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Deka A, Eksin C, Ndeffo-Mbah ML. Analyzing the use of non-pharmaceutical personal protective measures through self-interest and social optimum for the control of an emerging disease. Math Biosci 2024; 375:109246. [PMID: 38971368 DOI: 10.1016/j.mbs.2024.109246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/27/2024] [Accepted: 07/01/2024] [Indexed: 07/08/2024]
Abstract
Non-pharmaceutical personal protective (NPP) measures such as face masks use, and hand and respiratory hygiene can be effective measures for mitigating the spread of aerosol/airborne diseases, such as COVID-19, in the absence of vaccination or treatment. However, the usage of such measures is constrained by their inherent perceived cost and effectiveness for reducing transmission risk. To understand the complex interaction of disease dynamics and individuals decision whether to adopt NPP or not, we incorporate evolutionary game theory into an epidemic model such as COVID-19. To compare how self-interested NPP use differs from social optimum, we also investigated optional control from a central planner's perspective. We use Pontryagin's maximum principle to identify the population-level NPP uptake that minimizes disease incidence by incurring the minimum costs. The evolutionary behavior model shows that NPP uptake increases at lower perceived costs of NPP, higher transmission risk, shorter duration of NPP use, higher effectiveness of NPP, and shorter duration of disease-induced immunity. Though social optimum NPP usage is generally more effective in reducing disease incidence than self-interested usage, our analysis identifies conditions under which both strategies get closer. Our model provides new insights for public health in mitigating a disease outbreak through NPP.
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Affiliation(s)
- Aniruddha Deka
- Veterinary Integrative Biosciences, School of Veterinary Medicine, Texas A&M University, College Station, TX 77843, USA; Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC, USA.
| | - Ceyhun Eksin
- Industrial & Systems Engineering, College of Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Martial L Ndeffo-Mbah
- Veterinary Integrative Biosciences, School of Veterinary Medicine, Texas A&M University, College Station, TX 77843, USA; Epidemiology & Biostatistics, School of Public Health, Texas A&M University, College Station, TX 77843, USA
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Grass D, Wrzaczek S, Caulkins JP, Feichtinger G, Hartl RF, Kort PM, Kuhn M, Prskawetz A, Sanchez-Romero M, Seidl A. Riding the waves from epidemic to endemic: Viral mutations, immunological change and policy responses. Theor Popul Biol 2024; 156:46-65. [PMID: 38310975 DOI: 10.1016/j.tpb.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 02/06/2024]
Abstract
Nonpharmaceutical interventions (NPI) are an important tool for countering pandemics such as COVID-19. Some are cheap; others disrupt economic, educational, and social activity. The latter force governments to balance the health benefits of reduced infection and death against broader lockdown-induced societal costs. A literature has developed modeling how to optimally adjust lockdown intensity as an epidemic evolves. This paper extends that literature by augmenting the classic SIR model with additional states and flows capturing decay over time in vaccine-conferred immunity, the possibility that mutations create variants that erode immunity, and that protection against infection erodes faster than protecting against severe illness. As in past models, we find that small changes in parameter values can tip the optimal response between very different solutions, but the extensions considered here create new types of solutions. In some instances, it can be optimal to incur perpetual epidemic waves even if the uncontrolled infection prevalence would settle down to a stable intermediate level.
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Affiliation(s)
- D Grass
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Research Group Economics, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria
| | - S Wrzaczek
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/OeAW, University of Vienna), Austria.
| | - J P Caulkins
- Heinz College, Carnegie Mellon University, Pittsburgh, USA
| | - G Feichtinger
- Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/OeAW, University of Vienna), Austria; Research Group Variational Analysis, Dynamics & Operations Research, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria
| | - R F Hartl
- Department of Business Decisions and Analytics, University of Vienna, Vienna, Austria
| | - P M Kort
- Tilburg School of Economics and Management, Tilburg University, Tilburg, Netherlands
| | - M Kuhn
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/OeAW, University of Vienna), Austria
| | - A Prskawetz
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/OeAW, University of Vienna), Austria; Research Group Economics, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria
| | - M Sanchez-Romero
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Research Group Economics, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria; Vienna Institute of Demography (VID), Austrian Academy of Sciences (OeAW), Vienna, Austria
| | - A Seidl
- Department of Business Decisions and Analytics, University of Vienna, Vienna, Austria; Faculty of Management, Seeburg Castle University, Seekirchen am Wallersee, Austria
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Khan MMUR, Arefin MR, Tanimoto J. Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation. Infect Dis Model 2023; 8:656-671. [PMID: 37346475 PMCID: PMC10257886 DOI: 10.1016/j.idm.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/26/2023] [Accepted: 06/05/2023] [Indexed: 06/23/2023] Open
Abstract
The emergence of a novel strain during a pandemic, like the current COVID-19, is a major concern to the healthcare system. The most effective strategy to control this type of pandemic is vaccination. Many previous studies suggest that the existing vaccine may not be fully effective against the new strain. Additionally, the new strain's late arrival has a significant impact on the disease dynamics and vaccine coverage. Focusing on these issues, this study presents a two-strain epidemic model in which the new strain appears with a time delay. We considered two vaccination provisions, namely preinfection and postinfection vaccinations, which are governed by human behavioral dynamics. In such a framework, individuals have the option to commit vaccination before being infected with the first strain. Additionally, people who forgo vaccination and become infected with the first train have the chance to be vaccinated (after recovery) in an attempt to avoid infection from the second strain. However, a second strain can infect vaccinated and unvaccinated individuals. People may have additional opportunities to be vaccinated and to protect themselves from the second strain due to the time delay. Considering the cost of the vaccine, the severity of the new strain, and the vaccine's effectiveness, our results indicated that delaying the second strain decreases the peak size of the infected individuals. Finally, by estimating the social efficiency deficit, we discovered that the social dilemma for receiving immunization decreases with the delay in the arrival of the second strain.
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Affiliation(s)
- Md. Mamun-Ur-Rashid Khan
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka, 816-8580, Japan
- Department of Mathematics, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Md. Rajib Arefin
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka, 816-8580, Japan
- Department of Mathematics, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Jun Tanimoto
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka, 816-8580, Japan
- Faculty of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka, 816-8580, Japan
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Jing S, Milne R, Wang H, Xue L. Vaccine hesitancy promotes emergence of new SARS-CoV-2 variants. J Theor Biol 2023; 570:111522. [PMID: 37210068 PMCID: PMC10193816 DOI: 10.1016/j.jtbi.2023.111522] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 04/30/2023] [Accepted: 05/03/2023] [Indexed: 05/22/2023]
Abstract
The successive emergence of SARS-CoV-2 mutations has led to an unprecedented increase in COVID-19 incidence worldwide. Currently, vaccination is considered to be the best available solution to control the ongoing COVID-19 pandemic. However, public opposition to vaccination persists in many countries, which can lead to increased COVID-19 caseloads and hence greater opportunities for vaccine-evasive mutant strains to arise. To determine the extent that public opinion regarding vaccination can induce or hamper the emergence of new variants, we develop a model that couples a compartmental disease transmission framework featuring two strains of SARS-CoV-2 with game theoretical dynamics on whether or not to vaccinate. We combine semi-stochastic and deterministic simulations to explore the effect of mutation probability, perceived cost of receiving vaccines, and perceived risks of infection on the emergence and spread of mutant SARS-CoV-2 strains. We find that decreasing the perceived costs of being vaccinated and increasing the perceived risks of infection (that is, decreasing vaccine hesitation) will decrease the possibility of vaccine-resistant mutant strains becoming established by about fourfold for intermediate mutation rates. Conversely, we find increasing vaccine hesitation to cause both higher probability of mutant strains emerging and more wild-type cases after the mutant strain has appeared. We also find that once a new variant has emerged, perceived risk of being infected by the original variant plays a much larger role than perceptions of the new variant in determining future outbreak characteristics. Furthermore, we find that rapid vaccination under non-pharmaceutical interventions is a highly effective strategy for preventing new variant emergence, due to interaction effects between non-pharmaceutical interventions and public support for vaccination. Our findings indicate that policies that combine combating vaccine-related misinformation with non-pharmaceutical interventions (such as reducing social contact) will be the most effective for avoiding the establishment of harmful new variants.
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Affiliation(s)
- Shuanglin Jing
- College of Mathematical Sciences, Harbin Engineering University, Harbin, Heilongjiang, 150001, China
| | - Russell Milne
- Department of Mathematical and Statistical Sciences & Interdisciplinary Lab for Mathematical Ecology and Epidemiology, University of Alberta, Edmonton, Alberta T6G 2R3, Canada
| | - Hao Wang
- Department of Mathematical and Statistical Sciences & Interdisciplinary Lab for Mathematical Ecology and Epidemiology, University of Alberta, Edmonton, Alberta T6G 2R3, Canada.
| | - Ling Xue
- College of Mathematical Sciences, Harbin Engineering University, Harbin, Heilongjiang, 150001, China
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Khan MMUR, Arefin MR, Tanimoto J. Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach. APPLIED MATHEMATICS AND COMPUTATION 2022; 432:127365. [PMID: 35812766 PMCID: PMC9257552 DOI: 10.1016/j.amc.2022.127365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/19/2022] [Accepted: 06/26/2022] [Indexed: 06/15/2023]
Abstract
During a pandemic event like the present COVID-19, self-quarantine, mask-wearing, hygiene maintenance, isolation, forced quarantine, and social distancing are the most effective nonpharmaceutical measures to control the epidemic when the vaccination and proper treatments are absent. In this study, we proposed an epidemiological model based on the SEIR dynamics along with the two interventions defined as self-quarantine and forced quarantine by human behavior dynamics. We consider a disease spreading through a population where some people can choose the self-quarantine option of paying some costs and be safer than the remaining ones. The remaining ones act normally and send to forced quarantine by the government if they get infected and symptomatic. The government pays the forced quarantine costs for individuals, and the government has a budget limit to treat the infected ones. Each intervention derived from the so-called behavior model has a dynamical equation that accounts for a proper balance between the costs for each case, the total budget, and the risk of infection. We show that the infection peak cannot be reduced if the authority does not enforce a proactive (quantified by a higher sensitivity parameter) intervention. While comparing the impact of both self- and forced quarantine provisions, our results demonstrate that the latter is more influential to reduce the disease prevalence and the social efficiency deficit (a gap between social optimum payoff and equilibrium payoff).
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Affiliation(s)
- Md Mamun-Ur-Rashid Khan
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan
- Department of Mathematics, University of Dhaka, Dhaka 1000, Bangladesh
| | - Md Rajib Arefin
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan
- Department of Mathematics, University of Dhaka, Dhaka 1000, Bangladesh
| | - Jun Tanimoto
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan
- Faculty of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan
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Rosenberg NA, Boni MF. Mathematical epidemiology for a later age. Theor Popul Biol 2022; 144:81-83. [PMID: 35247319 PMCID: PMC8890614 DOI: 10.1016/j.tpb.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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