To meet the demands of a growing population, farmers are put under pressure to intensify farming practices. This often leads to short-term solutions focused solely on boosting food production. 

One such solution is the use of antimicrobial medicine to improve farm hygiene and ward off common diseases. Antimicrobials are used to treat common diseases like E. coli and Salmonella in cows, pigs, chickens, and other animals used for food. According to this study, 73% of antimicrobials sold worldwide are used for farmed animals. Unfortunately, as antimicrobial use has increased, their effectiveness at fighting certain diseases has decreased. In other words, some diseases have developed antimicrobial resistance (AMR). 

Our inability to effectively treat resistant diseases may have devastating consequences to both animal and human health. Furthermore, the authors of this study point out that AMR is not experienced equally throughout the world, with middle- and lower-income countries (MICs and LICs) at a higher risk. In higher-income countries, AMR surveillance and tracking has been a top priority for decades, leading to protective policies and prevention measures. In MICs and LICs, this type of surveillance is much less advanced. 

The authors of this study set out to map global AMR hotspots in MICs and LICs. They used machine learning to analyze previous research on the frequency of resistance to seven antimicrobials used to treat E. coli and Salmonella in farmed cows, pigs, and birds. They looked at tetracycline (TET), ampicillin (AMP), sulfamethoxazole-trimethoprim (SXT), chloramphenicol (CHL), ciprofloxacin (CIP), gentamicin (GEN) and cefotaxime (CTX). They were then able to create a map of AMR trends in different global regions over a twenty-year period (2000-2019). 

The authors found that AMR had significantly increased between 2000 and 2019 for all tested antimicrobials except TET. They note that there was a significant increase of resistance for certain antimicrobials among pigs and farmed birds, while cows showed no significant resistance increase for any of the seven tested antimicrobials. In terms of regions, they found that parts of China, central Asia, northern Brazil and India, and Chile were hotspots for E. Coli resistance, while northeastern China was a hotspot for Salmonella. 

The authors then mapped “priority antimicrobials” for AMR surveillance in MICs and LICs. An antimicrobial was classified as a priority if it had a high probability of reaching 50% resistance based on a number of risk factors. In most of Africa and South America (78%), they identified TET or AMP as priorities. In 77% of Asia, AMP or SXT were identified as priorities. In China, however, CHL and AMP were priorities. 

The authors are confident that their results are correct in highlighting the increase of AMR and in pinpointing areas that are especially at risk. However, with any study that uses predictive statistics, there is a level of uncertainty in the data. The authors took steps to limit this uncertainty by generating simulations and comparing the results to their findings. 

Even though MICs and LICs are more vulnerable to AMR, this problem is global and poses a major threat to human and animal health. From an advocacy perspective, reducing our reliance on farmed animals for food can protect us against drug resistance. In addition, the authors recommend educating farmers and veterinarians about AMR, creating strict regulations around antimicrobial use and monitoring farms to ensure their compliance, and focusing on other ways to improve farm hygiene (thus reducing the need for extensive antimicrobial use).