus, the sales data can be used for assessing the amounts of antimicrobials introduced into the marketplace each year but there are limitations in what conclusions can be drawn if the data are used to make comparisons between countries, animal species, or antimicrobial drug classes.…”

“… 28 , 33 Thus, the sales data can be used for assessing the amounts of antimicrobials introduced into the marketplace each year but there are limitations in what conclusions can be drawn if the data are used to make comparisons between countries, animal species, or antimicrobial drug classes. 32 …”

Di-anionic self-associating supramolecular amphiphiles (SSAs) as antimicrobial agents against MRSA andEscherichia coli

“…Antimicrobial resistance (AMR) is a growing threat to public health worldwide. 1 The misuse of antibiotics/antimicrobial agents within the veterinarian 2 and clinical 3 sectors has contributed to the emergence of multi-drug-resistant organisms, some of which are resistant to all antimicrobial agents currently marketed. 4 As a result, it has been predicted that by the year 2050 the number of global deaths attributed to the primary effects of AMR will be greater than those caused by cancer (2014), decreasing the worlds GDP by $100 trillion.…”

“…Fig.1Chemical structures of di-anionic SSAs (1, 3 and 4), mono-anionic SSA 5 and synthetic intermediate(2). TBA = tetrabutylammonium.…”