One Health drivers of antibacterial resistance: Quantifying the relative impacts of human, animal and environmental use and transmission

Abstract

Objectives: Antibacterial resistance (ABR) is a major global health security threat, with a disproportionate burden on lower-and middle-income countries (LMICs). It is not understood how 'One Health', where human health is co-dependent on animal health and the environment, might impact the burden of ABR in LMICs. Thailand's 2017 "National Strategic Plan on Antimicrobial Resistance" (NSP-AMR) aims to reduce AMR morbidity by 50% through 20% reductions in human and 30% in animal antibacterial use (ABU). There is a need to understand the implications of such a plan within a One Health perspective.

Methods: A model of ABU, gut colonisation with extended-spectrum beta-lactamase (ESBL)-producing bacteria and transmission was calibrated using estimates of the prevalence of ESBL-producing bacteria in Thailand. This model was used to project the reduction in human ABR over 20 years (2020-2040) for each One Health driver, including individual transmission rates between humans, animals and the environment, and to estimate the long-term impact of the NSP-AMR intervention.

Results: The model predicts that human ABU was the most important factor in reducing the colonisation of humans with resistant bacteria (maximum 65.7-99.7% reduction). The NSP-AMR is projected to reduce human colonisation by 6.0-18.8%, with more ambitious targets (30% reductions in human ABU) increasing this to 8.5-24.9%.

Conclusions: Our model provides a simple framework to explain the mechanisms underpinning ABR, suggesting that future interventions targeting the simultaneous reduction of transmission and ABU would help to control ABR more effectively in Thailand.

Keywords: Antibacterial resistance; Antibacterial usage; Mathematical model; One health; Thailand; Transmission.

Box 1

Two mechanisms of resistance driven by antibacterial exposure. First, antibacterial use selects resistant bacteria already present in the compartment (A), and second that antibacterial use can remove susceptible populations making transmission more likely (B). In (B), it is more likely for colonisation with resistant bacteria to occur when the native flora have been removed (via a ‘bacteriological vacuum’ - an absence of bacteria).

Fig. 1

Model schematic for human-animal-environment transmission of ABR in the One Health setting.

Fig. 2

Comparison of the model projections for animals, humans and the environment for the best 431 model fits (from 1 million samples). Error bars indicate data from which the model was calibrated (3/4 for humans, aside from 2009) and shaded areas indicate the 95% confidence interval among all fits. Model parameters and their uncertainty ranges can be found in Table 1.