POLYMOD
Improving Public Health Policy in Europe through the Modelling and Economic Evaluation of Interventions for the Control of Infectious Diseases
The aim of VENICE is to establish a network of public health staff involved in immunisation programs and providing them with available data and instruments to better evaluate extended immunisations. The project POLYMOD is EU-DG Research funded and is focused at improving Public Health Policy in Europe through the Modelling and Economic Evaluation of Interventions for the Control of Infectious Diseases.
The aim of POLYMOD is to strengthen public health decision making in Europe through the development, standardisation and application of mathematical, risk assessment and economic models of infectious diseases. There are a number of strands to this project.
First, it is imperative that modelling and economic analyses are useful and pertinent to public health policy-makers, especially those at European as well as national levels. POLYMOD will review the determinants of policy-making in Europe, and collate available epidemiological data. In addition it will set up structures to ensure that policy-oriented researchers and modellers interact closely to make maximal use of available data, ensure that the most pertinent public health questions are addressed and that results are disseminated in a timely and appropriate manner.
Second, mathematical models are only as good as the assumptions and parameters on which they are built. Patterns of mixing are central determinants of the transmission of many infections. However, little is known about contemporary mixing patterns. It is therefore proposed to improve the mathematical models used by elucidating relevant contemporary mixing patterns in a number of different European countries and utilising a number of data sources and techniques.
Quantitative microbial risk assessment (QMRA) models are also used to inform public-health decision-making, most often in the area of contamination of food, environmental or water sources. Although increasingly used, the predictions from these models are rarely compared to data (validated). There are other problems inherent with the usual approach; for instance, the models are based on a dose-response relationship, but the standard methods for deriving this information is either from animal studies (not necessarily application to humans), clinical volunteer studies (which usually select the least susceptible individuals and the least pathogenic strains), or analyses of outbreaks (which may be biased in the opposite direction as small outbreaks are less likely to be reported). As part of POLYMOD new methods for estimating dose-response relationships are being developed in addition to new ways to try and infer infection rates from the use of serological data. The aim of this work is to attempt to bridge the gap between QMRA and more mainstream epidemiological models and improve the validity of their findings.
Predicting the impact of control programmes against infectious diseases requires the use of sophisticated transmission dynamic models, as, due to the infectious nature of the organism, interventions often have knock-on effects beyond those who were directly targeted. It is proposed to adapt and develop such models to address a number of pressing public health issues, such as whether and when measles outbreaks are likely in those countries with declining MMR coverage, and the impact of varicella vaccination on the epidemiology of chickenpox and shingles.
Finally, results from the epidemic models will be combined with cost and outcome data and integrated within a series of economic analyses to allow an assessment of the cost-effectiveness of different control programmes in Europe.
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