Trends of foodborne diseases in China： lessons from laboratory- based surveillance since 2011

Abstract Foodborne disease is one of the most important public health issues worldwide. China faces various and unprecedented challenges in all aspects of the food chain. Data from laboratory-based foodborne disease surveillance systems from 2013 to 2016, as well as different regions and ages, can be found along with differences in the patterns of pathogens detected with diverse characteristics. Vibrioparahaemolyticus has been the leading cause of infectious diarrhea in China, especially among adults in coastal regions. Salmonella has been a serious and widely distributed pathogen responsible for substantial socioeconomic burden. Shigella was mostly identified in Northwest China and the inland province （Henan） with less-developed regions among children under 5 years. Data from foodborne disease outbreak reporting system from 2011 to 2016 showed that poisonous animals and plant factors responsible for most deaths were poisonous mushrooms （54.7%） in remote districts in southwest regions. The biological hazard that caused most cases reported （42.3%） was attributed to V. parahaemolyticus, the leading cause of foodborne outbreaks. In this review, we summarize the recent monitoring approach to foodborne diseases in China and compare the results with those in developed countries.

Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes

The frequent outbreak of severe foodborne diseases(e.g., haemolytic uraemic syndrome and Listeriosis) in 2011 warns of a potential threat that world trade could spread fatal pathogens(e.g., enterohemorrhagic Escherichia coli). The epidemic potential from trade involves both intra-proliferation and inter-diffusion. Here, we present a worldwide vegetable trade network and a stochastic computational model to simulate global trade-mediated epidemics by considering the weighted nodes and edges of the network and the dual-scale dynamics of epidemics. We address two basic issues of network structural impact in global epidemic patterns:(1) in contrast to the prediction of heterogeneous network models, the broad variability of node degree and edge weights of the vegetable trade network do not determine the threshold of global epidemics;(2) a ‘penetration effect', by which community structures do not restrict propagation at the global scale, quickly facilitates bridging the edges between communities, and leads to synchronized diffusion throughout the entire network. We have also defined an appropriate metric that combines dual-scale behavior and enables quantification of the critical role of bridging edges in disease diffusion from widespread trading. The unusual structure mechanisms of the trade network model may be useful in producing strategies for adaptive immunity and reducing international trade frictions.