Sign in
MicrobiologybioRxiv
Preprint

Dynamic model of bovine brucellosis to investigate control strategies in endemic settings

H. R. Holt, M. Walker, W. Beavais, P. Kaur, J. S. Bedi, P. Mangtani, N. S. Sharma, J. P. S. Gill, J. Godfroid, J. A. McGiven, J. Guitian

Abstract

Brucellosis imposes substantial impacts on livestock production and public health worldwide. A stochastic, age-structured model incorporating herd demographics was developed describing within- and between-herd transmission of Brucella abortus in dairy cattle herds. The model was fitted to data from a cross-sectional study conducted in Punjab State of India and used to evaluate the effectiveness of control strategies under consideration. Based on model results, stakeholder acceptance and constraints regarding vaccine supply, vaccination of replacement calves in large farms should be prioritised. Test and removal applied at early stages of the control programme where seroprevalence is high would not constitute an effective use of resources. Critically, under current model assumptions, significant numbers of animals removed (culled or not used for breeding) in this strategy would be removed based on false positive results. To achieve sustained reductions in brucellosis, policymakers must commit to maintaining vaccination in the long term, which may eventually reduce frequency of infection in the livestock reservoir to a low enough level for elimination to be a realistic objective. This exercise provided important insights into the control of brucellosis in India, which has the largest cattle population globally, and a general framework for evaluating control strategies in endemic settings.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISNjeru '20Smith '25Pandey '23Konzen '24Kumsa '23Horpienchar '23
68% semantic matchMicrobiology
J. Njeru, D. Nthiwa, J. Akoko+2 more·bioRxiv·Jun 25, 2020