Despite the increased use of vaccination in several Asian countries, Japanese Encephalitis (JE) remains the most important cause of viral encephalitis in Asia in humans with an estimated 68,000 cases annually. Considered a rural disease occurring mainly in paddy-field dominated landscapes where pigs are amplifying hosts, JE may nevertheless circulate in a wider range of environment given the diversity of its potential hosts and vectors. The main objective of this study was to assess the intensity of JE transmission to pigs in a peri-urban environment in the outskirt of Phnom Penh, Cambodia. We estimated the force of JE infection in two cohorts of 15 sentinel pigs by fitting a generalised linear model on seroprevalence monitoring data observed during two four-month periods in 2014. Our results provide evidence for intensive circulation of JE virus in a periurban area near Phnom Penh, the capital and most populated city of Cambodia. Understanding JE virus transmission in different environments is important for planning JE virus control in the long term and is also an interesting model to study the complexity of vector-borne diseases. Collecting quantitative data such as the force of infection will help calibrate epidemiological model that can be used to better understand complex vector-borne disease epidemiological cycles.

Hand, Foot and Mouth Disease (HFMD) is an emerging viral disease, and at present, there are no antiviral drugs or vaccines available to control it. Outbreaks have persisted for the past 10 years, particularly in northern Thailand. This study aimed to elucidate the phenomenon of HFMD outbreaks from 2003 to 2012 using general statistics and spatial-temporal analysis employing a GIS-based method. The spatial analysis examined data at the village level to create a map representing the distribution pattern, mean center, standard deviation ellipse and hotspots for each outbreak. A temporal analysis was used to analyze the correlation between monthly case data and meteorological factors. The results indicate that the disease can occur at any time of the year, but appears to peak in the rainy and cold seasons. The distribution of outbreaks exhibited a clustered pattern. Most mean centers and standard deviation ellipses occurred in similar areas. The linear directional mean values of the outbreaks were oriented toward the south. When separated by season, it was found that there was a significant correlation with the direction of the southwest monsoon at the same time. An autocorrelation analysis revealed that hotspots tended to increase even when patient cases subsided. In particular, a new hotspot was found in the recent year in Mae Hong Son province.

The cross-disciplinary activity of modelling and simulation is the core of the scientific activities addressing the complexity of nature. In this context, we need reliable computational environments to integrate heterogeneous representations coming from different scientific fields. Therefore, such environments must be able to integrate heterogeneous formalisms in the same model and assist the modeller for the design and implementation of models, the definition of the experimental frames and the analysis of simulation results. The aim of this article is to introduce a tool supporting all these features, the Virtual Laboratory Environment (VLE). VLE is a software and an API which supports multi-modelling, simulation and analysis. It addresses the reliability issue by using recent developments in the theory of modelling and simulation proposed by Zeigler. We present VLE in the context of the modelling and simulation cycle and show the effectiveness of the tool with a multimodel of fireman fighting a fire spread.

As Southeast Asia (SEA) is characterized by high human and domestic animal densities, growing intensification of trade, drastic land use changes and biodiversity erosion, this region appears to be a hotspot to study complex dynamics of zoonoses emergence and health issues at the Animal–Human–Environment interface. Zoonotic diseases and environmental health issues can have devastating socioeconomic and wellbeing impacts. Assessing and managing the related risks implies to take into account ecological and social dynamics at play, in link with epidemiological patterns.The implementation of a One Health (OH) approach in this context calls for improved integration among disciplines and improved cross-sectoral collaboration, involving stakeholders at different levels. For sure, such integration is not achieved spontaneously, implies methodological guidelines and has transaction costs. We explore pathways for implementing such collaboration in SEA context, highlighting the main challenges to be faced by researchers and other target groups involved in OH actions. On this basis, we propose a conceptual framework of OH integration. Throughout 3 components (field-based data management, professional training workshops and higher education), we suggest to develop a new culture of networking involving actors from various disciplines, sectors and levels (from the municipality to the Ministries) through a participatory modelling process, fostering synergies and cooperation. This framework could stimulate long-term dialogue process, based on the combination of case studies implementation and capacity building. It aims for implementing both institutional OH dynamics (multi-stakeholders and cross-sectoral) and research approaches promoting systems thinking and involving social sciences to follow-up and strengthen collective action.