Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades

Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.

In our study we performed ecological niche modelling and phylogeographic analyses to model how the endemic range of Lassa virus (LASV) may evolve in the next five decades in response to climate change, human population growth, and land use changes. Specifically, (i) we performed ecological niche modelling analyses for Lassa virus and his reservoir host, Mastomys natalensis to identify the determinants of ecological suitability for LASV, (ii) we projected the future ecological suitability for LASV across Africa, (iii) we estimated the human population living in areas suitable for LASV based on human population projections, (iv) we used a continuous phylogeographic approach to reconstruct the dispersal history of LASV in West Africa and estimate the virus mean lineage dispersal velocity, (v) we used a first landscape phylogeographic approach to test the impact of main waterways on the dispersal history of LASV lineages, (vi) we used a second landscape phylogeographic approach to test the impact of environmental factors on the dispersal velocity of LASV lineages, and (vii) we used phylogeographic simulations to illustrate how a slow lineage dispersal velocity may limit the spatial extent of LASV spread following a potential introduction event.
The climate information consists of daily gridded near-surface air temperature and surface precipitation fields derived from four biasadjusted global climate models (GCMs; GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We considered simulations conducted under historical climate forcings and RCPs 2.6, 6.0 and 8.5. In addition, we considered observed gridded temperature and precipitation from the concatenated products GSWP3 and EWEMBI for assessing the current (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) conditions. For land cover we use version 2 of the Land Use Harmonisation (LUH2) providing historical and projected land cover states under a range of shared socioeconomic pathways (SSPs), and from which we consider SSP1-26, SSP4-6.0 and SSP8-85. Finally, we retrieve gridded population projections under SSP2-26. For each combination of product (GCM, GSWP3-EWEMBI LUH2, gridded population), scenario (historical, RCP, SSP) and analysis window (1986-2005, 2021-2040, 2041-2060, and 2061-2080), we compute the grid-scale temporal mean. For both Mastomys natalensis and Muridae rodents data sets, duplicate occurrence records as well as occurrence records located in the ocean were excluded from the final rodent occurrence data sets (Mastomys natalensis and Muridae). For this study, we retrieved all Lassa virus sequences available on GenBank (November 20, 2019) and we also included in our data sets new sequences generated in 2019 and not available on GenBank (https://virological.org/t/2019-lassa-virus-sequencing-in-nigeria-final-field-report-75-samples/291). We then filtered the sequence data by: (i) excluding laboratory strains (adapted, passaged multiple times, recombinant, obtained from antiviral or vaccine experiments), (ii) excluding sequences without a timestamp, (iii) keeping only sequences from a single time point (if multiple time points were available for a patient), (iv) removing duplicates (when more than one sequence was available for a single strain), and (v) excluding sequences from identified hospital epidemics or sequences for which the location corresponded to the site of hospitalisation. Occurrence and sequence data correspond to all the available data we managed to collect and retrieve at the time of the study. The resulting data sets cover the respective ranges of the rodent host and Lassa virus.
We obtained data for the environmental factors used in the BRT analyses from the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b, https://data.isimip.org/). We collected M. natalensis species occurrence data online from publicly available databases and museum collections: from the Global Biodiversity Information Facility ( We used environmental data for the African continent and the following analysis windows: analysis window (1986-2005, 2021-2040, 2041-2060, and 2061-2080). The choice of the different time windows was arbitrary but they were defined to cover distinct periods of time. Mastomys natalensis and Muridae occurrence data were collected in Africa up to 2019 and are meant to represent all known spatial records of M. natalensis and Muridae available at the time of the analysis. Genomic sequences for LASV were collected in West Africa between 1969 and 2019 and are meant to represent all Lassa virus genomes publicly available at the time of the analysis that (1) have been identified in natural settings (in rodents or humans), and (2), for which the collection time is known.
There was no data exclusion.

(No experiment was performed)
There was no group allocation performed in our study.
This study is not a clinical research study and does not involve human subjects thus blinding was not necessary.