A probabilistic transmission and population dynamic model to assess tuberculosis infection risk

The purpose of this study was to examine tuberculosis (TB) population dynamics and to assess potential infection risk in Taiwan. A well‐established mathematical model of TB transmission built on previous models was adopted to study the potential impact of TB transmission. A probabilistic risk model was also developed to estimate site‐specific risks of developing disease soon after recent primary infection, exogenous reinfection, or through endogenous reactivation (latently infected TB) among Taiwan regions. Here, we showed that the proportion of endogenous reactivation (53–67%) was larger than that of exogenous reinfection (32–47%). Our simulations showed that as epidemic reaches a steady state, age distribution of cases would finally shift toward older age groups dominated by latently infected TB cases as a result of endogenous reactivation. A comparison of age‐weighted TB incidence data with our model simulation output with 95% credible intervals revealed that the predictions were in an apparent agreement with observed data. The median value of overall basic reproduction number (R₀) in eastern Taiwan ranged from 1.65 to 1.72, whereas northern Taiwan had the lowest R₀ estimate of 1.50. We found that total TB incidences in eastern Taiwan had 25–27% probabilities of total proportion of infected population exceeding 90%, whereas there were 36–66% probabilities having exceeded 20% of total proportion of infected population attributed to latently infected TB. We suggested that our Taiwan‐based analysis can be extended to the context of developing countries, where TB remains a substantial cause of elderly morbidity and mortality.     

Change in Public Concern and Responsive Behaviors Toward Air Pollution Under the Dome

This study evaluates the effect of the documentary Under the Dome on the concern and responsive behaviors of the public regarding air pollution in China, with two surveys conducted before and after watching the documentary. Employing difference-in-differences regression, this study answers two research questions: (1) Does Under the Dome change public concern about air pollution? (2) Does Under the Dome change public behaviors in response to air pollution, including protective behaviors (i.e., wearing face masks) and mitigation behaviors (i.e., reducing car driving)? We find that the information campaign (1) protects against the decline of public concern about air pollution in Beijing and (2) moderates the degree to which people's perceived severity, perceived susceptibility, and sense of self-efficacy influence protective behaviors and moderates the degree to which people's belief in the cooperative behaviors by others influences mitigation behaviors. This study provides evidence that information campaigns of the Under the Dome type are effective in raising public awareness; however, the information campaign did not directly influence public protective and mitigation behaviors.     

Considering the Risk of Infection by Cryptosporidium via Consumption of Municipally Treated Drinking Water from a Surface Water Source in a Southwestern Ontario Community

Through the use of case‐control analyses and quantitative microbial risk assessment (QMRA), relative risks of transmission of cryptosporidiosis have been evaluated (recreational water exposure vs. drinking water consumption) for a Canadian community with higher than national rates of cryptosporidiosis. A QMRA was developed to assess the risk of Cryptosporidium infection through the consumption of municipally treated drinking water. Simulations were based on site‐specific surface water contamination levels and drinking water treatment log₁₀ reduction capacity for Cryptosporidium. Results suggested that the risk of Cryptosporidium infection via drinking water in the study community, assuming routine operation of the water treatment plant, was negligible (6 infections per 10¹³ persons per day—5th percentile: 2 infections per 10¹⁵ persons per day; 95th percentile: 3 infections per 10¹² persons per day). The risk is essentially nonexistent during optimized, routine treatment operations. The study community achieves between 7 and 9 log₁₀Cryptosporidium oocyst reduction through routine water treatment processes. Although these results do not preclude the need for constant vigilance by both water treatment and public health professionals in this community, they suggest that the cause of higher rates of cryptosporidiosis are more likely due to recreational water contact, or perhaps direct animal contact. QMRA can be successfully applied at the community level to identify data gaps, rank relative public health risks, and forecast future risk scenarios. It is most useful when performed in a collaborative way with local stakeholders, from beginning to end of the risk analysis paradigm.     

Jordan's Public Policy Response to COVID-19 Pandemic: Insight and Policy Analysis

The aim of this study was to gain an understanding of how the Jordanian government has responded and continues to respond to the COVID-19 pandemic. It utilizes the interpretive policy analysis approach through document analysis. The analysis showed that Jordan created social protection policies to assist people who lost their jobs or whose work was suspended due to the coronavirus. The economic policies build solidarity and facilitate the private sector’s recovery. The health care measures firmly applied included lockdown, wearing masks, and restrictions on gatherings and public events. Jordan uses hard power and imposes sanctions on any violation that threatens the lives of others.

     

Hamiltonicity of hypercubes with a constraint of required and faulty edges

Let R and F be two disjoint edge sets in an n-dimensional hypercube Q _n . We give two constructing methods to build a Hamiltonian cycle or path that includes all the edges of R but excludes all of F. Besides, considering every vertex of Q _n incident to at most n−2 edges of F, we show that a Hamiltonian cycle exists if (A) |R|+2|F|≤2n−3 when |R|≥2, or (B) |R|+2|F|≤4n−9 when |R|≤1. Both bounds are tight. The analogous property for Hamiltonian paths is also given. Dedicated to Professor Frank K. Hwang on the occasion of his 65th birthday. Lih-Hsing Hsu’s research project is partially supported by NSC 95-2221-E-233-002. Shu-Chung Liu’s research project is partially supported by NSC 90-2115-M-163-003 and 95-2115-M-163-002. Yeong-Nan Yeh’s research project is partially supported by NSC 95-2115-M-001-009.     

带机会约束的动态投资决策模型研究

本文在BlackScholes型市场中,建立了具有投资机会约束的CaR动态投资决策模型: ,其中x是初始财富,π(t)=(π₁(t),…,π_d(t))′∈R^d为可行的证券组合过程,X^π(T)为计划期末的财富水平,CaR(x,π,T)为投资期末的在险资本,R是投资者事先给定的某正的财富水平,0<β<1通过对该模型的讨论,得到了最优常数再调整策略的显式表达式,其金融学含义包括:对于机会约束下的动态投资组合,在风险中性市场中,最优的常数再调整投资策略是纯债券投资策略,最优的在险资本值为零;在风险非中性市场中,最优的常数再调整投资策略蕴涵了共同基金定理的成立。     

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log₁₀ reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log₁₀ seed treatment alone was comparable to SIW testing alone, and each additional 1‐log₁₀ seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log₁₀ or a 5‐log₁₀ seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log₁₀ or 5‐log₁₀ seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log₁₀ seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.     

Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the availability of H&S incident data, utilizing them to mitigate accident occurrence effectively is challenging due to inherent limitations of existing data logging methods. In this study, we used a text-mining approach for retrieving meaningful terms from data and develop six deep learning (DL) models for H&S risks management in power infrastructure. The DL models include DNN_classify (risk or no risk), DNN_reg1 (loss time), DNN_reg2 (body injury), DNN_reg3 (plant and fleet), DNN_reg4 (equipment), and DNN_reg5 (environment). An H&S risk database obtained from a leading UK power infrastructure construction company was used in developing the models using the H2O framework of the R language. Performances of DL models were assessed and benchmarked with existing models using test data and appropriate performance metrics. The overall accuracy of the classification model was 0.93. The average R² value for the five regression models was 0.92, with mean absolute error between 0.91 and 0.94. The presented results, in addition to the developed user-interface module, will help practitioners obtain a better understanding of H&S challenges, minimize project costs (such as third-party insurance and equipment repairs), and offer effective strategies to mitigate H&S risk.     

The Effect of Proximity to Hurricanes Katrina and Rita on Subsequent Hurricane Outlook and Optimistic Bias

This study evaluated how individuals living on the Gulf Coast perceived hurricane risk after Hurricanes Katrina and Rita. It was hypothesized that hurricane outlook and optimistic bias for hurricane risk would be associated positively with distance from the Katrina‐Rita landfall (more optimism at greater distance), controlling for historically based hurricane risk and county population density, demographics, individual hurricane experience, and dispositional optimism. Data were collected in January 2006 through a mail survey sent to 1,375 households in 41 counties on the coast (n = 824, 60% response). The analysis used hierarchal regression to test hypotheses. Hurricane history and population density had no effect on outlook; individuals who were male, older, and with higher household incomes were associated with lower risk perception; individual hurricane experience and personal impacts from Katrina and Rita predicted greater risk perception; greater dispositional optimism predicted more optimistic outlook; distance had a small effect but predicted less optimistic outlook at greater distance (model R²= 0.21). The model for optimistic bias had fewer effects: age and community tenure were significant; dispositional optimism had a positive effect on optimistic bias; distance variables were not significant (model R²= 0.05). The study shows that an existing measure of hurricane outlook has utility, hurricane outlook appears to be a unique concept from hurricane optimistic bias, and proximity has at most small effects. Future extension of this research will include improved conceptualization and measurement of hurricane risk perception and will bring to focus several concepts involving risk communication.     

Effort-reward imbalance,overcommitment and sleep in a working population

The relationship between workplace characteristics and nocturnal sleep in a working population was investigated. Data from 709 employees (mean age=39 years; 87% men) from two German companies were analysed at the entry of the longitudinal cohort study (overall accrual 73%). We investigated the association between the effort-reward imbalance model at work (Siegrist, ) and self-reported sleep quality and sleep disturbances, as assessed by the Jenkins Sleep Quality Index. Effort and overcommitment were found to be higher, and reward was lower in participants with lower (N=328) vs. higher sleep quality (N=381), as well as in participants with (N=217) vs. without (N=492) disturbed sleep (all ps<.001). In regression analyses, lower sleep quality (R ²=.33) and sleep disturbances (R ² _Nagelkerke=.33) were predicted by older age, female gender (only significant for sleep disturbances), shift-work, lower physical and mental health functioning, and higher overcommitment. Individuals were 1.7 times more likely to report disturbed sleep per standard deviation increase in overcommitment. Gender-stratified analyses revealed that higher overcommitment was associated with unfavourable sleep in men, while in women poor sleep was related to lower reward. The findings suggest that overcommitment at work interferes with restful sleep in men, while in women disturbed sleep may be associated with the amount of overcommitment and perceived job reward and sleep quality associated with the perceived reward.     

Assessing the effect on the public health risk of current and alternative border control of Salmonella Typhimurium and Enteritidis in imported frozen poultry meat in Jordan

The JFDA applies border control for Salmonella Typhimurium and Salmonella Enteritidis in frozen poultry products. A QMRA model was developed to evaluate the effectiveness of this system in controlling the risk for consumers. The model consists of three modules; consumer phase, risk estimation, and risk reduction. The model inputs were the occurrence of Salmonella in different types of imported poultry products, the LOD of the Rapid’Salmonella, the number of tested samples of each batch, and the criteria for rejection. The model outputs were public health impact as the Minimum Relative Residual Risk (MRRR) given the batches’ refusal and the percentage of Batches that are Not-compliant with the Microbiological Criteria (BNMC) of rejection. To estimate the overall MRRR of the border control, the estimated country and product-specific MRRR were summarized and weighted by the total imports of each product from each country. The current border control based on one sample per batch gives an overall MRRR value of 27%. The alternative scenarios based on three and five samples per batch are 12% and 8%, respectively. Overall, the higher the prevalence and/or concentration of Salmonella in imported products, the more the likelihood that batches will be rejected. For products with up-to-date data of occurrence, the estimated BNMC was similar to the observed proportion of rejected batches. The lack of data on the Salmonella concentrations in poultry products from different countries is the major source of the uncertainties in the model. It reduces our opportunities to obtain valid estimates of the absolute risk.     

Exposure Factors for Wastewater‐Irrigated Asian Vegetables and a Probabilistic Rotavirus Disease Burden Model for Their Consumption

Many farmers in water‐scarce regions of developing countries use wastewater to irrigate vegetables and other agricultural crops, a practice that may expand with climate change. There are a number of health risks associated with wastewater irrigation for human food crops, particularly with surface irrigation techniques common in the developing world. The World Health Organization (WHO) recommends using quantitative microbial risk assessment (QMRA) to determine if the irrigation scheme meets health standards. However, only a few vegetables have been studied for wastewater risk and little information is known about the disease burden of wastewater‐irrigated vegetable consumption in China. To bridge this knowledge gap, an experiment was conducted to determine volume of water left on Asian vegetables and lettuce after irrigation. One hundred samples each of Chinese chard (Brassica rapa var. chinensis), Chinese broccoli (Brassica oleracea var. alboglabra), Chinese flowering cabbage (Brassica rapa var. parachinensis), and lettuce (Lactuca sativa) were harvested after overhead sprinkler irrigation. Chinese broccoli and flowering cabbage were found to capture the most water and lettuce the least. QMRAs were then constructed to estimate rotavirus disease burden from consumption of wastewater‐irrigated Asian vegetables in Beijing. Results indicate that estimated risks from these reuse scenarios exceed WHO guideline thresholds for acceptable disease burden for wastewater use, signifying that reduction of pathogen concentration or stricter risk management is necessary for safe reuse. Considering the widespread practice of wastewater irrigation for food production, particularly in developing countries, incorporation of water retention factors in QMRAs can reduce uncertainty regarding health risks for consumers worldwide.     

A Cross-national Analysis of Global E-government

To explore the determinants of global e-government performance, this paper examines the aggregate data of 163 different countries by conducting multivariate statistical analysis. The results of multivariate regression analysis indicate that the performance of digital government is likely to be determined by economic wealth, education, urbanization, civil liberties, government effectiveness, and the interaction between Internet usage and economic wealth, while the extent of internet penetration alone does not determine e-government performance. More importantly, this study indicates that government effectiveness is much more important than any other factors in determining global e-government performance. The countries with high e-government performance are likely to be the wealthy, developed, and Western countries or the rapidly developing Asian countries.

The Economic Value of Market Information for Farmers in Developing Economies

In developing countries, farmers lack information for making informed production, manufacturing/selling decisions to improve their earnings. To alleviate poverty, various non‐governmental organizations (NGOs) and for‐profit companies have developed different ways to distribute information about market price, crop advisory and farming technique to farmers. We investigate a fundamental question: will information create economic value for farmers? We construct a stylized model in which farmers face an uncertain market price (demand) and must make production decisions before the market price is realized. Each farmer has an imprecise private signal and an imprecise public signal to estimate the actual market price. By examining the equilibrium outcomes associated with a Cournot competition game, we show that private signals do create value by improving farmers' welfare. However, this value deteriorates as the public signal becomes available (or more precise). In contrast, in the presence of private signals, the public signal does not always create value for the farmers. Nevertheless, both private and public signals will reduce price variation. We also consider two separate extensions that involve non‐identical private signal precisions and farmers' risk‐aversion, and we find that the same results continue to hold. More importantly, we find that the public signal can reduce welfare inequality when farmers have non‐identical private signal precisions. Also, risk‐aversion can dampen the value created by private or public information.     

Efficient point coverage in wireless sensor networks

We study minimum-cost sensor placement on a bounded 3D sensing field, R, which comprises a number of discrete points that may or may not be grid points. Suppose we have ℓ types of sensors available with different sensing ranges and different costs. We want to find, given an integer σ ≥ 1, a selection of sensors and a subset of points to place these sensors such that every point in R is covered by at least σ sensors and the total cost of the sensors is minimum. This problem is known to be NP-hard. Let k_i denote the maximum number of points that can be covered by a sensor of the ith type. We present in this paper a polynomial-time approximation algorithm for this problem with a proven approximation ratio . In applications where the distance of any two points has a fixed positive lower bound, each k_i is a constant, and so we have a polynomial-time approximation algorithms with a constant guarantee. While γ may be large, we note that it is only a worst-case upper bound. In practice the actual approximation ratio is small, even on randomly generated points that do not have a fixed positive minimum distance between them. We provide a number of numerical results for comparing approximation solutions and optimal solutions, and show that the actual approximation ratios in these examples are all less than 3, even though γ is substantially larger. This research was supported in part by NSF under grant CCF-04080261 and by NSF of China under grant 60273062.     

An SEIR Model with Time-Varying Coefficients for Analyzing the SARS-CoV-2 Epidemic

In this study, we propose a time-dependent susceptible-exposed-infected-recovered (SEIR) model for the analysis of the SARS-CoV-2 epidemic outbreak in three different countries, the United States, Italy, and Iceland using public data inherent the numbers of the epidemic wave. Since several types and grades of actions were adopted by the governments, including travel restrictions, social distancing, or limitation of movement, we want to investigate how these measures can affect the epidemic curve of the infectious population. The parameters of interest for the SEIR model were estimated employing a composite likelihood approach. Moreover, standard errors have been corrected for temporal dependence. The adoption of restrictive measures results in flatten epidemic curves, and the future evolution indicated a decrease in the number of cases.     

DEFINING THE ROLE AND ESTIMATION OF THE DISCOUNT FACTOR IN A SECURITY VALUATION MODEL

In this paper we show that a striking improvement in the explanatory power of a “dividend type” of security valuation model can be obtained by classifying companies into equivalent risk categories, estimating the discount factor for a category, and then constructing a cross-sectional model for it. The increased homogenity of the data base improves the model's sensitivity to systematic forces, but does not sacrifice the heterogeneity of the independent variables. Assuming that the difference between the intrinsic value of a security and its market value should be zero, the authors demonstrate a method for estimating k_jt, the market discount rate for the j^th risk category in the t^th period. The results of the estimation procedure appear to be reasonable and when used in our security valuation model they produce higher coefficients of determination (R²) than those previously published for similar models.     

Testing for Common Conditionally Heteroskedastic Factors

This paper proposes a test for common conditionally heteroskedastic (CH) features in asset returns. Following Engle and Kozicki (1993), the common CH features property is expressed in terms of testable overidentifying moment restrictions. However, as we show, these moment conditions have a degenerate Jacobian matrix at the true parameter value and therefore the standard asymptotic results of Hansen (1982) do not apply. We show in this context that Hansen's (1982) J‐test statistic is asymptotically distributed as the minimum of the limit of a certain random process with a markedly nonstandard distribution. If two assets are considered, this asymptotic distribution is a fifty–fifty mixture of χ²_H−1 and χ²_H, where H is the number of moment conditions, as opposed to a χ²_H−1. With more than two assets, this distribution lies between the χ²_H−p and χ²_H (p denotes the number of parameters). These results show that ignoring the lack of first‐order identification of the moment condition model leads to oversized tests with a possibly increasing overrejection rate with the number of assets. A Monte Carlo study illustrates these findings.     

Media exposure,threat processing,and mitigation behaviors in Gulf Coast residents facing the co-occurring threats of COVID-19 and hurricanes

The 2020 hurricane season threatened millions of Americans concurrently grappling with COVID-19. Processes guiding individual-level mitigation for these conceptually distinct threats, one novel and chronic (COVID-19), the other familiar and episodic (hurricanes), are unknown. Theories of health protective behaviors suggest that inputs from external stimuli (e.g., traditional and social media) lead to threat processing, including perceived efficacy (self- and response) and perceived threat (susceptibility and severity), guiding mitigation behavior. We surveyed a representative sample of Florida and Texas residents (N = 1846) between April 14, 2020 and April 27, 2020; many had previous hurricane exposure; all were previously assessed between September 8, 2017 and September 11, 2017. Using preregistered analyses, two generalized structural equation models tested direct and indirect effects of media exposure (traditional media, social media) on self-reported (1) COVID-19 mitigation (handwashing, mask-wearing, social distancing) and (2) hurricane mitigation (preparation behaviors), as mediated through perceived efficacy (self- and response) and perceived threat (susceptibility and severity). Self-efficacy and response efficacy were associated with social distancing (p = .002), handwashing, mask-wearing, and hurricane preparation (ps < 0.001). Perceived susceptibility was positively associated with social distancing (p = 0.017) and hurricane preparation (p < 0.001). Perceived severity was positively associated with social distancing (p < 0.001). Traditional media exhibited indirect effects on COVID-19 mitigation through increased response efficacy (ps < 0.05), and to a lesser extent self-efficacy (p < 0.05), and on hurricane preparation through increased self-efficacy and response efficacy and perceived susceptibility (ps < 0.05). Social media did not exhibit indirect effects on COVID-19 or hurricane mitigation. Communications targeting efficacy and susceptibility may encourage mitigation behavior; research should explore how social media campaigns can more effectively target threat processing, guiding protective actions.     

Consideration of the Aerosol Transmission for COVID-19 and Public Health

This article analyzes the available evidence to address airborne, aerosol transmission of the SARS-CoV-2. We review and present three lines of evidence: case reports of transmission for asymptomatic individuals in association with studies that show that normal breathing and talking produce predominantly small droplets of the size that are subject to aerosol transport; limited empirical data that have recorded aerosolized SARS-CoV-2 particles that remain suspended in the air for hours and are subject to transport over distances including outside of rooms and intrabuilding, and the broader literature that further supports the importance of aerosol transmission of infectious diseases. The weight of the available evidence warrants immediate attention to address the significance of aerosols and implications for public health protection.