Antimicrobial resistance is a growing public health threat, killing millions of people worldwide. Sharing of antibiotic-resistant bacteria between people and animals is one obvious route for the spread. However, little is known about how the environment influences the spread of antimicrobial resistance. A model developed by mathematicians provides new insight into the dynamics between people, animals and the environment. This shows that antibiotic-resistant bacteria appear to persist in the environment long term, indicating that tiny quantities of contamination can have long-lasting effects.
Overuse and misuse. Antibiotics don’t work like they used to. Bacteria that could be combatted with standard antibiotics today just a few years ago now lead to stubborn skin and urinary infections and even death from diseases such as pneumonia, for which prescribing the “usual” antibiotics is no longer sufficient. In 2019, antimicrobial resistance killed more people than HIV or malaria.
“Very little is known about the impacts of indirect transmission through the environment on the dynamics of resistance in humans. So we investigated how incorporating the environment affects the long-term dynamics of antimicrobial resistance among people. One finding was the importance of how long an antibiotic-resistant bacterium actually survives in the environment. If they are very persistent, the reservoir of antimicrobial resistance could be very influential in human resistance rates,” explains Hannah Lepper, PhD student at the Epidemiology Research Group of the University of Edinburgh, United Kingdom.
The air, the water, the soil and everything else
Hannah Lepper is part of a project examining how local measurement data from urban sewage can inform about the abundance of genes associated with antimicrobial resistance worldwide. By analysing data from the Global Sewage Surveillance Project, the researchers are monitoring the global spread of antimicrobial resistance but also striving to answer basic questions such as what antimicrobial resistance is and what the genes and bacteria that spread it are doing in the environment.
“And how does resistance in sewage actually reflect what is happening to people? So what we wanted to do was start with a very simple model without too many assumptions to see what happens when we enter the data. My colleagues Bram van Bunnik and Mark Woolhouse had worked on a model including just people and animals. So a sensible step was to add the environment into this model to try to understand what happens when some antibiotic-resistant material is transmitted,” says Hannah Lepper.
This material can be transferred in different ways: between people, between people and animals or through the environment. To study how the environment affects human antimicrobial resistance levels, the researchers decided to build a mathematical model of antimicrobial resistance transmission with human, animal and environmental compartments. However, the environment is a huge category that requires considering the air, the water, the soil and everything else that surrounds and affects people and animals.
“But we don’t know what that actually means. So, in this model, we have to consider the environment as being quite similar to people or animals, but the environment is going to mean different things in different contexts. People living in the city have almost no interaction with animals at all, for example, and the environment to which you are exposed might differ greatly from that of someone living in a farm in the countryside. That was a big challenge,” explains Hannah Lepper.
Even though defining a unit of the environment might seem less clear than a unit of humans, the mathematician had to carry out this exercise to develop a model that made sense: a model to compare the outcomes under various transmission scenarios in which the environment is important, such as on a farm, and in an environment that was less important – such as in the city, where the contact is more limited.
“Our model shows that antimicrobial resistance levels in humans depended strongly on the rate of gain or loss of antimicrobial resistance genes from humans, and not so much from animals but also from the environment. That parameter was quite important. So how long an antibiotic-resistant bacterium actually survives in the environment turned out to be quite important,” says Hannah Lepper.
When they were building the model, the researchers thought they would find that the environment had to be very contaminated to maintain people’s quite high level of antimicrobial resistance. They therefore expected to find that very high environmental values were needed to maintain the high levels among humans, but this was not the case.
“So, we were surprised that the sharing of antimicrobial resistance between the environment and people influences the human epidemiology of antibiotic-resistant bacterial infections more than expected. And especially the persistence of the antimicrobial resistance genes in the environment was a great surprise,” explains Hannah Lepper.
We still don’t know enough
The use of antibiotics for people, animals and agriculture has undoubtedly led to the widespread rise of antimicrobial resistance: in livestock, food, hospitals and the human community at large. But the new model shows that how curtailing antibiotic consumption in animals affects human antimicrobial resistance also depends strongly on the interaction between people and the environment.
“We still don’t know enough about the environment, but we know that people pick up antibiotic-resistant material from it. And our new model clearly shows that this interaction is even more important than we might have thought. Antibiotic-resistant bacteria have many potential routes into the environment, including rivers, coastal waters and soil. The new models can be an important tool to study these complex dynamics in the emergence and spread of antimicrobial resistance,” says Hannah Lepper.
A 2016 review on antimicrobial resistance commissioned by the United Kingdom Government estimates that by 2050, as many as 10 million people could die each year as a result of the increase in antimicrobial resistance, resulting in the ability of bacteria, viruses, fungi and parasites to defeat the drugs designed to kill them.
“Nevertheless, a lack of data presents a major challenge in defining the modelling parameters of how the antimicrobial resistance spreads and thereby combatting it. The new model enables us to more easily determine what kinds of data we need to collect on the developing antimicrobial resistance in the environment and the frequency of transmission between people and the environment that are so crucial to understanding the dynamics of antimicrobial resistance,” concludes Hannah Lepper.