Comparative dynamics of monovalent and bivalent vaccination for immunologically unrelated pathogens

Multivalent vaccines are designed to immunize against two or more pathogens in a single dose vaccination. A challenge for wide spread use of these vaccines is their lower protection efficacy compared to monovalent vaccines that immunize individuals against a single pathogen. We sought, for the first time, to evaluate the outcomes of bivalent and monovalent vaccines in terms of the reduction in the number of infections over time. For this evaluation, we developed epidemiological models governing the transmission dynamics of two immunologically unrelated pathogens, where immunity conferred by vaccination or natural infection of one pathogen does not provide any cross-protection against the other pathogen. We assumed that a monovalent vaccine provides full, but temporary, protection against a particular pathogen. While protecting against both pathogens requires two pathogen-specific monovalent vaccines, a single dose of the bivalent vaccine provides partial protection against both pathogens. We analyzed the two models to investigate the impact of vaccination. In addition to examining global behaviors and disease persistence of the models, we performed simulations to show the existence of a biologically feasible region for the bivalent vaccine to outperform monovalent vaccines for prevention of disease transmission using a lower number of vaccines

Antiviral resistance during pandemic influenza: implications for stockpiling and drug use

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Variability in transmissibility of the 2009 H1N1 pandemic in Canadian communities

Abstract Background The prevalence and severity of the 2009 H1N1 pandemic appeared to vary significantly across populations and geographic regions. We sought to investigate the variability in transmissibility of H1N1 pandemic in different health regions (including urban centres and remote, isolated communities) in the province of Manitoba, Canada. Methods The Richards model was used to fit to the daily number of laboratory-confirmed cases and estimate transmissibility (referred to as the basic reproduction number, R0), doubling times, and turning points of outbreaks in both spring and fall waves of the H1N1 pandemic in several health regions. Results We observed considerable variation in R0 estimates ranging from 1.55 to 2.24, with confidence intervals ranging from 1.45 to 2.88, for an average generation time of 2.9 days, and shorter doubling times in some remote and isolated communities compared to urban centres, suggesting a more rapid spread of disease in these communities during the first wave. For the second wave, R e , the effective reproduction number, is estimated to be lower for remote and isolated communities; however, outbreaks appear to have been driven by somewhat higher transmissibility in urban centres. Conclusions There was considerable geographic variation in transmissibility of the 2009 pandemic outbreaks. While highlighting the importance of estimating R0 for informing health responses, the findings indicate that projecting the transmissibility for large-scale epidemics may not faithfully characterize the early spread of disease in remote and isolated communities

Coordination and resource-related difficulties encountered by Quebec's public health specialists and infectious diseases/medical microbiologists in the management of A (H1N1) - a mixed-method, exploratory survey

<p>Abstract</p> <p>Background</p> <p>In Quebec, the influenza A (H1N1) pandemic was managed using a top-down style that left many involved players with critical views and frustrations. We aimed to describe physicians' perceptions - infectious diseases specialists/medical microbiologists (IDMM) and public health/preventive medicine specialists (PHPMS) - in regards to issues encountered with the pandemics management at the physician level and highlight suggested improvements for future healthcare emergencies.</p> <p>Methods</p> <p>In April 2010, Quebec IDMM and PHPMS physicians were invited to anonymously complete a web-based learning needs assessment. The survey included both open-ended and multiple-choice questions. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic content analysis was used to analyse qualitative data generated from the survey and help understand respondents' experience and perceptions with the pandemics.</p> <p>Results</p> <p>Of the 102 respondents, 85.3% reported difficulties or frustrations in their practice during the pandemic. The thematic analysis revealed two core themes describing the problems experienced in the pandemic management: coordination and resource-related difficulties. Coordination issues included communication, clinical practice guidelines, decision-making, roles and responsibilities, epidemiological investigation, and public health expert advisory committees. Resources issues included laboratory resources, patient management, and vaccination process.</p> <p>Conclusion</p> <p>Together, the quantitative and qualitative data suggest a need for improved coordination, a better definition of roles and responsibilities, increased use of information technologies, merged communications, and transparency in the decisional process. Increased flexibility and less contradiction in clinical practice guidelines from different sources and increased laboratory/clinical capacity were felt critical to the proper management of infectious disease emergencies.</p

How to Minimize the Attack Rate during Multiple Influenza Outbreaks in a Heterogeneous Population

<div><h3>Background</h3><p>If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail.</p> <h3>Method</h3><p>An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity.</p> <h3>Results/Conclusion</h3><p>The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger.</p> </div

Post-exposure prophylaxis during pandemic outbreaks

<p>Abstract</p> <p>Background</p> <p>With the rise of the second pandemic wave of the novel influenza A (H1N1) virus in the current season in the Northern Hemisphere, pandemic plans are being carefully re-evaluated, particularly for the strategic use of antiviral drugs. The recent emergence of oseltamivir-resistant in treated H1N1 patients has raised concerns about the prudent use of neuraminidase inhibitors for both treatment of ill individuals and post-exposure prophylaxis of close contacts.</p> <p>Methods</p> <p>We extended an established population dynamical model of pandemic influenza with treatment to include post-exposure prophylaxis of close contacts. Using parameter estimates published in the literature, we simulated the model to evaluate the combined effect of treatment and prophylaxis in minimizing morbidity and mortality of pandemic infections in the context of transmissible drug resistance.</p> <p>Results</p> <p>We demonstrated that, when transmissible resistant strains are present, post-exposure prophylaxis can promote the spread of resistance, especially when combined with aggressive treatment. For a given treatment level, there is an optimal coverage of prophylaxis that minimizes the total number of infections (final size) and this coverage decreases as a higher proportion of infected individuals are treated. We found that, when treatment is maintained at intermediate levels, limited post-exposure prophylaxis provides an optimal strategy for reducing the final size of the pandemic while minimizing the total number of deaths. We tested our results by performing a sensitivity analysis over a range of key model parameters and observed that the incidence of infection depends strongly on the transmission fitness of resistant strains.</p> <p>Conclusion</p> <p>Our findings suggest that, in the presence of transmissible drug resistance, strategies that prioritize the treatment of only ill individuals, rather than the prophylaxis of those suspected of being exposed, are most effective in reducing the morbidity and mortality of the pandemic. The impact of post-exposure prophylaxis depends critically on the treatment level and the transmissibility of resistant strains and, therefore, enhanced surveillance and clinical monitoring for resistant mutants constitutes a key component of any comprehensive plan for antiviral drug use during an influenza pandemic.</p

Modelers' Perception of Mathematical Modeling in Epidemiology: A Web-Based Survey

International audienceBackground: Mathematical modeling in epidemiology (MME) is being used increasingly. However, there are many uncertainties in terms of definitions, uses and quality features of MME. Methodology/Principal Findings: To delineate the current status of these models, a 10-item questionnaire on MME was devised. Proposed via an anonymous internet-based survey, the questionnaire was completed by 189 scientists who had published in the domain of MME. A small minority (18%) of respondents claimed to have in mind a concise definition of MME. Some techniques were identified by the researchers as characterizing MME (e.g. Markov models), while others–at the same level of sophistication in terms of mathematics–were not (e.g. Cox regression). The researchers' opinions were also contrasted about the potential applications of MME, perceived as higly relevant for providing insight into complex mechanisms and less relevant for identifying causal factors. The quality criteria were those of good science and were not related to the size and the nature of the public health problems addressed. Conclusions/Significance: This study shows that perceptions on the nature, uses and quality criteria of MME are contrasted, even among the very community of published authors in this domain. Nevertheless, MME is an emerging discipline in epidemiology and this study underlines that it is associated with specific areas of application and methods. The development of this discipline is likely to deserve a framework providing recommendations and guidance at various steps of the studies, from design to report

Age-prioritized use of antivirals during an influenza pandemic

<p>Abstract</p> <p>Background</p> <p>The WHO suggested that governments stockpile, as part of preparations for the next influenza pandemic, sufficient influenza antiviral drugs to treat approximately 25% of their populations. Our aim is two-fold: first, since in many countries the antiviral stockpile is well below this level, we search for suboptimal strategies based on treatment provided only to an age-dependent fraction of cases. Second, since in some countries the stockpile exceeds the suggested minimum level, we search for optimal strategies for post-exposure prophylactic treatment of close contacts of cases.</p> <p>Methods</p> <p>We used a stochastic, spatially structured individual-based model, considering explicit transmission in households, schools and workplaces, to simulate the spatiotemporal spread of an influenza pandemic in Italy and to evaluate the efficacy of interventions based on age-prioritized use of antivirals.</p> <p>Results</p> <p>Our results show that the antiviral stockpile required for treatment of cases ranges from 10% to 35% of the population for <it>R</it>₀in 1.4 – 3. No suboptimal strategies, based on treatment provided to an age-dependent fraction of cases, were found able to remarkably reduce both clinical attack rate and antiviral drugs needs, though they can contribute to largely reduce the excess mortality. Treatment of all cases coupled with prophylaxis provided to younger individuals is the only intervention resulting in a significant reduction of the clinical attack rate and requiring a relatively small stockpile of antivirals.</p> <p>Conclusion</p> <p>Our results strongly suggest that governments stockpile sufficient influenza antiviral drugs to treat approximately 25% of their populations, under the assumption that <it>R</it>₀is not much larger than 2. In countries where the number of antiviral stockpiled exceeds the suggested minimum level, providing prophylaxis to younger individuals is an option that could be taken into account in preparedness plans. In countries where the number of antivirals stockpiled is well below 25% of the population, priority should be decided based on age-specific case fatality rates. However, late detection of cases (administration of antivirals 48 hours after the clinical onset of symptoms) dramatically affects the efficacy of both treatment and prophylaxis.</p