Whole-genome sequencing (WGS) information has played a crucial role in the SARS-CoV-2 (COVID-19) pandemic by providing evidence about variants to inform public health policy. The purpose of this study was to assess the representativeness of sequenced cases compared with all COVID-19 cases in England, between March 2020 and August 2021, by demographic and socio-economic characteristics, to evaluate the representativeness and utility of these data in epidemiological analyses. To achieve this, polymerase chain reaction (PCR)-confirmed COVID-19 cases were extracted from the national laboratory system and linked with WGS data. During the study period, over 10% of COVID-19 cases in England had WGS data available for epidemiological analysis. With sequencing capacity increasing throughout the period, sequencing representativeness compared to all reported COVID-19 cases increased over time, allowing for valuable epidemiological analyses using demographic and socio-economic characteristics, particularly during periods with emerging novel SARS-CoV-2 variants. This study demonstrates the comprehensiveness of England’s sequencing throughout the COVID-19 pandemic, rapidly detecting variants of concern, and enabling representative epidemiological analyses to inform policy.

The Democratic Republic of the Congo (DRC) officially reports low coronavirus disease 19 (COVID-19) prevalence. This cross-sectional study, conducted between September and November 2021, assessed the COVID-19 seroprevalence in people attending Goma’s two largest markets, Kituku and Virunga. A similar study in a slum of Bukavu overlapped for 1 month using identical methods. COVID-19-unvaccinated participants (n = 796 including 454 vendors and 342 customers, 60% of whom were women) were surveyed. The median age of vendors and customers was 34.2 and 30.1 years, respectively. The crude and adjusted anti-SARS-CoV-2 antibody seroprevalence rates were 70.2% (95% CI 66.9–73.4%) and 98.8% (95% CI 94.1–100%), respectively, with no difference between vendors and customers. COVID-19 symptoms reported by survey participants in the previous 6 months were mild or absent in 58.9% and 41.1% of participants with anti-SARS-CoV-2 antibodies, respectively. No COVID-19-seropositive participants reported hospitalisation in the last 6 months. These findings are consistent with those reported in Bukavu. They confirm that SARS-CoV-2 spread without causing severe symptoms in densely populated settlements and markets and suggest that many COVID-19 cases went unreported. Based on these results, the relevance of an untargeted hypothetical vaccination programme in these communities should be questioned.

This study determined long-term health outcomes (≥10 years) of Q-fever fatigue syndrome (QFS). Long-term complaints, health-related quality of life (HRQL), health status, energy level, fatigue, post-exertional malaise, anxiety, and depression were assessed. Outcomes and determinants were studied for the total sample and compared among age subgroups: young (<40years), middle-aged (≥40–<65years), and older (≥65years) patients. 368 QFS patients were included. Participants reported a median number of 12.0 long-term complaints. Their HRQL (median EQ-5D-5L index: 0.63) and health status (median EQ-VAS: 50.0) were low, their level of fatigue was high, and many experienced post-exertional malaise complaints (98.9%). Young and middle-aged patients reported worse health outcomes compared with older patients, with both groups reporting a significantly worse health status, higher fatigue levels and anxiety, and more post-exertional malaise complaints and middle-aged patients having a lower HRQL and a higher depression risk. Multivariate regression analyses confirmed that older age is associated with better outcomes, except for the number of health complaints. QFS has thus a considerable impact on patients’ health more than 10 years after infection. Young and middle-aged patients experience more long-term health consequences compared with older patients. Tailored health care is recommended to provide optimalcare for each QFS patient.

This paper analyses aspects of generalized method of moments (GMM) inference in moment equality models in settings where standard regularity conditions may break down. Explicit analytic formulations for the asymptotic distributions of estimable functions of the GMM estimator and statistics based on the GMM criterion function are derived under relatively mild assumptions. The moment Jacobian is allowed to be rank deficient, so first order identification may fail, the values of the Jacobian singular values are not constrained, thereby allowing for varying levels of identification strength, the long-run variance of the moment conditions can be singular, and the GMM criterion function weighting matrix may also be chosen sub-optimally. The large-sample properties are derived without imposing a specific structure on the functional form of the moment conditions. Closed-form expressions for the distributions are presented that can be evaluated using standard software without recourse to bootstrap or simulation methods. The practical operation of the results is illustrated via examples involving instrumental variables estimation of a structural equation with endogenous regressors and a common CH features model.

Within US professional sports, trades within one’s own division are often perceived to be disadvantageous. We ask how common this practice is. To examine this question, we construct a date-stamped network of all trades in the National Basketball Association between June 1976 and May 2019. We then use season-specific weighted exponential random graph models to estimate the likelihood of teams avoiding within-division trade partners, and how consistent that pattern is across the observed period. In addition to the empirical question, this analysis serves to demonstrate the necessity and difficulty of constructing the proper baseline for statistical comparison. We find limited-to-no support for the popular perception.

We study two models of discrete height functions, that is, models of random integer-valued functions on the vertices of a tree. First, we consider the random homomorphism model, in which neighbours must have a height difference of exactly one. The local law is uniform by definition. We prove that the height variance of this model is bounded, uniformly over all boundary conditions (both in terms of location and boundary heights). This implies a strong notion of localisation, uniformly over all extremal Gibbs measures of the system. For the second model, we consider directed trees, in which each vertex has exactly one parent and at least two children. We consider the locally uniform law on height functions which are monotone, that is, such that the height of the parent vertex is always at least the height of the child vertex. We provide a complete classification of all extremal gradient Gibbs measures, and describe exactly the localisation-delocalisation transition for this model. Typical extremal gradient Gibbs measures are localised also in this case. Localisation in both models is consistent with the observation that the Gaussian free field is localised on trees, which is an immediate consequence of transience of the random walk.

In this paper, a new point process is introduced. It combines the nonhomogeneous Poisson process with the generalized Polya process (GPP) studied in recent literature. In reliability interpretation, each event (failure) from this process is minimally repaired with a given probability and GPP-repaired with the complementary probability. Characterization of the new process via the corresponding bivariate point process is presented. The mean numbers of events for marginal processes are obtained via the corresponding rates, which are used for considering an optimal replacement problem as an application.

Acute pyelonephritis (AP) epidemiology has been sparsely described. This study aimed to describe the evolution of AP patients hospitalised in France and identify the factors associated with urinary diversion and fatality, in a cross-sectional study over the 2014–2019 period. Adult patients hospitalised for AP were selected by algorithms of ICD-10 codes (PPV 90.1%) and urinary diversion procedure codes (PPV 100%). 527,671 AP patients were included (76.5% female: mean age 66.1, 48.0% Escherichia coli), with 5.9% of hospital deaths. In 2019, the AP incidence was 19.2/10,000, slightly increasing over the period (17.3/10,000 in 2014). 69,313 urinary diversions (13.1%) were performed (fatality rate 6.7%), mainly in males, increasing over the period (11.7% to 14.9%). Urolithiasis (OR [95% CI] =33.1 [32.3–34.0]), sepsis (1.73 [1.69–1.77]) and a Charlson index ≥3 (1.32 [1.29–1.35]) were significantly associated with urinary diversion, whereas E. coli (0.75 [0.74–0.77]) was less likely associated. The same factors were significantly associated with fatality, plus old age and cancer (2.38 [2.32–2.45]). This nationwide study showed an increase in urolithiasis and identified, for the first time, factors associated with urinary diversion in AP along with death risk factors, which may aid urologists in clinical decision-making.

In 2008, Tóth and Vető defined the self-repelling random walk with directed edges as a non-Markovian random walk on $\unicode{x2124}$: in this model, the probability that the walk moves from a point of $\unicode{x2124}$ to a given neighbor depends on the number of previous crossings of the directed edge from the initial point to the target, called the local time of the edge. Tóth and Vető found that this model exhibited very peculiar behavior, as the process formed by the local times of all the edges, evaluated at a stopping time of a certain type and suitably renormalized, converges to a deterministic process, instead of a random one as in similar models. In this work, we study the fluctuations of the local times process around its deterministic limit, about which nothing was previously known. We prove that these fluctuations converge in the Skorokhod $M_1$ topology, as well as in the uniform topology away from the discontinuities of the limit, but not in the most classical Skorokhod topology. We also prove the convergence of the fluctuations of the aforementioned stopping times.

The global prevalence and spread of multidrug-resistant organisms (MDROs) represent an emerging public health threat. Day care centre (DCC) attendance is a risk factor for MDRO carriage in children and their environment. This study aimed to map the epidemiology of carriage and potential transmission of these organisms within 18 Flemish DDCs (Belgium). An MDRO prevalence survey was organised between November 2018 and February 2019 among children attending the centres. Selective chromogenic culture media were used for the detection of extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-E), carbapenemase-producing Enterobacterales (CPE), and vancomycin-resistant Enterococci (VRE) in faecal swabs obtained from diapers or jars (n = 448). All isolated MDROs were subjected to resistance gene sequencing. A total of 71 of 448 samples (15.8%) yielded isolates of ESBL-E with a predominance of Escherichia coli (92.2% of ESBL-E) and ESBL resistance gene blaCTX-M-15 (50.7% of ESBL coding genes in E. coli). ESBL-E prevalence varied between DCCs, ranging from 0 to 50%. Transmission, based on the clonal relatedness of ESBL-E strains, was observed. CPE was identified in only one child carrying an E. coli with an OXA-244 gene. VRE was absent from all samples. The observed prevalence of ESBL-E in Flemish DCCs is high compared with previous studies, and our findings re-emphasise the need for rigorous hygiene measures within such centres to control the further spread of MDROs in the community.

Hepatitis E virus infection is a major cause of acute hepatitis, typically self-limiting but occasionally leading to liver failure. Understanding disease progression factors could inform prevention strategies. This study aimed to analyse the characteristics of a large cohort of hospitalised hepatitis E patients in Tianjin, China, and explore factors influencing their progression to liver failure. A total of 1279 hospitalised patients with hepatitis E were included in this cross-sectional study in Tianjin, China. Student's t-test and the Mann–Whitney U-test were used for comparisons. Multiple logistic regression analysis was used to explore the association. Among these 1279 patients, 107 (8.4%) developed liver failure. Patients with diabetes mellitus (DM) (95% confidence interval [CI] 1.150–2.887, p = 0.011), liver cirrhosis (95% [CI] 2.229–7.224, p < 0.001), and hepatitis B (95% [CI] 1.159–4.512, p = 0.017) were more likely to progress to liver failure. Hepatitis E patients with comorbid DM, liver cirrhosis, or hepatitis B virus co-infection have higher risks of developing liver failure. Hepatitis E vaccination may be recommended for these vulnerable patients to curb disease severity.

A comparison theorem for state-dependent regime-switching diffusion processes is established, which enables us to pathwise-control the evolution of the state-dependent switching component simply by Markov chains. Moreover, a sharp estimate on the stability of Markovian regime-switching processes under the perturbation of transition rate matrices is provided. Our approach is based on elaborate constructions of switching processes in the spirit of Skorokhod’s representation theorem varying according to the problem being dealt with. In particular, this method can cope with switching processes in an infinite state space and not necessarily of birth–death type. As an application, some known results on the ergodicity and stability of state-dependent regime-switching processes can be improved.

Available data suggest that the immunogenicity of COVID-19 vaccines might decrease in the immunocompromised population, but data on vaccine immunogenicity and safety among people living with HIV (PLWH) are still lacking. The purpose of this meta-analysis is to compare the immunogenicity and safety of COVID-19 vaccines in PLWH with healthy controls. We comprehensively searched the following databases: PubMed, Cochrane Library, and EMBASE. The risk ratio (RR) of seroconversion after the first and second doses of a COVID-19 vaccine was separately pooled using random-effects meta-analysis. Seroconversion rate was lower among PLWH compared with healthy individuals after the first (RR = 0.77, 95% confident interval (CI) 0.64–0.92) and second doses (RR = 0.97, 95%CI 0.95–0.99). The risk of total adverse reactions among PLWH is similar to the risk in the healthy group, after the first (RR = 0.87, 95%CI 0.70–1.10) and second (RR = 0.83, 95%CI 0.65–1.07) doses. This study demonstrates that the immunogenicity and safety of SARS-CoV-2 vaccine in fully vaccinated HIV-infected patients were generally satisfactory. A second dose was related to seroconversion enhancement. Therefore, we considered that a booster dose may provide better seroprotection for PLWH. On the basis of a conventional two-dose regimen for COVID-19 vaccines, the booster dose is very necessary.

The coronavirus pandemic has created a new awareness of epidemics, and insurance companies have been reminded to consider the risk related to infectious diseases. This paper extends the traditional multi-state models to include epidemic effects. The main idea is to specify the transition intensities in a Markov model such that the impact of contagion is explicitly present in the same way as in epidemiological models. Since we can study the Markov model with contagious effects at an individual level, we consider individual risk and reserves relating to insurance products, conforming with the standard multi-state approach in life insurance mathematics. We compare our notions with other but related notions in the literature and perform numerical illustrations.

A foodborne outbreak related to milk cartons served in school lunches occurred in June 2021, which involved more than 1,800 cases from 25 schools. The major symptoms were abdominal pain, diarrhoea, vomiting, and fever. Although major foodborne toxins and pathogens were not detected, a specific Escherichia coli strain, serotype OUT (OgGp9):H18, was predominantly isolated from milk samples related to the outbreak and most patients tested. The strains from milk and patient stool samples were identified as the same clone by core genome multilocus sequence typing and single-nucleotide polymorphism analysis. The strain was detected in milk samples served for two days related to the foodborne outbreak at a rate of 69.6% and levels of less than ten most probable number/100 mL but not on days unrelated to the outbreak. The acid tolerance of the strain for survival in the stomach was similar to that of enterohaemorrhagic E. coli O157:H7, and the same inserts in the chu gene cluster in the acid fitness island were genetically revealed. The pathogenicity of the strain was not clear; however, it was indicated that the causative pathogen was atypical diarrhoeagenic E. coli OUT (OgGp9):H18.

In resource-limited countries, the lack of widespread screening masks the true situation of COVID-19. We conducted this study to assess SARS-CoV-2 spread by detection of specific antibodies and to determine associated factors. A population-based cross-sectional study was conducted. Subjects were tested for the presence of two antibodies (IgM and IgG) specific to SARS-CoV-2. Data collection was done using a smartphone with the KoboCollect application. Prevalence of antibodies was estimated with 95% confidence intervals. Logistic regression was used to determine factors associated with positive serological test. A total of 9,094 persons were tested in 4,340 households. The mean age was 30.18 ± 18.65 years, 46.5% male. The overall seroprevalence (prevalence, 95% CI) of SARS-CoV-2 antibodies was (48.2% [47.2%–49.2%]). Being vaccinated, having been in contact with a COVID-19 patient, being older than 50 years, living in a union, having secondary education and having tertiary education were factors independently associated with the likelihood of having anti-sars-CoV-2. We estimate in February 2022 that 48% persons had antibodies against the COVID-19 virus, more among those vaccinated. Vaccination intensification in low prevalence departments will reduce the risk of new outbreaks.

The SARS-CoV-2 pandemic persists with global repercussions. Initial COVID-19 symptoms encompass pneumonia, fever, myalgia, and fatigue. The human immune system produces IgM and IgG antibodies in response to SARS-CoV-2. Despite previous research, a comprehensive understanding of the interplay between clinical manifestations and humoral immune responses remains elusive. This study aims to scrutinize this association. 134 COVID-19 patients were enrolled, and stratified into mild, moderate, and severe symptom groups. Serum IgM and IgG levels were assessed thrice at one-month intervals using ELISA. The findings reveal significant elevation in serum IgG levels in moderate compared to mild cases (P < 0.001). Additionally, IgG production was significantly heightened in severe cases compared to both mild (P < 0.0001) and moderate (P < 0.05) groups. IgM and IgG levels peaked initially and diminished over time. While anti-SARS-CoV-2 antibodies are expected to confer protection, the direct correlation between IgG levels and symptom severity may arise from delayed immune activation, resulting in an intense antibody response in severe cases. Given evidence linking delayed immune function with a dysregulated innate immune response, comprehensive data collection should encompass not only serum IgG and IgM, but also early measurement of type I interferons at symptom onset. This could provide a more thorough understanding of COVID-19 progression.

Tests based on heteroskedasticity robust standard errors are an important technique in econometric practice. Choosing the right critical value, however, is not simple at all: conventional critical values based on asymptotics often lead to severe size distortions, and so do existing adjustments including the bootstrap. To avoid these issues, we suggest to use smallest size-controlling critical values, the generic existence of which we prove in this article for the commonly used test statistics. Furthermore, sufficient and often also necessary conditions for their existence are given that are easy to check. Granted their existence, these critical values are the canonical choice: larger critical values result in unnecessary power loss, whereas smaller critical values lead to overrejections under the null hypothesis, make spurious discoveries more likely, and thus are invalid. We suggest algorithms to numerically determine the proposed critical values and provide implementations in accompanying software. Finally, we numerically study the behavior of the proposed testing procedures, including their power properties.