To understand the main determinants behind worldwide antibiotic resistance dynamics, scientists developed a statistical model based on a large-scale spatial-temporal analysis. Using the ATLAS antimicrobial resistance surveillance database, the model revealed significant differences in trends and associated factors depending on bacterial species and resistance to certain antibiotics. For example, countries with high quality health systems were associated with low levels of antibiotic resistance among all the gram-negative bacteria1 investigated, while high temperatures were associated with high levels of antibiotic resistance in Enterobacteriaceae. Surprisingly, national antibiotic consumption levels were not correlated with resistance for the majority of the bacteria tested. The results suggest that antibiotic resistance control measures need to be adapted to the local context and to targeted bacteria-antibiotic combinations.
