1
|
Tovissodé CF, Baumgaertner B. Heterogeneous risk tolerance, in-groups, and epidemic waves. FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS 2024; 10:1360001. [PMID: 38818516 PMCID: PMC11138946 DOI: 10.3389/fams.2024.1360001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
There is a growing interest in the joint modeling of the dynamics of disease and health-related beliefs and attitudes, but coupling mechanisms are yet to be understood. We introduce a model where risk information, which can be delayed, comes in two flavors, including historical risk derived from perceived incidence data and predicted risk information. Our model also includes an interpretation domain where the behavioral response to risk information is subject to in-group pressure. We then simulate how the strength of behavioral reaction impacts epidemic severity as measured by epidemic peak size, number of waves, and final size. Simulated behavioral response is not effective when the level of protection that prophylactic behavior provides is as small as 50% or lower. At a higher level of 75% or more, we see the emergence of multiple epidemic waves. In addition, simulations show that different behavioral response profiles can lead to various epidemic outcomes that are non-monotonic with the strength of reaction to risk information. We also modeled heterogeneity in the response profile of a population and find they can lead to less severe epidemic outcome in terms of peak size.
Collapse
Affiliation(s)
| | - Bert Baumgaertner
- Department of Politics and Philosophy, University of Idaho, Moscow, ID, United States
| |
Collapse
|
2
|
Arshad S, Siddique I, Nawaz F, Shaheen A, Khurshid H. Dynamics of a fractional order mathematical model for COVID-19 epidemic transmission. PHYSICA A 2023; 609:128383. [PMID: 36506918 PMCID: PMC9721378 DOI: 10.1016/j.physa.2022.128383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 08/24/2022] [Indexed: 06/17/2023]
Abstract
To achieve the aim of immediately halting spread of COVID-19 it is essential to know the dynamic behavior of the virus of intensive level of replication. Simply analyzing experimental data to learn about this disease consumes a lot of effort and cost. Mathematical models may be able to assist in this regard. Through integrating the mathematical frameworks with the accessible disease data it will be useful and outlay to comprehend the primary components involved in the spreading of COVID-19. There are so many techniques to formulate the impact of disease on the population mathematically, including deterministic modeling, stochastic modeling or fractional order modeling etc. Fractional derivative modeling is one of the essential techniques for analyzing real-world issues and making accurate assessments of situations. In this paper, a fractional order epidemic model that represents the transmission of COVID-19 using seven compartments of population susceptible, exposed, infective, recovered, the quarantine population, recovered-exposed, and dead population is provided. The fractional order derivative is considered in the Caputo sense. In order to determine the epidemic forecast and persistence, we calculate the reproduction number R 0 . Applying fixed point theory, the existence and uniqueness of the solutions of fractional order derivative have been studied . Moreover, we implement the generalized Adams-Bashforth-Moulton method to get an approximate solution of the fractional-order COVID-19 model. Finally, numerical result and an outstanding graphic simulation are presented.
Collapse
Affiliation(s)
- Sadia Arshad
- Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
| | - Imran Siddique
- Department of Mathematics, University of Management and Technology, Lahore 54770, Pakistan
| | - Fariha Nawaz
- Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
| | - Aqila Shaheen
- School of Mathematics, Minhaj University, Lahore, Pakistan
| | - Hina Khurshid
- School of Mathematics, Minhaj University, Lahore, Pakistan
| |
Collapse
|
3
|
Sung CL. Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak. Ann Appl Stat 2022. [DOI: 10.1214/22-aoas1601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Chih-Li Sung
- Department of Statistics and Probability, Michigan State University
| |
Collapse
|
4
|
Shi Y, Huang R, Cui H. Prediction and Analysis of Tourist Management Strategy Based on the SEIR Model during the COVID-19 Period. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:10548. [PMID: 34639848 PMCID: PMC8508590 DOI: 10.3390/ijerph181910548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/22/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022]
Abstract
Tourism destinations are now facing a dilemma choice of controlling the epidemic or developing the economy. This paper takes Macao, a typical international tourist city, as an example to study the strategy of tourist source control during the COVID-19 period. According to the published epidemic data of Macao, this study has established an improved SEIR (Susceptible-Exposed-Infected-Recovered) model, formulated six control strategies against the current epidemic, and used the model above to simulate the time required for all confirmed cases to recover and discharge under different strategies. By taking into consideration the gross revenue of Macao's gambling industry from 2017 to 2019, the impact of different strategies on the economy is predicted and three control strategies are found to be feasible. This study shows that an effective way to break through the above dilemma is to design the tourist management strategy by screening the source of passengers and controlling the upper limit of capacity of destination. These findings provide a scientific basis for tourism destinations in formulating public policies. The improved SEIR model is more consistent with the actual conversion rule of patients in the current COVID-19 epidemic, and it can be applied to further public health related research.
Collapse
Affiliation(s)
- Yongdong Shi
- School of Business, Macau University of Science and Technology, Macao 999078, China; (Y.S.); (R.H.)
| | - Rongsheng Huang
- School of Business, Macau University of Science and Technology, Macao 999078, China; (Y.S.); (R.H.)
| | - Hanwen Cui
- School of Computer Science, Zhuhai College of Science and Technology, Zhuhai 519041, China
| |
Collapse
|
5
|
A Study on COVID-19 Incidence in Europe through Two SEIR Epidemic Models Which Consider Mixed Contagions from Asymptomatic and Symptomatic Individuals. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11146266] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The impact of the SARS-CoV-2 (COVID-19) on the world has been partially controlled through different measures of social isolation and prophylaxis. Two new SEIR (Susceptible-Exposed-Infected-Recovered) models are proposed in order to describe this spread through different countries of Europe. In both models the infectivity of the asymptomatic period during the exposed stage of the disease will be taken into account. The different transmission rates of the SEIR models are calculated by considering the different locations and, more importantly, the lockdown measures implemented in each region. A new classification of these intervention measures will be set and their influence on the values of the transmission rates will be estimated through regression analysis.
Collapse
|
6
|
Complex network model for COVID-19: Human behavior, pseudo-periodic solutions and multiple epidemic waves. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS 2021; 514:125171. [PMID: 33776143 PMCID: PMC7983391 DOI: 10.1016/j.jmaa.2021.125171] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Indexed: 02/08/2023]
Abstract
We propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders.
Collapse
|
7
|
Nistal R, de la Sen M, Gabirondo J, Alonso-Quesada S, Garrido AJ, Garrido I. A Modelization of the Propagation of COVID-19 in Regions of Spain and Italy with Evaluation of the Transmission Rates Related to the Intervention Measures. BIOLOGY 2021; 10:121. [PMID: 33562465 PMCID: PMC7915204 DOI: 10.3390/biology10020121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/01/2021] [Accepted: 02/01/2021] [Indexed: 01/07/2023]
Abstract
Two discrete mathematical SIR models (Susceptible-Infectious-Recovered) are proposed for modelling the propagation of the SARS-CoV-2 (COVID-19) through Spain and Italy. One of the proposed models is delay-free while the other one considers a delay in the propagation of the infection. The objective is to estimate the transmission, also known as infectivity rate, through time taking into account the infection evolution data supplied by the official health care systems in both countries. Such a parameter is estimated through time at different regional levels and it is seen to be strongly dependent on the intervention measures such as the total (except essential activities) or partial levels of lockdown. Typically, the infectivity rate evolves towards a minimum value under total lockdown and it increases again when the confinement measures are partially or totally removed.
Collapse
Affiliation(s)
- Raul Nistal
- Department of Electricity and Electronics, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; (M.d.l.S.); (J.G.); (S.A.-Q.)
| | - Manuel de la Sen
- Department of Electricity and Electronics, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; (M.d.l.S.); (J.G.); (S.A.-Q.)
| | - Jon Gabirondo
- Department of Electricity and Electronics, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; (M.d.l.S.); (J.G.); (S.A.-Q.)
| | - Santiago Alonso-Quesada
- Department of Electricity and Electronics, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; (M.d.l.S.); (J.G.); (S.A.-Q.)
| | - Aitor J. Garrido
- Automatic Control Group (ACG), Department of Automatic Control and Systems Engineering, Institute of Research and Development of Processes (IIDP), University of the Basque Country UPV/EHU, 48013 Bilbao, Spain; (A.J.G.); (I.G.)
| | - Izaskun Garrido
- Automatic Control Group (ACG), Department of Automatic Control and Systems Engineering, Institute of Research and Development of Processes (IIDP), University of the Basque Country UPV/EHU, 48013 Bilbao, Spain; (A.J.G.); (I.G.)
| |
Collapse
|
8
|
Liu X. A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan. RESULTS IN PHYSICS 2021; 20:103712. [PMID: 33391987 PMCID: PMC7759094 DOI: 10.1016/j.rinp.2020.103712] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 05/30/2023]
Abstract
In this study, an individual-based epidemic model, considering latent-infectious-recovery periods, is presented. The analytic solution of the model in the form of recursive formulae with a time-dependent transmission coefficient is derived and implanted in Excel. The simulated epidemic curves from the model fit very well with the daily reported cases of COVID-19 in Wuhan, China and New York City (NYC), USA. These simulations show that the transmission rate of NYC's COVID-19 is nearly 30% greater than the transmission rate of Wuhan's COVID-19, and that the actual number of cumulative infected people in NYC is around 9 times the reported number of cumulative COVID-19 cases in NYC. Results from this study also provide important information about latent period, infectious period and lockdown efficiency.
Collapse
Affiliation(s)
- Xiaoping Liu
- Department of Medicine, Department of Neuroscience, West Virginia University Health Science Center, Morgantown, WV 26506, United States
| |
Collapse
|
9
|
Restricted Prevalence Rates of COVID-19's Infectivity, Hospitalization, Recovery, Mortality in the USA and Their Implications. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH 2020; 5:133-150. [PMID: 33073166 PMCID: PMC7546524 DOI: 10.1007/s41666-020-00078-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 09/07/2020] [Accepted: 09/25/2020] [Indexed: 12/13/2022]
Abstract
This article constructs and demonstrates an alternate probabilistic approach (using incidence rate restricted model), compared with the deterministic mathematical models such as SIR, to capture the impact of healthcare efforts on the prevalence rate of the COVID-19’s infectivity, hospitalization, recovery, and mortality in the eastern, central, mountain, and pacific time zone states in the USA. We add additional new properties for the incidence rate restricted Poisson probability distribution. With new properties, our method becomes feasible to comprehend not only the patterns of the prevalence rate of the COVID-19’s infectivity, hospitalization, recovery, and mortality but also to quantitatively assess the effectiveness of social distancing, healthcare management’s efforts to hospitalize the patients, the patient’s immunity to recover, and lastly the unfortunate mortality itself. To make regional comparisons (as the people’s movement is far more frequent within than outside the regional zone on daily basis), we group the COVID-19 data in terms of eastern, central, mountain, and pacific zone states. Several non-intuitive findings in the data results are noticed. They include the existence of imbalance, different vulnerability, and risk reduction in these four regions. For example, the impact of healthcare efforts is high in the recovery category in the pacific states. The impact is less in the hospitalization category in the mountain states. The least impact is seen in the infectivity category in the eastern zone states. A few thoughts on future research work are cited. It requires collecting rich data on COVID-19 and extracting valuable information for better public health policies.
Collapse
|
10
|
Xu Z, Elomri A, Kerbache L, El Omri A. Impacts of COVID-19 on Global Supply Chains: Facts and Perspectives. IEEE ENGINEERING MANAGEMENT REVIEW 2020; 48:153-166. [PMCID: PMC8768947 DOI: 10.1109/emr.2020.3018420] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 08/17/2020] [Indexed: 11/29/2023]
Abstract
The COVID-19 pandemic has caused considerable damage to various industries worldwide. Availability and supply of a wide range of raw materials, intermediate goods, and finished products have been seriously disrupted. Global supply chains (GSCs), which had shown a high level of robustness and resiliency against several disruptions in recent decades, are genuinely compromised. Using a critical reading and a causal analysis of facts and figures, this article aims to investigate the COVID-19 impacts on the effectiveness and responsiveness of GSCs and to propose a set of managerial insights to mitigate their risks and enhance their resilience in various industrial sectors. The study showed that the COVID-19 pandemic has resulted in unprecedented disruptions to the mechanics of most GSCs such as pharmaceuticals, food, electronics, automotive industry, etc. Unlike previous major disruptions, COVID-19 has adversely affected GSCs throughout all their stages with major turbulences in manufacturing, processing, transport, and logistics, as well as significant shifts in demand. The analysis pinpointed that enhancing the supply chain resilience is the main key driver to reducing vulnerability in disruptive times. Furthermore, the analysis indicated that the post-COVID-19 GSCs will tend to be shorter through revamped strategies focusing more and more on relocations and back-shoring.
Collapse
Affiliation(s)
- Zhitao Xu
- Engineering Management and Decision SciencesCollege of Science and EngineeringHamad Bin Khalifa UniversityDoha34110Qatar
| | - Adel Elomri
- Engineering Management and Decision SciencesCollege of Science and EngineeringHamad Bin Khalifa UniversityDoha34110Qatar
| | - Laoucine Kerbache
- Engineering Management and Decision SciencesCollege of Science and EngineeringHamad Bin Khalifa UniversityDoha34110Qatar
| | - Abdelfatteh El Omri
- Center of Excellence in Bionanoscience ResearchKing Abdulaziz UniversityJeddah22254Saudi Arabia
| |
Collapse
|
11
|
Marfak A, Achak D, Azizi A, Nejjari C, Aboudi K, Saad E, Hilali A, Youlyouz-Marfak I. The hidden Markov chain modelling of the COVID-19 spreading using Moroccan dataset. Data Brief 2020; 32:106067. [PMID: 32789156 PMCID: PMC7380238 DOI: 10.1016/j.dib.2020.106067] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 07/17/2020] [Accepted: 07/20/2020] [Indexed: 11/20/2022] Open
Abstract
The World Health Organization (WHO) declared in March 12, 2020 the COVID-19 disease as pandemic. In Morocco, the first local transmission case was detected in March 13. The number of confirmed cases has gradually increased to reach 15,194 on July 10, 2020. To predict the COVID-19 evolution, statistical and mathematical models such as generalized logistic growth model [1], exponential model [2], segmented Poisson model [3], Susceptible-Infected-Recovered derivative models [4] and ARIMA [5] have been proposed and used. Herein, we proposed the use of the Hidden Markov Chain, which is a statistical system modelling transitions from one state (confirmed cases, recovered, active or death) to another according to a transition probability matrix to forecast the evolution of COVID-19 in Morocco from March 14, to October 5, 2020. In our knowledge the Hidden Markov Chain was not yet applied to the COVID-19 spreading. Forecasts for the cumulative number of confirmed, recovered, active and death cases can help the Moroccan authorities to set up adequate protocols for managing the post-confinement due to COVID-19. We provided both the recorded and forecasted data matrices of the cumulative number of the confirmed, recovered and active cases through the range of the studied dates.
Collapse
Affiliation(s)
- Abdelghafour Marfak
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco.,Higher Institute of Nursing Professions and Health Technology of Rabat, Morocco
| | - Doha Achak
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| | - Asmaa Azizi
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| | - Chakib Nejjari
- Epidemiology, Clinical Research and Community Health, Faculty of Medicine and Pharmacy of Fez, University Sidi Mohammed Ben Abdellah, Fez, Morocco.,International School of Public Health, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
| | - Khalid Aboudi
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| | - Elmadani Saad
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| | - Abderraouf Hilali
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| | - Ibtissam Youlyouz-Marfak
- Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
| |
Collapse
|