Fichet-Calvet, E. | Search bioRxiv

bioRxiv2025

Contact networks of small mammals highlight potential transmission foci of Lassa mammarenavirus.

Lassa fever (Mammarenavirus lassaense; LASV), is an endemic zoonosis in West Africa. Human infections arise from rodent-to-human transmission, mainly from the synanthropic reservoir Mastomys natalensis. In Sierra Leone, small-mammal communities vary across land use gradients, shaping LASV transmission risk. How anthropogenic environments facilitate the rodent-rodent interactions remains poorly understood. We sampled small mammals over 43,266 trap nights in Sierra Leones LASV-endemic Eastern Province, detecting 684 rodents and shrews. To assess potential transmission, we constructed space-sharing networks from co-trapping events within species-specific home range radii. These networks approximated shared space use, allowing comparison of encounter patterns across habitats. Network topology varied significantly by land use. Village networks were the most connected (highest average degree), whereas agricultural communities supported the most species (higher rarefied richness) and were the most fragmented (higher modularity). Notably, the probability of intraspecific space sharing among M. natalensis was highest in agriculture, suggesting land use modulates key intra-specific transmission pathways. LASV seroprevalence was 5.7% community-wide, with antibodies in nine species. We found no statistically significant association between overall seroprevalence and land use or aggregate network structure (mean degree). However, predictive modeling for M. natalensis indicated that higher individual degree is associated with seropositivity, suggesting complex, scale-dependent relationships. These findings show that simple ecological drivers do not fully explain LASV exposure, highlighting the importance of species-specific behaviors (i.e., M. natalensis clustering in agriculture) and the multi-host serological landscape in assessing transmission risk.

ecology↗

bioRxiv2019

Bayesian estimation of Lassa virus epidemiological parameters: implications for spillover prevention using wildlife vaccination

Lassa virus is a significant burden on human health throughout its endemic region in West Africa, with most human infections the result of spillover from the primary rodent reservoir of the virus, the natal multimammate mouse, M. natalensis. Here we develop a Bayesian methodology for estimating epidemiological parameters of Lassa virus within its rodent reservoir and for generating probabilistic predictions for the efficacy of rodent vaccination programs. Our approach uses Approximate Bayesian Computation (ABC) to integrate mechanistic mathematical models, remotely-sensed precipitation data, and Lassa virus surveillance data from rodent populations. Using simulated data, we show that our method accurately estimates key model parameters, even when surveillance data are available from only a relatively small number of points in space and time. Applying our method to previously published data from two villages in Guinea estimates the time-averaged R0 of Lassa virus to be 1.658 and 1.453 for rodent populations in the villages of Bantou and Tanganya, respectively. Using the posterior distribution for model parameters derived from these Guinean populations, we evaluate the likely efficacy of vaccination programs relying on distribution of vaccine-laced baits. Our results demonstrate that effective and durable reductions in the risk of Lassa virus spillover into the human population will require repeated distribution of large quantities of vaccine. Author SummaryLassa virus is a chronic source of illness throughout West Africa, and is considered to be a threat for widespread emergence. Because most human infections result from contact with infected rodents, interventions that reduce the number of rodents infected with Lassa virus represent promising opportunities for reducing the public health burden of this disease. Evaluating how well alternative interventions are likely to perform is complicated by our relatively poor understanding of viral epidemiology within the reservoir population. Here we develop a novel statistical approach that couples mathematical models and viral surveillance data from rodent populations to robustly estimate key epidemiological parameters. Applying our method to existing data from Guinea yields well-resolved parameter estimates and allows us to simulate a variety of rodent vaccination programs. Together, our results demonstrate that rodent vaccination alone is unlikely to be an effective tool for reducing that public health burden of Lassa fever within West Africa.

ecology↗