From June 1, 2008 to May 31, 2011
Aim
Main objective of the project was to arrive at an accurate and data-based modelling of the expected course of an influenza pandemic, and of the impact of public health measures on its scale and severity. Aims of the project include the study of the social acceptability of public health measures during a pandemic, and of the behavioural changes that are to be expected in such circumstances. Final aim was the development of a knowledge-based computational environment necessary for real-time analysis and modelling in case of a pandemic.
(Expected) results
Improvement of the characterisation of population contact and travel patterns in epidemic models, on the basis of extended data collection, and model-driven extrapolations when data are lacking.
Evaluation of the social acceptance of restriction measures in case of a pandemic, and of the impact of behavioural changes on the expected epidemic course. Development of a suite of models for the spatio-temporal spread of a new influenza pandemic, that integrate the dual approaches of compartmental modelling and individual-based simulations.
Extensive evaluation of the impact of intervention options for containing and mitigating a pandemic influenza outbreak.
Development of an integrated environment for the efficient and extensible simulations of individual-based models.
Potential applications
Providing advice to the health authorities in case of a pandemic.
Development of a research team with rapid analysis capability in case of an epidemic outbreak.
Indeed, during 2009 A/H1N1 influenza pandemic, occurred during the first part of the project activities, almost all groups participating in the project were involved in supporting national and international health agencies, by providing an assessment of the situation on the basis of available data, a quantification of unexpected finding (such as the much higher susceptibility to the new infection of children than adults or elderly) and scenario analyses according to different containment or mitigation strategies being implemented. The work already carried out within FLUMODCONT project had yielded an improvement and standardisation in estimation procedures, and a development of individual-based models that could be used for performing detailed scenario analyses of interventions. Especially, the work already started had extended the collaboration among groups from different countries, and thus facilitated the exchange of findings and ideas.
The members of the FLUMODCONT project provided a backbone for the informal ECDC Modelling Network, which was set up by ECDC in the spring 2009 at the emergence of the new pandemic; the network’s meetings (several by teleconference, one physical) helped in sharing information, and in better organization of surveillance and studies. Although no real-time modelling was performed in a coordinated way at the European level, both because of the lack of previous preparation and the relative mildness of 2009 pandemic, the experience has certainly been important in improving European preparedness at the level of modelling, that could be relevant in possible future crises. The activities of FLUMDOCONT partners, in the second part of the project, concerning retrospective analyses of the spread of 2009 pandemic and model validation provide a better assessment of the potential, as well as the limitations, of real-time modelling, that will be crucial in the future.
Because of the lack of previous proper validation of models and parameter estimation, uncertainties in infection severity and fear of potential virus mutations, the main use of modelling activities has been to provide limited but useful advice concerning the potential effect of intervention measures (border closure, timing of anti-viral treatment and prophylaxis, school closures). Since, on the whole, the estimates and predictions given in the early summer 2009 proved to be remarkably correct in the end, the potential role of modelling in helping public health planning becomes higher (Van Kerkhove et al, 2010).
Beyond the potential role of modelling in advising public health policies to improve human health and more generally societal well-being, modelling can also have a direct economic impact. Indeed, just purchase agreements for vaccines carried costs on the order of hundreds of millions euros per country; European countries followed different policies in this regard, from optioning stocks sufficient to vaccinate the whole population, in view of precautionary principles, to more limited purchases in view of a vaccination policy targeted mainly groups at risk groups, to no purchase at all. Proper modelling advice concerning the potential effect of mass vaccination according to the timing of vaccine availability and of the epidemic peak can then support policy decision; for instance, it has been reported at the final workshop of the project that Italy’s decision to purchase vaccines for 40% of the population was based also on modelling scenarios (Ajelli et al, 2010) about the expected timing of epidemic peak, that proved to be largely correct.
It must be acknowledged, however, that the estimates of the severity of the infection, a crucial feature for public health planning, carried, before the summer 2009, an uncertainty of order-of-magnitudes, that possibly was not properly communicated to the general public. This opens two big challenges: on the one hand, the management and communication of uncertainties; on the other hand, the improvement of techniques for early assessment of disease severity. This second aspect has been widely discussed during the second part of the project; beyond relying on more detailed and quick outbreak investigation (following the classical epidemiological methods) and their coordination with modelling activities, some ideas have been developed about exploiting, in a model-based framework, information from the spatial spread of the first identified cases for a first assessment of severity. These ideas will be further explored in the future, beyond the end of the project.
More generally, the project involving modelling groups based in the universities and research centres, as well as modellers, statisticians and public health specialists based in health institutes, has increased the intertwining of mathematical/statistical modelling and public health questions. Modellers have become more aware of the actual problems that public health authorities have to handle, and thus of the more relevant questions that models should address, while medical doctors working in public health have gathered a better understanding of what models can and cannot provide.
Moreover, some interactions have started within the project with social and behavioural scientists, given that social interactions drive the normal transmission of infections, and that compliance with public health measures, as well as spontaneous changes in the social relations, depend on individual behaviour. The results of the two surveys run (before and after the main 2009 pandemic wave), once completely analysed, will provide a wealth of information useful for public health agencies to set up pandemic planning, including communication strategies.
A very important moment of discussing the potential and actual use of modelling during the responses to a pandemic (as well as in planning) and of disseminating the results obtained in the project has been the workshop “The role of modelling in influenza pandemic planning and response: lessons from 2009” organized by the Consortium, just at the end of the project. The workshop has seen the participation of representatives of ECDC, WHO and of several member states, and has been an opportunity to compare the responses to the pandemic in different European countries, and to assess the use of modelling in the circumstances. The comparison of these experiences, and also those of selected extra-European countries (US, Canada, Hong Kong) where an established modelling network existed, has shown the opportunities provided by modelling in advising the responses of public health, the possible interactions with other European projects (scientists from EUROMOMO and EPIWORK took part to the workshop) and the areas in which further research is needed. Most presentations given at the workshop are publicly available at the project’s web site.
The project has consolidated a network of modellers and public health scientists in EU countries; several other interactions with public health institutes of countries not participating to the project have been built, thanks also to a leading effort from ECDC in promoting ties. Out of these experiences, a team of modellers that are used to working together, to developing and sharing methods and information, can be built, in order to provide capabilities of real-time analysis and modelling to the European Community and to the Member States.
One of the outputs of the project has been a software that simulates very efficiently, using an individual based model, the spread of influenza pandemic at European scale running on single computer nodes. The code is now available to EU and member state representatives. We expect to increase in the future its documentation and ease of use, as time allows; it will be possible to make it better available to modelling groups in other member states, by having specialized workshops focussed on this.