Search PubMed⌕ Search

Biomedical subjects

Xiaohong M Davis

Publications and source records attributed to Xiaohong M Davis.

4 recordsLinked to original sources

Incidence of adamantane resistance among influenza A (H3N2) viruses isolated worldwide from 1994 to 2005: a cause for concern.

BACKGROUND: Adamantanes have been used to treat influenza A virus infections for many years. Studies have shown a low incidence of resistance to these drugs among circulating influenza viruses; however, their use is rising worldwide and drug resistance has been reported among influenza A (H5N1) viruses isolated from poultry and human beings in Asia. We sought to assess adamantane resistance among influenza A viruses isolated during the past decade from countries participating in WHO's global influenza surveillance network. METHODS: We analysed data for influenza field isolates that were obtained worldwide and submitted to the WHO Collaborating Center for Influenza at the US Centers for Disease Control and Prevention between Oct 1, 1994, and Mar 31, 2005. We used pyrosequencing, confirmatory sequence analysis, and phenotypic testing to detect drug resistance among circulating influenza A H3N2 (n=6524), H1N1 (n=589), and H1N2 (n=83) viruses. FINDINGS: More than 7000 influenza A field isolates were screened for specific aminoacid substitutions in the M2 gene known to confer drug resistance. During the decade of surveillance a significant increase in drug resistance was noted, from 0.4% in 1994-1995 to 12.3% in 2003-2004. This increase in the proportion of resistant viruses was weighted heavily by those obtained from Asia with 61% of resistant viruses isolated since 2003 being from people in Asia. INTERPRETATION: Our data raise concerns about the appropriate use of adamantanes and draw attention to the importance of tracking the emergence and spread of drug-resistant influenza A viruses.

Adamantane↗

Estimating vaccine efficacy from household data observed over time.

Estimation of vaccine efficacy has traditionally focused on the reduction in susceptibility to infection, or the vaccine efficacy for susceptibility (VE(S)). However, a vaccine, such as a prophylactic HIV vaccine, may also lower the infectiousness of a vaccinated person who became infected. The relative reduction in infectiousness due to vaccination is the vaccine efficacy for infectiousness (VE(I)). Estimation of VE(I) is challenging because it requires information on exposure to infection, and gathering this type of information is often expensive and difficult, or even impossible. Household studies are expected to provide more information on who is exposed to whom. In a previous paper, we developed a method for estimating VE(S) and VE(I) from a household study where only the final outbreak data are available. However, the resulting estimates were quite unstable. In this work, we develop a survival model for the estimation of VE(S) and VE(I) from household data where the time of infection is known for every study participant. Using stochastic simulations, we show that the proposed method significantly reduces the bias and mean square error in the estimation of both VE(S) and VE(I) as compared to the method based on final outbreak data. We also show that when time-to-event data are available, a household study produces more robust estimators than a same-size study of unrelated individuals. In addition, we investigate the bias in estimating VE(S) and VE(I) due to misclassification of infection status when only illness data, rather than true infection data, are available.

Computer Simulation↗