Predicting the number of COVID-19 cases from the reported number of deaths

The new corona virus disease 2019 (COVID-2019) is rapidly spreading through the world. With insufficient testing, available case data may underestimate the total number of infections. We statistically estimated the cumulative number of cases with confidence intervals from the reported number of deaths, assuming that the number of infections grow exponentially with a constant doubling time. Our findings indicate that the number of unreported infections is likely at least one order of magnitude higher than the reported cases, in particular in the United States and the United Kingdom. This finding is supported by a recent mass screening for SARS-CoV-2 in Iceland which found that the actual case numbers may be about 20 times higher than the officially reported number

Development and psychometric testing of a barriers to HIV testing scale among individuals with HIV infection in Sweden; The Barriers to HIV testing scale-Karolinska version

© 2015 Wiklander et al. Background: Barriers to HIV testing experienced by individuals at risk for HIV can result in treatment delay and further transmission of the disease. Instruments to systematically measure barriers are scarce, but could contribute to improved strategies for HIV testing. Aims of this study were to develop and test a barriers to HIV testing scale in a Swedish context. Methods: An 18-item scale was developed, based on an existing scale with addition of six new items related to fear of the disease or negative consequences of being diagnosed as HIV-infected. Items were phrased as statements about potential barriers with a three-point response format representing not important, somewhat important, and very important. The scale was evaluated regarding missing values, floor and ceiling effects, exploratory factor analysis, and internal consistencies. Results: The questionnaire was completed by 292 adults recently diagnosed with HIV infection, of whom 7 were excluded (≥9 items missing) and 285 were included (≥12 items completed) in the analyses. The participants were 18-70 years old (mean 40.5, SD 11.5), 39 % were females and 77 % born outside Sweden. Routes of transmission were heterosexual transmission 63 %, male to male sex 20 %, intravenous drug use 5 %, blood product/transfusion 2 %, and unknown 9 %. All scale items had <3 % missing values. The data was feasible for factor analysis (KMO = 0.92) and a four-factor solution was chosen, based on level of explained common variance (58.64 %) and interpretability of factor structure. The factors were interpreted as; personal consequences, structural barriers, social and economic security, and confidentiality. Ratings on the minimum level (suggested barrier not important) were common, resulting in substantial floor effects on the scales. The scales were internally consistent (Cronbach's aα 0.78-0.91). Conclusions: This study gives preliminary evidence of the scale being feasible, reliable and valid to identify different types of barriers to HIV testing

Biodiversity loss through speciation collapse: Mechanisms, warning signals, and possible rescue

Speciation is the process that generates biodiversity, but recent empirical findings show that it can also fail, leading to the collapse of two incipient species into one. Here, we elucidate the mechanisms behind speciation collapse using a stochastic individual-based model with explicit genetics. We investigate the impact of two types of environmental disturbance: deteriorated visual conditions, which reduce foraging ability and impede mate choice, and environmental homogenization, which restructures ecological niches. We find that: (1) Species pairs can collapse into a variety of forms including new species pairs, monomorphic or polymorphic generalists, or single specialists. Notably, polymorphic generalist forms may be a transient stage to a monomorphic population; (2) Environmental restoration enables species pairs to re-emerge from single generalist forms, but not from single specialist forms; (3) Speciation collapse is up to four orders of magnitude faster than speciation, while the re-emergence of species pairs can be as slow as de novo speciation; (4) While speciation collapse can be predicted from either demographic, phenotypic, or genetic signals, observations of phenotypic changes allow the most general and robust warning signal of speciation collapse. We conclude that factors altering ecological niches can reduce biodiversity by reshaping the ecosystem's evolutionary attractors

Determining selection across heterogeneous landscapes: a perturbation-based method and its application to modeling evolution in space

Spatial structure can decisively influence the way evolutionary processes unfold. Several methods have thus far been used to study evolution in spatial systems, including population genetics, quantitative genetics, momentclosure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply in both continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very effi- cient, and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations

Modeling the ecology and evolution of communities: A review of past achievements, current efforts, and future promises

Background: The complexity and dynamical nature of community interactions make modeling a useful tool for understanding how communities develop over time and how they respond to external perturbations. Large community-evolution models (LCEMs) are particularly promising, since they can address both ecological and evolutionary questions, and can give rise to richly structured and diverse model communities. Questions: Which types of models have been used to study community structure and what are their key features and limitations? How do adaptations and/or invasions affect community formation? Which mechanisms promote diverse and table communities? What are the implications of LCEMs for management and conservation? What are the key challenges for future research? Models considered: Static models of community structure, demographic community models, and small and large community- evolution models. Conclusions: LCEMs encompass a variety of modeled traits and interactions, demographic dynamics, and evolutionary dynamics. They are able to reproduce empirical community structures. Already, they have generated new insights, such as the dual role of competition, which limits diversity through competitive exclusion, yet facilitates diversity through speciation. Other critical factors determining eventual community structure are the shape of trade-off functions, inclusion of adaptive foraging, and energy availability. A particularly interesting feature of LCEMs is that these models not only help to contrast outcomes of community formation via species assembly with those of community formation via gradual evolution and speciation, but that they can furthermore unify the underlying invasion processes and evolutionary processes into a single framework

A Method for Estimating the Number of Infections From the Reported Number of Deaths

At the outset of an epidemic, available case data typically underestimate the total number of infections due to insufficient testing, potentially hampering public responses. Here, we present a method for statistically estimating the true number of cases with confidence intervals from the reported number of deaths and estimates of the infection fatality ratio; assuming that the time from infection to death follows a known distribution. While the method is applicable to any epidemic with a significant mortality rate, we exemplify the method by applying it to COVID-19. Our findings indicate that the number of unreported COVID-19 infections in March 2020 was likely to be at least one order of magnitude higher than the reported cases, with the degree of underestimation among the countries considered being particularly high in the United Kingdom

Differentiation and displacement: Unpicking the relationship between accounts of illness and social structure

This article seeks to unpack the relationship between social structure and accounts of illness. Taking dentine hypersensitivity as an example, this article explores the perspective that accounts of illness are sense-making processes that draw on a readily available pool of meaning. This pool of meaning is composed of a series of distinctions that make available a range of different lines of communication and action about such conditions. Such lines of communication are condensed and preserved over time and are often formed around a concept and its counter concept. The study of such processes is referred to as semantic analysis and involves drawing on the tools and techniques of conceptual history. This article goes on to explore how the semantics of dentine hypersensitivity developed. It illustrates how processes of social differentiation led to the concept being separated from the more dominant concept of dentine sensitivity and how it was medicalised, scientised and economised. In short, this study seeks to present the story of how society has developed a specific language for communicating about sensitivity and hypersensitivity in teeth. In doing so, it proposes that accounts of dentine hypersensitivity draw on lines of communication that society has preserved over time

Climate change may enable Aedes aegypti infestation in major European cities by 2100

Background Climate change allows Aedes aegypti to infest new areas. Consequently, it enables the arboviruses the mosquito transmits ­- e.g., dengue, chikungunya, Zika and yellow fever -- to emerge in previously uninfected areas. An example is the Portuguese island of Madeira during 2012-13. Objective We aim to understand how climate change will affect the future spread of this potent vector, as an aid in assessing the risk of disease outbreaks and effectively allocating resources for vector control. Methods We used an empirically-informed, process-based mathematical model to study the feasibility of Aedes aegypti infestation into continental Europe. Based on established global climate-change scenario data, we assess the potential of Aedes aegypti to establish in Europe over the 21st century by estimating the vector population growth rate for five climate models (GCM5). Results In a low carbon emission future (RCP2.6), we find minimal change to the current situation throughout the whole of the 21st century. In a high carbon future (RCP8.5), a large parts of southern Europe risks being invaded by Aedes aegypti. Conclusion Our results show that successfully enforcing the Paris Agreement by limiting global warming to below 2 °C significantly lowers the risk for infestation of Aedes aegypti and consequently of potential large-scale arboviral disease outbreaks in Europe within the 21st century