Despite consistent public health efforts, the burden of viral disease in India remains high. The present study was undertaken to understand the aetiology, frequency and distribution of viral disease outbreaks in the state of Odisha between 2010 and 2019. This was a prospective study conducted at the Virology Research and Diagnostic Laboratory located at ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, wherein all the outbreaks of viral aetiologies were investigated and analysed to provide a comprehensive picture of the state of viral disease outbreaks in the region. A total of 191 suspected viral outbreaks were investigated by the team from VRDL during September 2010 and September 2019 reported from all the 30 districts of Odisha. Annual number of suspected cases ranged from 185 to 1002. The most commonly suspected outbreaks were of viral hepatitis (55 outbreaks; 1223 cases) followed by dengue (45 outbreaks; 1185 cases), chickenpox (30 outbreaks; 421 cases), viral encephalitis (27 outbreaks; 930 cases), measles (23 outbreaks; 464 cases), chikungunya (10 outbreaks; 593 cases) and rubella (1 outbreak; 60). The outbreaks peaked in frequency and intensity during the months of July and September. The epidemiology of viral disease outbreaks in the region is presented in the study. Health system preparedness based on evidence is essential for early detection and adequate response to such viral outbreaks.

In November 2017, Public Health England identified an outbreak of Shiga toxin-producing Escherichia coli O157:H7 in England where whole genome sequencing results indicated cases were likely to be linked to a common source, and began investigations. Hypothesis generation included a review of enhanced surveillance data, a case-case study and trawling interviews. The hypothesis of interest was tested through the administration of focussed questionnaires and review of shopping history using loyalty card data. Twelve outbreak cases were detected, eight were hospitalised and four developed haemolytic uraemic syndrome. Frozen beef burgers supplied by a national retailer were identified as the vehicle of the outbreak. Testing of two left-over burger samples obtained from the freezers of two separate (unlinked) cases and a retained sample from the production premises were tested and found to be positive for the outbreak strain. A voluntary recall of the burgers was implemented by the retailer. Investigations at the production premises identified no contraventions of food safety legislation. Cooking guidance on the product packaging was deemed to be adequate and interviews with the cases/carers who prepared the burgers revealed no deficiencies in cooking practices at home. Given the long-shelf life of frozen burgers, the product recall likely prevented more cases.

We show that, for a constant-degree algebraic curve γ in ℝD, every set of n points on γ spans at least Ω(n4/3) distinct distances, unless γ is an algebraic helix, in the sense of Charalambides [2]. This improves the earlier bound Ω(n5/4) of Charalambides [2].

We also show that, for every set P of n points that lie on a d-dimensional constant-degree algebraic variety V in ℝD, there exists a subset S ⊂ P of size at least Ω(n4/(9+12(d−1))), such that S spans $\left({\begin{array}{*{20}{c}} {|S|} \\ 2 \\\end{array}} \right)$ distinct distances. This improves the earlier bound of Ω(n1/(3d)) of Conlon, Fox, Gasarch, Harris, Ulrich and Zbarsky [4].

Both results are consequences of a common technical tool.

This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture.

There is limited information concerning the viral load of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in aerosols deposited on environmental surfaces and the effectiveness of infection prevention and control procedures on eliminating SARS-CoV-2 contamination in hospital settings. We examined the concentration of SARS-CoV-2 in aerosol samples and on environmental surfaces in a hospital designated for treating severe COVID-19 patients. Aerosol samples were collected by a microbial air sampler, and environmental surfaces were sampled using sterile premoistened swabs at multiple sites. Ninety surface swabs and 135 aerosol samples were collected. Only two swabs, sampled from the inside of a patient's mask, were positive for SARS-CoV-2 RNA. All other swabs and aerosol samples were negative for the virus. Our study indicated that strict implementation of infection prevention and control procedures was highly effective in eliminating aerosol and environmental borne SARS-CoV-2 RNA thereby reducing the risk of cross-infection in hospitals.

We compare results for 12 multi-population mortality models fitted to 10 distinct socio-economic groups in England, subdivided using the Index of Multiple Deprivation. Using the Bayes Information Criterion to compare models, we find that a special case of the common age effect (CAE) model fits best in a variety of situations, achieving the best balance between goodness of fit and parsimony. We provide a detailed discussion of key models to highlight which features are important. Group-specific period effects are found to be more important than group-specific age effects, and non-parametric age effects deliver significantly better results than parametric (e.g. linear) age effects. We also find that the addition of cohort effects is beneficial in some cases but not all. The preferred CAE model has the additional benefit of being coherent in the sense of Hyndman et al. ((2013) Demography50(1), 261–283); some of the other models considered are not.

Internet of Things (IoT) devices such as connected sensors are increasingly being used in the public sector, often deployed and collecting data in public spaces. A theme commonly seen in the rhetoric surrounding public space IoT initiatives is empowerment, and these deployments are broadly perceived as beneficial by policy makers. However, such technology presents new governance challenges. It is important to ask who is empowered and who benefits, and we must ensure that such technological interventions follow democratic principles and are trusted by citizens. In this paper, we investigate how risk, transparency, and data governance require careful consideration in this domain, describing work which investigates how these combine to form components of trusted IoT ecosystems. This includes an overview of the landscape of public space IoT deployments, consideration of how they may often be subsumed in idealized smart city focused rhetoric, and discussion of how methodologies such as design fiction in community settings can uncover potential risks and concerns. Our findings suggest that agency, value and intent associated with IoT systems are key components that must be made transparent, particularly when multiple actors and stakeholders are involved. We suggest that good governance requires consideration of these systems in their entirety, throughout the full planning, implementation, and evaluation process, and in consultation with multiple stakeholders who are impacted, including the public. To achieve this effectively, we argue for transparency at the device and system level, which may require legislative change.

Social relationships are important among persons experiencing homelessness, but there is little research on changes in social networks among persons moving into permanent supportive housing (PSH). Using data collected as part of a longitudinal study of 405 adults (aged 39+) moving into PSH, this study describes network upheaval during this critical time of transition. Interviews conducted prior to and after three months of living in PSH assessed individual-level (demographics, homelessness history, health, and mental health) and social network characteristics, including network size and composition (demographics, relationship type, and social support). Interviewers utilized network member characteristics to assess whether network members were new or sustained between baseline and three months post-housing. Multilevel logistic regression models assessed characteristics of network members associated with being newly gained or persisting in networks three months after PSH move-in. Results show only one-third of social networks were retained during the transition to PSH, and veterans, African Americans, and other racial/ethnic minorities, and those living in scattered site housing, were more likely to experience network disruption. Relatives, romantic partners, and service providers were most likely to be retained after move-in. Some network change was moderated by tie strength, including the retention of street-met persons. Implications are discussed.

We derive optimal portfolio choice patterns in retirement (ages 66–105) for a constant relative risk aversion utility maximisinginvestor facing risky capital market returns, stochastic mortality risk, and income-reducing health shocks. Beyond the usual stocks and bonds, the individual can invest his assets in tontines. Tontines are cost-efficient financial contracts providing age-increasing, but volatile cash flows, generated through the pooling of mortality without guarantees, which can help to match increasing financing needs at old ages. We find that a tontine invested in the risk-free asset dominates stock investments for older investors without a bequest motive. However, with a bequest motive, it is optimal to replace the tontine investment over time with traditional financial assets. Our results indicate that early in retirement, a tontine is only an attractive investment option, if the tontine funds are invested in a risky asset. In this case, they crowd out stocks and risk-free bonds in the optimal portfolios of younger investors. Over time, the average optimal portfolio weight of tontines decreases. Introducing systematic mortality risks noticeably reduces the peak allocation to tontines.

We consider the conditional mean risk allocation for an insurance pool, as defined by Denuit and Dhaene (2012). Precisely, we study the asymptotic behavior of the respective relative contributions of the participants as the total loss of the pool tends to infinity. The numerical illustration in Denuit (2019) suggests that the application of the conditional mean risk sharing rule may produce a linear sharing in the tail of the total loss distribution. This paper studies the validity of this empirical finding in the class of compound Panjer–Katz sums consisting of compound Binomial, compound Poisson, and compound Negative Binomial sums with either Gamma or Pareto severities. It is demonstrated that such a behavior does not hold in general since one term may dominate the other ones conditional of large total loss.

If the general level of house prices falls a long way, policymakers may introduce new policies which seek to support prices. This paper considers the effect of such interventions on the valuation of no-negative-equity guarantees (NNEG) in equity release mortgages. I model interventions by a reflecting barrier expressed as a fraction of the current level of house prices. Reflection at the barrier is instantaneous, so the no-arbitrage property is preserved, and hence risk-neutral valuation of NNEG is possible. The reflecting barrier can alternatively be justified as a representation of the different economic nature of the underlying housing (and particularly freehold land) assets in NNEG valuations, compared with the underlying equity assets in many other option valuations.

This paper investigates the processes involved when newly hired employees need to simultaneously build up and mobilize personal network ties during their organizational socialization. It focuses on the quality of ties at an early formative stage, characterized by the lack of a tie history between actors. Social capital theory would suggest that such nascent ties do not offer optimal channels for the kind and volume of resources that newcomers (need to) rely on during socialization. To better understand how this apparent mismatch between tie quality and resource needs is handled from an ego-centered perspective, the paper analyzes personal network data from 24 newcomers in nine organizations, using an adapted form of Qualitative Structural Analysis. Three tie-level qualities are found to explain how the lack of tie history may be alleviated, circumvented, or compensated. They comprise (a) variants of openness experienced with stronger ties, (b) perceptions of a lowered threshold towards weaker ties, and (c) sources of legitimacy regarding latent ties. Based on these findings, the paper presents an integrated conceptual model to clarify how nascent ties offer channels for network resources during socialization and discusses the need for further research on the role of specific moderators for the investigated processes.

Type I/II interferons (IFNα,β/IFNɣ) are cytokines that activate signal-transducer-and-activator-of-transcription-1 (STAT1). The STAT1 N-terminal domain (NTD) mediates dimerization and cooperative DNA-binding. The STAT1 DNA-binding domain (DBD) confers sequence-specific DNA-recognition. STAT1 has been connected to growth inhibition, replication stress and DNA-damage. We investigated how STAT1 and NTD/DBD mutants thereof affect fibrosarcoma cells. STAT1 and indicated mutants do not affect proliferation of resting and IFNα-treated cells as well as checkpoint kinase signaling, and phosphorylation of the tumor-suppressive transcription factor p53 ensuing ɣ-irradiation. Of the STAT1 reconstituted U3A cells those with STAT1 NTD mutants accumulate the highest levels of the replication stress/DNA-damage marker S139-phosphorylated histone H2AX (ɣH2AX). This is similarly seen with a STAT1 NTD/DBD double mutant, indicating transcription-independent effects. Furthermore, U3A cells with STAT1 NTD mutants are most susceptible to apoptotic DNA fragmentation and cleavage of the DNA repair protein PARP1. These data provide novel insights into the relevance of the STAT1 NTD.

In recent years the availability of geolocation data has increased considerably and can be found in various portable devices such as smartphones. These devices are intended for navigation in general, but can be used to carry out topographical surveys that do not require high accuracy of the surveyed data. To verify the applicability and accuracy of these devices we conducted the topographic survey in an area of approximately 5 ha using a GPS with RTK technology as reference, a Commercial Navigation Receiver (RNC) and a popular brand smartphone with the mobile applications C7 GPS Data and GPS Essentials previously installed. The GPS RNC showed the best planimetric results and the Smartphone with C7 GPS Data obtained the best result altimetric. None of the receivers analyzed showed high accuracy in results obtained. However, they can be used for tasks where high precision is not required.

In December 2019, cases of severe coronavirus 2019 (COVID-19) infection rapidly progressed to acute respiratory failure. This study aims to assess the association between the neutrophil-to-lymphocyte ratio (NLR) and the incidence of severe COVID-19 infection. A retrospective cohort study was conducted on 210 patients with COVID-19 infection who were admitted to the Central Hospital of Wuhan from 27 January 2020 to 9 March 2020. Peripheral blood samples were collected and examined for lymphocyte subsets by flow cytometry. Associations between tertiles of NLR and the incidence of severe illness were analysed by logistic regression.

Of the 210 patients with COVID-19, 87 were diagnosed as severe cases. The mean NLR of the severe group was higher than that of the mild group (6.6 vs. 3.3, P < 0.001). The highest tertile of NLR (5.1–19.7) exhibited a 5.9-fold (95% CI 1.3–28.5) increased incidence of severity relative to that of the lowest tertile (0.6–2.5) after adjustments for age, diabetes, hypertension and other confounders. The number of T cells significantly decreased in the severe group (0.5 vs. 0.9, P < 0.001). COVID-19 might mainly act on lymphocytes, particularly T lymphocytes. NLR was identified as an early risk factor for severe COVID-19 illness. Patients with increased NLR should be admitted to an isolation ward with respiratory monitoring and supportive care.

Coronavirus disease 2019 (COVID-19) has resulted in a global pandemic, and there is limited data on effective therapies. Bacillus Calmette–Guérin (BCG) vaccine, a live-attenuated strain derived from an isolate of Mycobacterium bovis and originally designed to prevent tuberculosis, has shown some efficacy against infection with unrelated pathogens. In this study, we reviewed 120 consecutive adult patients (≥18 years old) with COVID-19 at a major federally qualified health centre in Rhode Island, United States from 19 March to 29 April 2020. Median age was 39.5 years (interquartile range, 27.0–50.0), 30% were male and 87.5% were Latino/Hispanics. Eighty-two (68.3%) patients had BCG vaccination. Individuals with BCG vaccination were less likely to require hospital admission during the disease course (3.7% vs. 15.8%, P = 0.019). This association remained unchanged after adjusting for demographics and comorbidities (P = 0.017) using multivariate regression analysis. The finding from our study suggests the potential of BCG in preventing more severe COVID-19.