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Xie Y, Ahmad I, Ikpe TIS, Sofia EF, Seno H. What Influence Could the Acceptance of Visitors Cause on the Epidemic Dynamics of a Reinfectious Disease?: A Mathematical Model. Acta Biotheor 2024; 72:3. [PMID: 38402514 PMCID: PMC10894808 DOI: 10.1007/s10441-024-09478-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 01/30/2024] [Indexed: 02/26/2024]
Abstract
The globalization in business and tourism becomes crucial more and more for the economical sustainability of local communities. In the presence of an epidemic outbreak, there must be such a decision on the policy by the host community as whether to accept visitors or not, the number of acceptable visitors, or the condition for acceptable visitors. Making use of an SIRI type of mathematical model, we consider the influence of visitors on the spread of a reinfectious disease in a community, especially assuming that a certain proportion of accepted visitors are immune. The reinfectivity of disease here means that the immunity gained by either vaccination or recovery is imperfect. With the mathematical results obtained by our analysis on the model for such an epidemic dynamics of resident and visitor populations, we find that the acceptance of visitors could have a significant influence on the disease's endemicity in the community, either suppressive or supportive.
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Affiliation(s)
- Ying Xie
- Department of Mathematical and Information Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, 980-8579, Miyagi, Japan
| | - Ishfaq Ahmad
- Department of Mathematical and Information Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, 980-8579, Miyagi, Japan
| | - ThankGod I S Ikpe
- Department of Mathematical and Information Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, 980-8579, Miyagi, Japan
| | - Elza F Sofia
- Department of Mathematical and Information Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, 980-8579, Miyagi, Japan
| | - Hiromi Seno
- Department of Mathematical and Information Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, 980-8579, Miyagi, Japan.
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Policarpo JMP, Ramos AAGF, Dye C, Faria NR, Leal FE, Moraes OJS, Parag KV, Peixoto PS, Buss L, Sabino EC, Nascimento VH, Deppman A. Scale-free dynamics of COVID-19 in a Brazilian city. Appl Math Model 2023; 121:166-184. [PMID: 37151217 PMCID: PMC10154131 DOI: 10.1016/j.apm.2023.03.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 03/13/2023] [Accepted: 03/29/2023] [Indexed: 05/09/2023]
Abstract
A common basis to address the dynamics of directly transmitted infectious diseases, such as COVID-19, are compartmental (or SIR) models. SIR models typically assume homogenous population mixing, a simplification that is convenient but unrealistic. Here we validate an existing model of a scale-free fractal infection process using high-resolution data on COVID-19 spread in São Caetano, Brazil. We find that transmission can be described by a network in which each infectious individual has a small number of susceptible contacts, of the order of 2-5. This model parameter correlated tightly with physical distancing measured by mobile phone data, such that in periods of greater distancing the model recovered a lower average number of contacts, and vice versa. We show that the SIR model is a special case of our scale-free fractal process model in which the parameter that reflects population structure is set at unity, indicating homogeneous mixing. Our more general framework better explained the dynamics of COVID-19 in São Caetano, used fewer parameters than a standard SIR model and accounted for geographically localized clusters of disease. Our model requires further validation in other locations and with other directly transmitted infectious agents.
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Affiliation(s)
| | - A A G F Ramos
- Instituto de Física - Universidade de São Paulo, Brazil
| | - C Dye
- Department of Biology, University of Oxford, UK
| | - N R Faria
- Department of Biology, University of Oxford, UK
- Imperial Coll London, MRC Ctr Global Infect Dis Anal, Sch Publ Helth, London, England, UK
- Faculdade de Medicina - Universidade de São Paulo, Brazil
| | - F E Leal
- Universidade de São Caetano do Sul, São Caetano do Sul and Programa de Oncovirologia - Instituto Nacional de Câncer, Rio de Janeiro, Brazil
| | - O J S Moraes
- Instituto de Física - Universidade de São Paulo, Brazil
| | - K V Parag
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London W2 1PG, UK
| | - P S Peixoto
- Instituto de Matemática e Estatística, Universidade de São Paulo, Brazil
| | - L Buss
- Faculdade de Medicina - Universidade de São Paulo, Brazil
| | - E C Sabino
- Faculdade de Medicina - Universidade de São Paulo, Brazil
| | | | - A Deppman
- Instituto de Física - Universidade de São Paulo, Brazil
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Ahmad I, Seno H. An epidemic dynamics model with limited isolation capacity. Theory Biosci 2023; 142:259-273. [PMID: 37462903 DOI: 10.1007/s12064-023-00399-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 07/03/2023] [Indexed: 08/13/2023]
Abstract
We consider a modified SIR model with a four-dimensional system of ordinary differential equations to consider the influence of a limited isolation capacity on the final epidemic size defined as the total number of individuals who experienced the disease at the end of an epidemic season. We derive the necessary and sufficient condition that the isolation reaches the capacity in a finite time on the way of the epidemic process, and show that the final epidemic size is monotonically decreasing in terms of the isolation capacity. We find further that the final epidemic size could have a discontinuous change at the critical value of isolation capacity below which the isolation reaches the capacity in a finite time. Our results imply that the breakdown of isolation with a limited capacity would cause a drastic increase of the epidemic size. Insufficient capacity of the isolation could lead to an unexpectedly severe epidemic situation, while such a severity would be avoidable with the sufficient isolation capacity.
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Affiliation(s)
- Ishfaq Ahmad
- Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, Miyagi, 980-8579, Japan.
| | - Hiromi Seno
- Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai, Miyagi, 980-8579, Japan
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Harris JD, Park SW, Dushoff J, Weitz JS. How time-scale differences in asymptomatic and symptomatic transmission shape SARS-CoV-2 outbreak dynamics. Epidemics 2023; 42:100664. [PMID: 36706626 PMCID: PMC9830934 DOI: 10.1016/j.epidem.2022.100664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/07/2022] [Accepted: 12/24/2022] [Indexed: 01/12/2023] Open
Abstract
Asymptomatic and symptomatic SARS-CoV-2 infections can have different characteristic time scales of transmission. These time-scale differences can shape outbreak dynamics as well as bias population-level estimates of epidemic strength, speed, and controllability. For example, prior work focusing on the initial exponential growth phase of an outbreak found that larger time scales for asymptomatic vs. symptomatic transmission can lead to under-estimates of the basic reproduction number as inferred from epidemic case data. Building upon this work, we use a series of nonlinear epidemic models to explore how differences in asymptomatic and symptomatic transmission time scales can lead to changes in the realized proportion of asymptomatic transmission throughout an epidemic. First, we find that when asymptomatic transmission time scales are longer than symptomatic transmission time scales, then the effective proportion of asymptomatic transmission increases as total incidence decreases. Moreover, these time-scale-driven impacts on epidemic dynamics are enhanced when infection status is correlated between infector and infectee pairs (e.g., due to dose-dependent impacts on symptoms). Next we apply these findings to understand the impact of time-scale differences on populations with age-dependent assortative mixing and in which the probability of having a symptomatic infection increases with age. We show that if asymptomatic generation intervals are longer than corresponding symptomatic generation intervals, then correlations between age and symptoms lead to a decrease in the age of infection during periods of epidemic decline (whether due to susceptible depletion or intervention). Altogether, these results demonstrate the need to explore the role of time-scale differences in transmission dynamics alongside behavioral changes to explain outbreak features both at early stages (e.g., in estimating the basic reproduction number) and throughout an epidemic (e.g., in connecting shifts in the age of infection to periods of changing incidence).
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Affiliation(s)
- Jeremy D Harris
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Sang Woo Park
- Department of Ecology and Evolutionary Biology, Princeton, NJ, USA.
| | - Jonathan Dushoff
- Department of Biology, McMaster University, Hamilton, Ontario, Canada; Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada; M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada.
| | - Joshua S Weitz
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA; School of Physics, Georgia Institute of Technology, Atlanta, GA, USA; Institut de Biologie, École Normale Supérieure, Paris, France.
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Chen YY, Shen X, Wang YJ, Xie JW, Fang ZX, Lin LR, Yang TC. Evaluation of the cycle threshold values of RT-PCR for SARS-CoV-2 in COVID-19 patients in predicting epidemic dynamics and monitoring surface contamination. J Infect Public Health 2022; 15:1494-1496. [PMID: 36413872 PMCID: PMC9671601 DOI: 10.1016/j.jiph.2022.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 10/20/2022] [Accepted: 11/10/2022] [Indexed: 11/18/2022] Open
Abstract
To evaluate the application of cycle threshold (Ct) values of coronavirus disease 2019 (COVID-19) patients in predicting epidemic dynamics and monitoring surface contamination. The Ct value of reverse transcriptase-polymerase chain reaction for SARS‑CoV-2 from COVID-19 patients inbound overseas in Xiamen, China was collected from October 2020 to December 2021, and the correlation of patients' Ct values with epidemic dynamics and surface contamination was evaluated. The results showed that there was an extreme inverse correlation of positivity rate in the current calendar month (ORF1ab, r = -0.692, P = 0.004; N,r = -0.629, P = 0.012) and the following calendar month (ORF1ab,r = -0.801, P = 0.001; N,r = -0.620, P = 0.018) with the median Ct values. Ct value showed better performance for monitoring surface contamination, with the area under the curve value 0.808(95 %CI: 0.748-0.869) for ORF1ab and 0.807(95 %CI:0.746-0.868) for the N gene. The patients' ORF1ab Ct value< 29.09 or N Ct value< 28.03 were 11.25 times and 10.48 times more likely to result in surface contamination than those with ORF1ab Ct value ≥ 29.09 or N Ct value≥ 28.03 (OR:11.25,95 % CI: 5.52-22.35; OR:10.48,95 % CI:5.29-20.70). Ct values were associated with the positivity rate in the current or following calendar month and predicted the epidemic dynamics. The Ct values can be used as a predictor for monitoring surface contamination to develop public health responses to COVID-19.
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Affiliation(s)
- Yu-Yan Chen
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China
| | - Xu Shen
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China,Department of Hospital Infection Management, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yong-Jing Wang
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China
| | - Jia-Wen Xie
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China,Xiamen Medical College, Xiamen, China
| | - Zan-Xi Fang
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China,Xiamen Medical College, Xiamen, China
| | - Li-Rong Lin
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China,Xiamen Medical College, Xiamen, China,Corresponding authors at: Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Tian-Ci Yang
- Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, China,Corresponding authors at: Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
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Kokurin MM, Kokurin MY, Semenova AV. Iteratively regularized Gauss-Newton type methods for approximating quasi-solutions of irregular nonlinear operator equations in Hilbert space with an application to COVID-19 epidemic dynamics. Appl Math Comput 2022; 431:127312. [PMID: 35726337 PMCID: PMC9198416 DOI: 10.1016/j.amc.2022.127312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 12/16/2021] [Accepted: 06/06/2022] [Indexed: 06/15/2023]
Abstract
We investigate a class of iteratively regularized methods for finding a quasi-solution of a noisy nonlinear irregular operator equation in Hilbert space. The iteration uses an a priori stopping rule involving the error level in input data. In assumptions that the Frechet derivative of the problem operator at the desired quasi-solution has a closed range, and that the quasi-solution fulfills the standard source condition, we establish for the obtained approximation an accuracy estimate linear with respect to the error level. The proposed iterative process is applied to the parameter identification problem for a SEIR-like model of the COVID-19 pandemic.
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Affiliation(s)
- M M Kokurin
- Mari State University, 424020 Lenin sqr. 1, Yoshkar-Ola, Russia
| | - M Yu Kokurin
- Mari State University, 424020 Lenin sqr. 1, Yoshkar-Ola, Russia
| | - A V Semenova
- Mari State University, 424020 Lenin sqr. 1, Yoshkar-Ola, Russia
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Thompson R, Wood JG, Tempia S, Muscatello DJ. Global variation in early epidemic growth rates and reproduction number of seasonal influenza. Int J Infect Dis 2022; 122:382-388. [PMID: 35718299 DOI: 10.1016/j.ijid.2022.06.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/31/2022] [Accepted: 06/13/2022] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION Little is known about global variation in early epidemic growth rates and effective reproduction numbers (Re) of seasonal influenza. We aimed to estimate global variation in Re of influenza type A and B during a single period. METHODS Country influenza detection time series from September 2017 through January 2019 were obtained from an international database. Type A and B epidemics by country were selected based on Re estimates for a five-week moving window advanced by week. Associations of Re with absolute latitude, Human Development Index, percent of the population aged <15 years and percent living rurally in each country were assessed. RESULTS Time series were included for 119 of 169 available countries. There were 100 countries with influenza A and 79 with B epidemics. Median Re for both influenza A and B epidemics was 1.23 (ranges: A 1.10, 1.60; B 1.06, 1.58). Re of influenza B, but not A, was independently associated with absolute latitude, increasing by 0.022 (95% CI 0.002, 0.043) per 10 degrees. CONCLUSIONS Re of influenza A and B were similar. Only Re of influenza B was associated with country characteristics; increasing with distance from the equator. The approach may be suitable for continuous Re surveillance.
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Affiliation(s)
- R Thompson
- School of Population Health, University of New South Wales, Australia; School of Population Health, University of New South Wales, Australia
| | - J G Wood
- School of Population Health, University of New South Wales, Australia; School of Population Health, University of New South Wales, Australia
| | - S Tempia
- National Institute for Communicable Diseases, South Africa; School of Population Health, University of New South Wales, Australia
| | - D J Muscatello
- School of Population Health, University of New South Wales, Australia; School of Population Health, University of New South Wales, Australia.
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Abstract
The recent COVID-19 pandemic has led to an increasing interest in the modeling and analysis of infectious diseases. The pandemic has made a significant impact on the way we behave and interact in our daily life. The past year has witnessed a strong interplay between human behaviors and epidemic spreading. In this paper, we propose an evolutionary game-theoretic framework to study the coupled evolution of herd behaviors and epidemics. Our framework extends the classical degree-based mean-field epidemic model over complex networks by coupling it with the evolutionary game dynamics. The statistically equivalent individuals in a population choose their social activity intensities based on the fitness or the payoffs that depend on the state of the epidemics. Meanwhile, the spreading of the infectious disease over the complex network is reciprocally influenced by the players' social activities. We analyze the coupled dynamics by studying the stationary properties of the epidemic for a given herd behavior and the structural properties of the game for a given epidemic process. The decisions of the herd turn out to be strategic substitutes. We formulate an equivalent finite-player game and an equivalent network to represent the interactions among the finite populations. We develop a structure-preserving approximation technique to study time-dependent properties of the joint evolution of the behavioral and epidemic dynamics. The resemblance between the simulated coupled dynamics and the real COVID-19 statistics in the numerical experiments indicates the predictive power of our framework.
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Affiliation(s)
- Shutian Liu
- Department of Electrical and Computer Engineering, Tandon School of Engineering New York University, Brooklyn, NY 11201 USA
| | - Yuhan Zhao
- Department of Electrical and Computer Engineering, Tandon School of Engineering New York University, Brooklyn, NY 11201 USA
| | - Quanyan Zhu
- Department of Electrical and Computer Engineering, Tandon School of Engineering New York University, Brooklyn, NY 11201 USA
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9
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Bassett J, Gethmann J, Blunk P, Conraths FJ, Hövel P. Individual-based model for the control of Bovine Viral Diarrhea spread in livestock trade networks. J Theor Biol 2021; 527:110820. [PMID: 34216591 DOI: 10.1016/j.jtbi.2021.110820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 05/31/2021] [Accepted: 06/23/2021] [Indexed: 10/21/2022]
Abstract
Bovine Viral Diarrhea (BVD) is a cattle disease that causes substantial financial losses, in particular to the dairy industry. Hence, several countries including Germany introduced compulsory disease control programs. For the case of Germany in particular, all animals had to be tested and persistently infected animals (PI animals) were removed from the population. The program was successful in reducing the number of PI animals, but was overtly expensive. Alternative approaches were therefore discussed to eliminate the remaining PI animals and alter the testing system in order to reduce costs. Contributing to these efforts, we developed an agent-based model that aimed to cover all relevant aspects of the disease biology and would allow to evaluate different control strategies. For the biological part of the infection spread, the model includes horizontal and vertical transmission, transient and persistent infections. Moreover, several control strategies including import of animals, trade restrictions, vaccination, as well as various testing schemes were included. The model was furthermore defined to be stochastic, event-driven and hierarchical, with cattle movements as the main route of spreading between farms. For the spread within farms, we included susceptible-infected-recovered (SIR) dynamics with an additional permanently infectious class. The interaction between the farms was described by a supply and demand farm manager mechanism governing the network structure and dynamics. Additionally, we carried out a sensitivity analysis of the input parameters to study the impact of extreme values on the model. Since the population size in the model is limited, we tested the influence of the initial population size on the model results. Our results showed that the model could accurately describe the dynamics of the disease in the presence and absence of disease control. Although we developed the model for the spread of BVD, it may be adapted to similar diseases of cattle and swine.
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Affiliation(s)
- Jason Bassett
- Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, Berlin 10623, Germany; Center for Humans and Machines, Max Planck Institute for Human Development, Lentzeallee 94, Berlin 14195, Germany.
| | - Jörn Gethmann
- Friedrich-Loeffler-Institut, Institute of Epidemiology, Südufer 10, Greifswald - Insel Riems, 17493 Germany
| | - Pascal Blunk
- Beta Systems IAM Software AG, Alt-Moabit 90d, Berlin 10559, Germany
| | - Franz J Conraths
- Friedrich-Loeffler-Institut, Institute of Epidemiology, Südufer 10, Greifswald - Insel Riems, 17493 Germany
| | - Philipp Hövel
- Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, Berlin 10623, Germany; School of Mathematical Sciences, University College Cork, Cork T12 XF64, Ireland
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10
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Du B, Zhao Z, Zhao J, Yu L, Sun L, Lv W. Modelling the epidemic dynamics of COVID-19 with consideration of human mobility. Int J Data Sci Anal 2021; 12:369-382. [PMID: 34189256 PMCID: PMC8221990 DOI: 10.1007/s41060-021-00271-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/03/2021] [Indexed: 01/24/2023]
Abstract
So far COVID-19 has resulted in mass deaths and huge economic losses across the world. Various measures such as quarantine and social distancing have been taken to prevent the spread of this disease. These prevention measures have changed the transmission dynamics of COVID-19 and introduced new challenges for epidemic modelling and prediction. In this paper, we study a novel disease spreading model with two important aspects. First, the proposed model takes the quarantine effect of confirmed cases on transmission dynamics into account, which can better resemble the real-world scenario. Second, our model incorporates two types of human mobility, where the intra-region human mobility is related to the internal transmission speed of the disease in the focal area and the inter-region human mobility reflects the scale of external infectious sources to a focal area. With the proposed model, we use the human mobility data from 24 cities in China and 8 states in the USA to analyse the disease spreading patterns. The results show that our model could well fit/predict the reported cases in both countries. The predictions and findings shed light on how to effectively control COVID-19 by managing human mobility behaviours.
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Affiliation(s)
- Bowen Du
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
| | - Zirong Zhao
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
| | - Jiejie Zhao
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
| | - Le Yu
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
| | - Leilei Sun
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
| | - Weifeng Lv
- State Key Laboratory of Software Development Environment, Beihang University, Haidian District, Beijing, 100191 China
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11
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Dos Santos IFF, Almeida GMA, de Moura FABF. Adaptive SIR model for propagation of SARS-CoV-2 in Brazil. Physica A 2021; 569:125773. [PMID: 33495669 PMCID: PMC7816938 DOI: 10.1016/j.physa.2021.125773] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/05/2021] [Indexed: 05/21/2023]
Abstract
We study the spreading of SARS-CoV-2 in Brazil based on official data available since March 22, 2020. Calculations are done via an adaptive susceptible-infected-removed (SIR) model featuring dynamical recuperation and propagation rates. We are able reproduce the number of confirmed cases over time with less than 5% error and also provide with short- and long-term predictions. The model can also be used to account for the epidemic dynamics in other countries with great accuracy.
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Affiliation(s)
- I F F Dos Santos
- Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió - AL, Brazil
| | - G M A Almeida
- Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió - AL, Brazil
| | - F A B F de Moura
- Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió - AL, Brazil
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12
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Diaz H, España G, Castañeda N, Rodriguez L, de la Hoz-Restrepo F. Dynamical characteristics of the COVID-19 epidemic: Estimation from cases in Colombia. Int J Infect Dis 2021; 105:26-31. [PMID: 33529705 PMCID: PMC7846888 DOI: 10.1016/j.ijid.2021.01.053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 01/19/2021] [Accepted: 01/22/2021] [Indexed: 12/13/2022] Open
Abstract
Objective To characterize the dynamics of the
coronavirus disease 2019 (COVID-19) epidemic, for modeling
purposes. Methods Data from Colombian official case
information were collated for a period of 5 months. Dynamical parameters
of the disease spread were then estimated from the data. Probability
distribution models were identified, representing the time from symptom
onset to hospitalization, to intensive care unit (ICU) admission, and to
death. Kaplan–Meier estimates were also computed for the probability of
eventually requiring hospitalization, needing ICU attention, and dying
from the disease (the case fatality ratio). Results Probability distributions of the
times and probabilities were computed for the population and for groups
based on age and sex. The results showed that for the times that
characterize the course of the disease for a given patient (time to
hospitalization, ICU admission, or death), the variation from one age
group to another was very small (around 10% of the fixed effect
intercept) and the effect of sex was even smaller (around 1%). The course
of the disease appeared to be very similar for all patients. On the other
hand, the probability that a patient would advance from one stage of the
disease to another (to hospitalization, ICU admission, or death) was
heavily influenced by sex and age. The relative risk of death for male
individuals was 1.7 times that of female individuals (based on 22 924
deaths). Conclusions The times from one stage of the
disease to another were almost independent of the major patient variables
(sex, age). This was in stark contrast to the probabilities of
progressing from one stage to another, which showed a strong dependence
on age and sex. Data also showed that the length of hospital and ICU
stays were almost independent of sex and age. The only factor that
affected this length was the eventual outcome of the disease (survival or
death); the time was significantly longer for surviving
patients.
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Yu X, Duan J, Jiang Y, Zhang H. Distinctive trajectories of the COVID-19 epidemic by age and gender: A retrospective modeling of the epidemic in South Korea. Int J Infect Dis 2020; 98:200-205. [PMID: 32623081 PMCID: PMC7330572 DOI: 10.1016/j.ijid.2020.06.101] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 06/26/2020] [Accepted: 06/29/2020] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES Elderly people had suffered a disproportionate burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories. METHODS Using publicly available data from South Korea, daily new COVID-19 cases were assessed using generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored using interactions between smoothed time terms and age and gender. RESULTS A negative binomial distribution fitted the daily case counts best. The relationship between the dynamic patterns of daily new cases and age groups was statistically significant (p<0.001), but this was not the case with gender groups. People aged 20-39 years led the epidemic processes in South Korean society with two peaks - one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above trailed behind that of the younger age group, and with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations in case counts among young adults. CONCLUSIONS Although young people drove the COVID-19 epidemic throughout society, with multiple rebounds, elderly people could still be protected from infection after the peak of the epidemic.
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Affiliation(s)
- Xinhua Yu
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN 38152, United States.
| | - Jiasong Duan
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN 38152, United States.
| | - Yu Jiang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN 38152, United States.
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN 38152, United States.
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14
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Seno H. An SIS model for the epidemic dynamics with two phases of the human day-to-day activity. J Math Biol 2020. [PMID: 32270285 DOI: 10.1007/s00285-020-01491-0/figures/13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
An SIS model is analyzed to consider the contribution of community structure to the risk of the spread of a transmissible disease. We focus on the human day-to-day activity introduced by commuting to a central place for the social activity. We assume that the community is classified into two subpopulations: commuter and non-commuter, of which the commuter has two phases of the day-to-day activity: private and social. Further we take account of the combination of contact patterns in two phases, making use of mass-action and ratio-dependent types for the infection force. We investigate the dependence of the basic reproduction number on the commuter ratio and the daily expected duration at the social phase as essential factors characterizing the community structure, and show that the dependence is significantly affected by the combination of contact patterns, and that the difference in the commuter ratio could make the risk of the spread of a transmissible disease significantly different.
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Affiliation(s)
- Hiromi Seno
- Department of Computer and Mathematical Sciences, Research Center for Pure and Applied Mathematics, Graduate School of Information Sciences, Tohoku University, Sendai, Japan.
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15
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Abstract
An SIS model is analyzed to consider the contribution of community structure to the risk of the spread of a transmissible disease. We focus on the human day-to-day activity introduced by commuting to a central place for the social activity. We assume that the community is classified into two subpopulations: commuter and non-commuter, of which the commuter has two phases of the day-to-day activity: private and social. Further we take account of the combination of contact patterns in two phases, making use of mass-action and ratio-dependent types for the infection force. We investigate the dependence of the basic reproduction number on the commuter ratio and the daily expected duration at the social phase as essential factors characterizing the community structure, and show that the dependence is significantly affected by the combination of contact patterns, and that the difference in the commuter ratio could make the risk of the spread of a transmissible disease significantly different.
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Affiliation(s)
- Hiromi Seno
- Department of Computer and Mathematical Sciences, Research Center for Pure and Applied Mathematics, Graduate School of Information Sciences, Tohoku University, Sendai, Japan.
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16
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Abstract
Recently, COVID-19 has attracted a lot of attention of researchers from different fields. Wearing masks is a frequently adopted precautionary measure. In this paper, we investigate the effect of behavior of wearing masks on epidemic dynamics in the context of COVID-19. At each time, every susceptible individual chooses whether to wear a mask or not in the next time step, which depends on an evaluation of the potential costs and perceived risk of infection. When the cost of infection is high, the majority of the population choose to wear masks, where global awareness plays a significant role. However, if the mask source is limited, global awareness may give rise to a negative result. In this case, more mask source should be allocated to the individuals with high risk of infection.
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Affiliation(s)
- Weiqiang Li
- School of Mathematics and Statistics, Wuhan University, Wuhan, 430072 China
| | - Jin Zhou
- School of Mathematics and Statistics, Wuhan University, Wuhan, 430072 China
| | - Jun-an Lu
- School of Mathematics and Statistics, Wuhan University, Wuhan, 430072 China
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17
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Abstract
This paper proposes two spatio-temporal epidemic network models based on popularity and similarity optimization (PSO), called r-SI and r-SIS, respectively, in which new connections take both popularity and similarity into account. In the spatial dimension, the epidemic process is described by the diffusion equation; in the time dimension, the growth of an epidemic is described by the logistic map. Both models are represented by partial differential equations, and can be easily solved. Simulations are performed on both artificial and real networks, demonstrating the effectiveness of the two models.
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Affiliation(s)
- Dongmei Fan
- School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; School of Science, Anhui Agricultural University, Hefei 230036, China
| | - Guo-Ping Jiang
- School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
| | - Yu-Rong Song
- School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
| | - Yin-Wei Li
- School of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
| | - Guanrong Chen
- Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
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18
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Bozick BA, Worby CJ, Metcalf CJE. Phylogeography of rubella virus in Asia: Vaccination and demography shape synchronous outbreaks. Epidemics 2019; 28:100346. [PMID: 31201039 PMCID: PMC6731519 DOI: 10.1016/j.epidem.2019.100346] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 01/16/2019] [Accepted: 05/27/2019] [Indexed: 12/18/2022] Open
Abstract
Rubella virus causes mild disease in children but for women in the early stages of pregnancy, it can cause spontaneous abortion, congenital rubella syndrome (CRS) and associated birth defects. Despite the availability of an effective vaccine, rubella virus continues to circulate endemically in several regions of the world. This is particularly true in East and Southeast (E/SE) Asia, where control efforts vary widely among countries that are well connected through travel and immigration. It is therefore important to understand how the regional persistence of rubella is affected both by dynamics occurring across countries and susceptibility within countries. Here, we use genetic and epidemiological data from countries in E/SE Asia to explore the phylogeography of rubella virus in this region. Our results underline that metapopulation dynamics are key for rubella persistence and highlight the source-sink population structure of the region. We identify countries that contribute to the regional metapopulation network and link epidemic dynamics to susceptibility profiles within each country. Our results indicate that human movement plays an important role in driving epidemic dynamics in E/SE Asia.
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Affiliation(s)
- Brooke A Bozick
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States.
| | - Colin J Worby
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
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19
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Dansu EJ, Seno H. A model for epidemic dynamics in a community with visitor subpopulation. J Theor Biol 2019; 478:115-127. [PMID: 31228488 PMCID: PMC7094103 DOI: 10.1016/j.jtbi.2019.06.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 06/16/2019] [Accepted: 06/19/2019] [Indexed: 11/04/2022]
Abstract
With a model consisting of SIR and SIS models, we affirm claims in previous works. We derive different basic reproduction numbers looking at varying perspectives. We discuss the biological meanings of these basic reproduction numbers. All the basic reproduction numbers coincide with respect to the critical condition. Relevant public health policies are proposed based on our findings.
With a five dimensional system of ordinary differential equations based on the SIR and SIS models, we consider the dynamics of epidemics in a community which consists of residents and short-stay visitors. Taking different viewpoints to consider public health policies to control the disease, we derive different basic reproduction numbers and clarify their common/different mathematical natures so as to understand their meanings in the dynamics of the epidemic. From our analyses, the short-stay visitor subpopulation could become significant in determining the fate of diseases in the community. Furthermore, our arguments demonstrate that it is necessary to choose one variant of basic reproduction number in order to formulate appropriate public health policies.
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Affiliation(s)
- Emmanuel J Dansu
- Research Center for Pure and Applied Mathematics, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai 980-8579, Japan.
| | - Hiromi Seno
- Research Center for Pure and Applied Mathematics, Graduate School of Information Sciences, Tohoku University, Aramaki-Aza-Aoba 6-3-09, Aoba-ku, Sendai 980-8579, Japan
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20
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Li C, Jiang GP, Song Y, Xia L, Li Y, Song B. Modeling and analysis of epidemic spreading on community networks with heterogeneity. J Parallel Distrib Comput 2018; 119:136-145. [PMID: 32288171 PMCID: PMC7127304 DOI: 10.1016/j.jpdc.2018.04.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Revised: 04/09/2018] [Accepted: 04/13/2018] [Indexed: 06/11/2023]
Abstract
A large number of real world networks exhibit community structure, and different communities may often possess heterogeneity. In this paper, considering the heterogeneity among communities, we construct a new community network model in which the communities show significant differences in average degree. Based on this heterogeneous community network, we propose a novel mathematical epidemic model for each community and study the epidemic dynamics in this network model. We find that the location of the initial infection node only affects the spreading velocity and barely influences the epidemic prevalence. And the epidemic threshold of entire network decreases with the increase of heterogeneity among communities. Moreover, the epidemic prevalence increases with the increase of heterogeneity around the epidemic threshold, while the converse situation holds when the infection rate is much greater than the epidemic threshold.
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Affiliation(s)
- Chanchan Li
- School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Guo-ping Jiang
- School of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Yurong Song
- School of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Lingling Xia
- School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Yinwei Li
- School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Bo Song
- School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
- Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
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21
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Kühnert D, Coscolla M, Brites D, Stucki D, Metcalfe J, Fenner L, Gagneux S, Stadler T. Tuberculosis outbreak investigation using phylodynamic analysis. Epidemics 2018; 25:47-53. [PMID: 29880306 PMCID: PMC6227250 DOI: 10.1016/j.epidem.2018.05.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 05/07/2018] [Accepted: 05/13/2018] [Indexed: 01/08/2023] Open
Abstract
Phylodynamic analysis gives insight into mycobacterium tuberculosis outbreaks. Robust estimation of epidemiological parameters in Bern thanks to high sampling rate. Infectious period for WTK cases significantly longer than in Bernese outbreak.
The fast evolution of pathogenic viruses has allowed for the development of phylodynamic approaches that extract information about the epidemiological characteristics of viral genomes. Thanks to advances in whole genome sequencing, they can be applied to slowly evolving bacterial pathogens like Mycobacterium tuberculosis. In this study, we investigate and compare the epidemiological dynamics underlying two M. tuberculosis outbreaks using phylodynamic methods. Specifically, we (i) test if the outbreak data sets contain enough genetic variation to estimate short-term evolutionary rates and (ii) reconstruct epidemiological parameters such as the effective reproduction number. The first outbreak occurred in the Swiss city of Bern (1987–2012) and was caused by a drug-susceptible strain belonging to the phylogenetic M. tuberculosis Lineage 4. The second outbreak was caused by a multidrug-resistant (MDR) strain of Lineage 2, imported from the Wat Tham Krabok (WTK) refugee camp in Thailand into California. There is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set. Thanks to its high sampling proportion (90%) the Bern outbreak allows robust estimation of epidemiological parameters despite the poor temporal signal. Conversely, there is much uncertainty in the epidemiological estimates concerning the sparsely sampled (9%) WTK outbreak. Our results suggest that both outbreaks peaked around 1990, although they were only recognized as outbreaks in 1993 (Bern) and 2004 (WTK). Furthermore, individuals were infected for a significantly longer period (around 9 years) in the WTK outbreak than in the Bern outbreak (4–5 years). Our work highlights both the limitations and opportunities of phylodynamic analysis of outbreaks involving slowly evolving pathogens: (i) estimation of the evolutionary rate is difficult on outbreak time scales and (ii) a high sampling proportion allows quantification of the age of the outbreak based on the sampling times, and thus allows for robust estimation of epidemiological parameters.
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Affiliation(s)
- Denise Kühnert
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Zürich, Switzerland; Institute of Medical Virology, University of Zürich, Zürich, Switzerland; Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
| | - Mireia Coscolla
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Switzerland; University of Basel, Switzerland
| | - Daniela Brites
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Switzerland; University of Basel, Switzerland
| | - David Stucki
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Switzerland; University of Basel, Switzerland
| | - John Metcalfe
- University of California, San Francisco, School of Medicine, United States
| | - Lukas Fenner
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Switzerland; University of Basel, Switzerland; Institute of Social and Preventive Medicine, University of Bern, 3012 Bern, Switzerland
| | - Sebastien Gagneux
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Switzerland; University of Basel, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
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22
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Huang G. Artificial infectious disease optimization: A SEIQR epidemic dynamic model-based function optimization algorithm. Swarm Evol Comput 2016; 27:31-67. [PMID: 32288989 PMCID: PMC7104270 DOI: 10.1016/j.swevo.2015.09.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Revised: 08/05/2015] [Accepted: 09/21/2015] [Indexed: 05/04/2023]
Abstract
To solve some complicated function optimization problems, an artificial infectious disease optimization algorithm based on the SEIQR epidemic model is constructed, it is called as the SEIQR algorithm, or SEIQRA in short. The algorithm supposes that some human individuals exist in an ecosystem; each individual is characterized by a number of features; an infectious disease (SARS) exists in the ecosystem and spreads among individuals, the disease attacks only a part of features of an individual. Each infected individual may pass through such states as susceptibility (S), exposure (E), infection (I), quarantine (Q) and recovery (R). State S, E, I, Q and R can automatically and dynamically divide all people in the ecosystem into five classes, it provides the diversity for SEIQRA; that people can be attacked by the infectious disease and then transfer it to other people can cause information exchange among people, information exchange can make a person to transit from one state to another; state transitions can be transformed into operators of SEIQRA; the algorithm has 13 legal state transitions, which corresponds to 13 operators; the transmission rules of the infectious disease among people is just the logic to control state transitions of individuals among S, E, I, Q and R, it is just the synergy of SEIQRA, the synergy can be transformed into the logic structure of the algorithm. The 13 operators in the algorithm provide a native opportunity to integrate many operations with different purposes; these operations include average, differential, expansion, chevy, reflection and crossover. The 13 operators are executed equi-probably; a stable heart rhythm of the algorithm is realized. Because the infectious disease can only attack a small part of organs of a person when it spreads among people, the part variables iteration strategy (PVI) can be ingeniously applied, thus enabling the algorithm to possess of high performance of computation, high suitability for solving some kinds of complicated optimization problems, especially high dimensional optimization problems. Results show that SEIQRA has characteristics of strong search capability and global convergence, and has a high convergence speed for some complicated functions optimization problems.
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Affiliation(s)
- Guangqiu Huang
- School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
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23
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Abstract
To better understand the spread of disease in nature, it is fundamentally important to have broadly applicable model systems with readily available species which can be replicated and controlled in the laboratory. Here we used an experimental model system of fish hosts and monogenean parasites to determine whether host sex, group size and group composition (single-sex or mixed-sex) influenced host-parasite dynamics at an individual and group level. Parasite populations reached higher densities and persisted longer in groups of fish compared with isolated hosts and reached higher densities on isolated females than on isolated males. However, individual fish within groups had similar burdens to isolated males regardless of sex, indicating that females may benefit more than males by being in a group. Relative condition was positively associated with high parasite loads for isolated males, but not for isolated females or grouped fish. No difference in parasite dynamics between mixed-sex groups and single-sex groups was detected. Overall, these findings suggest that while host sex influences dynamics on isolated fish, individual fish in groups have similar parasite burdens, regardless of sex. We believe our experimental results contribute to a mechanistic understanding of host-parasite dynamics, although we are cautious about directly extrapolating these results to other systems.
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Gong YW, Song YR, Jiang GP. Time-varying human mobility patterns with metapopulation epidemic dynamics. Physica A 2013; 392:4242-4251. [PMID: 32288087 PMCID: PMC7126299 DOI: 10.1016/j.physa.2013.05.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Revised: 04/29/2013] [Indexed: 05/10/2023]
Abstract
In this paper, explicitly considering the influences of an epidemic outbreak on human travel, a time-varying human mobility pattern is introduced to model the time variation of global human travel. The impacts of the pattern on epidemic dynamics in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number of individuals, are investigated by using a mean-field approach. The results show that the pattern does not alter the epidemic threshold, but can slightly lower the final average density of infected individuals as a whole. More importantly, we also find that the pattern produces different impacts on nodes with different degree, and that there exists a critical degree k c . For nodes with degree smaller than k c , the pattern produces a positive impact on epidemic mitigation; conversely, for nodes with degree larger than k c , the pattern produces a negative impact on epidemic mitigation.
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Affiliation(s)
- Yong-Wang Gong
- College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
- School of Information Engineering, Yancheng Institute of Technology, Yancheng 224051, China
| | - Yu-Rong Song
- College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
| | - Guo-Ping Jiang
- College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
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Abstract
The complex dynamics of HIV transmission and subsequent progression to AIDS make the mathematical analysis untraceable and problematic. In this paper, we develop an extended CA simulation model to study the dynamical behaviors of HIV/AIDS transmission. The model incorporates heterogeneity into agents' behaviors. Agents have various attributes such as infectivity and susceptibility, varying degrees of influence on their neighbors and different mobilities. Additional, we divide the post-infection process of AIDS disease into several sub-stages in order to facilitate the study of the dynamics in different development stages of epidemics. These features make the dynamics more complicated. We find that the epidemic in our model can generally end up in one of the two states: extinction and persistence, which is consistent with other researchers' work. Higher population density, higher mobility, higher number of infection source, and greater neighborhood are more likely to result in high levels of infections and in persistence. Finally, we show in four-class agent scenario, variation in susceptibility (or infectivity) and various fractions of four classes also complicates the dynamics, and some of the results are contradictory and needed for further research.
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Affiliation(s)
- Huiyu Xuan
- School of Management, Xian Jiaotong University, Xi’an, 710049 China
| | - Lida Xu
- College of Economics and Management, Beijing Jiaotong University, Beijing, 100044 China
- Department of Information Technology & Decision Science, Old Dominion University, Norfolk, VA 23529 USA
| | - Lu Li
- School of Management, Xian Jiaotong University, Xi’an, 710049 China
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