Table.
Attributes of recent (2009 onwards) mathematical model studies incorporating the impact of antiretroviral drug resistance.
| Author | Setting | Structure | Objective | Resistance-related assumptions* | Outcomes |
|---|---|---|---|---|---|
| Therapeutic cART | |||||
| Smith? et al 2010 (9) | MSM, San Francisco, US | Deterministic, multiple disease stages, specific resistant phenotypes based on ARV classes | Trace the evolutionary history of ARV resistance in San Francisco and predict future dynamics | 7 resistance categories (single, dual or triple class). Withdrawal from treatment is possible but no reversion to wild-type or loss of mutations to any ARV class. | cART has prevented 1° resistance reaching >15% in San Francisco. However patterns continue to evolve; 60% of currently circulating resistant strains can cause self-sustaining epidemics. A wave of NNRTI-resistant strains will emerge over the next 5 years. |
| Marks et al 2010 (8) | Theoretical (based on an MSM transmission model (4)) | Stochastic version based on deterministic model (4) (similar to Figure 1a) | “Thought experiment”: how chance events affect the emergence of resistance | Allows reversion from resistant to wild-type HIV infection upon cessation of cART. No explicit differentiation of 1° and 2° resistance. | Variability in 1° resistance prevalence within an epidemic is large when numbers of new infections are small (<200/y) but diminishes rapidly with higher numbers |
| Bhunu et al 2009 (6) | Theoretical | Deterministic, HIV and AIDS stages | Mathematical analysis of competing wild-type and resistant strains | A fraction of those initiating cART immediately develop resistance; the remainder are transferred from the AIDS to HIV compartment. No compartments distinguish treated from untreated individuals. | Qualitative analysis involving analytic solutions including stability analysis. Wild-type and resistant strains would co-exist, rather than being driven to extinction, whenever the reproduction numbers** >1. Resistance increases with increasing ARV use. |
| Hoare et al 2010 (7) | Southeast Asia (Thailand as example) | Deterministic, multiple disease stages, separation of those with 1° and 2° resistance | Impact of universal one-regimen cART on ARV resistance in Southeast Asian settings | Those with 1° resistance may revert to wild-type when untreated but resistance redevelops upon treatment. | Without monitoring, ∼24% new infections could include resistance mutations after 10 years. |
| Antiretroviral microbicides (ARV-VMB) or Pre-exposure prophylaxis (PrEP) | |||||
| Abbas et al 2010 (abstract) (12) | Sub-Saharan Africa, heterosexual | Age, gender, sexual activity and disease stage stratified (likely deterministic compartmental but not specified). Allows drug discontinuation. | PrEP, optimistic and pessimistic scenarios determined by parameter values | Optimistic (pessimistic): 75% (25%) PrEP effectiveness, 60% (15%) at-risk population use PrEP, 5% (25%) already infected inadvertently use PrEP | Optimistic (pessimistic): 2.5% (40%) resistance prevalence after 10 years. Inadvertent PrEP use by previously-infected people is the major determinant of resistance prevalence from PrEP. |
| Dimitrov et al 2010 (14) | Heterosexual populations, low-or middle-income settings | Deterministic, HIV and AIDS stages, gender | Population-level benefits of ARV-VMB by gender | Resistance transmission but no reversion. No explicit differentiation of 1° and 2° resistance. | Women are more likely than men to benefit from ARV-VMB use. A substantial male advantage only occurs if risk of resistance developing is high and HIV-positive women use the ARV-VMB indefinitely (because when resistance develops it reduces risk of female-to-male HIV transmission). |
| Supervie et al 2010 (11) | MSM, San Francisco, US | Deterministic, multiple disease stages, ARV use as cART as well as PrEP, separation of those with 1° and 2° resistance | Predicting public health impact of PrEP | Assumes individuals are HIV tested before being prescribed PrEP. Allows PrEP cessation and reversion to wild-type. “Fairly high” prevalence of 1° resistance when PrEP introduced. “Resistance” is the same for PrEP and cART. | “Paradox” that PrEP could increase proportion of new infections that are ARV resistant, even though absolute numbers decrease, if PrEP is effective (efficacy >30%, relative efficacy against resistant strains >0.2 but <1). If there is risk compensation, PrEP could significantly increase 1° resistance; if not, it is likely to decrease. |
*
Resistant strains were assumed to be less infectious than wild-type and unless stated, risk compensation was not considered.
**
The reproductive number is the number of secondary (onward) infections transmitted by one infected individual.
1° and 2° - primary (transmitted) and secondary (acquired) resistance, respectively.
NNRTIs – Non-nucleoside reverse transcriptase inhibitors; MSM – men who have sex with men