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Peste des petits ruminants (PPR) is a highly contagious disease affecting mainly sheep and goats. Livestock movements contribute to the spread of the disease by introducing it to naive areas or exposing susceptible animals to it in infected regions. Because of its socio-economic impact, the Food and Agriculture Organisation (FAO) and the World Organization for Animal Health (WOAH) have set the goal to eradicate it by 2030, one of the key steps being the improvement of surveillance networks. The present study aimed to provide tools to identify areas that could serve as sentinel nodes, i.e. areas that may be rapidly infected at the onset of epidemics. Using data from a market survey conducted in Northern Nigeria, we reconstructed the small ruminants mobility network and simulated the diffusion of PPR virus through animal movement. From the analysis of simulation outcomes, we investigated which nodes could act as sentinel nodes under specific conditions for disease transmission. We considered several modified networks to get around the problem of data only being available for part of the overall network structure and to account for potential errors made during the field study. For each configuration, we simulated the spread of PPR using a stochastic Susceptible-Infectious (SI) model based on animal movements to assess the epidemics' extent and the presence of recurrent patterns to identify potential sentinel nodes. We extracted the backbone of the reference network and checked for the presence of sentinel nodes within it. We investigated how the origin (seed) of the epidemics could affect the propagation pattern by comparing and grouping seeds based on their respective transmission paths. Results showed that the isolated backbone contains 45% of sentinel nodes that remain stable or undergo only minor changes in 9 out of 11 configurations. On top of that, the characteristics of sentinel nodes identified in the backbone are not influenced by the severity of the disease. The H index, in-degree, and eigenvector are the most essential variables. This study provides an overview of the major axes of animal movements in Nigeria and the most vulnerable locations that should be prioritized for monitoring livestock diseases like PPR. [ABSTRACT FROM AUTHOR]

BackgroundWest Nile virus (WNV) has an enzootic cycle between birds and mosquitoes, humans being incidental dead-end hosts. Circulation of WNV is an increasing public health threat in Europe. While detection of WNV is notifiable in humans and animals in the European Union, surveillance based on human case numbers presents some limitations, including reporting delays.AimWe aimed to perform risk mapping of WNV circulation leading to human infections in Europe by integrating two types of surveillance systems: indicator-based and event-based surveillance.MethodsFor indicator-based surveillance, we used data on human case numbers reported to the European Centre for Disease Prevention and Control (ECDC), and for event-based data, we retrieved information from news articles collected through an automated biosurveillance platform. In addition to these data sources, we also used environmental data to train ecological niche models to map the risk of local WNV circulation leading to human infections.ResultsThe ecological niche models based on both types of surveillance data highlighted new areas potentially at risk of WNV infection in humans, particularly in Spain, Italy, France and Greece.ConclusionAlthough event-based surveillance data do not constitute confirmed occurrence records, integrating both indicator-based and event-based surveillance data proved useful. These results underscore the potential for a more proactive and comprehensive strategy in managing the threat of WNV in Europe by combining indicator- and event-based and environmental data for effective surveillance and public health response.