Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Abstract

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data.

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

“…As 10% of these samples were collected in areas reporting human cases, the proportion of seropositive animals may have been overestimated. However, most animal sampling was conducted from January 2019 onwards, when RVF virus , of the livestock population was immune at the end of the simulated epidemic wave (August 2019), which was in line with estimates from the previous emergence in 2007-2008 (9).…”

“…Further data collection estimating human post-epidemic seroprevalence would allow an accurate estimation of this reporting rate. Finally, the livestock model was built with similar assumptions than in our previous paper (9). This included a latent (E) and an infectious (I) period of 7 days in livestock, accounting for the extrinsic incubation period in the vector (3-7 days), and the latent (1-6 days) and infectious stages (3-6 days) in livestock (30)(31)(32)(33), without explicitly modelling these processes.…”

“…without introduction of infectious animals). However, a few imported infectious animals could trigger another large epidemic, as the herd immunity declined due to livestock population turnover (9). In 2018, about ten years after the previous epidemic, RVF outbreaks were reported in several East African countries (e.g.…”

“…These investigations generated a uniquely well documented RVF epidemic dataset, including RVF seroprevalence and incidence data in animal and humans. 2 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 We present these data and use them to extend and fit a mathematical model of RVF virus transmission in livestock (9), and explicitly account for viral spillover from livestock into the human population. We fit this model simultaneously to the infection patterns in livestock and human observed during the 2018-2019 epidemic, allowing for the first time, (i) to estimate the level of RVF virus transmission amongst livestock and spillover from livestock to humans by both direct contact and vector-mediated routes, (ii) to estimate the likelihood of another epidemic the following year, and (iii) to assess the impact of potential vaccination strategies in livestock and humans on reducing disease occurrence in humans.…”

Rift Valley fever in northern Senegal : a modelling approach to analyse the processes underlying virus circulation recurrence

“…Since its first recognition in 1931 in Kenya, RVF outbreaks have been regularly reported in sub-Saharan Africa [12–18], Indian Ocean [19, 20] and Arabic Peninsula [21]. The most recent outbreaks occurred in Mauritania (2015), Niger (2016), Uganda (2016) and Mayotte (2018-2019) [12, 22–24].…”