Complexity Science Hub: First global dataset for SARS-CoV-2 infections in animals (c) Shutterstock



Study unveils first global dataset for SARS-CoV-2 infections in animals

In a pioneering initiative, a multidisciplinary Austrian team created the most comprehensive global dataset of SARS-CoV-2 infections in animals. Their findings were published Saturday, July 23, in the journal Scientific Data and are presented in a user-friendly dashboard at

“There was an urgent need for a global dataset on SARS-CoV-2 events in animals that can be easily imported, processed, and analysed,” says CSH scientist Amélie Desvars-Larrive, the principal investigator of the study.

The initiative intends to facilitate One Health approaches on SARS-CoV-2. The idea is to create a collaborative approach that recognizes the interdependence of human, animal, and environmental health to obtain optimal health for all. 

“To tackle major threats to human health, we need integrated approaches,” points out Amélie. “Although animals do not appear to play a significant role in the spread of COVID-19 among people currently, One Health tools that enable the integrative analysis and visualization of SARS-CoV-2 events are critical.” 


For the past months, Amélie and her team meticulously extracted, combined, and structured information on SARS-CoV-2 cases in animals. They included publicly available data from two major animal health databases: the Program for Monitoring Emerging Diseases (ProMED), a reporting system of the International Society for Infectious Diseases; and the World Animal Health Information System (WAHIS) of the World Organisation for Animal Health.

The unified dataset, called SARS-ANI, feeds a dashboard designed by our vis experts Liuhuaying Yang and Johannes Sorger. The dashboard includes an overview of SARS-CoV-2 events in animals worldwide, stratified by species; clinical signs that were allegedly associated to the disease; control measures and outcomes; and a geographical overview of all events. The dashboard is linked to the live dataset available on GitHub.


The dataset can help answering some of the many questions regarding SARS-CoV-2 in animals, according to the authors. It shows, for instance, that the number of reported SARS-CoV-2 cases in animals is steadily increasing worldwide. A total of 704 events (one event can include one or more cases that are epidemiologically related) have been reported in 39 countries, across 27 animal species (as of July 25, 2022).

In addition, the team described a high diversity of SARS-CoV-2 variants in the animal hosts, especially in American mink and white-tailed deer. These variants show similarities with human variants. In terms of animal case fatality rates, they are relatively low.


Also, the dataset can be useful for estimating the impact of SARS-CoV-2 on pets, farm animals, wildlife, and conservation programs. In addition, scientists and policy makers can use it to develop guidelines for prevention, risk-based surveillance, and response to SARS-CoV-2.

“We believe the SARS-ANI dataset, with timely and reliable information, can assist in the development of national and international regulations and agreements aiming to reduce the risk of transmission at the human-animal interfaces,” declares Amélie, who is also a professor in infection epidemiology at the University of Veterinary Medicine Vienna. 

The dataset – a joint effort by experts from CSH, University of Veterinary Medicine Vienna, and Wildlife Conservation Society – will be updated weekly for at least one year. “We also hope to receive new data from researchers around the world to develop it further and expand its use”, says Amélie.

The study SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals by Afra Nerpel, Liuhuaying Yang, Johannes Sorger, Annemarie Käsbohrer, Chris Walzer and Amélie Desvars-Larrive appeared in Scientific Data 9 (438) (2022). 

Learn more about the SARS-ANI dashboard: 



A. Nerpel, L. Yang, J. Sorger, A. Käsbohrer, C. Walzer, A. Desvars-Larrive
Scientific Data

Get intuitive insights into specific aspects of SARS-CoV-2 events in animals at-a-glance.

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