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

Abstract

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 R 0 of Lassa virus to be 1.74 and 1.54 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.

Bridging the gap: Using reservoir ecology and human serosurveys to estimate Lassa virus spillover in West Africa

“…However, it is unclear whether the density fluctuations that have been observed outside of the LASV geographic range (e.g., Tanzania [ 79 ]) also occur within West Africa. At least in Guinea and Sierra Leone, research on the population dynamics of M. natalensis indicates that density fluctuations are much weaker than those in East Africa [ 83 ]. In the case of rodent vaccination, understanding population dynamics is particularly important because distributing vaccines at seasonal population lows in wildlife demographic cycles can, in theory, substantially increase the probability of pathogen elimination [ 83 , 84 ].…”

Quantifying the effectiveness of betaherpesvirus-vectored transmissible vaccines

“…Although the primary reservoir of LASV, the multimammate rat Mastomys natalensis , is only distantly related to the domestic mouse, both LASV and LCMV do infect species within the genus Mus ( 21 ). Using published estimates for the seroprevalence and infectious period of these pathogens ( 22 , 23 ) we developed models describing their response to an MCMV-vectored transmissible vaccine. These models were used to simulate the introduction of a transmissible vaccine into a reservoir population where the target pathogen was endemic.…”

“…The greater resistance to the vaccine exhibited by LCMV is mostly due to its increased infectious period which we have assumed is, on average, lifelong. In contrast, the infectious period for LASV has been estimated to be 22 d, on average ( 22 , 23 ). These results highlight that pathogens that generate acute, short-term infections and have relatively low R 0 are most readily controlled using MCMV-vectored transmissible vaccines.…”

“…We estimated epidemiological parameters for LASV and LCMV using published serological data and duration of infection estimates from previous studies ( 22 , 23 ). Similar to the methods used in Model Parameterization Using MCMV Prevalence and Steady-State Assumptions , we find the steady-state solutions to our general pathogen model, and identify the solution where the pathogen is endemic.…”

“…where p is the prevalence for the given pathogen, , and δ is assigned a value based on LASV and LCMV literature [LASV: 1/ δ = 22 d ( 22 ), LCMV: 1/ δ = 365 d ( 23 )].…”