What’s the point of farm-level antibiotic usage data analysis? Clarity.
Earlier this year, I was asked to review an article on antibiotic usage data analysis. The article Antimicrobial Use and Antimicrobial Resistance Indicators—Integration of Farm-Level Surveillance Data From Broiler Chickens and Turkeys in British Columbia, Canada is interesting and well written, but it resonated with me particularly for its demonstration of the dynamic use of equations to judge antibiotic usage. The researchers used the on-farm recording of antibiotic usage and infection analysis to better understand the links between antibiotic usage and resistance.
Without the availability of detailed antibiotic usage data, there can be no granular measurement or targeted analysis. There can be no proof of progress.
“The most notable AMR Ix trend was the decrease in ceftriaxone AMR Ix among Escherichia coli (0.19 to 0.07); indicative of the success of the poultry industry action to eliminate the preventive use of third generation cephalosporins. Other trends observed were the increase in ciprofloxacin AMR Ix among Campylobacter from 0.23 to 0.41 and gentamicin AMR Ix among E. coli from 0.11 to 0.22, suggestive of the persistence/emergence of resistance related to previous and current AMU not captured in our surveillance timeframe. These data highlight the necessity of multiple AMU and AMR indicators for monitoring the impact of stewardship activities and interventions. “https://www.frontiersin.org/articles/10.3389/fvets.2019.00131/full
The researchers combined the insights of several indicators and calculations in their determination of AMU and AMR indicators, noting that any single method can obscure the real wold context. The real world context is vitally important to understand and appreciate. In VirtualVet’s experience, the biggest factor in overuse of antibiotics (which we see on a regular basis) is a lack of ownership of actions on-farm. The analysis of farm-level surveillance data clarifies for the vets, farmers and farm workers their role, responsibility and contribution to the challenge of antimicrobial resistance. Clarity; clarity of the scale of the problem; clarity of the level of usage on each farm; clarity of the impacts of that usage. That’s the point of farm-level surveillance data.