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Sy C, Ching PM, San Juan JL, Bernardo E, Miguel A, Mayol AP, Culaba A, Ubando A, Mutuc JE. Systems Dynamics Modeling of Pandemic Influenza for Strategic Policy Development: a Simulation-Based Analysis of the COVID-19 Case. PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2021. [PMCID: PMC7841385 DOI: 10.1007/s41660-021-00156-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The novel coronavirus disease 2019 (COVID-19) is a truly wicked problem which has remained a stubborn issue plaguing multiple countries worldwide. The continuously increasing number of infections and deaths has driven several countries to implement control and response strategies including community lockdowns, physical distancing, and travel bans with different levels of success. However, a disease outbreak and the corresponding policies can cause disastrous economic consequences due to business closures and risk minimization behaviors. This paper develops a system dynamics framework of a disease outbreak system covering various policies to evaluate their effectiveness in mitigating transmission and the resulting economic burden. The system dynamics modeling approach captures the relationships, feedbacks, and delays in such a system, revealing meaningful insights on the dynamics of several response strategies.
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Affiliation(s)
- Charlle Sy
- Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Phoebe Mae Ching
- Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Jayne Lois San Juan
- Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Ezekiel Bernardo
- Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Angelimarie Miguel
- Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Andres Philip Mayol
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Alvin Culaba
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Aristotle Ubando
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
| | - Jose Edgar Mutuc
- Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
- Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines
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Omori R, Mizumoto K, Chowell G. Changes in testing rates could mask the novel coronavirus disease (COVID-19) growth rate. Int J Infect Dis 2020; 94:116-118. [PMID: 32320809 PMCID: PMC7167222 DOI: 10.1016/j.ijid.2020.04.021] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 04/06/2020] [Accepted: 04/08/2020] [Indexed: 11/25/2022] Open
Abstract
Since the novel coronavirus disease (COVID-19) emerged in December 2019 in China, it has rapidly spread around the world, leading to one of the most significant pandemic events of recent history. Deriving reliable estimates of the COVID-19 epidemic growth rate is quite important to guide the timing and intensity of intervention strategies. Indeed, many studies have quantified the epidemic growth rate using time-series of reported cases during the early phase of the outbreak to estimate the basic reproduction number, R0. Using daily time series of COVID-19 incidence, we illustrate how epidemic curves of reported cases may not always reflect the true epidemic growth rate due to changes in testing rates, which could be influenced by limited diagnostic testing capacity during the early epidemic phase.
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Affiliation(s)
- Ryosuke Omori
- Research Center for Zoonosis Control, Hokkaido University, Hokkaido 001-0020, Japan.
| | - Kenji Mizumoto
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Yoshida-Nakaadachi-cho, Sakyo-ku, Kyoto, Japan; Hakubi Center for Advanced Research, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, Japan
| | - Gerardo Chowell
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
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Chowell G, Sullivan P, Rothenberg R. Introduction to symposium: a century after the 1918 influenza pandemic. Ann Epidemiol 2018; 28:265-266. [DOI: 10.1016/j.annepidem.2018.03.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 03/20/2018] [Indexed: 10/17/2022]
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Matsuyama R, Akhmetzhanov AR, Endo A, Lee H, Yamaguchi T, Tsuzuki S, Nishiura H. Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November-December 2017. PeerJ 2018; 6:e4583. [PMID: 29629244 PMCID: PMC5885970 DOI: 10.7717/peerj.4583] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 03/14/2018] [Indexed: 11/20/2022] Open
Abstract
Background A Rohingya refugee camp in Cox's Bazar, Bangladesh experienced a large-scale diphtheria epidemic in 2017. The background information of previously immune fraction among refugees cannot be explicitly estimated, and thus we conducted an uncertainty analysis of the basic reproduction number, R0. Methods A renewal process model was devised to estimate the R0 and ascertainment rate of cases, and loss of susceptible individuals was modeled as one minus the sum of initially immune fraction and the fraction naturally infected during the epidemic. To account for the uncertainty of initially immune fraction, we employed a Latin Hypercube sampling (LHS) method. Results R0 ranged from 4.7 to 14.8 with the median estimate at 7.2. R0 was positively correlated with ascertainment rates. Sensitivity analysis indicated that R0 would become smaller with greater variance of the generation time. Discussion Estimated R0 was broadly consistent with published estimate from endemic data, indicating that the vaccination coverage of 86% has to be satisfied to prevent the epidemic by means of mass vaccination. LHS was particularly useful in the setting of a refugee camp in which the background health status is poorly quantified.
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Affiliation(s)
- Ryota Matsuyama
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
| | - Andrei R Akhmetzhanov
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
| | - Akira Endo
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,London School of Hygiene & Tropical Medicine, University of London, London, UK
| | - Hyojung Lee
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
| | - Takayuki Yamaguchi
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
| | - Shinya Tsuzuki
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
| | - Hiroshi Nishiura
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Saitama, Japan
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