What, where and weather? Integrating open-source taxonomic, spatial and climatologic information into a comprehensive database of livestock infections

What are all the species of pathogen that affect our livestock? It is important to answer this question, to help protect the animals that produce our food, and also because nearly 7 out of every 10 human pathogens came from animals, with a good number from the livestock and pets that we closely associate with. Remarkably, however, even for humans this question was only answered ten years ago (1415 were listed) and there remains no definitive answer for livestock, domestic pets and other animals.
This proposal aims to further develop a new database of livestock (and other) pathogens, called EID2 (ENHanCED Infectious Diseases 2). EID2 has been built largely from the tens of millions of records of DNA and RNA sequences that are uploaded onto public databases; where such sequences are from a pathogen, they are frequently uploaded with further information on the host (which animal the pathogen was obtained from), where and when it was obtained, and who by. EID2 takes this information, and draws conclusions; for example, that a certain type of pathogen infects a certain host species, and is/was present in a certain country at a certain time. Similar conclusions can be drawn, and added to EID2, from the tens of millions of publications held in other public databases, thereby covering times and places where sequencing has not been extensive. EID2 can map the pathogens and, using incorporated climate data, it can model the climate conditions that determine their distribution. EID2 is open access.
TRDF funding will enable us to finalise the development of EID2 into a tool and resource for researchers of pathogens of livestock and domestic pets. We will develop the database to hold more spatially detailed information (at county rather than country level) and improve its ability to handle records where the host species is not clearly defined. We will add further environmental data to allow users to produce better models to explain pathogen distributions, and even predict them...