Data on SARS-CoV-2 events in animals: mind the gap!
Creators: name: Nerpel, Afra
name: Käsbohrer, Annemarie
name: Desvars-Larrive, Amélie
name: Walzer, Chris
Publisher: name: figshare
Year: 2023
Subjects: classificationCode: 300905
subject: Veterinary epidemiology
classificationCode: 460504
subject: Data quality
classificationCode: 420202
subject: Disease surveillance
classificationCode: 420699
subject: Public health not elsewhere classified

description: This repository provides the data and R code to reproduce the results and figures of the paper <b><i>"Data on SARS-CoV-2 events in animals: mind the gap!"</i></b>, by: Afra Nerpel, Annemarie Käsbohrer, Chris Walzer, and Amélie Desvars-Larrive.<br><b>Summary of the Study</b>Current research on SARS-CoV-2 has largely focused on the pandemic's impact on humans, with insufficient attention paid to monitoring, sharing, and communicating information about viral circulation and evolution in animal hosts. The objective of this study was to estimate and characterise the data gap between the number of SARS-CoV-2 cases and related deaths in animals officially notified to the World Organisation for Animal Health (WOAH) via its World Animal Health Information System (WAHIS) and known cases reported through two other data sources: ProMED-mail and scientific papers.We used the previously published dataset SARS-ANI to retrieve SARS-CoV-2 events in animals published through WAHIS and ProMED-mail. Additionally, we generated SARS-ANI SciLit v1.0, a novel structured dataset of SARS-CoV-2 events in animals published through scientific literature retrieved from PubMed.We evidenced that at least 52.8% of the SARS-CoV-2 animal cases and 65.8% of the deaths were not reported to WAHIS during 29/02/2020-16/08/2022. Combining information from three different data sources, we compiled a new comprehensive list of 35 animal species reported as susceptible to SARS-CoV-2 under natural conditions, representing a significant advance from the figures reported by the WOAH and the Food and Agriculture Organization of the United Nations. Furthermore, we identified animal species that were underreported to the WAHIS and found that dogs and cats garnered the most attention in research studies. We also showed that, compared to the official WAHIS reports, scientific papers generally experienced longer publication lags and demonstrated that national strategies regarding reporting/publishing of SARS-CoV-2 events in animals greatly differed among countries.This analysis provides valuable insights into the patterns of reporting animal infections with SARS-CoV-2. The study emphasises the need for improvements in data sharing regarding SARS-CoV-2 events in animals, as this is crucial for effective One Health surveillance, prevention, and control of emerging diseases of zoonotic origin.<br><b>This repository contains:</b><b>Nerpel-et-al_Script_v2.R:</b> R script to check the data quality of the dataset SARS-ANI SciLit and reproduce the results and figures of the paper <i>"Data on SARS-CoV-2 events in animals: mind the gap!".</i><b>sars_ani_data.csv: </b>version of the SARS-ANI Dataset used in this study (GitHub commit 6d03527). Methods to build this dataset are published here: https://doi.org/10.1038/s41597-022-01543-8. Data and metadata are available here: https://github.com/amel-github/sars-ani.<b>sars_ani_SciLit_v1.0.csv:</b> Dataset (version 1.0) of SARS-CoV-2 events in animals obtained from scientific papers gathered through the PubMed online database. Methods to build this dataset are described in the paper: <i>"Data on SARS-CoV-2 events in animals: mind the gap!".</i>