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. 2019;8(1):640-649.
doi: 10.1080/22221751.2019.1605846.

Evaluation of rodent control to fight Lassa fever based on field data and mathematical modelling

Affiliations

Evaluation of rodent control to fight Lassa fever based on field data and mathematical modelling

Joachim Mariën et al. Emerg Microbes Infect. 2019.

Abstract

The Natal multimammate mouse (Mastomys natalensis) is the reservoir host of Lassa virus, an arenavirus that causes Lassa haemorrhagic fever in humans in West Africa. Because no vaccine exists and therapeutic options are limited, preventing infection through rodent control and human behavioural measures is currently considered to be the only option. In order to assess the efficacy of rodent control, we performed a 4-year field experiment in rural Upper Guinea and developed a mathematical model to simulate different control strategies (annual density control, continuous density control, and rodent vaccination). For the field study, rodenticide baits were placed each year in three rural villages, while three other villages were used as controls. Rodents were trapped before and after every treatment and their antibody status and age were determined. Data from the field study were used to parameterize the mathematical model. In the field study, we found a significant negative effect of rodent control on seroprevalence, but this effect was small especially given the effort. Furthermore, the rodent populations recovered rapidly after rodenticide application, leading us to conclude that an annual control strategy is unlikely to significantly reduce Lassa virus spillover to humans. In agreement with this finding, the mathematical model suggests that the use of continuous control or rodent vaccination is the only strategy that could lead to Lassa virus elimination. These field and model results can serve as a guide for determining how long and frequent rodent control should be done in order to eliminate Lassa virus in rural villages.

Keywords: Lassa virus; arenavirus; rodent control; rodent vaccination; rodent-borne virus.

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Conflict of interest statement

No potential conflict of interest was reported by the authors.

Figures

Figure 1.
Figure 1.
Schematic illustration of the individual-based model used to simulate the spread of Lassa virus in populations of M. natalensis in Guinea. Individual rodents are assigned different states according to infection status: susceptible (S), exposed (E), acutely infectious (I), recovered (R), maternal antibody positive (M), and chronically infectious (C). State transition rates depend on the following parameters: transmission coefficient (β), latent period (σ−1), infectious period (γ−1), maternal antibody period (ω−1). Fat solid arrows indicate possible transitions between different states. The dashed lines show the demographic parameters: Φ (birth rate) and μ (mortality rate). The probability to become acutely infected after vertical transmission is given by V_I and to become chronically infected by V_C. Thin solid arrows indicate that the rate at which individuals move from one state to another depends on the number of individuals in another state.
Figure 2.
Figure 2.
Mean eye lens weight (ELW) of M. natalensis for the control (black) and treatment villages (red) in function of year. The ELW is used as a proxy for age in the rodents. The error bars indicate standard errors on the means.
Figure 3.
Figure 3.
Mean LASV seroprevalence of M. natalensis in the treatment (Brissa, Dalafilani, and Yarawalia) and control (Damania, Sokourala, and Sonkonia) villages over time (years). The seroprevalence was corrected by the mean eye lens weight (number on top of the bars in mg), a known proxy for age in mammals. Bars indicate 95% (binomial) confidence intervals on the mean seroprevalence.
Figure 4.
Figure 4.
Model simulations to predict the effect of rodent control on LASV extinction probability in a population of M. natalensis in a rural village in Upper Guinea. The figures a, b and c show the number of consecutive years that rodents need to be controlled/vaccinated to ensure LASV extinction (>95% of simulation extinct). If "years to extinction" equals 10 years, at least 10 years or more will be necessary to ensure extinction. Figure d shows the invasion probability of LASV when one LASV positive M. natalensis enters a completely susceptible population in a rural village. The different colours represent simulations at different values of the transmission-density coefficient (q = 0 is density-dependent transmission; q = 1 is frequency-dependent transmission) or times that rodents were vaccinated per year (when q = 0.25).

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