Transmission dynamics of lyssavirus in Myotis myotis: mechanistic modelling study based on longitudinal seroprevalence data. Issue 1997 (26th April 2023)

• Record Type: Journal Article
• Authors: Kim, Younjung; Leopardi, Stefania; Scaravelli, Dino; Zecchin, Barbara; Priori, Pamela; Festa, Francesca; Drzewnioková, Petra; De Benedictis, Paola; Nouvellet, Pierre
• Is Part Of: Proceedings. Volume 290:Issue 1997(2023)
• Publication Date: 2023-04-26
• Subjects: lyssavirus -- EBLV-1 -- Myotis bats -- bat-borne virus -- zoonosis -- transmission dynamics; Biology -- Periodicals; 570.5
• DOI: 10.1098/rspb.2023.0183
• Languages: English
• ISSNs: 0962-8452

Abstract

Abstract : We investigated the transmission dynamics of lyssavirus in Myotis myotis and Myotis blythii, using serological, virological, demographic and ecological data collected between 2015 and 2022 from two maternity colonies in northern Italian churches. Despite no lyssavirus detection in 556 bats sampled over 11 events by reverse transcription-polymerase chain reaction (RT-PCR), 36.3% of 837 bats sampled over 27 events showed neutralizing antibodies to European bat lyssavirus 1, with a significant increase in summers. By fitting sets of mechanistic models to seroprevalence data, we investigated factors that influenced lyssavirus transmission within and between years. Five models were selected as a group of final models: in one model, a proportion of exposed bats (median model estimate: 5.8%) became infectious and died while the other exposed bats recovered with immunity without becoming infectious; in the other four models, all exposed bats became infectious and recovered with immunity. The final models supported that the two colonies experienced seasonal outbreaks driven by: (i) immunity loss particularly during hibernation, (ii) density-dependent transmission, and (iii) a high transmission rate after synchronous birthing. These findings highlight the importance of understanding ecological factors, including colony size and synchronous birthing timing, and potential infection heterogeneities to enable more robust assessments of lyssavirus spillover risk.