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Hemorrhagic fever with renal syndrome (HFRS) caused by hantaviruses and transmitted by rodents is a significant public health problem in China, and occurs more frequently in selenium-deficient regions. To study the role of selenium concentration in HFRS incidence we used a multidisciplinary approach combining ecological analysis with preliminary experimental data. The incidence of HFRS in humans was about six times higher in severe selenium-deficient and double in moderate deficient areas compared to non-deficient areas. This association became statistically stronger after correction for other significant environment-related factors (low elevation, few grasslands, or an abundance of forests) and was independent of geographical scale by separate analyses for different climate regions. A case-control study of HFRS patients admitted to the hospital revealed increased activity and plasma levels of selenium binding proteins while selenium supplementation in vitro decreased viral replication in an endothelial cell model after infection with a low multiplicity of infection (MOI). Viral replication with a higher MOI was not affected by selenium supplementation. Our findings indicate that selenium deficiency may contribute to an increased prevalence of hantavirus infections in both humans and rodents. Future studies are needed to further examine the exact mechanism behind this observation before selenium supplementation in deficient areas could be implemented for HFRS prevention.

Zoonotic disease surveillance is typically triggered after animal pathogens have already infected humans. Are there ways to identify high-risk viruses before they emerge in humans? If so, then how and where can identifications be made and by what methods? These were the fundamental questions driving a workshop to examine the future of predictive surveillance for viruses that might jump from animals to infect humans. Virologists, ecologists and computational biologists from academia, federal government and non-governmental organizations discussed opportunities as well as obstacles to the prediction of species jumps using genetic and ecological data from viruses and their hosts, vectors and reservoirs. This workshop marked an important first step towards envisioning both scientific and organizational frameworks for this future capability. Canine parvoviruses as well as seasonal H3N2 and pandemic H1N1 influenza viruses are discussed as exemplars that suggest what to look for in anticipating species jumps. To answer the question of where to look, prospects for discovering emerging viruses among wildlife, bats, rodents, arthropod vectors and occupationally exposed humans are discussed. Finally, opportunities and obstacles are identified and accompanied by suggestions for how to look for species jumps. Taken together, these findings constitute the beginnings of a conceptual framework for achieving a virus surveillance capability that could predict future species jumps.

Zoonotic disease surveillance is typically triggered after animal pathogens have already infected humans. Are there ways to identify high-risk viruses before they emerge in humans? If so, then how and where can identifications be made and by what methods? These were the fundamental questions driving a workshop to examine the future of predictive surveillance for viruses that might jump from animals to infect humans. Virologists, ecologists and computational biologists from academia, federal government and non-governmental organizations discussed opportunities as well as obstacles to the prediction of species jumps using genetic and ecological data from viruses and their hosts, vectors and reservoirs. This workshop marked an important first step towards envisioning both scientific and organizational frameworks for this future capability. Canine parvoviruses as well as seasonal H3N2 and pandemic H1N1 influenza viruses are discussed as exemplars that suggest what to look for in anticipating species jumps. To answer the question of where to look, prospects for discovering emerging viruses among wildlife, bats, rodents, arthropod vectors and occupationally exposed humans are discussed. Finally, opportunities and obstacles are identified and accompanied by suggestions for how to look for species jumps. Taken together, these findings constitute the beginnings of a conceptual framework for achieving a virus surveillance capability that could predict future species jumps.