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1.  The epidemiological impact of childhood influenza vaccination using live-attenuated influenza vaccine (LAIV) in Germany: predictions of a simulation study 
Background
Routine annual influenza vaccination is primarily recommended for all persons aged 60 and above and for people with underlying chronic conditions in Germany. Other countries have already adopted additional childhood influenza immunisation programmes. The objective of this study is to determine the potential epidemiological impact of implementing paediatric influenza vaccination using intranasally administered live-attenuated influenza vaccine (LAIV) in Germany.
Methods
A deterministic age-structured model is used to simulate the population-level impact of different vaccination strategies on the transmission dynamics of seasonal influenza in Germany. In our base-case analysis, we estimate the effects of adding a LAIV-based immunisation programme targeting children 2 to 17 years of age to the existing influenza vaccination policy. The data used in the model is based on published evidence complemented by expert opinion.
Results
In our model, additional vaccination of children 2 to 17 years of age with LAIV leads to the prevention of 23.9 million influenza infections and nearly 16 million symptomatic influenza cases within 10 years. This reduction in burden of disease is not restricted to children. About one third of all adult cases can indirectly be prevented by LAIV immunisation of children.
Conclusions
Our results demonstrate that vaccinating children 2–17 years of age is likely associated with a significant reduction in the burden of paediatric influenza. Furthermore, annual routine childhood vaccination against seasonal influenza is expected to decrease the incidence of influenza among adults and older people due to indirect effects of herd protection. In summary, our model provides data supporting the introduction of a paediatric influenza immunisation programme in Germany.
doi:10.1186/1471-2334-14-40
PMCID: PMC3905925  PMID: 24450996
Influenza; Vaccination; Live-attenuated influenza vaccine; Children; Transmission model; Germany
2.  Finding and removing highly connected individuals using suboptimal vaccines 
Background
Social networks are often highly skewed, meaning that the vast majority of the population has only few contacts whereas a small minority has a large number of contacts. These highly connected individuals may play an important role in case of an infectious disease outbreak.
Methods
We propose a novel strategy of finding and immunizing highly connected individuals and evaluate this strategy by computer simulations, using a stochastic, individual-and network-based simulation approach. A small random sample of the population is asked to list their acquaintances, and those who are mentioned most frequently are offered vaccination. This intervention is combined with case isolation and contact tracing.
Results
Asking only 10% of the population for 10 acquaintances each and vaccinating the most frequently named people strongly diminishes the magnitude of an outbreak which would otherwise have exhausted the available isolation units and gone out of control. It is extremely important to immunize all identified highly connected individuals. Omitting a few of them because of unsuccessful vaccination jeopardizes the overall success, unless non-immunized individuals are taken under surveillance.
Conclusions
The strategy proposed in this paper is particularly successful because it attacks the very point from which the transmission network draws its strength: the highly connected individuals. Current preparedness and containment plans for smallpox and other infectious diseases may benefit from such knowledge.
doi:10.1186/1471-2334-12-51
PMCID: PMC3316139  PMID: 22385506
3.  Small islands and pandemic influenza: Potential benefits and limitations of travel volume reduction as a border control measure 
Background
Some island nations have explicit components of their influenza pandemic plans for providing travel warnings and restricting incoming travellers. But the potential value of such restrictions has not been quantified.
Methods
We developed a probabilistic model and used parameters from a published model (i.e., InfluSim) and travel data from Pacific Island Countries and Territories (PICTs).
Results
The results indicate that of the 17 PICTs with travel data, only six would be likely to escape a major pandemic with a viral strain of relatively low contagiousness (i.e., for R0 = 1.5) even when imposing very tight travel volume reductions of 99% throughout the course of the pandemic. For a more contagious viral strain (R0 = 2.25) only five PICTs would have a probability of over 50% to escape. The total number of travellers during the pandemic must not exceed 115 (for R0 = 3.0) or 380 (for R0 = 1.5) if a PICT aims to keep the probability of pandemic arrival below 50%.
Conclusion
These results suggest that relatively few island nations could successfully rely on intensive travel volume restrictions alone to avoid the arrival of pandemic influenza (or subsequent waves). Therefore most island nations may need to plan for multiple additional interventions (e.g., screening and quarantine) to raise the probability of remaining pandemic free or achieving substantial delay in pandemic arrival.
doi:10.1186/1471-2334-9-160
PMCID: PMC2761921  PMID: 19788751
4.  Antiviral prophylaxis during pandemic influenza may increase drug resistance 
Background
Neuraminidase inhibitors (NI) and social distancing play a major role in plans to mitigate future influenza pandemics.
Methods
Using the freely available program InfluSim, the authors examine to what extent NI-treatment and prophylaxis promote the occurrence and transmission of a NI resistant strain.
Results
Under a basic reproduction number of R0 = 2.5, a NI resistant strain can only spread if its transmissibility (fitness) is at least 40% of the fitness of the drug-sensitive strain. Although NI drug resistance may emerge in treated patients in such a late state of their disease that passing on the newly developed resistant viruses is unlikely, resistant strains quickly become highly prevalent in the population if their fitness is high. Antiviral prophylaxis further increases the pressure on the drug-sensitive strain and favors the spread of resistant infections. The authors show scenarios where pre-exposure antiviral prophylaxis even increases the number of influenza cases and deaths.
Conclusion
If the fitness of a NI resistant pandemic strain is high, any use of prophylaxis may increase the number of hospitalizations and deaths in the population. The use of neuraminidase inhibitors should be restricted to the treatment of cases whereas prophylaxis should be reduced to an absolute minimum in that case.
doi:10.1186/1471-2334-9-4
PMCID: PMC2654456  PMID: 19154598
5.  Influenza pandemic intervention planning using InfluSim: pharmaceutical and non- pharmaceutical interventions 
Background
Influenza pandemic preparedness plans are currently developed and refined on national and international levels. Much attention has been given to the administration of antiviral drugs, but contact reduction can also be an effective part of mitigation strategies and has the advantage to be not limited per se. The effectiveness of these interventions depends on various factors which must be explored by sensitivity analyses, based on mathematical models.
Methods
We use the freely available planning tool InfluSim to investigate how pharmaceutical and non-pharmaceutical interventions can mitigate an influenza pandemic. In particular, we examine how intervention schedules, restricted stockpiles and contact reduction (social distancing measures and isolation of cases) determine the course of a pandemic wave and the success of interventions.
Results
A timely application of antiviral drugs combined with a quick implementation of contact reduction measures is required to substantially protract the peak of the epidemic and reduce its height. Delays in the initiation of antiviral treatment (e.g. because of parsimonious use of a limited stockpile) result in much more pessimistic outcomes and can even lead to the paradoxical effect that the stockpile is depleted earlier compared to early distribution of antiviral drugs.
Conclusion
Pharmaceutical and non-pharmaceutical measures should not be used exclusively. The protraction of the pandemic wave is essential to win time while waiting for vaccine development and production. However, it is the height of the peak of an epidemic which can easily overtax general practitioners, hospitals or even whole public health systems, causing bottlenecks in basic and emergency medical care.
doi:10.1186/1471-2334-7-76
PMCID: PMC1939851  PMID: 17629919
6.  The influenza pandemic preparedness planning tool InfluSim 
Background
Planning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality.
Results
InfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers.
Conclusion
InfluSim is an online available software which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability.
doi:10.1186/1471-2334-7-17
PMCID: PMC1832202  PMID: 17355639

Results 1-6 (6)