The EMPRES-i genetic module: a novel tool linking epidemiological outbreak information and genetic characteristics of influenza viruses

F Claes,F Larfaoui,B Dinh Truong,D Conversa,S Ramazzotto,A Gleizes,J Pinto,S Von Dobschuetz,A Colonna,I Xenarios,P Le Mercier,G Dauphin,E Demaio,D Kuznetsov,R Liechti

doi:10.1093/database/bau008

F Claes, F Larfaoui + Show 13 more

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https://doi.org/10.1093/database/bau008

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Abstract

Combining epidemiological information, genetic characterization and geomapping in the analysis of influenza can contribute to a better understanding and description of influenza epidemiology and ecology, including possible virus reassortment events. Furthermore, integration of information such as agroecological farming system characteristics can provide new knowledge on risk factors of influenza emergence and spread. Integrating viral characteristics into an animal disease information system is therefore expected to provide a unique tool to trace-and-track particular virus strains; generate clade distributions and spatiotemporal clusters; screen for distribution of viruses with specific molecular markers; identify potential risk factors; and analyze or map viral characteristics related to vaccines used for control and/or prevention. For this purpose, a genetic module was developed within EMPRES-i (FAO’s global animal disease information system) linking epidemiological information from influenza events with virus characteristics and enabling combined analysis. An algorithm was developed to act as the interface between EMPRES-i disease event data and publicly available influenza virus sequences in OpenfluDB. This algorithm automatically computes potential links between outbreak event and sequences, which are subsequently manually validated by experts. Subsequently, other virus characteristics such as antiviral resistance can then be associated to outbreak data. To visualize such characteristics on a geographic map, shape files with virus characteristics to overlay on other EMPRES-i map layers (e.g. animal densities) can be generated. The genetic module allows export of associated epidemiological and sequence data for further analysis. FAO has made this tool available for scientists and policy makers. Contributions are expected from users to improve and validate the number of linked influenza events and isolate information as well as the quality of information. Possibilities to interconnect with other influenza sequence databases or to expand the genetic module to other viral diseases (e.g. foot and mouth disease) are being explored.Database OpenfluDB URL: http://openflu.vital-it.chDatabase EMPRES-i URL: http://EMPRES-i.fao.org/

Highlights

Both spatial and molecular data are important to the field of infectious disease epidemiology and ecology; these types of data should be considered within a common framework
To understand how, when and where animal influenza viruses may evolve into pandemic agents, monitoring the occurrence, evolution and spread of these viruses is needed as well as a better understanding of the factors that drive these aspects
In this article we present a proof of concept for a genetic module developed at the interface between EMPRES-i and OpenFluDB, able to link influenza genetic and epidemiological data

Summary

Introduction

Both spatial and molecular data are important to the field of infectious disease epidemiology and ecology; these types of data should be considered within a common framework. Molecular tools provide new opportunities for understanding the ecology of infectious diseases, for example, by increasing our understanding of factors that determine spatial and temporal distribution of pathogens and disease [1, 2]. Influenza virus segmented genome is highly dynamic and evolves through genetic shift or drift events [3]. To understand how, when and where animal influenza viruses may evolve into pandemic agents, monitoring the occurrence, evolution and spread of these viruses is needed as well as a better understanding of the factors that drive these aspects. To be able to early detect progenitors with high potential risk to public health, there is an absolute need to monitor a combination of both epidemiological and genetic aspects of influenza events in humans, swine and birds [6,7,8,9]

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