ArticleProceedings. Biological sciences2011
Optimal antiviral treatment strategies and the effects of resistance.
Article in Proceedings. Biological sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 25 citations in OpenAlex.
- Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels.PLoS computational biology · 2019Article
- Time-optimal control strategies in SIR epidemic models.Mathematical biosciences · 2017Article
- Mathematical epidemiology: Past, present, and future.Infectious Disease Modelling · 2017Review
- Integrating Antimicrobial Therapy with Host Immunity to Fight Drug-Resistant Infections: Classical vs. Adaptive Treatment.PLoS computational biology · 2016Article
- Within-host stochastic emergence dynamics of immune-escape mutants.PLoS computational biology · 2015Article
- Timing of antimicrobial use influences the evolution of antimicrobial resistance during disease epidemics.Evolution, medicine, and public health · 2014Article
- React or wait: which optimal culling strategy to control infectious diseases in wildlife.Journal of mathematical biology · 2014Article
- Effects of influenza antivirals on individual and population immunity over many epidemic waves.Epidemiology and infection · 2013Article
- Optimality of a time-dependent treatment profile during an epidemic.Journal of biological dynamics · 2013Article
- Optimizing treatment regimes to hinder antiviral resistance in influenza across time scales.PloS one · 2013Article
- The timing and targeting of treatment in influenza pandemics influences the emergence of resistance in structured populations.PLoS computational biology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent pandemic planning has highlighted the importance of understanding the effect that widespread antiviral use will have on the emergence and spread of resistance. A number of recent studies have determined that if resistance to antiviral medication can evolve, then deploying treatment at a less than maximum rate often minimizes the outbreak size. This finding, however, involves the assumption that treatment levels remain constant during the entire outbreak. Using optimal control theory, we address the question of optimal antiviral use by considering a large class of time-varying treatment strategies. We prove that, contrary to previous results, it is always optimal to treat at the maximum rate provided that this treatment occurs at the right time. In general the optimal strategy is to wait some fixed amount of time and then to deploy treatment at the maximum rate for the remainder of the outbreak. We derive analytical conditions that characterize this optimal amount of delay. Our results show that it is optimal to start treatment immediately when one of the following conditions holds: (i) immediate treatment can prevent an outbreak, (ii) the initial pool of susceptibles is small, or (iii) when the maximum possible rate of treatment is low, such that there is little de novo emergence of resistant strains. Finally, we use numerical simulations to verify that the results also hold under more general conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.