The aim of this paper is to describe the prevalence of Mycoplasma genitalium and Trichomonas vaginalis in patients who visited general practitioners in the Netherlands. Additionally, we describe the prevalence of M. genitalium resistance to azithromycin and moxifloxacin. We used data from 7,411 consecutive female patients who were screened for Chlamydia trachomatis, Neisseria gonorrhoeae, M. genitalium, and T. vaginalis and data from 5,732 consecutive male patients screened for C. trachomatis, N. gonorrhoeae, and M. genitalium. The prevalence of M. genitalium and T. vaginalis in female patients was 6.7% (95% CI: 6.2 to 7.4) and 1.9% (95%CI: 1.6 to 2.2%), respectively. M. genitalium prevalence in male patients was 3.7% (3.3 to 4.3). M. genitalium co-occurred with C. trachomatis in 1.4% (0.3 to 0.6%) of female and in 0.7% (0.5 to 0.9) of male patients. Macrolide resistance gene mutations and fluoroquinolone resistance gene mutations were detected in 73.8% and 9.9%, respectively. We concluded that M.genitalium is relatively infrequently found in a large general practitioner population in the Netherlands. It can co-occur with C. trachomatis, and is often resistant to azithromycin. Therefore, when treating sexually transmitted infections, these prevalence and resistance data should be taken into account.

In 2014, Nigeria halted transmission of wild poliovirus for the first time in its history. A critical enabling component in this historic achievement was the use of satellite data to produce more accurate maps and population estimates used in planning and implementing vaccination campaigns. This article employs a value-of-information approach to estimate the net socioeconomic benefits associated with this use of satellite data. We calculate the increase in the likelihood of halting transmission of polio associated with the use of satellite-based information compared to traditional data sources, and we consider the benefits associated with savings to the healthcare system as well as health benefits. Using a conservative approach focused on just 1 year of benefits, we estimate net socioeconomic benefits of between $46.0 million and $153.9 million. In addition to these quantified benefits, we also recognize qualitative benefits associated with improving human health, reaching marginalized communities, and building capacity among local populations. We also explore the substantial benefits associated with follow-on projects that have made use of the satellite-based data products and methodologies originally developed for the Nigeria polio eradication effort.

In the literature on active redundancy allocation, the redundancy lifetimes are usually postulated to be independent of the component lifetimes for the sake of technical convenience. However, this unrealistic assumption leads to a risk of inaccurately evaluating system reliability, because it overlooks the statistical dependence of lifetimes due to common stresses. In this study, for k-out-of-n:F systems with component and redundancy lifetimes linked by the Archimedean copula, we show that (i) allocating more homogeneous redundancies to the less reliable components tends to produce a redundant system with stochastically larger lifetime, (ii) the reliability of the redundant system can be uniformly maximized through balancing the allocation of homogeneous redundancies in the context of homogeneous components, and (iii) allocating a more reliable matched redundancy to a less reliable component produces a more reliable system. These novel results on k-out-of-n:F systems in which component and redundancy lifetimes are statistically dependent are more applicable to the complicated engineering systems that arise in real practice. Some numerical examples are also presented to illustrate these findings.

To mitigate the known high transmission risk in day-care facilities for children aged 0–6 years, day-care staff were given priority for SARS-CoV-2 vaccination in Rhineland-Palatinate, Germany, in March 2021. This study assessed direct and indirect effects of early vaccination of day-care staff on SARS-CoV-2 transmission in daycares with the aim to provide a basis for the prioritisation of scarce vaccines in the future. Data came from statutory infectious disease notifications in educational institutions and from in-depth investigations by the district public health authorities. Using interrupted time series analyses, we measured the effect of mRNA-based vaccination of day-care staff on SARS-CoV-2 infections and transmission. Among 566 index cases from day-care centres, the mean number of secondary SARS-CoV-2 infections per index case dropped by −0.60 case per month after March 2021. The proportion of staff among all cases reported from daycares was around 60% in the pre-interruption phase and significantly decreased by 27 percentage points immediately in March 2021 and by further 6 percentage points each month in the post-interruption phase. Early vaccination of day-care staff reduced SARS-CoV-2 cases in the overall day-care setting and thus also protected unvaccinated children. This should inform future decisions on vaccination prioritisation.

We propose a robust inference method for predictive regression models under heterogeneously persistent volatility as well as endogeneity, persistence, or heavy-tailedness of regressors. This approach relies on two methodologies, nonlinear instrumental variable estimation and volatility correction, which are used to deal with the aforementioned characteristics of regressors and volatility, respectively. Our method is simple to implement and is applicable both in the case of continuous and discrete time models. According to our simulation study, the proposed method performs well compared with widely used alternative inference procedures in terms of its finite sample properties in various dependence and persistence settings observed in real-world financial and economic markets.

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.