Temporal trends in the discovery of human viruses

On average, more than two new species of human virus are reported every year. We constructed the cumulative species discovery curve for human viruses going back to 1901. We fitted a statistical model to these data; the shape of the curve strongly suggests that the process of virus discovery is far from complete. We generated a 95% credible interval for the pool of as yet undiscovered virus species of 38–562. We extrapolated the curve and generated an estimate of 10–40 new species to be discovered by 2020. Although we cannot predict the level of health threat that these new viruses will present, we conclude that novel virus species must be anticipated in public health planning. More systematic virus discovery programmes, covering both humans and potential animal reservoirs of human viruses, should be considered

How many cows do I need? Sample size calculations for testing co-infection using existing study data

Background There is little empirical research on the co-infection of Fasciola hepatica and Escherichia coli O157 in cattle. E. coli is controlled in the gut by a Type 1 immune response, whereas F. hepatica is known to suppress these immune responses and induce an anti-inflammatory environment in the host. We evaluate the statistical feasibility of re-testing isolates from a planned UK Food Standards Agency study on E. coli prevalence for F. hepatica presence, in order to establish whether there is an association. Methods We simulate synthetic datasets representing the proposed FSA sampling strategy. Sample sizes within farms and F. hepatica infections are simulated using Beta-Binomial distributions. E. coli infections are simulated using a logistic random-intercepts model under an alternative hypothesis that the odds ratio of E. coli presence is double when F. hepatica is present, with farm- and isolate-level prevalence rates constrained to current estimates. Statistical power is calculated by fitting models to each of the simulated datasets assuming a type I error rate of 5%. Owing to the E. coli status being known in advance of the F. hepatica test, we restrict the sampling strategy to only test farms with >0% an

Global discovery of human-infective RNA viruses:A modelling analysis

RNA viruses are a leading cause of human infectious diseases and the prediction of where new RNA viruses are likely to be discovered is a significant public health concern. Here, we geocoded the first peer-reviewed reports of 223 human RNA viruses. Using a boosted regression tree model, we matched these virus data with 33 explanatory factors related to natural virus distribution and research effort to predict the probability of virus discovery across the globe in 2010-2019. Stratified analyses by virus transmissibility and transmission mode were also performed. The historical discovery of human RNA viruses has been concentrated in eastern North America, Europe, central Africa, eastern Australia, and north-eastern South America. The virus discovery can be predicted by a combination of socio-economic, land use, climate, and biodiversity variables. Remarkably, vector-borne viruses and strictly zoonotic viruses are more associated with climate and biodiversity whereas non-vector-borne viruses and human transmissible viruses are more associated with GDP and urbanization. The areas with the highest predicted probability for 2010-2019 include three new regions including East and Southeast Asia, India, and Central America, which likely reflect both increasing surveillance and diversity of their virome. Our findings can inform priority regions for investment in surveillance systems for new human RNA viruses

E. coli O157 on Scottish cattle farms: evidence of local spread and persistence using repeat cross-sectional data

<b>Background</b><p></p> Escherichia coli (E. coli) O157 is a virulent zoonotic strain of enterohaemorrhagic E. coli. In Scotland (1998-2008) the annual reported rate of human infection is 4.4 per 100,000 population which is consistently higher than other regions of the UK and abroad. Cattle are the primary reservoir. Thus understanding infection dynamics in cattle is paramount to reducing human infections.<p></p> A large database was created for farms sampled in two cross-sectional surveys carried out in Scotland (1998 - 2004). A statistical model was generated to identify risk factors for the presence of E. coli O157 on farms. Specific hypotheses were tested regarding the presence of E. coli O157 on local farms and the farms previous status. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred.<p></p> <b>Results</b><p></p> The presence of an E. coli O157 positive local farm (average distance: 5.96km) in the Highlands, North East and South West, farm size and the number of cattle moved onto the farm 8 weeks prior to sampling were significant risk factors for the presence of E. coli O157 on farms. Previous status of a farm was not a significant predictor of current status (p = 0.398). Farms within the same sampling cluster were significantly more likely to be the same PFGE type (p < 0.001), implicating spread of strains between local farms. Isolates with identical PFGE types were observed to persist across the two surveys, including 3 that were identified on the same farm, suggesting an environmental reservoir. PFGE types that were persistent were more likely to have been observed in human clinical infections in Scotland (p < 0.001) from the same time frame.<p></p> <b>Conclusions</b><p></p> The results of this study demonstrate the spread of E. coli O157 between local farms and highlight the potential link between persistent cattle strains and human clinical infections in Scotland. This novel insight into the epidemiology of Scottish E. coli O157 paves the way for future research into the mechanisms of transmission which should help with the design of control measures to reduce E. coli O157 from livestock-related sources

Applying phylogenomics to understand the emergence of Shiga Toxin producing Escherichia coli O157:H7 strains causing severe human disease in the United Kingdom

Shiga Toxin producing Escherichia coli (STEC) O157:H7 is a recently emerged zoonotic pathogen with considerable morbidity. Since the serotype emerged in the 1980s, research has focussed on unravelling the evolutionary events from the E. coli O55:H7 ancestor to the contemporaneous globally dispersed strains. In this study the genomes of over 1000 isolates from human clinical cases and cattle, spanning the history of STEC O157:H7 in the United Kingdom were sequenced. Phylogenetic analysis reveals the ancestry, key acquisition events and global context of the strains. Dated phylogenies estimate the time to the most recent common ancestor of the current circulating global clone to 175 years ago, followed by rapid diversification. We show the acquisition of specific virulence determinates occurred relatively recently and coincides with its recent detection in the human population. Using clinical outcome data from 493 cases of STEC O157:H7 we assess the relative risk of severe disease including HUS from each of the defined clades in the population and show the dramatic effect Shiga toxin complement has on virulence. We describe two strain replacement events that have occurred in the cattle population in the UK over the last 30 years; one resulting in a highly virulent strain that has accounted for the majority of clinical cases in the UK over the last decade. This work highlights the need to understand the selection pressures maintaining Shiga-toxin encoding bacteriophages in the ruminant reservoir and the study affirms the requirement for close surveillance of this pathogen in both ruminant and human populations

Performance status: A key factor in predicting mortality in the first wave of COVID-19 in South-East Scotland

BACKGROUND: COVID-19 mortality risk factors have been established in large cohort studies; long-term mortality outcomes are less documented. METHODS: We performed multivariable logistic regression to identify factors associated with in-patient mortality and intensive care unit (ICU) admission in symptomatic COVID-19 patients admitted to hospitals in South-East Scotland from 1st March to 30th June 2020. One-year mortality was reviewed. RESULTS: Of 726 patients (median age 72; interquartile range: 58–83 years, 55% male), 104 (14%) required ICU admission and 199 (27%) died in hospital. A further 64 died between discharge and 30th June 2021 (36% overall 1-year mortality). Stepwise logistic regression identified age >79 (odds ratio (OR), 4.77 (95% confidence interval (CI), 1.96–12.75)), male sex (OR, 1.83 (95% CI, 1.21–2.80)) and higher European Cooperative Oncology Group/World Health Organization performance status as associated with higher mortality risk. DISCUSSION: Poor functional baseline was the predominant independent risk factor for mortality in COVID-19. More than one-third of individuals had died by 1 year following admission

The feasibility of testing whether Fasciola hepatica is associated with increased risk of verocytotoxin producing Escherichia coli O157 from an existing study protocol

The parasite Fasciola hepatica is a major cause of economic loss to the agricultural community worldwide as a result of morbidity and mortality in livestock, including cattle. Cattle are the principle reservoir of verocytotoxigenic Escherichia coli O157 (VTEC O157), an important cause of disease in humans. To date there has been little empirical research on the interaction between F. hepatica and VTEC O157. It is hypothesised that F. hepatica, which is known to suppress type 1 immune responses and induce an anti-inflammatory or regulatory immune environment in the host, may promote colonisation of the bovine intestine with VTEC O157. Here we assess whether it is statistically feasible to augment a prospective study to quantify the prevalence of VTEC O157 in cattle in Great Britain with a pilot study to test this hypothesis. We simulate data under the framework of a mixed-effects logistic regression model in order to calculate the power to detect an association effect size (odds ratio) of 2. In order to reduce the resources required for such a study, we exploit the fact that the test results for VTEC O157 will be known in advance of testing for F. hepatica by restricting analysis to farms with a VTEC O157 sample prevalence of >0% and <100%. From a total of 270 farms (mean 27 cows per farm) that will be tested for VTEC O157, power of 87% can be achieved, whereby testing of F. hepatica would only be necessary for an expected 50 farms, thus considerably reducing costs. Pre-study sample size calculations are an important part of any study design. The framework developed here is applicable to the study of other co-infections