Antiviral resistance during pandemic influenza: implications for stockpiling and drug use.
BACKGROUND
The anticipated extent of antiviral use during an influenza pandemic can have adverse consequences for the development of drug resistance and rationing of limited stockpiles. The strategic use of drugs is therefore a major public health concern in planning for effective pandemic responses.


METHODS
We employed a mathematical model that includes both sensitive and resistant strains of a virus with pandemic potential, and applies antiviral drugs for treatment of clinical infections. Using estimated parameters in the published literature, the model was simulated for various sizes of stockpiles to evaluate the outcome of different antiviral strategies.


RESULTS
We demonstrated that the emergence of highly transmissible resistant strains has no significant impact on the use of available stockpiles if treatment is maintained at low levels or the reproduction number of the sensitive strain is sufficiently high. However, moderate to high treatment levels can result in a more rapid depletion of stockpiles, leading to run-out, by promoting wide-spread drug resistance. We applied an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. Our results show that if high treatment levels are enforced too early during the outbreak, a second wave of infections can potentially occur with a substantially larger magnitude. However, a timely implementation of wide-scale treatment can prevent resistance spread in the population, and minimize the final size of the pandemic.


CONCLUSIONS
Our results reveal that conservative treatment levels during the early stages of the outbreak, followed by a timely increase in the scale of drug-use, will offer an effective strategy to manage drug resistance in the population and avoid run-out. For a 1918-like strain, the findings suggest that pandemic plans should consider stockpiling antiviral drugs to cover at least 20% of the population.
Arino
Julien
J
Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada. arinoj@cc.umanitoba.ca
Bowman
Christopher S
CS
Moghadas
Seyed M
SM
D000998:Antiviral Agents / Q000600:supply & distribution / Q000627:therapeutic use*; D004189:Disaster Planning; D004196:Disease Outbreaks / Q000517:prevention & control*; D024882:Drug Resistance, Viral; D006801:Humans; D007251:Influenza, Human / Q000188:drug therapy / Q000453:epidemiology* / Q000517:prevention & control; D008954:Models, Biological; D009975:Orthomyxoviridae / Q000235:genetics
D000998:Antiviral Agents