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. 2024 Apr 4;15(1):2887.
doi: 10.1038/s41467-024-46979-1.

Bat species assemblage predicts coronavirus prevalence

Magdalena Meyer #  1 , Dominik W Melville #  2 , Heather J Baldwin  2   3 , Kerstin Wilhelm  2 , Evans Ewald Nkrumah  4 , Ebenezer K Badu  4 , Samuel Kingsley Oppong  4 , Nina Schwensow  2 , Adam Stow  3 , Peter Vallo  2   5 , Victor M Corman  6   7 , Marco Tschapka  2 , Christian Drosten  6   7 , Simone Sommer  8
Affiliations

Bat species assemblage predicts coronavirus prevalence

Magdalena Meyer et al. Nat Commun. .

Abstract

Anthropogenic disturbances and the subsequent loss of biodiversity are altering species abundances and communities. Since species vary in their pathogen competence, spatio-temporal changes in host assemblages may lead to changes in disease dynamics. We explore how longitudinal changes in bat species assemblages affect the disease dynamics of coronaviruses (CoVs) in more than 2300 cave-dwelling bats captured over two years from five caves in Ghana. This reveals uneven CoV infection patterns between closely related species, with the alpha-CoV 229E-like and SARS-related beta-CoV 2b emerging as multi-host pathogens. Prevalence and infection likelihood for both phylogenetically distinct CoVs is influenced by the abundance of competent species and naïve subadults. Broadly, bat species vary in CoV competence, and highly competent species are more common in less diverse communities, leading to increased CoV prevalence in less diverse bat assemblages. In line with the One Health framework, our work supports the notion that biodiversity conservation may be the most proactive measure to prevent the spread of pathogens with zoonotic potential.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Spatio-temporal community characteristics and coronavirus prevalence.
Sample sites and sampling regime (A) over a two-year field study in central Ghana. The relative community composition (B), abundance of subadults (C) and coronavirus prevalence (D) of captured bats at the five bimonthly-sampled caves. Map was created with OpenStreetMap and adapted in BioRender.com. Source data are provided as a Source Data file.
Fig. 2
Fig. 2. Diversity-disease relationship.
Spearman-correlation between coronavirus prevalence (alpha-CoV 229E-like, beta-CoV 2b) and Shannon species diversity index (A, B). Solid line and grey band show best fit and 95 percent confidence interval, respectively. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Ecological determinants of coronavirus infection likelihood.
Coronavirus (CoV) infection probability (alpha-CoV 229E-like, beta-CoV 2b) in relation to the Shannon Diversity Index (A, B), the relative abundance of the most common (n < 50) species Hipposideros (H.) abae (apricot), H. caffer B (light blue), C (yellow), D (dark blue) as well as Coleura (C.) afra (slate grey) and Nycteris (N.) macrotis (orange) (C, D), and the relative abundance of subadults (adults=magenta; subadults=pink) (E, F) in each of the five sampling sites in central Ghana modelled using generalised linear mixed effect models. Solid and dashed lines represent significant (FDR-corrected) and non-significant fitted model curves, respectively, and lightly shaded area the respective 95% confidence interval. Icons were created with BioRender.com. Source data are provided as a Source Data file.
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