Mathematical modelling to understand the long term evolution of HIV drug resistance
Antimicrobial resistance (AMR) is the ability of any microbe to evade the control of treatments such as antivirals and antibiotics. AMR remains one of the greatest challenges to human and animal health globally, with many common gastrointestinal diseases from K. pneumoniae, urinary tract infections from E. coli, tuberculosis, gonorrhoea, and HIV being resistant against first-line treatment, with some infections having developed resistance against second- and third-line treatment.
Amongst these warnings, there is considerable variation in the observed frequency of resistance across microbes. For example, penicillin-resistant gonorrhoea reached 100% prevalence quickly after the 1940s in Europe, while in the same regions, penicillin-resistant pneumococcal pneumonia has been maintained at low levels, often less than 15%. These differences likely arise through a complex interplay between the epidemiology, the pathogen biology and its genetic constraints. Moreover, for many pathogens, it is unclear whether an observed intermediate resistance frequency is part of a temporal trend toward all isolates being resistant, or whether resistance has stabilised at this intermediate frequency.
Determining the long-term stable resistance frequency – that is, the probability that an infection is resistant to at least one drug – predicts the worst-case public health scenario. It is clear from our empirical data that while each pathogen-drug combination is different, many pathogens do evolve an intermediate frequency of resistance for a given treatment rate, contrary to the intuition of the ‘doomsday’ scenario in which all currently treatable infections will eventually be resistant.
Explaining this phenomenon of stable ‘coexistence’ between resistant and sensitive strains has been a long-standing problem. For commensal bacteria at least, we are now beginning to understand the mechanisms underlying pathogen evolution that give rise to the empirical relationship observed between increasing antibiotic use and increasing stable frequencies of resistance.
However, due to the recency of these developments, there has been no concerted effort both to determine the long-term stable equilibrium resistance frequency and to explain the underlying mechanisms for the many other types of pathogens for which drug resistance is a growing public health threat, such as HIV. Without a mechanistic understanding of whether resistance stabilises at intermediate frequencies, we will not be able to predict whether we are likely to enter an era of untreatable HIV infections. Furthermore, our experience with bacterial resistance teaches us that it is also impossible to confidently predict the impact of control strategies.
- PhD position
- University of Edinburgh
- Closing date
- January 7th, 2021
- Posted on
- November 12th, 2020 18:05
- Last updated
- November 12th, 2020 18:05