Article
Multidisciplinary Sciences
James Van Yperen, Eduard Campillo-Funollet, Rebecca Inkpen, Anjum Memon, Anotida Madzvamuse
Summary: The mathematical interpretation of interventions for epidemics often focuses on finding the optimal time to intervene and managing impact based on the number of infections. However, effectively implementing these methods can be challenging due to the lack of available information during an epidemic or imperfect data on infection levels. This paper presents an alternative approach to mathematical modeling by considering hospital demand and capacity as the basis for interventions. By calibrating a susceptible-exposed-infectious-recovered-died model using data-driven modeling, the dynamics of the epidemic in different regions of the UK are analyzed. The calibrated parameters are then used to forecast scenarios and understand how the timing, severity, and conditions for releasing interventions affect the overall picture of the epidemic.
Article
Engineering, Multidisciplinary
Tijs W. Alleman, Michiel Rollier, Jenna Vergeynst, Jan M. Baetens
Summary: In this work, a compartmental SEIQRD model is extended to incorporate SARS-CoV-2 variants of concern, vaccines, and seasonality in the context of the COVID-19 pandemic in Belgium. The model includes geographic stratification and interprovincial mobility, although the latter was found to be unnecessary for accurately describing the pandemic. The study demonstrates the usefulness of the model in informing decision-making regarding the relaxation of social restrictions and highlights the advantages and disadvantages of geographically stratified models compared to national-level models.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Engineering, Environmental
Xavier Fernandez-Cassi, Andreas Scheidegger, Carola Banziger, Federica Cariti, Alex Tunas Corzon, Pravin Ganesanandamoorthy, Joseph C. Lemaitre, Christoph Ort, Timothy R. Julian, Tamar Kohn
Summary: The study found that wastewater monitoring can more accurately track the timing and shape of COVID-19 infection peaks, while confirmed cases provide a better estimate of the subsequent decline in infections. Under conditions of high test positivity rates, wastewater-based epidemiology provides critical information that complements clinical data in monitoring the pandemic trajectory.
Article
Mathematics, Applied
Jiaxin Wang, Chun Yang, Bo Chen
Summary: This research proposes a novel epidemiological model in multiplex networks, exploring the interplay between disease and awareness. Simulation results show that stronger heterogeneity in individual activities promotes disease spreading, while stronger heterogeneity in the network impedes disease spreading. Furthermore, the distribution of individual infection ability has varying effects on disease spreading.
Article
Infectious Diseases
Qiuping Chen, Shanshan Yu, Jia Rui, Yichao Guo, Shiting Yang, Guzainuer Abudurusuli, Zimei Yang, Chan Liu, Li Luo, Mingzhai Wang, Zhao Lei, Qinglong Zhao, Laurent Gavotte, Yan Niu, Roger Frutos, Tianmu Chen
Summary: Despite the steady decline in the global tuberculosis epidemic, school tuberculosis outbreaks have been frequently reported in China. This study found that the non-student population plays a dominant role in the transmission of tuberculosis, exerting a strong influence on the transmission among students.
INFECTIOUS DISEASES OF POVERTY
(2022)
Article
Biochemical Research Methods
Daipeng Chen, Yuyi Xue, Yanni Xiao
Summary: This study introduces a strategy to restrict population travel to prevent the spatial spread of infectious diseases and proposes a model for describing the spread of infectious diseases. The focus of the study is on determining when travel restrictions can be lifted and providing a new travel flux triggering scheme.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Gavin M. Abernethy, David H. Glass
Summary: This article presents the use of an age-structured SEIR model to simulate the spread of COVID-19 in the population of Northern Ireland. The model is used to identify optimal timings for short-term lockdowns that can enable long-term pandemic exit strategies.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Mathematics, Applied
Julia Calatayud, Marc Jornet, Jorge Mateu
Summary: We study the dynamics of abstract models for crime evolution, taking into account participation in crime and incarceration. Individuals transition between three segments, and crime is viewed as a social epidemic. The models incorporate spatial variability using discrete and continuous forms of space, and the effect of the basic reproduction number on the long-term dynamics of crime is examined.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Zakaria Shams Siam, Rubyat Tasnuva Hasan, Hossain Ahamed, Samiya Kabir Youme, Soumik Sarker Anik, Sumaia Islam Alita, Rashedur M. Rahman
Summary: This study proposes a fuzzy rule-based compartmental model to predict the transmission dynamics of SARS-CoV-2. By considering a dynamic transmission possibility variable as a function of time and three fuzzy linguistic intervention variables, the model can effectively analyze and predict active cases and total death cases. The integration of fuzzy logic in the model generates a more realistic dynamic transmission possibility variable and helps in controlling the transmission of SARS-CoV-2 by addressing intervention and transmission heterogeneity.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2022)
Article
Biochemical Research Methods
Elise J. Kuylen, Andrea Torneri, Lander Willem, Pieter J. K. Libin, Steven Abrams, Pietro Coletti, Nicolas Franco, Frederik Verelst, Philippe Beutels, Jori Liesenborgs, Niel Hens
Summary: Superspreading events play a significant role in the spread of pathogens, and individual heterogeneity in infectiousness and contact behavior can result in different effects on outbreaks. Variations in infectiousness and contact-related heterogeneity can impact the persistence, total case numbers, speed, peak timing, and herd immunity threshold of outbreaks.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Philippe Lemey, Nick Ruktanonchai, Samuel L. Hong, Vittoria Colizza, Chiara Poletto, Frederik Van den Broeck, Mandev S. Gill, Xiang Ji, Anthony Levasseur, Bas B. Oude Munnink, Marion Koopmans, Adam Sadilek, Shengjie Lai, Andrew J. Tatem, Guy Baele, Marc A. Suchard, Simon Dellicour
Summary: In late summer 2020, more than half of the SARS-CoV-2 lineages circulating in many European countries resulted from new introductions, and the success in onward transmission of these newly introduced lineages was negatively associated with the local incidence of COVID-19. The widespread dissemination of variants in summer 2020 highlights the threat of viral spread when restrictions are lifted.
Article
Computer Science, Interdisciplinary Applications
Alberto Olivares, Ernesto Staffetti
Summary: This study compares the effects of different vaccination strategies on SARS-CoV-2 virus transmission, indicating that early control measures significantly reduce the number of symptomatic infected subjects. The proposed approach based on optimal control of compartmental epidemic models provides a suitable method for scheduling vaccination plans and testing policies to control the spread of the virus.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Engineering, Chemical
Jamal Darand, Ali Jafarian, Shahriar Tizbin
Summary: Forced Circulation (FC) crystallizer plays a critical role in Zero Liquid Discharge desalination process. This study utilizes a hybrid compartmental-CFD model to modify the compartmental model with CFD simulation results, effectively considering the hydrodynamic effects. The results demonstrate narrower distribution and decreased Sauter diameter after considering the hydrodynamic effects.
Article
Microbiology
Nora M. M. Gerhards, Jose L. L. Gonzales, Sandra Vreman, Lars Ravesloot, Judith M. A. van den Brand, Harmen P. P. Doekes, Herman F. F. Egberink, Arjan Stegeman, Nadia Oreshkova, Wim H. M. van der Poel, Mart C. M. de Jong
Summary: This study shows that domestic cats can be infected with SARS-CoV-2 through direct and indirect contact with infected cats or contaminated environments. The transmission rate between cats is efficient, but the infectiousness of a contaminated environment decays rapidly.
MICROBIOLOGY SPECTRUM
(2023)
Article
Biochemical Research Methods
Robert Hinch, William J. M. Probert, Anel Nurtay, Michelle Kendall, Chris Wymant, Matthew Hall, Katrina Lythgoe, Ana Bulas Cruz, Lele Zhao, Andrea Stewart, Luca Ferretti, Daniel Montero, James Warren, Nicole Mather, Matthew Abueg, Neo Wu, Olivier Legat, Katie Bentley, Thomas Mead, Kelvin Van-Vuuren, Dylan Feldner-Busztin, Tommaso Ristori, Anthony Finkelstein, David G. Bonsall, Lucie Abeler-Dorner, Christophe Fraser
Summary: OpenABM-Covid19 is a detailed epidemic model that simulates the spread of COVID-19 in a population of individuals. It allows scientists and policymakers to quickly compare the effectiveness of non-pharmaceutical interventions and provides accurate simulation results.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Statistics & Probability
Cathy W. S. Chen, Sangyeol Lee, K. Khamthong
Summary: This study introduces a class of nonlinear hysteretic integer-valued GARCH models to describe the occurrence of weekly dengue hemorrhagic fever cases using three meteorological covariates. The model incorporates a three-regime switching mechanism with a buffer zone to explain various characteristics and includes Poisson, negative binomial, and log-linked forms. Results suggest that the hysteretic negative binomial integer-valued GARCH model is superior in describing larger counts.
COMPUTATIONAL STATISTICS
(2021)
Article
Economics
Cathy W. S. Chen, Hong Than-Thi, Manabu Asai
Summary: This paper investigates a conditionally dynamic asymmetric structure in correlations when multivariate time series follow a hysteretic autoregressive GARCH process that exhibits nonlinear switching in mean, volatility, and correlation. The new model allows for distinct responses to negative return shocks and employs an adaptive Bayesian MCMC method for parameter estimation and quantile forecasting. Backtesting is conducted to measure the effectiveness of value-at-risk forecasting, and the accuracy of volatility forecast is evaluated to determine persistence of conditional asymmetry in target time series.
COMPUTATIONAL ECONOMICS
(2021)
Article
Infectious Diseases
Cathy W. S. Chen, Sangyeol Lee, Manh Cuong Dong, Masanobu Taniguchi
Summary: This research analyzes open-source survey data from 14 countries and finds that the public pays more attention to the effectiveness of government responses to COVID-19 rather than the policies themselves. Health policies and economic support policies impact public approval of national responses. Citizens in Japan and South Korea have significantly different levels of satisfaction with their government responses compared to other countries.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2021)
Article
Statistics & Probability
Cathy W. S. Chen, Bonny Lee
Summary: This research introduces a method based on segmented autoregressive models and GARCH errors, utilizing skew Student-t distribution to detect structural changes in financial time series. By employing Bayesian methods and deviance information criterion, the number and locations of structural change points can be accurately determined, achieving more efficient capturing of market volatility.
STATISTICAL METHODS AND APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Cathy W. S. Chen, Tsai-Hung Fan
Summary: This research examines the political issues resulting from governments' responses to the COVID-19 pandemic and their impact on public opinion from an international perspective. The study aims to measure the association between approval ratings during the pandemic and political support, as well as identify exceptional cases. Findings reveal partisan polarization on COVID-19 policies, influencing differences in political support.
Article
Statistics & Probability
Aljo Clair Pingal, Cathy W. S. Chen
Summary: This research introduces a class of transfer function models for integer-valued time series and evaluates their effectiveness in detecting different types of interventions. Bayesian methods and statistical criteria are used for model comparisons, and simulation studies and real crime data application are conducted for validation.
STATISTICAL MODELLING
(2022)
Article
Economics
Cathy W. S. Chen, Edward M. H. Lin, Tara F. J. Huang
Summary: This research introduces a new model, the realized hysteretic GARCH, which incorporates delayed mean and volatility switching based on a hysteresis variable. The Bayesian MCMC procedure is employed to estimate model parameters and forecast volatility, VaR, and ES. Simulation and empirical results demonstrate the superior performance of the realized hysteretic GARCH model as a quantile forecasting tool.
JOURNAL OF FORECASTING
(2022)
Editorial Material
Operations Research & Management Science
Mike K. P. So, Cathy W. S. Chen
Summary: This paper proposes a novel Bayesian approach based on dynamic linear models for multivariate dynamic modeling, which enables information sharing among different sectors, local store groups, and item categories through the use of auxiliary information. The authors demonstrate the feasibility of parallel computing with multiple item categories, making the Bayesian method highly scalable. The proposed method in the paper should have wide applicability in inventory and revenue management.
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2022)
Article
Public, Environmental & Occupational Health
Cathy W. S. Chen, Mike K. P. So, Feng-Chi Liu
Summary: This study assesses the effectiveness of long-term non-pharmaceutical interventions implemented by governments in East Asia during the COVID-19 pandemic. The findings indicate that these interventions have reduced COVID-19 infections before the emergence of the Omicron variant. Additionally, Taiwan does not exhibit a policy lag between daily new confirmed cases and government interventions. The case fatality ratios for the elderly population are relatively low in Japan, Hong Kong, and South Korea, but high in Taiwan.
EPIDEMIOLOGY AND INFECTION
(2022)
Article
Business, Finance
Cathy W. S. Chen, Hsiao-Yun Hsu, Toshiaki Watanabe
Summary: This research proposes a new class of RES-CAViaR models that utilize daily realized volatility and expected shortfall to simultaneously forecast VaR and ES. The inclusion of weekly and monthly realized volatilities approximates a long-memory process. The results show that the realized CAViaR-type models outperform other models in various tests and measurements.
FINANCE RESEARCH LETTERS
(2023)
Article
Statistics & Probability
Cathy W. S. Chen, Feng-Chi Liu, Aljo Clair Pingal
Summary: This study proposes integer-valued transfer function models with zero-inflated generalized Poisson and negative binomial distributions to describe overdispersion, a large proportion of zeros, and the influence of exogenous variables. Effective Bayesian estimation and model selection methods are provided for analyzing weekly dengue cases with two meteorological covariates.
STATISTICS & PROBABILITY LETTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Kai Y. K. Wang, Cathy W. S. Chen, Mike K. P. So
Summary: The Fama-French three-factor model improves the capital asset pricing model by including size risk and value risk factors as market risk factors. This study proposes a quantile Fama-French three-factor model with GARCH-type dynamics, leptokurtosis, and skewness through asymmetric Student t errors to address the limitations of existing models. The proposed model allows for investigating the effects of daily volatility and market risk factors under different market conditions represented by quantile levels.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2023)
Article
Computer Science, Interdisciplinary Applications
Cathy W. S. Chen, Chun-Shu Chen, Mo-Hua Hsiung
Summary: The study proposes a new model to investigate the spread of infectious diseases. By considering the neighboring locations of the target series, the model presents a continuous conceptualization of distance and highlights the non-separability of space and time. The proposed model successfully captures the characteristics of spatial dependency, over-dispersion, and a large portion of zeros, providing a comprehensive model for the observed phenomena in the data.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2023)
Article
Economics
Cathy W. S. Chen, Toshiaki Watanabe, Edward M. H. Lin
Summary: Advances in various GARCH models have effectively accounted for biases in realized volatility and have been extended to nonlinear or long-term memory patterns. These models demonstrate potential in quantile forecasts of financial returns and volatility forecasting.
ECONOMETRICS AND STATISTICS
(2023)
Article
Business, Finance
Manh Cuong Dong, Cathy W. S. Chen, Manabu Asai
Summary: This article examines the non-linear responses of a stock market's realized measure of volatility to its potential factors across different quantile levels. Using a threshold quantile autoregressive model and GARCH specification, the study finds that volatility clustering, leverage effect, and negative and asymmetric impact of trading volume on market volatility exist. The asymmetric characteristic of the news impact curve of the stock market varies over different quantile levels.
INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS
(2023)
