A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making.

The unprecedented scale of the Ebola outbreak in West Africa has, as of 29 April 2015, resulted in more than 10,884 deaths among 26,277 cases. Prior to the ongoing outbreak, Ebola virus disease (EVD) caused relatively small outbreaks (maximum outbreak size 425 in Gulu, Uganda) in isolated populations in central Africa. Here, we have compiled a comprehensive database of estimates of epidemiological parameters based on data from past outbreaks, including the incubation period distribution, case fatality rate, basic reproduction number (R 0), effective reproduction number (R t) and delay distributions. We have compared these to parameter estimates from the ongoing outbreak in West Africa. The ongoing outbreak, because of its size, provides a unique opportunity to better understand transmission patterns of EVD. We have not performed a meta-analysis of the data, but rather summarize the estimates by virus from comprehensive investigations of EVD and Marburg outbreaks over the past 40 years. These estimates can be used to parameterize transmission models to improve understanding of initial spread of EVD outbreaks and to inform surveillance and control guidelines

Extending backcalculation to analyse BSE data.

We review the origins of backcalculation (or back projection) methods developed for the analysis of AIDS (acquired immunodeficiency syndrome) incidence data. These techniques have been used extensively for >15 years to deconvolute clinical case incidence, given knowledge of the incubation period distribution, to obtain estimates of past HIV (human immunodeficiency virus) infection incidence and short-term predictions of future AIDS incidence. Adaptations required for the analysis of bovine spongiform encephalopathy (BSE) incidence included: stratification of BSE incidence by age as well as birth cohort; allowance for incomplete survival between infection and the onset of clinical signs of disease; and decomposition of the age- and time-related infection incidence into a time-dependent feed risk component and an age-dependent exposure/susceptibility function. The most recent methodological developments focus on the incorporation of data from clinically unaffected cattle screened using recently developed tests for preclinical BSE infection. Backcalculation-based predictions of future BSE incidence obtained since 1996 are examined. Finally, future directions of epidemiological analysis of BSE epidemics are discussed taking into account ongoing developments in the science of BSE and possible changes in BSE-related policies

Do Older Adults Hate Video Games until they Play them? A Proof-of-Concept Study

The issue of negative video game influences on youth remains contentious in public debate, the scholarly community and among policy makers. Recent research has indicated that negative attitudes toward video games are, in part, generational in nature with older adults more inclined to endorse negative beliefs about video games. The current mixed design study examined the impact of exposure to games on beliefs about video games in a small (n = 34) sample of older adults. Results indicated that older adults were more concerned about video games as an abstract concept but when exposed to a particular video game, even an M-rated violent game, expressed fewer concerns about that specific video game. Results support the hypothesis that negative attitudes toward video games exists mainly in the abstract and do not survive direct exposure to individual games. Further, older adults were not uniform in their condemnation of video games with older adults having varying opinions about the harmfulness of video games. Related to specific concerns, older adults tended to worry more about issues such as addiction than they did violent content.<br/

Violent video games and morality: a meta-ethical approach

This paper considers what it is about violent video games that leads one reasonably minded person to declare "That is immoral" while another denies it. Three interpretations of video game content a re discussed: reductionist, narrow, and broad. It is argued that a broad interpretation is required for a moral objection to be justified. It is further argued that understanding the meaning of moral utterances – like "x is immoral" – is important to an understanding of why there is a lack of moral consensus when it comes to the content of violent video games. Constructive ecumenical expressivism is presented as a means of explaining what it is that we are doing when we make moral pronouncements and why, when it comes to video game content, differing moral attitudes abound. Constructive ecumenical expressivism is also presented as a means of illuminating what would be required for moral consensus to be achieved

Understanding disease control: influence of epidemiological and economic factors

We present a local spread model of disease transmission on a regular network and compare different control options ranging from treating the whole population to local control in a well-defined neighborhood of an infectious individual. Comparison is based on a total cost of epidemic, including cost of palliative treatment of ill individuals and preventive cost aimed at vaccination or culling of susceptible individuals. Disease is characterized by pre- symptomatic phase which makes detection and control difficult. Three general strategies emerge, global preventive treatment, local treatment within a neighborhood of certain size and only palliative treatment with no prevention. The choice between the strategies depends on relative costs of palliative and preventive treatment. The details of the local strategy and in particular the size of the optimal treatment neighborhood weakly depends on disease infectivity but strongly depends on other epidemiological factors. The required extend of prevention is proportional to the size of the infection neighborhood, but this relationship depends on time till detection and time till treatment in a non-nonlinear (power) law. In addition, we show that the optimal size of control neighborhood is highly sensitive to the relative cost, particularly for inefficient detection and control application. These results have important consequences for design of prevention strategies aiming at emerging diseases for which parameters are not known in advance

Does the revised cardiac risk index predict cardiac complications following elective lung resection?

Background: Revised Cardiac Risk Index (RCRI) score and Thoracic Revised Cardiac Risk Index (ThRCRI) score were developed to predict the risks of postoperative major cardiac complications in generic surgical population and thoracic surgery respectively. This study aims to determine the accuracy of these scores in predicting the risk of developing cardiac complications including atrial arrhythmias after lung resection surgery in adults. Methods: We studied 703 patients undergoing lung resection surgery in a tertiary thoracic surgery centre. Observed outcome measures of postoperative cardiac morbidity and mortality were compared against those predicted by risk. Results: Postoperative major cardiac complications and supraventricular arrhythmias occurred in 4.8% of patients. Both index scores had poor discriminative ability for predicting postoperative cardiac complications with an area under receiver operating characteristic (ROC) curve of 0.59 (95% CI 0.51-0.67) for the RCRI score and 0.57 (95% CI 0.49-0.66) for the ThRCRI score. Conclusions: In our cohort, RCRI and ThRCRI scores failed to accurately predict the risk of cardiac complications in patients undergoing elective resection of lung cancer. The British Thoracic Society (BTS) recommendation to seek a cardiology referral for all asymptomatic pre-operative lung resection patients with > 3 RCRI risk factors is thus unlikely to be of clinical benefit

Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus

A proposal for ethical research conduct in Madagascar

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. The attached file is the published version of the article

Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April–May, 2018: an epidemiological study

Background On May 8, 2018, the Government of the Democratic Republic of the Congo reported an outbreak of Ebola virus disease in Équateur Province in the northwest of the country. The remoteness of most affected communities and the involvement of an urban centre connected to the capital city and neighbouring countries makes this outbreak the most complex and high risk ever experienced by the Democratic Republic of the Congo. We provide early epidemiological information arising from the ongoing investigation of this outbreak. Methods We classified cases as suspected, probable, or confirmed using national case definitions of the Democratic Republic of the Congo Ministère de la Santé Publique. We investigated all cases to obtain demographic characteristics, determine possible exposures, describe signs and symptoms, and identify contacts to be followed up for 21 days. We also estimated the reproduction number and projected number of cases for the 4-week period from May 25, to June 21, 2018. Findings As of May 30, 2018, 50 cases (37 confirmed, 13 probable) of Zaire ebolavirus were reported in the Democratic Republic of the Congo. 21 (42%) were reported in Bikoro, 25 (50%) in Iboko, and four (8%) in Wangata health zones. Wangata is part of Mbandaka, the urban capital of Équateur Province, which is connected to major national and international transport routes. By May 30, 2018, 25 deaths from Ebola virus disease had been reported, with a case fatality ratio of 56% (95% CI 39–72) after adjustment for censoring. This case fatality ratio is consistent with estimates for the 2014–16 west African Ebola virus disease epidemic (p=0·427). The median age of people with confirmed or probable infection was 40 years (range 8–80) and 30 (60%) were male. The most commonly reported signs and symptoms in people with confirmed or probable Ebola virus disease were fever (40 [95%] of 42 cases), intense general fatigue (37 [90%] of 41 cases), and loss of appetite (37 [90%] of 41 cases). Gastrointestinal symptoms were frequently reported, and 14 (33%) of 43 people reported haemorrhagic signs. Time from illness onset and hospitalisation to sample testing decreased over time. By May 30, 2018, 1458 contacts had been identified, of which 746 (51%) remained under active follow-up. The estimated reproduction number was 1·03 (95% credible interval 0·83–1·37) and the cumulative case incidence for the outbreak by June 21, 2018, is projected to be 78 confirmed cases (37–281), assuming heterogeneous transmissibility. Interpretation The ongoing Ebola virus outbreak in the Democratic Republic of the Congo has similar epidemiological features to previous Ebola virus disease outbreaks. Early detection, rapid patient isolation, contact tracing, and the ongoing vaccination programme should sufficiently control the outbreak. The forecast of the number of cases does not exceed the current capacity to respond if the epidemiological situation does not change. The information presented, although preliminary, has been essential in guiding the ongoing investigation and response to this outbreak

Canalization of the evolutionary trajectory of the human influenza virus

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure