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International audience; In recent decades, the incidence of Lyme borreliosis (LB) in Europe seems to have increased, underpinning a growing public health concern. LB surveillance systems across the continent are heterogeneous, and the spatial and temporal patterns of LB reports have been little documented. In this study, we explored the spatio-temporal patterns of LB cases reported in France from 2016 to 2019, to describe high-risk clusters and generate hypotheses on their occurrence. The space-time K-function and the Kulldorf's scan statistic were implemented separately for each year to evaluate space-time interaction between reported cases and searching clusters. The results show that the main spatial clusters, of radius size up to 97 km, were reported in central and northeastern France each year. In 2017-2019, spatial clusters were also identified in more southern areas (near the Alps and the Mediterranean coast). Spatio-temporal clustering occurred between May and August, over one-month to three-month windows in 2016-2017 and in 2018-2019. A strong spatio-temporal interaction was identified in 2018 within 16 km and seven days, suggesting a potential local and intense pathogen transmission process. Ongoing improved surveillance and accounting for animal hosts, vectors, meteorological factors and human behaviors are keys to further elucidate LB spatio-temporal patterns.

International audience; Peste des Petits Ruminants (PPR) is a viral disease affecting domestic and small wild ruminants. Endemic in large parts of the world, PPR causes severe damages to animal production and household economies. In 2015, FAO and OIE launched a global eradication program (GCSE) based on vaccination campaigns. The success of GCSE shall depend on the implementation of vaccination campaigns, accounting for husbandry practices, mobility and the periodicity of small ruminants' population renewal. In Mauritania, PPR outbreaks occur annually despite ongoing annual vaccination campaigns since 2008. Here, we developed a mathematical model to assess the impact of four vaccination strategies (including the GSCE one), the importance of their timing of implementation and the usefulness of individual animal identification on the reduction of PPR burden. The model was calibrated on data collected through ad-hoc surveys about demographic dynamics, disease impact, and national seroprevalence using Monte Carlo Markov Chain procedure. Numerical simulations were used to estimate the number of averted deaths over the next 12 years. The model results showed that the GSCE strategy prevented the largest number of deaths (9.2 million vs. 6.2 for random strategy) and provided one of the highest economic returns among all strategies (Benefit-Cost Ratio around 16 vs. 7 for random strategy). According to its current cost, identification would be a viable investment that could reduce the number of vaccine doses to distribute by 20-60%. Whilst the implementation of the identification system is crucial for PPR control, its success depends also on a coordinated approach at the regional level.

International audience; Mayotte is an island located in the Mozambique Channel, between Mozambique and Madagascar, in the South Western Indian Ocean region. A severe syndrome of unknown aetiology has been observed seasonally since 2009 in cattle (locally named "cattle flu"), associated with anorexia, nasal discharge, hyperthermia and lameness. We sampled blood from a panel of those severely affected animals at the onset of disease signs and analysed these samples by next-generation sequencing. We first identified the presence of ephemeral bovine fever viruses (BEFV), an arbovirus belonging to the genus Ephemerovirus within the family Rhabdoviridae, thus representing the first published sequences of BEFV viruses of African origin. In addition, we also discovered and genetically characterized a potential new species within the genus Ephemerovirus, called Mavingoni virus (MVGV) from one diseased animal. Finally, both MVGV and BEFV have been identified in cattle from the same herd, evidencing a co-circulation of different ephemeroviruses on the island. The clinical, epidemiological and virological information strongly suggests that these viruses represent the etiological agents of the observed "cattle flu" within this region. This study highlights the importance of the strengthening and harmonizing arboviral surveillance in Mayotte and its neighbouring areas, including Africa mainland, given the importance of the diffusion of infectious diseases (such as BEFV) mediated by animal and human movements in the South Western Indian Ocean area.

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., Author summary Rift Valley fever (RVF) is an arboviral hemorrhagic fever affecting primarily livestock in Africa and in the Arabian Peninsula. The conditions leading to RVF emergence are not fully understood, mainly because of data scarcity. Applied to the island of Mayotte (our ecosystem under study), for which 12 years RVF serological dataset are available, and by using a mechanistic model, we demonstrate that RVF epidemics related mainly to the introduction of infectious animals. Our work confirms that anthropogenic factors, such as livestock movements, need to be accounted for in order to understand the epidemiology of this disease. Our model should be tested elsewhere, with ecosystem-specific data.

The potential role of Eulemur fulvus (brown lemur) in the epidemiology of Rift Valley fever (RVF) in Mayotte, during an interepidemic period, was explored. In February and March 2016, 72 animals were blood sampled and tested for RVF. No evidence of RVF genome or antibodies was found in the samples. The role of other wild mammals on the island should, however, be further investigated.\ud \ud

Rift Valley fever (RVF) is a zoonotic arboviral disease that is a threat to human health, animal health and production, mainly in Sub-Saharan Africa. RVF virus dynamics have been poorly studied due to data scarcity. On the island of Mayotte in the Indian Ocean, off the Southeastern African coast, RVF has been present since at least 2004. Several retrospective and prospective serological surveys in livestock have been conducted over eleven years (2004–15). These data are collated and presented here. Temporal patterns of seroprevalence were plotted against time, as well as age-stratified seroprevalence. Results suggest that RVF was already present in 2004–07. An epidemic occurred between 2008 and 2010, with IgG and IgM peak annual prevalences of 36% in 2008–09 (N = 142, n = 51, 95% CI [17–55]) and 41% (N = 96, n = 39, 95% CI [25–56]), respectively. The virus seems to be circulating at a low level since 2011, causing few new infections. In 2015, about 95% of the livestock population was susceptible (IgG annual prevalence was 6% (N = 584, n = 29, 95% CI [3–10])). Monthly rainfall varied a lot (2–540mm), whilst average temperature remained high with little variation (about 25–30°C). This large dataset collected on an insular territory for more than 10 years, suggesting a past epidemic and a current inter-epidemic period, represents a unique opportunity to study RVF dynamics. Further data collection and modelling work may be used to test different scenarios of animal imports and rainfall pattern that could explain the observed epidemiological pattern and estimate the likelihood of a potential re-emergence., Author Summary Rift Valley fever (RVF) is a viral zoonotic disease mainly present in Sub-Saharan Africa, transmitted by mosquitoes and primarily affecting livestock (cattle, sheep and goats). The epidemiology of the disease is not fully known, mainly because of data scarcity. In Mayotte, an island close to Madagascar, RVF has been present since at least 2004, and retrospective and prospective surveys have been conducted to collect data from livestock over 11 years. Our work uses this 2004–15 dataset to describe the past and current epidemiology of RVF on the island. Results suggest that the disease was endemic between 2004–07. An epidemic occurred between 2008 and 2010. Since 2011, the virus appears to be circulating at a low-level causing few new infections. Modelling work may be used to explain the observed epidemiological pattern, and estimate the likelihood of a potential re-emergence.

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.