Sympatric Occurrence of 3 Arenaviruses, Tanzania

To determine the specificity of Morogoro virus for its reservoir host, we studied its host range and genetic diversity in Tanzania. We found that 2 rodent species other than Mastomys natalensis mice carry arenaviruses. Analysis of 340 nt of the viral RNA polymerase gene showed sympatric occurrence of 3 distinct arenaviruses

Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.status: publishe

The linear no-threshold model is less realistic than threshold or hormesis-based models: An evolutionary perspective

International audienceThe linear no-threshold (LNT) risk model is the current human health risk assessment paradigm. This model states that adverse stochastic biological responses to high levels of a stressor can be used to estimate the response to low or moderate levels of that stressor. In recent years the validity of the LNT risk model has increasingly been questioned because of the recurring observation that an organism's response to high stressor doses differs from that to low doses. This raises important questions about the biological and evolutionary validity of the LNT model. In this review we reiterate that the LNT model as applied to stochastic biological effects of low and moderate stressor levels has less biological validity than threshold or, particularly, hormetic models. In so doing, we rely heavily on literature from disciplines like ecophysiology or evolutionary ecology showing how exposure to moderate amounts of stress can have severe impacts on phenotype and organism reproductive fitness. We present a mathematical model that illustrates and explores the hypothetical conditions that make a particular kind of hormesis (conditioning hormesis) ecologically and evolutionarily plausible

The linear no-threshold model is less realistic than threshold or hormesis-based models : an evolutionary perspective

International audienceThe linear no-threshold (LNT) risk model is the current human health risk assessment paradigm. This model states that adverse stochastic biological responses to high levels of a stressor can be used to estimate the response to low or moderate levels of that stressor. In recent years the validity of the LNT risk model has increasingly been questioned because of the recurring observation that an organism's response to high stressor doses differs from that to low doses. This raises important questions about the biological and evolutionary validity of the LNT model. In this review we reiterate that the LNT model as applied to stochastic biological effects of low and moderate stressor levels has less biological validity than threshold or, particularly, hormetic models. In so doing, we rely heavily on literature from disciplines like ecophysiology or evolutionary ecology showing how exposure to moderate amounts of stress can have severe impacts on phenotype and organism reproductive fitness. We present a mathematical model that illustrates and explores the hypothetical conditions that make a particular kind of hormesis (conditioning hormesis) ecologically and evolutionarily plausible

The shape of the contact-density function matters when modelling parasite transmission in fluctuating populations

Models of disease transmission in a population with changing densities must assume a relation between infectious contacts and density. Typically, a choice is made between a constant (frequency-dependence) and a linear (density-dependence) contact-density function, but it is becoming increasingly clear that intermediate, nonlinear functions are more realistic. It is currently not clear, however, what the exact consequences would be of different contact-density functions in fluctuating populations. By combining field data on rodent host (Mastomys natalensis) demography, experimentally derived contact-density data, and laboratory and field data on Morogoro virus infection dynamics, we explored the effects of different contact-density function shapes on transmission dynamics and invasion/persistence. While invasion and persistence were clearly affected by the shape of the function, the effects on outbreak characteristics such as infection prevalence and seroprevalence were less obvious. This means that it may be difficult to distinguish between the different shapes based on how well models fit to real data. The shape of the transmission-density function should therefore be chosen with care, and is ideally based on existing information such as a previously quantified contact-or transmission-density relationship or the underlying biology of the host species in relation to the infectious agent.University of Antwerp [GOA BOF FFB3567]; Deutsche Forschungsgemeinschaft [1596]; Antwerp Study Centre for Infectious Diseases (ASCID); European Union's Horizon research and innovation programme under the Marie Sklodowska-Curie grant [707840]contact rates; disease invasion; disease persistence; mass action; nonlinearity; threshol