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The Ebola virus disease epidemic that threatened West Africa between 2013 and 2016 was of unprecedented health magnitude. After this health crisis, studies highlighted the need to introduce community-based surveillance systems and to adopt a One Health approach. This study aimed to provide preparatory insights for the definition of a community-based surveillance system for emerging zoonoses such as viral hemorrhagic fevers in Guinea. The objective was to explore the disease detection capacity and the surveillance network opportunities at the community level in two pilot areas in the forest region of Guinea, where the epidemic emerged. Based on a participatory epidemiological and One Health approach, we conducted Focus Group Discussions with human, animal and ecosystem health actors. We used a range of participatory tools, included semi-structured interviews, ranking, scoring and flow diagram, to estimate the local knowledge and perception of diseases and clinical signs and to investigate the existing health information exchange network and its related strengths and weaknesses. The results showed that there is heterogeneity in knowledge of diseases and perception of the clinical signs among actors and that there are preferred and more effective health communication channels opportunities. This preparatory study suggests that it is necessary to adapt the case definitions and the health communication channels to the different actors who can play a role in a future community-based surveillance system and provides recommendations for future surveillance activities to be carried out in West Africa. Author summary: Viral hemorrhagic diseases have a high risk of emergence in tropical regions. The consequences on public health are often disastrous in the low- and middle-income countries that face difficulties to control epidemics. This scenario has unfortunately occurred in West Africa between 2013 and 2016 with the Ebola virus disease epidemic. There is an urgent need to increase the capacity for rapid detection of the emergence of such diseases and adopting a One Health approach since most of them are zoonotic. Community-based surveillance seems appropriate to address this issue in the context of these countries. We collected preparatory data through semi-structured interviews of community actors in human health, animal health and ecosystem health in Guinea. We used participatory epidemiology that appears to be a consistent method to assess local knowledge and perceptions of diseases and clinical signs and to identify health information exchange network opportunities. We aimed to provide relevant recommendations for the design of adapted case definitions and surveillance network in the prospect of implementing a community-based surveillance system of viral hemorrhagic fevers in Guinea and future surveillance activities to be carried out in West Africa. [ABSTRACT FROM AUTHOR]

An epidemic of Ebola Virus Disease (EVD) broke out in Guinea in December 2013. It was only identified in March 2014 while it had already spread out in Liberia and Sierra Leone. The spill over of the disease became uncontrollable and the epidemic could not be stopped before 2016. The time evolution of this epidemic is revisited here with the global modeling technique which was designed to obtain the deterministic models from single time series. A generalized formulation of this technique for multivariate time series is introduced. It is applied to the epidemic of EVD in West Africa focusing on the period between March 2014 and January 2015, that is, before any detected signs of weakening. Data gathered by the World Health Organization, based on the official publications of the Ministries of Health of the three main countries involved in this epidemic, are considered in our analysis. Two observed time series are used: the daily numbers of infections and deaths. A four-dimensional model producing a very complex dynamical behavior is obtained. The model is tested in order to investigate its skills and drawbacks. Our global analysis clearly helps to distinguish three main stages during the epidemic. A characterization of the obtained attractor is also performed. In particular, the topology of the chaotic attractor is analyzed and a skeleton is obtained for its structure. [ABSTRACT FROM AUTHOR]