The GBADs Ethiopia case study was launched in 2021 as proof of concept of GBADs frameworks and methods in estimating the social and economic burden of animal diseases. The workshop … Continue reading GBADs Ethiopia Workshop, May 2023
GBADs special session, ISVEE 2022
The Global Burden of Animal Diseases (GBADs) programme gave a Special Session presentation at ISVEE 16. Members of the GBADs team gave multiple talks on the work each theme are … Continue reading GBADs special session, ISVEE 2022
GBADs Annual Meeting, 2022
On Saturday 13th August, we had our annual meeting for 2022 in Halifax, Canada after ISVEE. We had discussions on side meetings we had during the week and linking with … Continue reading GBADs Annual Meeting, 2022
GBADs at the 16th International Symposium of Veterinary Epidemiology and Economics (ISVEE)
From August 7-12, 2022, members of the GBADs programme attended the 16th International Symposium of Veterinary Epidemiology and Economics (ISVEE), in Halifax, Canada, to share and discuss the current work … Continue reading GBADs at the 16th International Symposium of Veterinary Epidemiology and Economics (ISVEE)
A scoping review of burden of disease studies estimating disability-adjusted life years due to Taenia solium
Andrew Larkins, Mieghan Bruce, Carlotta Di Bari, Brecht Devleesschauwer, David M. Pigott and Amanda Ash have had the following publication published. You can find the abstract below and the full … Continue reading A scoping review of burden of disease studies estimating disability-adjusted life years due to Taenia solium
Estimating the burden of multiple endemic diseases and health conditions using Bayes’ Theorem: A conditional probability model applied to UK dairy cattle
Phillip Rasmussen, University of Zurich, has recently had his comorbidity paper published online. You can find this here. Phil is one of our Postdoctoral Fellows in the section of Epidemiology.” AbstractThe … Continue reading Estimating the burden of multiple endemic diseases and health conditions using Bayes’ Theorem: A conditional probability model applied to UK dairy cattle