Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo (2020)
Attributed to:
New Approaches to Bayesian Data Science: Tackling Challenges from the Health Sciences
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.1101/2020.10.26.20219485
Publication URI: http://dx.doi.org/10.1101/2020.10.26.20219485
Type: Preprint