Combining viral genetic and animal mobility network data to unravel peste des petits ruminants transmission dynamics in West Africa.

Peste des petits ruminants (PPR) is a deadly viral disease that mainly affects small domestic ruminants. This disease threaten global food security and rural economy but its control is complicated notably because of extensive, poorly monitored animal movements in infected regions. Here we combined the largest PPR virus genetic and animal mobility network data ever collected in a single region to improve our understanding of PPR endemic transmission dynamics in West African countries. Phylogenetic analyses identified the presence of multiple PPRV genetic clades that may be considered as part of different transmission networks evolving in parallel in West Africa. A strong correlation was found between virus genetic distance and network-related distances. Viruses sampled within the same mobility communities are significantly more likely to belong to the same genetic clade. These results provide evidence for the importance of animal mobility in PPR transmission in the region. Some nodes of the network were associated with PPRV sequences belonging to different clades, representing potential "hotspots" for PPR circulation. Our results suggest that combining genetic and mobility network data could help identifying sites that are key for virus entrance and spread in specific areas. Such information could enhance our capacity to develop locally adapted control and surveillance strategies, using among other risk factors, information on animal mobility.

Intercontinental Spread of Eurasian Highly Pathogenic Avian Influenza A(H5N1) to Senegal.

In January 2021, Senegal reported the emergence of highly pathogenic avian influenza virus A(H5N1), which was detected on a poultry farm in Thies, Senegal, and in great white pelicans in the Djoudj National Bird Sanctuary. We report evidence of new transcontinental spread of H5N1 from Europe toward Africa.

Environmental and economic determinants of temporal dynamics of the ruminant movement network of Senegal.

Our understanding of the drivers of the temporal dynamics of livestock mobility networks is currently limited, despite their significant implications for the surveillance and control of infectious diseases. We analyzed the effect of time-varying environmental and economic variables-biomass production, rainfall, livestock market prices, and religious calendar on long-distance movements of cattle and small ruminant herds in Senegal in the years 2014 and 2019. We used principal component analysis to explore the variation of the hypothesized explanatory variables in space and time and a generalized additive modelling approach to assess the effect of those variables on the likelihood of herd movement between pairs of administrative units. Contrary to environmental variables, the patterns of variation of market prices show significant differences across locations. The explanatory variables at origin had the highest contribution to the model deviance reduction. Biomass production and rainfall were found to affect the likelihood of herd movement for both species on at least 1 year. Market price at origin had a strong and consistent effect on the departure of small ruminant herds. Our study shows the potential benefits of regular monitoring of market prices for future efforts at forecasting livestock movements and associated sanitary risks.

Identification of drivers of Rift Valley fever after the 2013-14 outbreak in Senegal using serological data in small ruminants.

Rift Valley fever (RVF) is a mosquito-borne disease mostly affecting wild and domestic ruminants. It is widespread in Africa, with spillovers in the Arab Peninsula and the southwestern Indian Ocean. Although RVF has been circulating in West Africa for more than 30 years, its epidemiology is still not clearly understood. In 2013, an RVF outbreak hit Senegal in new areas that weren't ever affected before. To assess the extent of the spread of RVF virus, a national serological survey was implemented in young small ruminants (6-18 months old), between November 2014 and January 2015 (after the rainy season) in 139 villages. Additionally, the drivers of this spread were identified. For this purpose, we used a beta-binomial ([Formula: see text]) logistic regression model. An Integrated Nested Laplace Approximation (INLA) approach was used to fit the spatial model. Lower cumulative rainfall, and higher accessibility were both associated with a higher RVFV seroprevalence. The spatial patterns of fitted RVFV seroprevalence pointed densely populated areas of western Senegal as being at higher risk of RVFV infection in small ruminants than rural or southeastern areas. Thus, because slaughtering infected animals and processing their fresh meat is an important RVFV transmission route for humans, more human populations might have been exposed to RVFV during the 2013-2014 outbreak than in previous outbreaks in Senegal.

Seroprevalence of African swine fever in Senegal, 2006.

In Senegal, during 2002-2007, 11 outbreaks of African swine fever (ASF) were reported to the World Organisation for Animal Health. Despite this, little was known of the epidemiology of ASF in the country. To determine the prevalence of ASF in Senegal in 2006, we tested serum specimens collected from a sample of pigs in the 3 main pig-farming regions for antibodies to ASF virus using an ELISA. Of 747 serum samples examined, 126 were positive for ASF, suggesting a prevalence of 16.9%. The estimated prevalences within each of the regions (Fatick, Kolda, and Ziguinchor) were 13.3%, 7.8%, and 22.1%, respectively, with statistical evidence to suggest that the prevalence in Ziguinchor was higher than in Fatick or Kolda. This regional difference is considered in relation to different farming systems and illegal trade with neighboring countries where the infection is endemic.

Using a participatory qualitative risk assessment to estimate the risk of introduction and spread of transboundary animal diseases in scarce-data environments: A Spatial Qualitative Risk Analysis applied to foot-and-mouth disease in Tunisia 2014-2019.

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Mapping livestock movements in Sahelian Africa.

In the dominant livestock systems of Sahelian countries herds have to move across territories. Their mobility is often a source of conflict with farmers in the areas crossed, and helps spread diseases such as Rift Valley Fever. Knowledge of the routes followed by herds is therefore core to guiding the implementation of preventive and control measures for transboundary animal diseases, land use planning and conflict management. However, the lack of quantitative data on livestock movements, together with the high temporal and spatial variability of herd movements, has so far hampered the production of fine resolution maps of animal movements. This paper proposes a general framework for mapping potential paths for livestock movements and identifying areas of high animal passage potential for those movements. The method consists in combining the information contained in livestock mobility networks with landscape connectivity, based on different mobility conductance layers. We illustrate our approach with a livestock mobility network in Senegal and Mauritania in the 2014 dry and wet seasons.

Assessing the Risk of Occurrence of Bluetongue in Senegal.

Bluetongue is a non-contagious viral disease affecting small ruminants and cattle that can cause severe economic losses in the livestock sector. The virus is transmitted by certain species of the genus Culicoides and consequently, understanding their distribution is essential to enable the identification of high-risk transmission areas. In this work we use bioclimatic and environmental variables to predict vector abundance, and estimate spatial variations in the basic reproductive ratio  R0. The resulting estimates were combined with livestock mobility and serological data to assess the risk of Bluetongue outbreaks in Senegal. The results show an increasing abundance of C. imicola, C. oxystoma, C. enderleini, and C. miombo from north to south. R0 < 1 for most areas of Senegal, whilst southern (Casamance) and southeastern (Kedougou and part of Tambacounda) agro-pastoral areas have the highest risk of outbreak (R0 = 2.7 and 2.9, respectively). The next higher risk areas are in the Senegal River Valley (R0 = 1.07), and the Atlantic coast zones. Seroprevalence rates, shown by cELISA, weren't positively correlated with outbreak probability. Future works should include follow-up studies of competent vector abundancies and serological surveys based on the results of the risk analysis conducted here to optimize the national epidemiological surveillance system.