ArticleFrontiers in veterinary science2020
Prediction Models in Veterinary and Human Epidemiology: Our Experience With Modeling Sars-CoV-2 Spread.
Article in Frontiers in veterinary science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic.Scientific reports · 2021Article
- Global health security must embrace a One Health approach: Contributions and experiences of veterinarians during the COVID-19 response in Australia.One health (Amsterdam, Netherlands) · 2021Article
- Brief Research Report: Veterinary Student Perspective on COVID-19 and Veterinary Medicine.Frontiers in veterinary science · 2021Article
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Authors and funding
5 authors.
Funding
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Abstract
The worldwide outbreak of Sars-CoV-2 resulted in modelers from diverse fields being called upon to help predict the spread of the disease, resulting in many new collaborations between different institutions. We here present our experience with bringing our skills as veterinary disease modelers to bear on the field of human epidemiology, building models as tools for decision makers, and bridging the gap between the medical and veterinary fields. We describe and compare the key steps taken in modeling the Sars-CoV-2 outbreak: criteria for model choices, model structure, contact structure between individuals, transmission parameters, data availability, model validation, and disease management. Finally, we address how to improve on the contingency infrastructure available for Sars-CoV-2.
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