This note re-investigates the smooth tests for the equality of distributions introduced by Bera et al. (2013, Econometric Theory 29, 419–446) and provides a modified smooth test which works for the general case with two sample sizes m and n. Asymptotic properties of the proposed test statistic under both the null and the alternative hypothesis are studied.

This paper considers the estimation of dynamic causal effects using a proxy structural vector-autoregressive model with possibly nonstationary regressors. We provide general conditions under which the asymptotic normal approximation remains valid. In this case, the asymptotic variance depends on the persistence property of each series. We further provide a consistent asymptotic covariance matrix estimator that requires neither knowledge of the presistence properties of the variables nor pretests for nonstationarity. The proposed consistent covariance matrix estimator is robust and is easy to implement in practice. When all regressors are indeed stationary, the method becomes the same as the standard procedure.

This paper develops an asymptotic theory of nonlinear least squares estimation by establishing a new framework that can be easily applied to various nonlinear regression models with heteroscedasticity. As an illustration, we explore an application of the framework to nonlinear regression models with nonstationarity and heteroscedasticity. In addition to these main results, this paper provides a maximum inequality for a class of martingales, which is of interest in its own right.

Severe COVID-19 cases place immediate pressure on hospital resources. To assess this, we analysed survival duration in the first 39 fatal cases in Wuhan, China. Time from onset and hospitalization to death declined rapidly, from ~40 to 7 days, and ~25 to 4 days, respectively, in the outbreak’s first month.

It is important to understand the temporal trend of the paediatric severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load to estimate the transmission potential of children in schools and communities. We determined the differences in SARS-CoV-2 viral load dynamics between nasopharyngeal samples of infected asymptomatic and symptomatic children. Serial cycle threshold values of SARS-CoV-2 from the nasopharynx of a cohort of infected children were collected for analysis. Among 17 infected children, 10 (58.8%) were symptomatic. Symptomatic children, when compared to asymptomatic children, had higher viral loads (mean cycle threshold on day 7 of illness 28.6 vs. 36.7, P = 0.02). Peak SARS-CoV-2 viral loads occurred around day 2 of illness in infected children. Although we were unable to directly demonstrate infectivity, the detection of significant amount of virus in the upper airway of asymptomatic children suggest that they have the potential to shed and transmit SARS-CoV-2. Our study highlights the importance of contact tracing and screening for SARS-CoV-2 in children with epidemiological risk factors regardless of their symptom status, in order to improve containment of the virus in the community, including educational settings.

This paper considers the customers’ equilibrium and socially optimal joining–balking behavior in a single-server Markovian queue with a single working vacation and Bernoulli interruptions. The model is motivated by practical service systems where the service rate can be adjusted according to whether or not the system is empty. Specifically, we focus on a single-server queue in which the server's service rate is reduced from a regular to a lower one when the system becomes empty. This lower rate period is called a working vacation for the server which may represent that part of the service facility is under a maintenance process or works on other non-queueing job, or simply for saving the energy (for a machine server case). In this paper, we assume that the working vacation period is terminated after a random period or with probability p after serving a customer in a non-empty system. Such a system is called a queue with single working vacation and Bernoulli interruptions. Customers are strategic and can make choice of joining or balking based on different levels of system information. We consider four scenarios: fully observable, almost observable, almost unobservable, and fully unobservable queue cases. Under a reward-cost structure, we analyze the customer's equilibrium and social-optimal strategies. In addition, the effects of system parameters on optimal strategies are illustrated by numerical examples.

In this paper, we give a two-line proof of a long-standing conjecture of Ben-Akiva in his 1973 PhD thesis regarding the random utility representation of the nested logit model, thus providing a renewed and straightforward textbook treatment of that model. As an application, we provide a closed-form formula for the correlation between two Fréchet random variables coupled by a Gumbel copula.

This study applied causal criteria in directed acyclic graphs for handling covariates in associations for prognosis of severe coronavirus disease 2019 (COVID-19) cases. To identify non-specific blood tests and risk factors as predictors of hospitalisation due to COVID-19, one has to exclude noisy predictors by comparing the concordance statistics (area under the curve − AUC) for positive and negative cases of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Predictors with significant AUC at negative stratum should be either controlled for their confounders or eliminated (when confounders are unavailable). Models were classified according to the difference of AUC between strata. The framework was applied to an open database with 5644 patients from Hospital Israelita Albert Einstein in Brazil with SARS-CoV-2 reverse transcription – polymerase chain reaction (RT-PCR) exam. C-reactive protein (CRP) was a noisy predictor: hospitalisation could have happened due to causes other than COVID-19 even when SARS-CoV-2 RT-PCR is positive and CRP is reactive, as most cases are asymptomatic to mild. Candidates of characteristic response from moderate-to-severe inflammation of COVID-19 were: combinations of eosinophils, monocytes and neutrophils, with age as risk factor; and creatinine, as risk factor, sharpens the odds ratio of the model with monocytes, neutrophils and age.

COVID-19 has challenged the mental health of healthcare workers confronting it world-wide. Our study identifies the prevalence and risk of anxiety among emergency healthcare workers confronting COVID-19 in Pakistan. We conducted a cross-sectional survey in an Emergency Department using the Generalized Anxiety Scale (GAD-7), and questions about sources of anxiety. Of 107 participants, 61.7% were frontline workers. The prevalence of anxiety was 50.5%. Nonparametric tests determined that nurses, younger and inexperienced staff, developed significant anxiety. Multivariate ordinal regression determined independent risk factors for developing anxiety were younger age (OR 2.11, 95% CI 0.89–4.99) and frontline placement (OR 1.34, 95% CI 0.33–1.66). Significant sources of stress were fear of infecting family (P = 0.003), lack of social support when the health care providers were themselves unwell (P = 0.02) and feelings of inadequate work performance (P = 0.05). Our study finds that HCWs’ anxiety is considerable. Appropriate measures for its alleviation and prevention are required.

Pre-existing health conditions may exacerbate the severity of coronavirus disease 2019 (COVID-19). We aimed to estimate the case-fatality rate (CFR) and rate ratios (RR) for patients with hypertension (HBP) and diabetes mellitus (DM) in the New York state. We obtained the age-specific number of COVID-19 confirmed cases and deaths from public reports provided by the New York State Department of Health, and age-specific prevalence of HBP and DM from the Behavioral Risk Factor Surveillance System 2017. We calculated CFR and RR for COVID-19 patients with HBP and DM based on the reported number of deaths with the comorbidity divided by the expected number of COVID-19 cases with the comorbidity. We performed subgroup analysis by age and calculated the CFR and RR for ages of 18–44, 45–64 and 65+ years, respectively. We found that the older population had a higher CFR, but the elevated RRs associated with comorbidities are more pronounced among the younger population. Our findings suggest that besides the elderly, the young population with comorbidity should also be considered as a vulnerable group.

The ten-item short form of the Autism-Spectrum Quotient (AQ-10) has been used to efficiently assess autistic traits in the general population; however, the psychometric properties of the AQ-10 in terms of its internal reliability and its unifactorial structure have recently been questioned. In the present study (N = 797), whether the internal reliability is increased when the AQ-10 is applied with six rather than the conventional four response categories has been investigated. Moreover, correlational and confirmatory factor analyses were conducted to examine the reason for potential inhomogeneity within the AQ-10. The results suggest that the internal reliability of the AQ-10 was slightly increased but is still unsatisfactory, likely due to the incompatibility of items from two subdimensions: attention to detail and imagination. With six of the AQ-10 items, crucial aspects of the autistic personality may be measured, but other important aspects would be neglected; thus, the measure requires further psychometric development.

Only studies in the UK on individuals dying from coronavirus disease 2019 (COVID-19) in hospital have been published, to date. Cremation law requires collection of clinical information that can improve understanding of deaths in both hospital and community settings. Age, sex, date and place of death, occupation, comorbidities and where infection acquired was recorded for all deaths from COVID-19, between 6 April and 30 May, for whom an application was made for cremation at a South Wales' crematorium. Of 752 cremations, 215 (28.6%) were COVID-19 (115 (53.5%) male and 100 (46.5%) female). Median age was 82 years (youngest patient 47 and the oldest 103 years). Over half the deaths (121/215: 56.3%) were over 80 years. Males' odds of dying in hospital, rather than the community were 1.96 times that of females (95% confidence intervals (CI) 1.03–3.74, P = 0.054) despite being of similar age and having a similar number of comorbidities. Only 21 (9.8%) of 215 patients had no comorbidities recorded. Patients dying in care homes were significantly older than those dying in hospital (median 88 years (interquartile (IQ) range 82–93 years) vs. 80 years (IQ range 71–87 years): P < 0.0001). Patients dying in hospital had significantly more comorbidities than those dying in care homes (median 2: IQ range 1–3 vs. 1: IQ range 1–2: P < 0.001). Sixty three (29.3%) of infections were hospital acquired and a further 55 (25.6%) acquired in care homes. In a series, of hospital and community deaths, persons over 80 with an average two comorbidities predominated. Men were more likely to die in hospital. Half the infections were acquired in hospitals or care homes with implications for management of the pandemic.

We prove a number of results related to a problem of Po-Shen Loh [9], which is equivalent to a problem in Ramsey theory. Let a = (a1, a2, a3) and b = (b1, b2, b3) be two triples of integers. Define a to be 2-less than b if ai < bi for at least two values of i, and define a sequence a1, …, am of triples to be 2-increasing if ar is 2-less than as whenever r < s. Loh asks how long a 2-increasing sequence can be if all the triples take values in {1, 2, …, n}, and gives a log* improvement over the trivial upper bound of n2 by using the triangle removal lemma. In the other direction, a simple construction gives a lower bound of n3/2. We look at this problem and a collection of generalizations, improving some of the known bounds, pointing out connections to other well-known problems in extremal combinatorics, and asking a number of further questions.

In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.

Expansion of cultivated lands and field management impacts greenhouse gas (GHG) emissions from agriculture soils. Soils naturally cycle GHGs and can be sources or sinks depending on physical and chemical properties affected by cultivation and management status. We looked at how cultivation history influences GHG emissions from subtropical soils. We measured CO2, N2O, and CH4 fluxes, and soil properties from newly converted and continuously cultivated lands during the summer rainy season in calcareous soils from south Florida. Newly converted soils had more soil organic matter (OM), more moisture, higher porosity, and lower bulk density, leading to more GHG emissions compared to historically cultivated soils. Although more nutrients make newly converted lands more desirable for cultivation, conversion of new areas for agriculture was shown to release more GHGs than cultivated lands. Our data suggest that GHG emissions from agricultural soils may decrease over time with continued cultivation.

The coronavirus disease 2019 (COVID-19) pandemic is currently the most critical challenge in public health. An understanding of the factors that affect severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection will help fight the COVID-19 pandemic. This study sought to investigate the association between SARS-CoV-2 infection and blood type distribution. The big data provided by the World Health Organization (WHO) and Johns Hopkins University were used to assess the dynamics of the COVID-19 epidemic. The infection data in the early phase of the pandemic from six countries in each of six geographic zones divided according to the WHO were used, representing approximately 5.4 billion people around the globe. We calculated the infection growth factor, doubling times of infection and death cases, reproductive number and infection and death cases in relation to the blood type distribution. The growth factor of infection and death cases significantly and positively correlated with the proportion of the population with blood type A and negatively correlated with the proportion of the population with blood type B. Compared with the lower blood type A population (<30%), the higher blood type A population (⩾30%) showed more infection and death cases, higher growth factors and shorter case doubling times for infections and deaths and thus higher epidemic dynamics. Thus, an association exists between SARS-CoV-2 and the ABO blood group distribution, which might be useful for fighting the COVID-19 pandemic.