RESUMO
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.
RESUMO
The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use.
