Spatial Pattern Switching Enables Cyclic Evolution in Spatial Epidemics

Infectious diseases often spread as spatial epidemic outbreak waves. A number of model studies have shown that such spatial pattern formation can have important consequences for the evolution of pathogens. Here, we show that such spatial patterns can cause cyclic evolutionary dynamics in selection for the length of the infectious period. The necessary reversal in the direction of selection is enabled by a qualitative change in the spatial pattern from epidemic waves to irregular local outbreaks. The spatial patterns are an emergent property of the epidemic system, and they are robust against changes in specific model assumptions. Our results indicate that emergent spatial patterns can act as a rich source for complexity in pathogen evolution

Screening for colorectal cancer: random comparison of guaiac and immunochemical faecal occult blood testing at different cut-off levels

Immunochemical faecal occult blood testing (FIT) provides quantitative test results, which allows optimisation of the cut-off value for follow-up colonoscopy. We conducted a randomised population-based trial to determine test characteristics of FIT (OC-Sensor micro, Eiken, Japan) screening at different cut-off levels and compare these with guaiac-based faecal occult blood test (gFOBT) screening in an average risk population. A representative sample of the Dutch population (n=10 011), aged 50–74 years, was 1 : 1 randomised before invitation to gFOBT and FIT screening. Colonoscopy was offered to screenees with a positive gFOBT or FIT (cut-off 50 ng haemoglobin/ml). When varying the cut-off level between 50 and 200 ng ml−1, the positivity rate of FIT ranged between 8.1% (95% CI: 7.2–9.1%) and 3.5% (95% CI: 2.9–4.2%), the detection rate of advanced neoplasia ranged between 3.2% (95% CI: 2.6–3.9%) and 2.1% (95% CI: 1.6–2.6%), and the specificity ranged between 95.5% (95% CI: 94.5–96.3%) and 98.8% (95% CI: 98.4–99.0%). At a cut-off value of 75 ng ml−1, the detection rate was two times higher than with gFOBT screening (gFOBT: 1.2%; FIT: 2.5%; P<0.001), whereas the number needed to scope (NNscope) to find one screenee with advanced neoplasia was similar (2.2 vs 1.9; P=0.69). Immunochemical faecal occult blood testing is considerably more effective than gFOBT screening within the range of tested cut-off values. From our experience, a cut-off value of 75 ng ml−1 provided an adequate positivity rate and an acceptable trade-off between detection rate and NNscope

Isolation-by-Distance and Outbreeding Depression Are Sufficient to Drive Parapatric Speciation in the Absence of Environmental Influences

A commonly held view in evolutionary biology is that speciation (the emergence of genetically distinct and reproductively incompatible subpopulations) is driven by external environmental constraints, such as localized barriers to dispersal or habitat-based variation in selection pressures. We have developed a spatially explicit model of a biological population to study the emergence of spatial and temporal patterns of genetic diversity in the absence of predetermined subpopulation boundaries. We propose a 2-D cellular automata model showing that an initially homogeneous population might spontaneously subdivide into reproductively incompatible species through sheer isolation-by-distance when the viability of offspring decreases as the genomes of parental gametes become increasingly different. This simple implementation of the Dobzhansky-Muller model provides the basis for assessing the process and completion of speciation, which is deemed to occur when there is complete postzygotic isolation between two subpopulations. The model shows an inherent tendency toward spatial self-organization, as has been the case with other spatially explicit models of evolution. A well-mixed version of the model exhibits a relatively stable and unimodal distribution of genetic differences as has been shown with previous models. A much more interesting pattern of temporal waves, however, emerges when the dispersal of individuals is limited to short distances. Each wave represents a subset of comparisons between members of emergent subpopulations diverging from one another, and a subset of these divergences proceeds to the point of speciation. The long-term persistence of diverging subpopulations is the essence of speciation in biological populations, so the rhythmic diversity waves that we have observed suggest an inherent disposition for a population experiencing isolation-by-distance to generate new species

Multilevel Selection in Models of Prebiotic Evolution II: A Direct Comparison of Compartmentalization and Spatial Self-Organization

Multilevel selection has been indicated as an essential factor for the evolution of complexity in interacting RNA-like replicator systems. There are two types of multilevel selection mechanisms: implicit and explicit. For implicit multilevel selection, spatial self-organization of replicator populations has been suggested, which leads to higher level selection among emergent mesoscopic spatial patterns (traveling waves). For explicit multilevel selection, compartmentalization of replicators by vesicles has been suggested, which leads to higher level evolutionary dynamics among explicitly imposed mesoscopic entities (protocells). Historically, these mechanisms have been given separate consideration for the interests on its own. Here, we make a direct comparison between spatial self-organization and compartmentalization in simulated RNA-like replicator systems. Firstly, we show that both mechanisms achieve the macroscopic stability of a replicator system through the evolutionary dynamics on mesoscopic entities that counteract that of microscopic entities. Secondly, we show that a striking difference exists between the two mechanisms regarding their possible influence on the long-term evolutionary dynamics, which happens under an emergent trade-off situation arising from the multilevel selection. The difference is explained in terms of the difference in the stability between self-organized mesoscopic entities and externally imposed mesoscopic entities. Thirdly, we show that a sharp transition happens in the long-term evolutionary dynamics of the compartmentalized system as a function of replicator mutation rate. Fourthly, the results imply that spatial self-organization can allow the evolution of stable folding in parasitic replicators without any specific functionality in the folding itself. Finally, the results are discussed in relation to the experimental synthesis of chemical Darwinian systems and to the multilevel selection theory of evolutionary biology in general. To conclude, novel evolutionary directions can emerge through interactions between the evolutionary dynamics on multiple levels of organization. Different multilevel selection mechanisms can produce a difference in the long-term evolutionary trend of identical microscopic entities

Genetic Data Provide Evidence for Wind-Mediated Transmission of Highly Pathogenic Avian Influenza

Outbreaks of highly pathogenic avian influenza in poultry can cause severe economic damage and represent a public health threat. Development of efficient containment measures requires an understanding of how these influenza viruses are transmitted between farms. However, the actual mechanisms of interfarm transmission are largely unknown. Dispersal of infectious material by wind has been suggested, but never demonstrated, as a possible cause of transmission between farms. Here we provide statistical evidence that the direction of spread of avian influenza A(H7N7) is correlated with the direction of wind at date of infection. Using detailed genetic and epidemiological data, we found the direction of spread by reconstructing the transmission tree for a large outbreak in the Netherlands in 2003. We conservatively estimate the contribution of a possible wind-mediated mechanism to the total amount of spread during this outbreak to be around 18%

Monitoring the spread of meticillin-resistant Staphylococcus aureus in The Netherlands from a reference laboratory perspective

Background In The Netherlands, efforts to control meticillin-resistant Staphylococcus aureus (MRSA) in hospitals have been largely successful due to stringent screening of patients on admission and isolation of those that fall into defined risk categories. However, Dutch hospitals are not free of MRSA, and a considerable number of cases are found that do not belong to any of the risk categories. Some of these may be due to undetected nosocomial transmission, whereas others may be introduced from unknown reservoirs. Aim Identifying multi-institutional clusters of MRSA isolates to estimate the contribution of potential unobserved reservoirs in The Netherlands. Methods We applied a clustering algorithm that combines time, place, and genetics to routine data available for all MRSA isolates submitted to the Dutch Staphylococcal Reference Laboratory between 2008 and 2011 in order to map the geo-temporal distribution of MRSA clonal lineages in The Netherlands. Findings Of the 2966 isolates lacking obvious risk factors, 579 were part of geo-temporal clusters, whereas 2387 were classified as MRSA of unknown origin (MUOs). We also observed marked differences in the proportion of isolates that belonged to geo-temporal clusters between specific multi-locus variable number of tandem repeat analysis (MLVA) clonal complexes, indicating lineage-specific transmissibility. The majority of clustered isolates (74%) were present in multi-institutional clusters. Conclusion The frequency of MRSA of unknown origin among patients lacking obvious risk factors is an indication of a largely undefined extra-institutional but genetically highly diverse reservoir. Efforts to understand the emergence and spread of high-risk clones require the pooling of routine epidemiological information and typing data into central databases

Finding Evidence for Local Transmission of Contagious Disease in Molecular Epidemiological Datasets

<p>Surveillance systems of contagious diseases record information on cases to monitor incidence of disease and to evaluate effectiveness of interventions. These systems focus on a well-defined population; a key question is whether observed cases are infected through local transmission within the population or whether cases are the result of importation of infection into the population. Local spread of infection calls for different intervention measures than importation of infection. Besides standardized information on time of symptom onset and location of cases, pathogen genotyping or sequencing offers essential information to address this question. Here we introduce a method that takes full advantage of both the genetic and epidemiological data to distinguish local transmission from importation of infection, by comparing inter-case distances in temporal, spatial and genetic data. Cases that are part of a local transmission chain will have shorter distances between their geographical locations, shorter durations between their times of symptom onset and shorter genetic distances between their pathogen sequences as compared to cases that are due to importation. In contrast to generic clustering algorithms, the proposed method explicitly accounts for the fact that during local transmission of a contagious disease the cases are caused by other cases. No pathogen-specific assumptions are needed due to the use of ordinal distances, which allow for direct comparison between the disparate data types. Using simulations, we test the performance of the method in identifying local transmission of disease in large datasets, and assess how sensitivity and specificity change with varying size of local transmission chains and varying overall disease incidence.</p>

Different transmission patterns in the early stages of the influenza A(H1N1) v pandemic: A comparative analysis of 12 European countries

Following the emergence of a novel strain of influenza A(H1N1) in Mexico and the United States in April 2009, its epidemiology in Europe during the summer was limited to sporadic and localised outbreaks. Only the United Kingdom experienced widespread transmission declining with school holidays in late July. Using statistical modelling where applicable we explored the following causes that could explain this surprising difference in transmission dynamics: extinction by chance, differences in the susceptibility profile, age distribution of the imported cases, differences in contact patterns, mitigation strategies, school holidays and weather patterns. No single factor was able to explain the differences sufficiently. Hence an additive mixed model was used to model the country-specific weekly estimates of the effective reproductive number using the extinction probability, school holidays and weather patterns as explanatory variables. The average extinction probability, its trend and the trend in absolute humidity were found to be significantly negatively correlated with the effective reproduction number - although they could only explain about 3% of the variability in the model. By comparing the initial epidemiology of influenza A (H1N1) across different European countries, our analysis was able to uncover a possible role for the timing of importations (extinction probability), mixing patterns and the absolute humidity as underlying factors. However, much uncertainty remains. With better information on the role of these epidemiological factors, the control of influenza could be improved. (C) 2011 Elsevier B. V. All rights reserved