The world of genomics is transforming medicine, and is likely to influence the future development of new drugs, diagnostics, and vaccines. To date, the greater focus of genomics and medicine has been on conditions affecting resourcewealthy settings, primarily involving scientists and companies in those settings. However, we believe that it is possible to expand genomics into a more global technology that can also focus on diseases of resource-limited settings. This goal can be achieved if genomics is made a global priority. We feel one way to move in this direction is through a comprehensive approach to infectious diseases-i.e., an Infectious Disease Genomics Project-that would mirror the Human Genome Project. Without an active, unified effort specifically focused on allowing actors at any level to participate in the genomics revolution, infectious diseases that primarily affect the poor will likely not achieve the same level of scientifici advancement as diseases affecting the wealthy.

Background: Decisions on the timing and extent of vaccination against pandemic (H1N1) 2009 virus are complex.

Objective: To estimate the effectiveness and cost-effectiveness of pandemic influenza (H1N1) vaccination under different scenarios in October or November 2009.

Design: Compartmental epidemic model in conjunction with a Markov model of disease progression.

Data Sources: Literature and expert opinion.

Target Population: Residents of a major U.S. metropolitan city with a population of 8.3 million.

Time Horizon: Lifetime.

Perspective: Societal.

Interventions: Vaccination in mid-October or mid-November 2009.

Outcome Measures: Infections and deaths averted, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness.

Results of Base-Case Analysis: Assuming each primary infection causes 1.5 secondary infections, vaccinating 40% of the population in October or November would be cost-saving. Vaccination in October would avert 2051 deaths, gain 69 679 QALYs, and save $469 million compared with no vaccination; vaccination in November would avert 1468 deaths, gain 49 422 QALYs, and save $302 million.

Results of Sensitivity Analysis: Vaccination is even more cost-saving if longer incubation periods, lower rates of infectiousness, or increased implementation of nonpharmaceutical interventions delay time to the peak of the pandemic. Vaccination saves fewer lives and is less cost-effective if the epidemic peaks earlier than mid-October.

Limitations: The model assumed homogenous mixing of case-patients and contacts; heterogeneous mixing would result in faster initial spread, followed by slower spread. Additional costs and savings not included in the model would make vaccination more cost-saving.

Conclusion: Earlier vaccination against pandemic (H1N1) 2009 prevents more deaths and is more cost-saving. Complete population coverage is not necessary to reduce the viral reproductive rate sufficiently to help shorten the pandemic.

Primary Funding Source: Agency for Healthcare Research and Quality and National Institute on Drug Abuse.

Background: The pandemic potential of influenza A (H5N1) virus is a prominent public health concern of the 21st century.

Objective: To estimate the effectiveness and cost-effectiveness of alternative pandemic (H5N1) mitigation and response strategies.

Design: Compartmental epidemic model in conjunction with a Markov model of disease progression.

Data Sources: Literature and expert opinion.

Target Population: Residents of a U.S. metropolitan city with a population of 8.3 million.

Time Horizon: Lifetime.

Perspective: Societal.

Interventions: 3 scenarios: 1) vaccination and antiviral pharmacotherapy in quantities similar to those currently available in the U.S. stockpile (stockpiled strategy), 2) stockpiled strategy but with expanded distribution of antiviral agents (expanded prophylaxis strategy), and 3) stockpiled strategy but with adjuvanted vaccine (expanded vaccination strategy). All scenarios assumed standard nonpharmaceutical interventions.

Outcome Measures: Infections and deaths averted, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness.

Results of Base-Case Analysis: Expanded vaccination was the most effective and cost-effective of the 3 strategies, averting 68% of infections and deaths and gaining 404 030 QALYs at $10 844 per QALY gained relative to the stockpiled strategy.

Results of Sensitivity Analysis: Expanded vaccination remained incrementally cost-effective over a wide range of assumptions.

Limitations: The model assumed homogenous mixing of cases and contacts; heterogeneous mixing would result in faster initial spread, followed by slower spread. We did not model interventions for children or older adults; the model is not designed to target interventions to specific groups.

Conclusion: Expanded adjuvanted vaccination is an effective and cost-effective mitigation strategy for an influenza A (H5N1) pandemic. Expanded antiviral prophylaxis can help delay the pandemic while additional strategies are implemented.

Primary Funding Source: National Institutes of Health and Agency for Healthcare Research and Quality.

Background: Neuraminidase inhibitors (NAIs) are stockpiled internationally for extended use in an influenza pandemic.

Purpose: To evaluate the safety and efficacy of extended-duration (>4 weeks) NAI chemoprophylaxis against influenza.

Data Sources: Studies published in any language through 11 June 2009 identified by searching 10 electronic databases and 3 trial registries.

Study Selection: Randomized, placebo-controlled, double-blinded human trials of extended-duration NAI chemoprophylaxis that reported outcomes of laboratory-confirmed influenza or adverse events.

Data Extraction: 2 reviewers independently assessed study quality and abstracted information from eligible studies.

Data Synthesis: Of 1876 potentially relevant citations, 7 trials involving 7021 unique participants met inclusion criteria. Data were pooled by using random-effects models. NAI chemoprophylaxis decreased the frequency of symptomatic influenza (relative risk [RR], 0.26 [95% CI, 0.18 to 0.37]; risk difference [RD], –3.9 percentage points [CI, –5.8 to –1.9 percentage points]) but not asymptomatic influenza (RR, 1.03 [CI, 0.81 to 1.30]; RD, –0.4 percentage point [CI, –1.6 to 0.9 percentage point). Adverse effects were not increased overall among NAI recipients (RR, 1.01 [CI, 0.94 to 1.08]; RD, 0.1 percentage point [CI, –0.2 to 0.4 percentage point), but nausea and vomiting were more common among those who took oseltamivir (RR, 1.48 [CI, 1.86 to 2.33]; RD, 1.7 percentage points [CI, 0.6 to 2.9 percentage points]). Prevention of influenza did not statistically significantly differ between zanamivir and oseltamivir.

Limitations: All trials were industry-sponsored. No study was powered to detect rare adverse events, and none included diverse racial groups, children, immunocompromised patients, or individuals who received live attenuated influenza virus vaccine.

Conclusion: Extended-duration zanamivir and oseltamivir chemoprophylaxis appears to be highly efficacious for preventing symptomatic influenza among immunocompetent white and Japanese adults. Extended-duration oseltamivir is associated with increased nausea and vomiting. Safety and efficacy in several subpopulations that might receive extended-duration influenza chemoprophylaxis are unknown.

ABSTRACT

Control of infectious diseases is a key global health priority. This paper describes the role that simulation can play in evaluating policies for infectious disease control. We describe ongoing simulation studies in three different areas: HIV prevention and treatment, contact tracing, and hepatitis B prevention and control.