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PARAMETRA: A Transmission Modelling Database for Livestock Diseases

A transmission modelling database for livestock diseases
Authors: Antonopoulos, Alistair; Ciria, Natalia; Regan, Áine; Tubay, Jerrold; Ciaravino, Giovanna; Hayes, Brandon; Lambert, Sébastien; +8 Authors

PARAMETRA: A Transmission Modelling Database for Livestock Diseases

Abstract

Research done as part of the Horizon Europe project 'Enhanced and cost-effective biosecurity in livestock production', BIOSECURE. Abstract Dynamic modelling of infectious diseases of importance to livestock production is a valuable tool for policy and decision makers. Mathematical and simulation models play an essential role in understanding complex systems, but parameterising these models can be challenging, especially in data-sparse environments. When parameters are unable to be estimated from epidemiological or experimental data, a time-consuming and labour-intensive literature review—to identify suitable literature-informed values—is often necessary. In service of this, here we present PARAMETRA, a parameter database for 20 pathogens of livestock, envisaged as an open-source collaborative tool for the research community to aid in the development of future transmission models of livestock pathogens. Pathogens included in the database so far were selected using a disease prioritisation exercise.Parameters of interest were selected by experts with a strong background in epidemiology and mathematical modelling. We populated the database with over 2000 individual values, covering a wide range of different parameters including transmission rates, diagnostic test efficacies, pathogen survival on surfaces, and the farm and regional level prevalences of selected diseases. Finally, we present an initial illustrative analysis of the database contents and the associated metadata of studies included. One of the principal conclusions we can draw from the data available is that in many cases research is reactive, rather than proactive, with research only tending to focus on specific diseases after outbreaks have already occurred, as is the case for African swine fever for example. This has important implications for future research moving to a more proactive approach for experimental and epidemiological studies based on observations of gaps in the data, and high-risk diseases. This publication represents the first step in development for the PARAMETRA database, which will be updated and expanded in the coming years.

Countries
Belgium, Netherlands, Spain
Keywords

Livestock, Livestock disease, Databases, Factual, Mathematical modelling, Epidemiology, Parameter, DAIRY-CATTLE HERDS, MOUTH-DISEASE, Models, Biological, Communicable Diseases, Modelling, Animal Diseases, Database, FEVER, SDG 3 - Good Health and Well-being, QUANTITATIVE RISK-ASSESSMENT, Biosecurity, VIRUS, Animals, Transmission, Veterinary Sciences, HEALTH, Veterinary epidemiology, SWINE, SPREAD

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
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