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Roberts MG, Hickson RI, McCaw JM. How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space. J Math Biol 2024; 88:48. [PMID: 38538962 PMCID: PMC10973021 DOI: 10.1007/s00285-024-02076-x] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 02/25/2024] [Accepted: 03/05/2024] [Indexed: 04/01/2024]
Abstract
We extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.
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Affiliation(s)
- M G Roberts
- New Zealand Institute for Advanced Study and the Infectious Disease Research Centre, Massey University, Auckland, New Zealand.
| | - R I Hickson
- Health and Biosecurity, CSIRO, Townsville, QLD, 4814, Australia
- Australian Institute of Tropical Medicine and Hygiene, and College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, 4814, Australia
- School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - J M McCaw
- School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, VIC, 3010, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC, 3010, Australia
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Walker CR, Hickson RI, Chang E, Ngor P, Sovannaroth S, Simpson JA, Price DJ, McCaw JM, Price RN, Flegg JA, Devine A. A model for malaria treatment evaluation in the presence of multiple species. Epidemics 2023; 44:100687. [PMID: 37348379 PMCID: PMC7614843 DOI: 10.1016/j.epidem.2023.100687] [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: 07/13/2022] [Revised: 03/12/2023] [Accepted: 05/12/2023] [Indexed: 06/24/2023] Open
Abstract
Plasmodium falciparum and P. vivax are the two most common causes of malaria. While the majority of deaths and severe morbidity are due to P. falciparum, P. vivax poses a greater challenge to eliminating malaria outside of Africa due to its ability to form latent liver stage parasites (hypnozoites), which can cause relapsing episodes within an individual patient. In areas where P. falciparum and P. vivax are co-endemic, individuals can carry parasites of both species simultaneously. These mixed infections complicate dynamics in several ways: treatment of mixed infections will simultaneously affect both species, P. falciparum can mask the detection of P. vivax, and it has been hypothesised that clearing P. falciparum may trigger a relapse of dormant P. vivax. When mixed infections are treated for only blood-stage parasites, patients are at risk of relapse infections due to P. vivax hypnozoites. We present a stochastic mathematical model that captures interactions between P. falciparum and P. vivax, and incorporates both standard schizonticidal treatment (which targets blood-stage parasites) and radical cure treatment (which additionally targets liver-stage parasites). We apply this model via a hypothetical simulation study to assess the implications of different treatment coverages of radical cure for mixed and P. vivax infections and a "unified radical cure" treatment strategy where P. falciparum, P. vivax, and mixed infections all receive radical cure after screening glucose-6-phosphate dehydrogenase (G6PD) normal. In addition, we investigated the impact of mass drug administration (MDA) of blood-stage treatment. We find that a unified radical cure strategy leads to a substantially lower incidence of malaria cases and deaths overall. MDA with schizonticidal treatment was found to decrease P. falciparum with little effect on P. vivax. We perform a univariate sensitivity analysis to highlight important model parameters.
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Affiliation(s)
- C R Walker
- School of Mathematics and Statistics, University of Melbourne, Australia.
| | - R I Hickson
- School of Mathematics and Statistics, University of Melbourne, Australia; Australian Institute of Tropical Health and Medicine, and College of Public Health, Medical & Veterinary Sciences, James Cook University, Australia; Health and Biosecurity, CSIRO, Australia
| | - E Chang
- School of Mathematics and Statistics, University of Melbourne, Australia
| | - P Ngor
- Cambodian National Center for Parasitology, Entomology and Malaria Control, Cambodia; Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand
| | - S Sovannaroth
- Cambodian National Center for Parasitology, Entomology and Malaria Control, Cambodia
| | - J A Simpson
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Australia
| | - D J Price
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Australia; Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Australia
| | - J M McCaw
- School of Mathematics and Statistics, University of Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Australia
| | - R N Price
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand; Division of Global and Tropical Health, Menzies School of Health Research and Charles Darwin University, Australia; Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, UK
| | - J A Flegg
- School of Mathematics and Statistics, University of Melbourne, Australia
| | - A Devine
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Australia; Division of Global and Tropical Health, Menzies School of Health Research and Charles Darwin University, Australia
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Grzybowska H, Hickson RI, Bhandari B, Cai C, Towke M, Itzstein B, Jurdak R, Liebig J, Najeebullah K, Plani A, Shoghri AE, Paini D. SAfE transport: wearing face masks significantly reduces the spread of COVID-19 on trains. BMC Infect Dis 2022; 22:694. [PMID: 35978312 PMCID: PMC9382008 DOI: 10.1186/s12879-022-07664-0] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/25/2022] [Indexed: 12/21/2022] Open
Abstract
COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.
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Affiliation(s)
- Hanna Grzybowska
- Data61, CSIRO, Sydney, Australia. .,Research Centre for Integrated Transport Innovation,School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia.
| | - R I Hickson
- Health and Biosecurity, CSIRO, Sydney , Australia.,College of Public Health, Medical and Veterinary Sciences, and Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia
| | | | - Chen Cai
- Data61, CSIRO, Sydney, Australia
| | | | | | - Raja Jurdak
- Queensland University of Technology, Brisbane, QLD, Australia
| | | | | | | | | | - Dean Paini
- Health and Biosecurity, CSIRO, Sydney , Australia
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Roberts MG, Hickson RI, McCaw JM, Talarmain L. A simple influenza model with complicated dynamics. J Math Biol 2018; 78:607-624. [DOI: 10.1007/s00285-018-1285-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Revised: 07/16/2018] [Indexed: 01/03/2023]
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Ndii MZ, Allingham D, Hickson RI, Glass K. The effect of Wolbachia on dengue outbreaks when dengue is repeatedly introduced. Theor Popul Biol 2016; 111:9-15. [PMID: 27217229 DOI: 10.1016/j.tpb.2016.05.003] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [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: 08/19/2015] [Revised: 05/09/2016] [Accepted: 05/11/2016] [Indexed: 02/01/2023]
Abstract
Use of the Wolbachia bacterium is a proposed new strategy to reduce dengue transmission, which results in around 390 million individuals infected annually. In places with strong variations in climatic conditions such as temperature and rainfall, dengue epidemics generally occur only at a certain time of the year. Where dengue is not endemic, the time of year in which imported cases enter the population plays a crucial role in determining the likelihood of outbreak occurrence. We use a mathematical model to study the effects of Wolbachia on dengue transmission dynamics and dengue seasonality. We focus in regions where dengue is not endemic but can spread due to the presence of a dengue vector and the arrival of people with dengue on a regular basis. Our results show that the time-window in which outbreaks can occur is reduced in the presence of Wolbachia-carrying Aedes aegypti mosquitoes by up to six weeks each year. We find that Wolbachia reduces overall case numbers by up to 80%. The strongest effect is obtained when the amplitude of the seasonal forcing is low (0.02-0.30). The benefits of Wolbachia also depend on the transmission rate, with the bacteria most effective at moderate transmission rates ranging between 0.08-0.12. Such rates are consistent with fitted estimates for Cairns, Australia.
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Affiliation(s)
- Meksianis Z Ndii
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia; Department of Mathematics, Nusa Cendana University, Kupang-NTT, Indonesia.
| | - David Allingham
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia.
| | - R I Hickson
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia; IBM Research - Australia, Melbourne, Australia.
| | - Kathryn Glass
- National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia.
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