Population-level mathematical modeling of antimicrobial resistance: a systematic review

Anna Maria Niewiadomska,Bryan Grenfell,David Spiro,Jessica C Seidman,Bamini Jayabalasingham,Cecile Viboud,Lander Willem

doi:10.1186/s12916-019-1314-9

Abstract

BackgroundMathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006–2016) to gauge the state of research and identify gaps warranting further work.MethodsWe performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.ResultsWe identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.ConclusionsThe AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Highlights

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, in the context of emerging pathogens; the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear
In addition to the threat posed by healthcare-acquired infections (HCAI), low-income countries need to contend with the emergence of drug resistance to long-standing pathogens, namely human immunodeficiency virus (HIV), tuberculosis (TB), and Plasmodium parasites [1]
We describe the characteristics of all studies below and focus on key findings for the five pathogens or diseases most commonly modeled: methicillin-resistant Staphylococcus aureus (MRSA), tuberculosis (TB), human immunodeficiency virus (HIV), influenza, and malaria

Summary

Introduction

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, in the context of emerging pathogens; the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. According to a World Health Organization (WHO) global report [1], healthcare-acquired infections (HCAI) with AMR pathogens such as methicillin-resistant Staphyloccus aureus are a serious problem in high- and middle-income countries where surveillance is well established. In addition to the threat posed by HCAIs, low-income countries need to contend with the emergence of drug resistance to long-standing pathogens, namely human immunodeficiency virus (HIV), tuberculosis (TB), and Plasmodium parasites (malaria) [1]. Antimicrobial use in animals for growth promotion and intensive crop farming facilitate evolution of AMR organisms, which can enter the food chain. Antimicrobial release from pharmaceutical manufacturers and non-pharmaceutical industries, combined with human and agricultural use, can lead to contamination of the soil and water [3, 4]

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