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Modelling the spread of pandemic influenza and strategies for its containment and mitigation

Final Report - FLUMODCONT (Modelling the spread of pandemic influenza and strategies for its containment and mitigation)

Executive summary:

FLUMODCONT is a project aiming to support the development of coherent, evidence-based and publicly acceptable policy, planning and response procedures to mitigate the public health impacts of influenza pandemic.

In this context, mathematical models are powerful tools for simulating realistic pandemic spread scenarios and for evaluation of the potential impact of control policies. The general aim of the project was therefore, building on previous experience and projects, to provide a methodological framework, supporting data and computational tools for modelling the spread of an emerging influenza pandemic, and for advance planning and real-time refinement of containment and mitigation strategies.

The emergence of the 2009 A / H1N1 flu pandemic has made the need to be prepared for an influenza pandemic even more obvious, but has also been a challenge to researchers. Most researchers participating in the project have been involved with public health agencies in analysing the incoming data, and in providing estimates, forecasting and advice to health authorities on the basis of available evidence including model output.

The main technical achievements of the project are the following:
- the development and improvement of different techniques to estimate key epidemiological parameters from early available data from various sources;
- a quantification of the role of transmission within schools, and within classes; and thus an assessment of the potential role of school holidays or closures in shaping the infection impact, and possibly mitigating it;
- the analysis of data from past pandemics and seasonal influenza, to obtain unified estimates of generation time, of the strength of seasonal forcing, and of the reporting rate in surveillance systems;
- the development of an individual based model of pandemic influenza transmission for Europe, and of techniques to make it useful in real-time;
- a retrospective analysis of the factors determining the observed pattern of spread of the 2009 H1N1 pandemic in Europe, demonstrating its partial predictability;
- the collection of a large dataset on planned and actual behavioural responses during an influenza pandemic in the general population of four European countries.

The activities of the researchers of the project have greatly contributed to the analysis of 2009 A / H1N1 pandemic, showing the capability of an early assessment of epidemiological parameters, the potential of real-time modelling, as well as the aspects that need to be improved. The on-going retrospective analysis of the epidemiological data relative to the pandemic strain from early summer 2009 to winter 2010-11 is going to improve our understanding of the factors most influential in determining the patterns of spread of the infection, and will help in better designing surveillance, planning and responses.

The project has consolidated a network of modellers and public health scientists in European Union (EU) countries, thanks also to a leading effort from the European Centre for Disease Prevention and Control (ECDC) in promoting ties with other groups. Out of these experiences, a team of modellers can be built, in order to provide capabilities of real-time analysis and modelling to the European Community and to the Member States.

Project context and objectives:

FLUMODCONT is a project funded by the European Commission (EC)'s Seventh Framework Programme (FP7) after a specific call by EC for the 'Development of pandemic influenza containment and mitigation strategies'.

The call was issued in recognition, especially after the emergence of the highly pathogenic avian H5N1 virus, of the potentially catastrophic threat posed by novel strains of influenza A gaining transmissibility in people and causing a human pandemic.

The project was then aimed at supporting the development of coherent, evidence-based and publicly acceptable policy, planning and response procedures to mitigate the potentially devastating public health impacts of the next influenza pandemic.

In this context, mathematical models are powerful tools for simulating realistic pandemic spread scenarios and for evaluation of the potential impact of control policies. They may be useful to develop a strategy for use of pharmaceutical and non-pharmaceutical public health interventions, to set priorities and to establish criteria for deployment and use of antivirals and vaccine. They had also been used to provide advice in 'real-time' in the 2001 Foot-and-mouth disease (FMD) epidemic in the United Kingdom (UK) cattle and in the global outbreak of Severe acute respiratory syndrome (SARS).

The general aim of the project was therefore, building on previous experience and projects, to provide a methodological framework, supporting data and computational tools for modelling the spread of an emerging influenza pandemic, and for advance planning and real-time refinement of containment and mitigation strategies.

In summary, the specific objectives of the project, corresponding to its Work packages (WPs), were to:
1. improve characterisation of population contact and travel patterns in models;
2. evaluate behavioural responses to epidemics and social acceptance of restriction measures;
3. develop a suite of models for the spatio-temporal spread of a new influenza pandemic;
4. estimate model parameters and test model adequacy using data on seasonal flu and endemic diseases;
5. evaluate the impact of intervention options for containing and mitigating a pandemic influenza outbreak;
6. develop efficient, extensible and usable individual-based simulation models.

The emergence of the 2009 A / H1N1 flu pandemic has made the need to be prepared for an influenza pandemic even more obvious, but has also been a challenge to researchers. Most researchers participating in the project have been involved with public health agencies in analysing the incoming data, and in providing estimates, forecasting and advice to health authorities on the basis of available evidence including model output. This interaction of researchers with public health issues has provided a direct experience with the problems arising in the emergence, with the priorities needed and with the questions asked to modellers. It has also forced the use of techniques of real-time modelling, not quite developed and tested.

Beyond the immediate impact on public health policy, the experience has helped in focussing the research priorities on the questions that have arisen during the emergence and especially on the analysis of the data collected during and after the pandemic. Through this work, several relevant results have been obtained that however not always correspond exactly to what was planned at the project start, when nobody expected to obtain data about a new influenza pandemic.

Finally, it has to be remarked that 2009 A / H1N1 flu pandemic is forcing health authorities towards a re-assessment of pandemic planning, that was tailored in view of a very severe infection like that caused by A / H5N1. Pandemic planning is now being revised (several meetings organised by ECDC and WHO are upcoming) allowing for responses to depend on the ascertained level of the severity of the infection. In the project, we have explored these ongoing changes through a survey of policy advisors; on the basis of the outcomes, we are now working at methods for estimating severity on the basis of early available data, and on integrating these into general methods for optimising interventions.

Project results:

The project has obtained several technical advancements in the development of models for the spread of an influenza epidemic, in the analysis of relative data, and in the assessment of intervention options.

The main achievements, that are described in greater detail below following the scheme of the WPs, of the project can be summarised as follows:
- the development and improvement of different techniques to estimate generation interval and reproduction number from data from various sources (outbreak investigations, FF100s, general surveillance, sequence analysis);
- a quantification of the role of transmission within schools, and within classes; and thus an assessment of the potential role of school holidays or closures in shaping the infection impact, and possibly mitigating it;
- the collection of available data on past pandemics (1889 to 1968) and the re-estimation of parameters, using a unified approach;
- the analysis of data on seasonal influenza, that has provided some of the first estimates for the strength of seasonal forcing, and for the reporting rate in surveillance systems;
- the development of an individual based model of pandemic influenza transmission for Europe, and of techniques to make it useful in real-time;
- a retrospective analysis of the factors determining the observed pattern of spread of the 2009 H1N1 pandemic in Europe, demonstrating its partial predictability;
- the preparation, on the basis of data from POLYMOD project, from Eurostat and from their modelling, of contact matrices between age classes that provide an accepted standard for modelling through patch models;
- the comparison between different large-scale computational modelling approaches, thus providing the first step towards their integration;
- the development of a novel algorithm to approximate optimal allocation patterns for vaccines and for social distancing, on the basis only of available information up to that time;
- the collection of a large dataset on planned and actual behavioural responses during an influenza pandemic in the general population of four European countries. Thanks to running two surveys, the first one when news of the pandemic were widespread but the infection spread was extremely limited in Europe (except for UK), the second one the summer after the main pandemic wave, it has been possible to connect stated intention with actual behaviour, and to test the effect of information on this. This information can be essential for planning communication strategies, and are now being tested in the first epidemic models that include behavioural responses.

WP1: The survey carried out by the POLYMOD project has provided the first data for several European countries on the pattern of contacts amongst people of different ages. Data from that project have been obtained, and integrated with information from Eurostat and other international sources by the UK HPA partner into a unified database and repository for the use of the consortium, thus completing deliverables of the project.

WP2: Analysis of the data from the 1918 Spanish flu in different United States cities showed that public health measures affected the size and the duration of the epidemic. In order to be able to likely assess the impact of public interventions, it becomes important trying to predict the acceptance of control measures, as well as the behavioural changes that may occur in response to epidemics, in particular lethal ones. To this aim, a survey of the general public was planned in the FLUMODCONT project with questions concerning seasonal influenza, and hypothetical scenarios of a pandemic.

WP3: A major aim of the project is the development and validation of a European-wide modelling environment that could be used as a support for policy decisions. Building on micro-simulation models accounting for household, school / workplace and community transmission already developed, a European model built using detailed socio-demographic information that stress the diversity of European countries.

WP4: Key to the potential utility of models is the quality of the input parameters, and the reliability of model assumptions. The main objectives of the project were the development of statistical methods useful for the analysis of spatiotemporal data on epidemics, and their application to existing datasets, concerning especially seasonal influenza, in order to assess the adequacy of existing models to describe actual patterns in epidemic spatiotemporal spread.

WP5: This WP was designed to evaluate the impact of intervention options for containing and mitigating a pandemic influenza outbreak.

WP6
Individual-based simulation models are an important modelling tool for pandemic planning, especially when individually targeted intervention measures are considered; in future individual-based simulation models might be used - in conjunction with real-time data analysis - for prediction and to refine control policies in the face of an outbreak. Within the project a very efficient code of the European-wide model outlined above has been developed that allows for rapid simulations on a single workstation.

List of websites: www.flumodcont.eu

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