Back

Cross-sector collaboration reduces SARS-CoV-2 risk in deer

Cook, J. D.; Rosenblatt, E.; DiRenzo, G. V.; Campbell Grant, E. H.; Mosher, B.; Arce, F.; Christensen, S.; Ghai, R.; Runge, M.

2023-10-17 ecology
10.1101/2023.10.13.562192 bioRxiv
Show abstract

One Health helps achieve optimal health outcomes for people, animals, plants, and their shared environments. We describe a multidisciplinary effort to better understand and mitigate SARS-CoV-2 spread in white-tailed deer across One Health sectors. We first framed the risk problem with three governance sectors that manage captive and wild deer and human public health. The framing included the objectives for each sector, interactions that facilitate human-to-deer and deer-to-deer transmission, and alternatives intended to reduce risk. We then developed a dynamic compartmental model that linked wild and captive deer herds and humans and simulated SARS-CoV-2 dynamics. For baseline conditions, we estimated that median SARS-CoV-2 prevalence in wild and captive herds varied between 0.03 - 0.07, incidence between 0.68 - 1.46, and probability of persistence between 0.64 - 0.97 across 120-day simulations. We then tested single-sector alternatives alone and in combination with other sector actions. We found that single sector alternatives varied in their ability to reduce transmission and that the best performing alternative required collaborative actions among wildlife management, agricultural management, and public health agencies.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.