Ethical Alternatives to Experiments with Novel Potential Pandemic Pathogens

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Temporal Stability and Geographic Variation in Cumulative Case Fatality Rates and Average Doubling Times of SARS Epidemics

We analyze temporal stability and geographic trends in cumulative case fatality rates and average doubling times of severe acute respiratory syndrome (SARS). In part, we account for correlations between case fatality rates and doubling times through differences in control measures. We discuss factors that may alter future estimates of case fatality rates. We also discuss reasons for heterogeneity in doubling times among countries and the implications for the control of SARS in different countries and parameterization of epidemic models

Severe Acute Respiratory Syndrome: Temporal Stability and Geographic Variation in Death Rates and Doubling Times

We analyzed temporal stability and geographic trends in cumulative case-fatality rates and average doubling times of severe acute respiratory syndrome (SARS). In part, we account for correlations between case-fatality rates and doubling times through differences in control measures. Factors that may alter future estimates of case-fatality rates, reasons for heterogeneity in doubling times among countries, and implications for the control of SARS are discussed

The effect of treatment on pathogen virulence.

The optimal virulence of a pathogen is determined by a trade-off between maximizing the rate of transmission and maximizing the duration of infectivity. Treatment measures such as curative therapy and case isolation exert selective pressure by reducing the duration of infectivity, reducing the value of duration-increasing strategies to the pathogen and favoring pathogen strategies that maximize the rate of transmission. We extend the trade-off models of previous authors, and represents the reproduction number of the pathogen as a function of the transmissibility, host contact rate, disease-induced mortality, recovery rate, and treatment rate, each of which may be influenced by the virulence. We find that when virulence is subject to a transmissibility-mortality trade-off, treatment can lead to an increase in optimal virulence, but that in other scenarios (such as the activity-recovery trade-off) treatment decreases the optimal virulence. Paradoxically, when levels of treatment rise with pathogen virulence, increasing control efforts may raise predicted levels of optimal virulence. Thus we show that conflict can arise between the epidemiological benefits of treatment and the evolutionary risks of heightened virulence

Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions

We present a study of the worldwide spread of a pandemic influenza and its possible containment at a global level taking into account all available information on air travel. We studied a metapopulation stochastic epidemic model on a global scale that considers airline travel flow data among urban areas. We provided a temporal and spatial evolution of the pandemic with a sensitivity analysis of different levels of infectiousness of the virus and initial outbreak conditions (both geographical and seasonal). For each spreading scenario we provided the timeline and the geographical impact of the pandemic in 3,100 urban areas, located in 220 different countries. We compared the baseline cases with different containment strategies, including travel restrictions and the therapeutic use of antiviral (AV) drugs. We show that the inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks. The large-scale therapeutic usage of AV drugs in all hit countries would be able to mitigate a pandemic effect with a reproductive rate as high as 1.9 during the first year; with AV supply use sufficient to treat approximately 2% to 6% of the population, in conjunction with efficient case detection and timely drug distribution. For highly contagious viruses (i.e., a reproductive rate as high as 2.3), even the unrealistic use of supplies corresponding to the treatment of approximately 20% of the population leaves 30%-50% of the population infected. In the case of limited AV supplies and pandemics with a reproductive rate as high as 1.9, we demonstrate that the more cooperative the strategy, the more effective are the containment results in all regions of the world, including those countries that made part of their resources available for global use.Comment: 16 page

Optimal H1N1 vaccination strategies based on self-interest versus group interest

Background\ud Influenza vaccination is vital for reducing H1N1 infection-mediated morbidity and mortality. To reduce transmission and achieve herd immunity during the initial 2009-2010 pandemic season, the US Centers for Disease Control and Prevention (CDC) recommended that initial priority for H1N1 vaccines be given to individuals under age 25, as these individuals are more likely to spread influenza than older adults. However, due to significant delay in vaccine delivery for the H1N1 influenza pandemic, a large fraction of population was exposed to the H1N1 virus and thereby obtained immunity prior to the wide availability of vaccines. This exposure affects the spread of the disease and needs to be considered when prioritizing vaccine distribution.\ud \ud Methods\ud To determine optimal H1N1 vaccine distributions based on individual self-interest versus population interest, we constructed a game theoretical age-structured model of influenza transmission and considered the impact of delayed vaccination.\ud \ud Results\ud Our results indicate that if individuals decide to vaccinate according to self-interest, the resulting optimal vaccination strategy would prioritize adults of age 25 to 49 followed by either preschool-age children before the pandemic peak or older adults (age 50-64) at the pandemic peak. In contrast, the vaccine allocation strategy that is optimal for the population as a whole would prioritize individuals of ages 5 to 64 to curb a growing pandemic regardless of the timing of the vaccination program.\ud \ud Conclusions\ud Our results indicate that for a delayed vaccine distribution, the priorities that are optimal at a population level do not align with those that are optimal according to individual self-interest. Moreover, the discordance between the optimal vaccine distributions based on individual self-interest and those based on population interest is even more pronounced when vaccine availability is delayed. To determine optimal vaccine allocation for pandemic influenza, public health agencies need to consider both the changes in infection risks among age groups and expected patterns of adherence

Potential for rabies control through dog vaccination in wildlife-abundant communities of Tanzania

Canine vaccination has been successful in controlling rabies in diverse settings worldwide. However, concerns remain that coverage levels which have previously been sufficient might be insufficient in systems where transmission occurs both between and within populations of domestic dogs and other carnivores. To evaluate the effectiveness of vaccination targeted at domestic dogs when wildlife also contributes to transmission, we applied a next-generation matrix model based on contract tracing data from the Ngorongoro and Serengeti Districts in northwest Tanzania. We calculated corresponding values of R0, and determined, for policy purposes, the probabilities that various annual vaccination targets would control the disease, taking into account the empirical uncertainty in our field data. We found that transition rate estimates and corresponding probabilities of vaccination-based control indicate that rabies transmission in this region is driven by transmission within domestic dogs. Different patterns of rabies transmission between the two districts exist, with wildlife playing a more important part in Ngorongoro and leading to higher recommended coverage levels in that district. Nonetheless, our findings indicate that an annual dog vaccination campaign achieving the WHO-recommended target of 70% will control rabies in both districts with a high level of certainty. Our results support the feasibility of controlling rabies in Tanzania through dog vaccination

The Geographic Spread of the CCR5 Δ32 HIV-Resistance Allele

The Δ32 mutation at the CCR5 locus is a well-studied example of natural selection acting in humans. The mutation is found principally in Europe and western Asia, with higher frequencies generally in the north. Homozygous carriers of the Δ32 mutation are resistant to HIV-1 infection because the mutation prevents functional expression of the CCR5 chemokine receptor normally used by HIV-1 to enter CD4+ T cells. HIV has emerged only recently, but population genetic data strongly suggest Δ32 has been under intense selection for much of its evolutionary history. To understand how selection and dispersal have interacted during the history of the Δ32 allele, we implemented a spatially explicit model of the spread of Δ32. The model includes the effects of sampling, which we show can give rise to local peaks in observed allele frequencies. In addition, we show that with modest gradients in selection intensity, the origin of the Δ32 allele may be relatively far from the current areas of highest allele frequency. The geographic distribution of the Δ32 allele is consistent with previous reports of a strong selective advantage (>10%) for Δ32 carriers and of dispersal over relatively long distances (>100 km/generation). When selection is assumed to be uniform across Europe and western Asia, we find support for a northern European origin and long-range dispersal consistent with the Viking-mediated dispersal of Δ32 proposed by G. Lucotte and G. Mercier. However, when we allow for gradients in selection intensity, we estimate the origin to be outside of northern Europe and selection intensities to be strongest in the northwest. Our results describe the evolutionary history of the Δ32 allele and establish a general methodology for studying the geographic distribution of selected alleles

Cost-Effectiveness of Rotavirus Vaccination in France-Accounting for Indirect Protection.

BACKGROUND: Vaccination against rotavirus has shown great potential for reducing the primary cause of severe childhood gastroenteritis. Previous economic evaluations of rotavirus vaccination in France have not modeled the potential impact of vaccines on disease burden via reduced transmission. OBJECTIVE: To determine the cost-effectiveness of the introduction of pentavalent rotavirus vaccination into the French infant vaccination schedule. METHODS: We developed an age-structured model of rotavirus transmission calibrated to 6 years of French gastroenteritis incidence and vaccine clinical trial data. We evaluated the cost-effectiveness of pentavalent rotavirus vaccination considering that 75% of infants would receive the three-dose vaccine course. RESULTS: Our model predicts that rotavirus vaccination will decrease rotavirus gastroenteritis incidence and associated clinical outcomes in vaccinated and unvaccinated individuals, delay the seasonal peak of infection, and increase the age of infection. From the societal perspective, our base-case scenario predicts that vaccination coverage would be cost-effective at €115 or €135 per vaccine course at €28,500 and €39,500/quality-adjusted life-year (QALY) gained, respectively, and suggests that almost 95% of the financial benefits will be recouped within the first 5 years following vaccination implementation. From the third-party payer perspective, incremental cost-effectiveness ratios ranged from €12,500 to €20,000/QALY, respectively. Our uncertainty analysis suggests that findings were sensitive to various assumptions including the number of hospitalizations, outpatient visits, and the extent of QALY losses per rotavirus episode. CONCLUSIONS: Introducing pentavalent rotavirus vaccination into the French infant vaccination schedule would significantly reduce the burden of rotavirus disease in children, and could be cost-effective under plausible conditions