We consider a stochastic SIR (susceptible $\rightarrow$ infective $\rightarrow$ removed) model in which the infectious periods are modulated by a collection of independent and identically distributed Feller processes. Each infected individual is associated with one of these processes, the trajectories of which determine the duration of his infectious period, his contamination rate, and his type of removal (e.g. death or immunization). We use a martingale approach to derive the distribution of the final epidemic size and severity for this model and provide some general examples. Next, we focus on a single infected individual facing a given number of susceptibles, and we determine the distribution of his outcome (number of contaminations, severity, type of removal). Using a discrete-time formulation of the model, we show that this distribution also provides us with an alternative, more stable method to compute the final epidemic outcome distribution.

For smart cities, data-driven innovation promises societal benefits and increased well-being for residents and visitors. At the same time, the deployment of data-driven innovation poses significant ethical challenges. Although cities and other public-sector actors have increasingly adopted ethical principles, employing them in practice remains challenging. In this commentary, we use a virtue-based approach that bridges the gap between abstract principles and the daily work of practitioners who engage in and with data-driven innovation processes. Inspired by Aristotle, we describe practices of data-driven innovation in a smart city applying the concepts of virtue and phronêsis, meaning good judgment of and sensitivity to ethical issues. We use a dialogic case-study approach to study two cases of data-driven innovation in the city of Helsinki. We then describe as an illustration of how our approach can help bridge the gap between concrete practices of data-driven innovation and high-level principles. Overall, we advance a theoretically grounded, virtue-based approach, which is practice oriented and linked to the daily work of data scientists and other practitioners of data-driven innovation. Further, this approach helps understand the need for and importance of individual application of phronêsis, which is particularly important in public-sector organizations that can experience gaps between principle and practice. This importance is further intensified in cases of data-driven innovation in which, by definition, novel and unknown contexts are explored.

We consider a one-dimensional superprocess with a supercritical local branching mechanism $\psi$, where particles move as a Brownian motion with drift $-\rho$ and are killed when they reach the origin. It is known that the process survives with positive probability if and only if $\rho<\sqrt{2\alpha}$, where $\alpha=-\psi'(0)$. When $\rho<\sqrt{2 \alpha}$, Kyprianou et al. [18] proved that $\lim_{t\to \infty}R_t/t =\sqrt{2\alpha}-\rho$ almost surely on the survival set, where $R_t$ is the rightmost position of the support at time t. Motivated by this work, we investigate its large deviation, in other words, the convergence rate of $\mathbb{P}_{\delta_x} (R_t >\gamma t+\theta)$ as $t \to \infty$, where $\gamma >\sqrt{2 \alpha} -\rho$, $\theta \ge 0$. As a by-product, a related Yaglom-type conditional limit theorem is obtained. Analogous results for branching Brownian motion can be found in Harris et al. [13].

A chordal graph is a graph with no induced cycles of length at least $4$. Let $f(n,m)$ be the maximal integer such that every graph with $n$ vertices and $m$ edges has a chordal subgraph with at least $f(n,m)$ edges. In 1985 Erdős and Laskar posed the problem of estimating $f(n,m)$. In the late 1980s, Erdős, Gyárfás, Ordman and Zalcstein determined the value of $f(n,n^2/4+1)$ and made a conjecture on the value of $f(n,n^2/3+1)$. In this paper we prove this conjecture and answer the question of Erdős and Laskar, determining $f(n,m)$ asymptotically for all $m$ and exactly for $m \leq n^2/3+1$.

The prominence of the Euler allocation rule (EAR) is rooted in the fact that it is the only return on risk-adjusted capital (RORAC) compatible capital allocation rule. When the total regulatory capital is set using the value-at-risk (VaR), the EAR becomes – using a statistical term – the quantile-regression (QR) function. Although the cumulative QR function (i.e., an integral of the QR function) has received considerable attention in the literature, a fully developed statistical inference theory for the QR function itself has been elusive. In the present paper, we develop such a theory based on an empirical QR estimator, for which we establish consistency, asymptotic normality, and standard error estimation. This makes the herein developed results readily applicable in practice, thus facilitating decision making within the RORAC paradigm, conditional mean risk sharing, and current regulatory frameworks.

This study aims to evaluate the impact of non-pharmaceutical interventions (NPIs) on the prevalence of respiratory pathogens among hospitalised children with acute respiratory infections (ARIs) in Suzhou. Children with ARIs admitted to the Children’s Hospital of Soochow University between 1 September 2021 and 31 December 2022 and subjected to 13 respiratory pathogen multiplex PCR assays were included in the study. We retrospectively collected demographic details, results of respiratory pathogen panel tests, and discharge diagnostic information of the participants, and described the age and seasonal distribution of respiratory pathogens and risk factors for developing pneumonia. A total of 10,396 children <16 years of age, including 5,905 males and 4,491 females, were part of the study. The positive rates of the 11 respiratory pathogen assays were 23.3% (human rhinovirus (HRV)), 15.9% (human respiratory syncytial virus (HRSV)), 10.5% (human metapneumovirus (HMPV)), 10.3% (human parainfluenza virus (HPIV)), 8.6% (mycoplasma pneumoniae (MP)), 5.8% (Boca), 3.5% (influenza A (InfA)), 2.9% (influenza B (InfB)), 2.7% (human coronavirus (HCOV)), 2.0% (adenovirus (ADV)), and 0.5% (Ch), respectively. Bocavirus and HPIV detection peaked during the period from September to November (autumn), and MP and HMPV peaked in the months of November and December. The peak of InfA detection was found to be in summer (July and August), whereas the InfB peak was observed to be in winter (December, January, and February). HRSV and HRV predominated in the <3 years age group. HRV and HMPV were common in the 3–6 years group, whereas MP was predominant in the ≥6 years group. MP (odds ratio (OR): 70.068, 95%CI: 32.665–150.298, P < 0.01), HMPV (OR: 6.493, 95%CI: 4.802–8.780, P < 0.01), Boca (OR: 3.300, 95%CI: 2.186–4.980, P < 0.01), and HRSV (OR: 2.649, 95%CI: 2.089–3.358, P < 0.01) infections were more likely to develop into pneumonia than the other pathogens. With the use of NPIs, HRV was the most common pathogen in children with ARIs, and MP was more likely to progress to pneumonia than other pathogens.

This article analyzes the theoretical properties of the hybrid test for superior predictive ability. A simple example reveals that the test may not be size-controlled at common significance levels with rejection rates exceeding $11\%$ at a $5\%$ nominal level. Generalizing this observation, the main results show the pointwise asymptotic invalidity of the hybrid test under reasonable conditions. Monte Carlo simulations support these theoretical findings.

The aim of our study was to examine the position of vaccinated people regarding the proposal for mandatory and seasonal vaccination against COVID-19 in Serbia. A cross-sectional study was conducted in a sample of people who came to receive a third dose of COVID-19 at the Institute of Public Health of Serbia in September and October 2021. Data were collected by means of a sociodemographic questionnaire. The study sample comprised 366 vaccinated adults. Factors associated with the belief that vaccination against COVID-19 should become mandatory were being married, being informed about COVID-19 from TV programmes and medical journals, trust in health professionals, and having friends affected by COVID-19. In addition to these predictors, factors associated with the belief that COVID-19 vaccination should become seasonal were being older, consistently wearing facemasks, and not being employed. The results of this study highlight that trust in information delivery, evidence-based data, and healthcare providers may be a major driver of mandatory and seasonal vaccine uptake. A careful assessment of the epidemiological situation, the capacity of the health system, and the risk–benefit ratio is needed in order to introduce seasonal and/or mandatory vaccination against COVID-19.

My 5 moments (M5M) was used less frequently among cleaning staff members, suggesting that a poor compliance score in this group may not indicate deficient handwashing. This quasi-experimental study compared hand hygiene compliance (HHC), hand hygiene (HH) moments, and HH time distribution in the control group (no HH intervention; n = 21), case group 1 (normal M5M intervention; n = 26), case group 2 (extensive novel six moments (NSM) training; n = 24), and case group 3 (refined NSM training; n = 18). The intervention’s effect was evaluated after 3 months. The HHC gap among the four groups gradually increased in the second intervention month (control group, 31.43%; case group 1, 38.74%; case group 2, 40.19%; case group 3, 52.21%; p < 0.05). After the intervention period, the HHC of case groups 2 and 3 improved significantly from the baseline (23.85% vs. 59.22%, 27.41% vs. 83.62%, respectively; p < 0.05). ‘After transferring medical waste from the site’ had the highest HHC in case group 3, 90.72% (95% confidence interval, 0.1926–0.3967). HH peak hours were from 6 AM to 9 AM and 2 PM to 3 PM. The study showed that the implementation of an NSM practice can serve as an HHC monitoring indicator and direct relevant training interventions to improve HH among hospital cleaning staff.

This experimental study aimed to determine the activity of a near-UVA (405 nm) LED ceiling system against the SARS-CoV-2 virus. The ceiling system comprised 17 near-UVA LED lights with a radiant power of 1.1 W/each centred at 405 nm wavelength. A 96-multiwell plate, fixed to a wooden base, was inoculated with suspensions of VERO E6 cell cultures infected with SARS-CoV-2 virus and irradiated at a distance of 40 cm with a dose of 20.2 J/cm2 for 120 min. The collected suspensions were transferred to VERO cell culture plates and incubated for 3 days. The maximum measurable log reduction obtained, starting from a concentration of 107.2 TCID50/mL, was 3.0 log10 and indicated inhibition of SARS-CoV-2 replication by the near-UVA LED ceiling system. Near-UVA light at a 405-nm wavelength is emerging as a potential alternative treatment for localised infections and environmental decontamination because it is far less harmful to living organisms’ cells than UV-C irradiation.

Blastocystis is a protist of controversial pathogenicity inhabiting the gut of humans and other animals. Despite a century of intense study, understanding of the epidemiology of Blastocystis remains fragmentary. Here, we aimed to explore its prevalence, stability of colonisation and association with various factors in a rural elementary school in northern Thailand. One hundred and forty faecal samples were collected from 104 children at two time points (tp) 105 days apart. For tp2, samples were also obtained from 15 animals residing on campus and seven water locations. Prevalence in children was 67% at tp1 and 89% at tp2, 63% in chickens, 86% in pigs, and 57% in water. Ten STs were identified, two of which were shared between humans and animals, one between animals and water, and three between humans and water. Eighteen children (out of 36) carried the same ST over both time points, indicating stable colonisation. Presence of Blastocystis (or ST) was not associated with body mass index, ethnicity, birth delivery mode, or milk source as an infant. This study advances understanding of Blastocystis prevalence in an understudied age group, the role of the environment in transmission, and the ability of specific STs to stably colonise children.

An edge flipping is a non-reversible Markov chain on a given connected graph, as defined in Chung and Graham (2012). In the same paper, edge flipping eigenvalues and stationary distributions for some classes of graphs were identified. We further study edge flipping spectral properties to show a lower bound for the rate of convergence in the case of regular graphs. Moreover, we show by a coupling argument that a cutoff occurs at $\frac{1}{4} n \log n$ for the edge flipping on the complete graph.

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.

We study the coupon collector’s problem with group drawings. Assume there are n different coupons. At each time precisely s of the n coupons are drawn, where all choices are supposed to have equal probability. The focus lies on the fluctuations, as $n\to\infty$, of the number $Z_{n,s}(k_n)$ of coupons that have not been drawn in the first $k_n$ drawings. Using a size-biased coupling construction together with Stein’s method for normal approximation, a quantitative central limit theorem for $Z_{n,s}(k_n)$ is shown for the case that $k_n=({n/s})(\alpha\log(n)+x)$, where $0<\alpha<1$ and $x\in\mathbb{R}$. The same coupling construction is used to retrieve a quantitative Poisson limit theorem in the boundary case $\alpha=1$, again using Stein’s method.

For a fixed infinite graph $H$, we study the largest density of a monochromatic subgraph isomorphic to $H$ that can be found in every two-colouring of the edges of $K_{\mathbb{N}}$. This is called the Ramsey upper density of $H$ and was introduced by Erdős and Galvin in a restricted setting, and by DeBiasio and McKenney in general. Recently [4], the Ramsey upper density of the infinite path was determined. Here, we find the value of this density for all locally finite graphs $H$ up to a factor of 2, answering a question of DeBiasio and McKenney. We also find the exact density for a wide class of bipartite graphs, including all locally finite forests. Our approach relates this problem to the solution of an optimisation problem for continuous functions. We show that, under certain conditions, the density depends only on the chromatic number of $H$, the number of components of $H$ and the expansion ratio $|N(I)|/|I|$ of the independent sets of $H$.

The prevalence rate of coinfection Chagas disease (CD) and HIV in Brazil is between 1.3 and 5%. Serological tests for detecting CD use total antigen, which present cross reactivity with other endemic diseases, such as leishmaniasis. It is urge the use of a specific test to determinate the real prevalence of T. cruzi infection in people living with HIV AIDS (PLWHA). Here, we evaluated the prevalence of T. cruzi infection in a cohort of 240 PLWHA living in urban area from São Paulo, Brazil. Enzyme Linked Immunosorbent Assay, using epimastigote alkaline extract antigen from T. cruzi (ELISA EAE), returned a 2.0% prevalence. However by Immunoblotting, using trypomastigote excreted-secreted antigen (TESA Blot) from T. cruzi, we detected a prevalence of 0.83%. We consider that the real prevalence of T. cruzi-infection in PLWHA is 0.83%, lower than reported in literature; this is due to TESA Blot specificity, probably excluding false positives for CD immunodiagnosis. Our results demonstrate a real need to apply diagnostic tests with high sensitivity and specificity that can help assess the current status of CD/HIV coinfection in Brazil in order to stratify the effective risk of reactivation and consequently decreasing mortality.

We propose various semiparametric estimators for nonlinear selection models, where slope and intercept can be separately identified. When the selection equation satisfies a monotonic index restriction, we suggest a local polynomial estimator, using only observations for which the marginal cumulative distribution function of the instrument index is close to one. Data-driven procedures such as cross-validation may be used to select the bandwidth for this estimator. We then consider the case in which the monotonic index restriction does not hold and/or the set of observations with a propensity score close to one is thin so that convergence occurs at a rate that is arbitrarily close to the cubic rate. We explore the finite sample behavior in a Monte Carlo study and illustrate the use of our estimator using a model for count data with multiplicative unobserved heterogeneity.

The notion of cross-intersecting set pair system of size $m$, $ (\{A_i\}_{i=1}^m, \{B_i\}_{i=1}^m )$ with $A_i\cap B_i=\emptyset$ and $A_i\cap B_j\ne \emptyset$, was introduced by Bollobás and it became an important tool of extremal combinatorics. His classical result states that $m\le\binom{a+b}{a}$ if $|A_i|\le a$ and $|B_i|\le b$ for each $i$. Our central problem is to see how this bound changes with the additional condition $|A_i\cap B_j|=1$ for $i\ne j$. Such a system is called $1$-cross-intersecting. We show that these systems are related to perfect graphs, clique partitions of graphs, and finite geometries. We prove that their maximum size is

• at least $5^{n/2}$ for $n$ even, $a=b=n$,

• equal to $\bigl (\lfloor \frac{n}{2}\rfloor +1\bigr )\bigl (\lceil \frac{n}{2}\rceil +1\bigr )$ if $a=2$ and $b=n\ge 4$,

• at most $|\cup _{i=1}^m A_i|$,

• asymptotically $n^2$ if $\{A_i\}$ is a linear hypergraph ($|A_i\cap A_j|\le 1$ for $i\ne j$),

• asymptotically ${1\over 2}n^2$ if $\{A_i\}$ and $\{B_i\}$ are both linear hypergraphs.