The present paper introduces a simple aggregated reserving model based on claim count and payment dynamics, which allows for claim closings and re-openings. The modelling starts off from individual Poisson process claim dynamics in discrete time, keeping track of accident year, reporting year and payment delay. This modelling approach is closely related to the one underpinning the so-called double chain-ladder model, and it allows for producing separate reported but not settled and incurred but not reported reserves. Even though the introduction of claim closings and re-openings will produce new types of dependencies, it is possible to use flexible parametrisations in terms of, for example, generalised linear models (GLM) whose parameters can be estimated based on aggregated data using quasi-likelihood theory. Moreover, it is possible to obtain interpretable and explicit moment calculations, as well as having consistency of normalised reserves when the number of contracts tend to infinity. Further, by having access to simple analytic expressions for moments, it is computationally cheap to bootstrap the mean squared error of prediction for reserves. The performance of the model is illustrated using a flexible GLM parametrisation evaluated on non-trivial simulated claims data. This numerical illustration indicates a clear improvement compared with models not taking claim closings and re-openings into account. The results are also seen to be of comparable quality with machine learning models for aggregated data not taking claim openness into account.

China and the US are two contrasting countries in terms of functional disability and long-term care. China is experiencing declining family support for long-term care and developing private long-term care insurance. The US has a more developed public aged care system and private long-term care insurance market than China. Changes in the demand for long-term care are driven by the levels, trends and uncertainty in mortality and functional disability. To understand the future potential demand for long-term care, we compare mortality and functional disability experiences in China and the US, using a multi-state latent factor intensity model with time trends and systematic uncertainty in transition rates. We estimate the model with the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and the US Health and Retirement Study (HRS) data. The estimation results show that if trends continue, both countries will experience longevity improvement with morbidity compression and a declining proportion of the older population with functional disability. Although the elderly Chinese have a shorter estimated life expectancy, they are expected to spend a smaller proportion of their future lifetime functionally disabled than the elderly Americans. Systematic uncertainty is shown to be significant in future trends in disability rates and our model estimates higher uncertainty in trends for the Chinese elderly, especially for urban residents.

The public health measures implemented to control coronavirus disease 2019 (COVID-19) may influence also other infectious diseases. Using national laboratory surveillance data, we assessed the impact of the COVID-19 pandemic on human salmonellosis in the Netherlands until March 2021. Salmonellosis incidence decreased significantly after March 2020: in the second, third and fourth quarters of 2020, and in the first quarter of 2021, the incidence decreased by 55%, 57%, 47% and 37%, respectively, compared to the same quarters of 2016–2019. The decrease was strongest among travel-related cases (94%, 84%, 79% and 93% in the aforementioned quarters, respectively). Other significant changes were: increased proportion of cases among older adults and increased proportion of invasive infections, decreased proportion of trimethoprim resistance and increased proportion of serovar Typhimurium monophasic variant vs. Enteritidis. This led to decreased contributions of laying hens and increased contributions of pigs and cattle as sources of human infections. The observed changes probably reflect a combination of reduced exposure to Salmonella due to restrictions on international travels and gatherings, closure of dine-in restaurants, catering and hospitality sectors at large and changes in healthcare-seeking and diagnostic behaviours.

We quantified the potential impact of different social distancing and self-isolation scenarios on the coronavirus disease 2019 (COVID-19) pandemic trajectory in Saudi Arabia and compared the modelling results to the confirmed epidemic trajectory. Using the susceptible, exposed, infected, quarantined and self-isolated, requiring hospitalisation, recovered/immune individuals, fatalities model, we assessed the impact of a non-pharmacological interventions’ subset. An unmitigated scenario (baseline), mitigation scenarios (25% reduction in social contact/twofold increase in self-isolation) and enhanced mitigation scenarios (50% reduction in social contact/twofold increase in self-isolation) were assessed and compared to the actual epidemic trajectory. For the unmitigated scenario, mitigation scenarios, enhanced mitigation scenarios and actual observed epidemic, the peak daily incidence rates (per 10 000 population) were 77.00, 16.00, 9.00 and 1.14 on days 71, 54, 35 and 136, respectively. The peak fatality rates were 35.00, 13.00, 5.00 and 0.016 on days 150, 125, 60 and 155, respectively. The R0 was 1.15, 1.14, 1.22 and 2.50, respectively. Aggressive implementation of social distancing and self-isolation contributed to the downward trend of the disease. We recommend using extensive models that comprehensively consider the natural history of COVID-19, social and behavioural patterns, age-specific data, actual network topology and population to elucidate the epidemic's magnitude and trajectory.

This study aimed to describe the incidence of Streptococcus bovis/Streptococcus equinus complex (SBSEC) bacteremia, distribution of the SBSEC subspecies, and their respective association with colorectal cancer (CRC). A population-based retrospective cohort study of all episodes of SBSEC-bacteremia from 2003 to 2018 in Skåne Region, Sweden. Subspecies was determined by whole-genome sequencing. Medical charts were reviewed. The association between subspecies and CRC were analysed using logistic regression. In total 266 episodes of SBSEC-bacteremia were identified and the average annual incidence was 2.0 per 100 000 inhabitants. Of the 236 isolates available for typing, the most common subspecies was S. gallolyticus subsp. pasteurianus 88/236 (37%) followed by S. gallolyticus subsp. gallolyticus 58/236 (25%). In order to determine the risk of cancer following bacteremia, an incidence cohort of 174 episodes without a prior diagnosis of CRC or metastasised cancer was followed for 560 person-years. CRC was found in 13/174 (7%), of which 9 (69%) had S. gallolyticus subsp. gallolyticus-bacteremia. In contrast to other European studies, S. gallolyticus subsp. pasteurianus was the most common cause of SBSEC-bacteremia. CRC diagnosis after bacteremia was strongly associated with S. gallolyticus subsp. gallolyticus-bacteremia. Identification of SBSEC subspecies can guide clinical decision-making regarding CRC work-up following bacteremia.

Let $\mathrm{AP}_k=\{a,a+d,\ldots,a+(k-1)d\}$ be an arithmetic progression. For $\varepsilon>0$ we call a set $\mathrm{AP}_k(\varepsilon)=\{x_0,\ldots,x_{k-1}\}$ an $\varepsilon$-approximate arithmetic progression if for some a and d, $|x_i-(a+id)|<\varepsilon d$ holds for all $i\in\{0,1\ldots,k-1\}$. Complementing earlier results of Dumitrescu (2011, J. Comput. Geom. 2(1) 16–29), in this paper we study numerical aspects of Van der Waerden, Szemerédi and Furstenberg–Katznelson like results in which arithmetic progressions and their higher dimensional extensions are replaced by their $\varepsilon$-approximation.

Due to the importance of generalized order statistics (GOS) in many branches of Statistics, a wide interest has been shown in investigating stochastic comparisons of GOS. In this article, we study the likelihood ratio ordering of $p$-spacings of GOS, establishing some flexible and applicable results. We also settle certain unresolved related problems by providing some useful lemmas. Since we do not impose restrictions on the model parameters (as previous studies did), our findings yield new results for comparison of various useful models of ordered random variables including order statistics, sequential order statistics, $k$-record values, Pfeifer's record values, and progressive Type-II censored order statistics with arbitrary censoring plans. Some results on preservation of logconvexity properties among spacings are provided as well.

Artificial intelligence (AI) systems are playing an overarching role in the disinformation phenomenon our world is currently facing. Such systems boost the problem not only by increasing opportunities to create realistic AI-generated fake content, but also, and essentially, by facilitating the dissemination of disinformation to a targeted audience and at scale by malicious stakeholders. This situation entails multiple ethical and human rights concerns, in particular regarding human dignity, autonomy, democracy, and peace. In reaction, other AI systems are developed to detect and moderate disinformation online. Such systems do not escape from ethical and human rights concerns either, especially regarding freedom of expression and information. Having originally started with ascending co-regulation, the European Union (EU) is now heading toward descending co-regulation of the phenomenon. In particular, the Digital Services Act proposal provides for transparency obligations and external audit for very large online platforms’ recommender systems and content moderation. While with this proposal, the Commission focusses on the regulation of content considered as problematic, the EU Parliament and the EU Council call for enhancing access to trustworthy content. In light of our study, we stress that the disinformation problem is mainly caused by the business model of the web that is based on advertising revenues, and that adapting this model would reduce the problem considerably. We also observe that while AI systems are inappropriate to moderate disinformation content online, and even to detect such content, they may be more appropriate to counter the manipulation of the digital ecosystem.

Compressible magnetohydrodynamic (MHD) turbulence is a common feature of astrophysical systems such as the solar atmosphere and interstellar medium. Such systems are rife with shock waves that can redistribute and dissipate energy. For an MHD system, three broad categories of shocks exist (slow, fast, and intermediate); however, the occurrence rates of each shock type are not known for turbulent systems. Here, we present a method for detecting and classifying the full range of MHD shocks applied to the Orszag–Tang vortex. Our results show that the system is dominated by fast and slow shocks, with far less-frequent intermediate shocks appearing most readily near magnetic reconnection sites. We present a potential mechanism that could lead to the formation of intermediate shocks in MHD systems, and study the coherency and abundances of shocks in compressible MHD turbulence.

Evidence demonstrates increased vulnerability to thoughts and behaviors related to suicide (i.e., suicidal ideation) in students. This study examined the interaction between insomnia-symptoms and student-status (students vs. non-students) on reports of suicidal thoughts of behaviors. A total of 363 (N = 363) university students and 300 (N = 300) members of the general population provided complete data on measures of insomnia-symptoms and suicidal ideation. Students indicated greater reports of both total and lifetime ideation while also considering suicidal behavior within the past year. However, no differences were observed in reports of possible future attempt(s) and the disclosure of suicidal thoughts and behaviors to another person. Moreover, students presenting concurrent symptoms of insomnia reported significantly elevated levels of suicidal ideation relative to nonstudents. These outcomes highlight the possible role of insomnia symptoms in accentuating suicidal thoughts and behaviors in the student population.

Proton electrochemical gradient-driven multidrug efflux activity of representatives of the major facilitator superfamily (MFS) of secondary active transporters contributes to antimicrobial resistance of pathogenic bacteria. Integral to the mechanism of these transporters is a proposed competition between substrate and protons for the binding site of the protein. The current work investigated the competition between protons and antimicrobial substrate for binding to the Escherichia coli MFS multidrug/H+ antiporter MdtM by measuring the quench of intrinsic protein fluorescence upon titration of substrate tetraphenylphosphonium into a solution of purified MdtM over a range of pH values between pH 8.8 and 5.9. The results, which revealed that protons inhibit binding of substrate to MdtM in a competitive manner, are consistent with those reported in a study on the related MFS multidrug/H+ antiporter MdfA and provide further evidence that competition for binding between substrate and protons is a general feature of secondary multidrug efflux.

We consider fragmentation processes with values in the space of marked partitions of $\mathbb{N}$, i.e. partitions where each block is decorated with a nonnegative real number. Assuming that the marks on distinct blocks evolve as independent positive self-similar Markov processes and determine the speed at which their blocks fragment, we get a natural generalization of the self-similar fragmentations of Bertoin (Ann. Inst. H. Poincaré Prob. Statist. 38, 2002). Our main result is the characterization of these generalized fragmentation processes: a Lévy–Khinchin representation is obtained, using techniques from positive self-similar Markov processes and from classical fragmentation processes. We then give sufficient conditions for their absorption in finite time to a frozen state, and for the genealogical tree of the process to have finite total length.

This paper investigates the ordering properties of largest claim amounts in heterogeneous insurance portfolios in the sense of some transform orders, including the convex transform order and the star order. It is shown that the largest claim amount from a set of independent and heterogeneous exponential claims is more skewed than that from a set of independent and homogeneous exponential claims in the sense of the convex transform order. As a result, a lower bound for the coefficient of variation of the largest claim amount is established without any restrictions on the parameters of the distributions of claim severities. Furthermore, sufficient conditions are presented to compare the skewness of the largest claim amounts from two sets of independent multiple-outlier scaled claims according to the star order. Some comparison results are also developed for the multiple-outlier proportional hazard rates claims. Numerical examples are presented to illustrate these theoretical results.

Drawdown/regret times feature prominently in optimal stopping problems, in statistics (CUSUM procedure), and in mathematical finance (Russian options). Recently it was discovered that a first passage theory with more general drawdown times, which generalize classic ruin times, may be explicitly developed for spectrally negative Lévy processes [9, 20]. In this paper we further examine the general drawdown-related quantities in the (upward skip-free) time-homogeneous Markov process, and then in its (general) tax process by noticing the pathwise connection between general drawdown and the tax process.

In this paper we study the allocation problem of relevations in coherent systems. The optimal allocation strategies are obtained by implementing stochastic comparisons of different policies according to the usual stochastic order and the hazard rate order. As special cases of relevations, the load-sharing and minimal repair policies are further investigated. Sufficient (and necessary) conditions are established for various stochastic orderings. Numerical examples are also presented as illustrations.

Ethnoveterinary use of plants dates back to ancient times. This study aimed to validate purported efficacy of Sericocomopsis hildebrandtii and a concoction of Carissa edulis and Ximenia americana in treating Taenia solium cysticercosis in pigs. Twenty-four infected pigs were randomly allocated to T1, T2, and T0 groups, each with eight pigs. Each T1 pig was provided with 8 g of S. hildebrandtii root powder, whereas each T2 pig was given 8 g of the concoction. T0 was a control. The pigs were slaughtered 16 weeks post treatment and carcase dissections were performed to establish cyst numbers. T1 cyst numbers were significantly lower than those of T0 (p = .004) and T2 (p = .013). No difference was observed between T2 and T0. This study validated efficacy of S. hildebrandtii but not of X. americana and C. edulis. Further studies are necessary for validation and documentation of plants of ethnoveterinary importance.

Let $\mathbf{X}$ be a $p\times n$ random matrix whose entries are independent and identically distributed real random variables with zero mean and unit variance. We study the limiting behaviors of the 2-normal condition number k(p,n) of $\mathbf{X}$ in terms of large deviations for large n, with p being fixed or $p=p(n)\rightarrow\infty$ with $p(n)=o(n)$. We propose two main ingredients: (i) to relate the large-deviation probabilities of k(p,n) to those involving n independent and identically distributed random variables, which enables us to consider a quite general distribution of the entries (namely the sub-Gaussian distribution), and (ii) to control, for standard normal entries, the upper tail of k(p,n) using the upper tails of ratios of two independent $\chi^2$ random variables, which enables us to establish an application in statistical inference.

We revisit the forward algorithm, developed by Irle, to characterize both the value function and the stopping set for a large class of optimal stopping problems on continuous-time Markov chains. Our objective is to renew interest in this constructive method by showing its usefulness in solving some constrained optimal stopping problems that have emerged recently.

Random intersection graphs model networks with communities, assuming an underlying bipartite structure of communities and individuals, where these communities may overlap. We generalize the model, allowing for arbitrary community structures within the communities. In our new model, communities may overlap, and they have their own internal structure described by arbitrary finite community graphs. Our model turns out to be tractable. We analyze the overlapping structure of the communities, show local weak convergence (including convergence of subgraph counts), and derive the asymptotic degree distribution and the local clustering coefficient.