Estimation of Rift Valley fever virus spillover to humans during the Mayotte 2018-2019 epidemic

Abstract

Rift Valley fever (RVF) is an emerging, zoonotic, arboviral haemorrhagic fever threatening livestock and humans mainly in Africa. RVF is of global concern, having expanded its geographical range over the last decades. The impact of control measures on epidemic dynamics using empirical data has not been assessed. Here, we combined seroprevalence livestock and human RVF case data from the 2018-2019 epidemic in Mayotte, with a dynamic mathematical model. Using a Bayesian inference framework, we estimated viral transmission potential amongst livestock, and spillover from livestock to humans, through both direct contact and vector-mediated routes. Model simulations were used to assess the impact of vaccination on reducing the human epidemic size. Reactive vaccination immunising 20% of the livestock population reduced the number of human cases by 30%. To achieve a similar impact, delaying the vaccination by one month required using 50% more vaccine doses, and vaccinating only humans required 20 times as more as the number of doses for livestock. Finally, with 53. ) of livestock estimated to be immune at the end of the epidemic wave, viral re-emergence in the next rainy season (2019-2020) was unlikely. We present the first mathematical model for RVF fitted to real-world data to estimate virus transmission parameters, and able to inform potential control programmes. Human and animal health surveillance, and timely livestock vaccination appear to be key in reducing disease risk in humans. We furthermore demonstrate the value of a One Health quantitative approach to surveillance and control of zoonotic infectious diseases.

Rift Valley Fever – assessment of effectiveness of surveillance and control measures in the EU

“…is the probability of transmission at distance r, K(r) is the transmission kernel, R 0 is the basic reproduction number, here assumed to be 2, based on previous epidemics in Mayotte (Métras et al., 2017, 2020). On the other side, for EU, the calculation with different R 0 values is provided, since the R 0 under the EU condition is not known: it is reported to vary between 2.3 and 6.8 as from modelled values or from epidemics reported in Africa (Braks et al., 2017) and I is the number of infected animals in the zone (in the best‐case scenario assumed to be at least one).…”

“…To model the spread and control of RVFV in Mayotte, we used a stochastic version of a model previously developed by Métras et al. (2017, 2020).…”

“…all species are equally susceptible and there is no spatial structure in the population). The model has been fitted to data on RVFV IgG seroprevalence in Mayotte from 2005 to 2016 (Métras et al., 2017) and from 2018 to 2019 (Métras et al., 2020).…”

“…Parameters and their estimates are summarised in Table 1. Parameters in the model for the transmission of RVFV in Mayotte (from Métras et al., 2020). Data on animal populations and farm management that have been used for this Opinion were derived from the websites of the Statistic and Prospective Service of the French Ministry of Agriculture and Food (Service de la statistique et de la prospective, Ministère de l’ Agriculture et de l’ Alimentation1 ) and from the Direction of Food, Agriculture and Forestry (Direction de l’ Agriculture de l’ Alimentation et la Forêt, DAAF) of Mayotte 2.…”

Fractional-Order Derivative Model of Rift Valley Fever in Urban Peridomestic Cycle

“…ere are possibilities also for human infections to result from other blood-feeding insects, which might be serve as mechanical transmitters of infection. e current urban peridomestic outbreaks of RVF include the 2019 outbreak in Sudan where 1,129 case patients and 19 deaths were reported [5] and that of Mayotte (France) where 143 human cases were reported [6].…”