| Literature DB >> 28032326 |
Carla Nisii1, Roland Grunow2, Andreas Brave3, Giuseppe Ippolito1, Daniela Jacob2, Pontus Jureen3, Barbara Bartolini1, Antonino Di Caro4.
Abstract
Highly infectious diseases can spread rapidly across borders through travel or trade, and international coordination is essential to a prompt and efficient response by public health laboratories. Therefore, developing strategies to identify priorities for a rational allocation of resources for research and surveillance has been the focus of a large body of research in recent years. This paper describes the activities and the strategy used by a European-wide consortium funded by the European Commission, named EMERGE (Efficient response to highly dangerous and emerging pathogens at EU level), for the selection of high-threat pathogens with cross-border potential that will become the focus of its preparedness activities. The approach used is based on an objective scoring system, a close collaboration with other networks dealing with highly infection diseases, and a diagnostic gaps analysis. The result is a tool that is simple, objective and adaptable, which will be used periodically to re-evaluate activities and priorities, representing a step forward towards a better response to infectious disease emergencies.Entities:
Mesh:
Year: 2017 PMID: 28032326 PMCID: PMC7120423 DOI: 10.1007/5584_2016_152
Source DB: PubMed Journal: Adv Exp Med Biol ISSN: 0065-2598 Impact factor: 2.622
Individual scores attributed to viral agents with cross-border threat by the EMERGE consortium, and their weighted average
| Agent | INMI | Marburg | FHOM | PHE | INSERM | Weighted averagea |
|---|---|---|---|---|---|---|
| Italy | Germany | Sweden | UK | France | ||
| Filoviruses | ||||||
| Ebola Zaire | 9 | 8 | 8 | 10 | 8 |
|
| Ebola Sudan | 9 | 8 | 8 | 10 | 7 |
|
| Ebola Cote d’Ivoire | 9 | 3 | 8 | 10 | 7 |
|
| Ebola Bundibugyo | 9 | 8 | 8 | 10 | 7 |
|
| Marburg | 9 | 9 | 7 | 10 | 7 |
|
| Arenaviruses | ||||||
| Lassa | 8 | 10 | 7 | 10 | 8 |
|
| Junin | 8 | 10 | 8 | 13 | 7 |
|
| Machupo | 8 | 10 | 7 | 13 | 6 |
|
| Guanarito | 8 | 9 | 7 | 13 | 6 |
|
| Sabia | 8 | 7 | 4 | 13 | 6 |
|
| Lujo | 8 | 7 | 4 | 13 | 3 |
|
| Bunyaviruses | ||||||
| CCHF | 12 | 11 | 11 | 12 | 13 |
|
| Coronaviruses | ||||||
| MERS | 8 | 7 | 7 | 10 | Not scored |
|
| Orthomyxoviruses | ||||||
| HPI | 14 | 11 | 12 | 11 | 16 |
|
| Paramyxoviruses | ||||||
| Nipah | 7 | 8 | 8 | 9 | 7 |
|
| Hendra | 7 | 8 | 7 | 9 | 6 |
|
| Orthopoxviruses | ||||||
| Monkeypox | 7 | 9 | 8 | 7 | Not scored |
|
| Cowpox | 8 | 10 | 10 | 7 | Not scored |
|
CCHF crimean-congo haemorrhagic fever, MERS middle east respiratory syndrome, HPI highly pathogenic influenza
aTo calculate the weighted average, the sum of individual scores was divided by the number of respondents, as not all pathogens were scored by all laboratories
Fig. 1Example of the form sent in December 2015 to BSL-4 laboratories forming the Sterring Committee of EMERGE. It contains general information and number of ProMed posts (bottom), and was used to collect data on diagnostic tests available at each laboratory (top left), and the rationale for including each virus, based on a four-tiered scoring system. Respondents were also asked if they were aware of the existence of other networks dealing with the pathogen (top right)
Fig. 2Algorithm used by the EMERGE consortium for the selection of pathogens to include in the annual work plan, taking into account the score attributed by the Steering Committee members, the lack of other networks and the existence of diagnostic gaps