1
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Bull JJ, Koelle K, Antia R. Waning immunity drives respiratory virus evolution and reinfection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.23.604867. [PMID: 39091870 PMCID: PMC11291175 DOI: 10.1101/2024.07.23.604867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Reinfections with respiratory viruses such as influenza viruses and coronaviruses are thought to be driven by ongoing antigenic immune escape in the viral population. However, this does not explain why antigenic variation is frequently observed in these viruses relative to viruses such as measles that undergo systemic replication. Here, we suggest that the rapid rate of waning immunity in the respiratory tract is the key driver of antigenic evolution in respiratory viruses. Waning immunity results in hosts with immunity levels that protect against homologous reinfection but are insufficient to protect against infection with a heterologous, antigenically different strain. As such, when partially immune hosts are present at a high enough density, an immune escape variant can invade the viral population even though that variant cannot infect fully immune hosts. Invasion can occur even when the variant's immune escape mutation incurs a fitness cost, and we expect the expanding mutant population will evolve compensatory mutations that mitigate this cost. Thus the mutant lineage should replace the wild-type, and as immunity to it builds, the process will repeat. Our model provides a new explanation for the pattern of successive emergence and replacement of antigenic variants that has been observed in many respiratory viruses. We discuss our model relative to others for understanding the drivers of antigenic evolution in these and other respiratory viruses.
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Affiliation(s)
- James J Bull
- Dept of Biological Sciences, University of Idaho, Moscow, ID USA
| | - Katia Koelle
- Dept of Biology, Emory University, Atlanta, GA USA
- Emory Center of Excellence for Influenza Research and Response (CEIRR), Atlanta GA, USA
| | - Rustom Antia
- Dept of Biology, Emory University, Atlanta, GA USA
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2
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McGough L, Cobey S. A speed limit on serial strain replacement from original antigenic sin. Proc Natl Acad Sci U S A 2024; 121:e2400202121. [PMID: 38857397 PMCID: PMC11194583 DOI: 10.1073/pnas.2400202121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 05/06/2024] [Indexed: 06/12/2024] Open
Abstract
Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if [Formula: see text] is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.
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Affiliation(s)
- Lauren McGough
- Department of Ecology and EvolutionThe University of Chicago, Chicago, IL60637
| | - Sarah Cobey
- Department of Ecology and EvolutionThe University of Chicago, Chicago, IL60637
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3
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McGough L, Cobey S. A speed limit on serial strain replacement from original antigenic sin. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.04.574172. [PMID: 38260288 PMCID: PMC10802292 DOI: 10.1101/2024.01.04.574172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive new constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if R 0 is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.
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Affiliation(s)
- Lauren McGough
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
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4
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Ashby B, Smith CA, Thompson RN. Non-pharmaceutical interventions and the emergence of pathogen variants. Evol Med Public Health 2022; 11:80-89. [PMID: 37007165 PMCID: PMC10052376 DOI: 10.1093/emph/eoac043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 09/30/2022] [Indexed: 12/24/2022] Open
Abstract
Non-pharmaceutical interventions (NPIs), such as social distancing and contact tracing, are important public health measures that can reduce pathogen transmission. In addition to playing a crucial role in suppressing transmission, NPIs influence pathogen evolution by mediating mutation supply, restricting the availability of susceptible hosts, and altering the strength of selection for novel variants. Yet it is unclear how NPIs might affect the emergence of novel variants that are able to escape pre-existing immunity (partially or fully), are more transmissible or cause greater mortality. We analyse a stochastic two-strain epidemiological model to determine how the strength and timing of NPIs affect the emergence of variants with similar or contrasting life-history characteristics to the wild type. We show that, while stronger and timelier NPIs generally reduce the likelihood of variant emergence, it is possible for more transmissible variants with high cross-immunity to have a greater probability of emerging at intermediate levels of NPIs. This is because intermediate levels of NPIs allow an epidemic of the wild type that is neither too small (facilitating high mutation supply), nor too large (leaving a large pool of susceptible hosts), to prevent a novel variant from becoming established in the host population. However, since one cannot predict the characteristics of a variant, the best strategy to prevent emergence is likely to be an implementation of strong, timely NPIs.
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Affiliation(s)
- Ben Ashby
- Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada
- Department of Mathematical Sciences, University of Bath, Bath, UK
- The Pacific Institute on Pathogens, Pandemics and Society (PIPPS), Simon Fraser University, Burnaby, BC, Canada
| | - Cameron A Smith
- Department of Mathematical Sciences, University of Bath, Bath, UK
| | - Robin N Thompson
- Mathematics Institute, University of Warwick, Coventry, UK
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK
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5
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Wen FT, Malani A, Cobey S. The Potential Beneficial Effects of Vaccination on Antigenically Evolving Pathogens. Am Nat 2022; 199:223-237. [DOI: 10.1086/717410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Frank T. Wen
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
| | - Anup Malani
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
- University of Chicago Law School, Chicago, Illinois 60637; and University of Chicago Pritzker School of Medicine, Chicago, Illinois 60637
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
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6
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Morris DH, Petrova VN, Rossine FW, Parker E, Grenfell BT, Neher RA, Levin SA, Russell CA. Asynchrony between virus diversity and antibody selection limits influenza virus evolution. eLife 2020; 9:e62105. [PMID: 33174838 PMCID: PMC7748417 DOI: 10.7554/elife.62105] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 11/04/2020] [Indexed: 12/14/2022] Open
Abstract
Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.
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MESH Headings
- Antibodies, Neutralizing/genetics
- Antibodies, Neutralizing/immunology
- Antibodies, Viral/immunology
- Biological Evolution
- Genetic Variation/genetics
- Humans
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza A virus/genetics
- Influenza A virus/immunology
- Influenza, Human/immunology
- Influenza, Human/transmission
- Influenza, Human/virology
- Models, Statistical
- Selection, Genetic/genetics
- Selection, Genetic/immunology
- Virion/genetics
- Virion/immunology
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Affiliation(s)
- Dylan H Morris
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Velislava N Petrova
- Department of Human Genetics, Wellcome Trust Sanger InstituteCambridgeUnited Kingdom
| | - Fernando W Rossine
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Edyth Parker
- Department of Veterinary Medicine, University of CambridgeCambridgeUnited Kingdom
- Department of Medical Microbiology, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
| | - Bryan T Grenfell
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
- Fogarty International Center, National Institutes of HealthBethesdaUnited States
| | | | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Colin A Russell
- Department of Medical Microbiology, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
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7
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Yang W, Lau EHY, Cowling BJ. Dynamic interactions of influenza viruses in Hong Kong during 1998-2018. PLoS Comput Biol 2020; 16:e1007989. [PMID: 32542015 PMCID: PMC7316359 DOI: 10.1371/journal.pcbi.1007989] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 06/25/2020] [Accepted: 05/27/2020] [Indexed: 11/19/2022] Open
Abstract
Influenza epidemics cause substantial morbidity and mortality every year worldwide. Currently, two influenza A subtypes, A(H1N1) and A(H3N2), and type B viruses co-circulate in humans and infection with one type/subtype could provide cross-protection against the others. However, it remains unclear how such ecologic competition via cross-immunity and antigenic mutations that allow immune escape impact influenza epidemic dynamics at the population level. Here we develop a comprehensive model-inference system and apply it to study the evolutionary and epidemiological dynamics of the three influenza types/subtypes in Hong Kong, a city of global public health significance for influenza epidemic and pandemic control. Utilizing long-term influenza surveillance data since 1998, we are able to estimate the strength of cross-immunity between each virus-pairs, the timing and frequency of punctuated changes in population immunity in response to antigenic mutations in influenza viruses, and key epidemiological parameters over the last 20 years including the 2009 pandemic. We find evidence of cross-immunity in all types/subtypes, with strongest cross-immunity from A(H1N1) against A(H3N2). Our results also suggest that A(H3N2) may undergo antigenic mutations in both summers and winters and thus monitoring the virus in both seasons may be important for vaccine development. Overall, our study reveals intricate epidemiological interactions and underscores the importance of simultaneous monitoring of population immunity, incidence rates, and viral genetic and antigenic changes.
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Affiliation(s)
- Wan Yang
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
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8
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Early prediction of antigenic transitions for influenza A/H3N2. PLoS Comput Biol 2020; 16:e1007683. [PMID: 32069282 PMCID: PMC7048310 DOI: 10.1371/journal.pcbi.1007683] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 02/28/2020] [Accepted: 01/26/2020] [Indexed: 11/20/2022] Open
Abstract
Influenza A/H3N2 is a rapidly evolving virus which experiences major antigenic transitions every two to eight years. Anticipating the timing and outcome of transitions is critical to developing effective seasonal influenza vaccines. Using a published phylodynamic model of influenza transmission, we identified indicators of future evolutionary success for an emerging antigenic cluster and quantified fundamental trade-offs in our ability to make such predictions. The eventual fate of a new cluster depends on its initial epidemiological growth rate––which is a function of mutational load and population susceptibility to the cluster––along with the variance in growth rate across co-circulating viruses. Logistic regression can predict whether a cluster at 5% relative frequency will eventually succeed with ~80% sensitivity, providing up to eight months advance warning. As a cluster expands, the predictions improve while the lead-time for vaccine development and other interventions decreases. However, attempts to make comparable predictions from 12 years of empirical influenza surveillance data, which are far sparser and more coarse-grained, achieve only 56% sensitivity. By expanding influenza surveillance to obtain more granular estimates of the frequencies of and population-wide susceptibility to emerging viruses, we can better anticipate major antigenic transitions. This provides added incentives for accelerating the vaccine production cycle to reduce the lead time required for strain selection. The efficacy of annual seasonal influenza vaccines depends on selecting the strain that best matches circulating viruses. This selection takes place 9–12 months prior to the influenza season. To advise this decision, we used an influenza A/H3N2 phylodynamic simulation to explore how reliably and how far in advance can we identify strains that will dominate future influenza seasons? What data should we collect to accelerate and improve the accuracy of such forecasts? And importantly, what is the gap between the theoretical limit of prediction and prediction based on current influenza surveillance? Our results suggest that even with detailed virological information, the tight race between the antigenic turnover dynamics and the vaccine development timeline limits early detection of emerging viruses. Predictions based on current influenza surveillance do not achieve the theoretical limit and thus our results provide impetus for denser sampling and the development of rapid methods for estimating viral fitness.
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9
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Wen F, Bedford T, Cobey S. Explaining the geographical origins of seasonal influenza A (H3N2). Proc Biol Sci 2017; 283:rspb.2016.1312. [PMID: 27629034 PMCID: PMC5031657 DOI: 10.1098/rspb.2016.1312] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 08/24/2016] [Indexed: 12/17/2022] Open
Abstract
Most antigenically novel and evolutionarily successful strains of seasonal influenza A (H3N2) originate in East, South and Southeast Asia. To understand this pattern, we simulated the ecological and evolutionary dynamics of influenza in a host metapopulation representing the temperate north, tropics and temperate south. Although seasonality and air traffic are frequently used to explain global migratory patterns of influenza, we find that other factors may have a comparable or greater impact. Notably, a region's basic reproductive number (R0) strongly affects the antigenic evolution of its viral population and the probability that its strains will spread and fix globally: a 17-28% higher R0 in one region can explain the observed patterns. Seasonality, in contrast, increases the probability that a tropical (less seasonal) population will export evolutionarily successful strains but alone does not predict that these strains will be antigenically advanced. The relative sizes of different host populations, their birth and death rates, and the region in which H3N2 first appears affect influenza's phylogeography in different but relatively minor ways. These results suggest general principles that dictate the spatial dynamics of antigenically evolving pathogens and offer predictions for how changes in human ecology might affect influenza evolution.
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Affiliation(s)
- Frank Wen
- Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, IL 60637, USA
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, IL 60637, USA
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10
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Fox SJ, Miller JC, Meyers LA. Seasonality in risk of pandemic influenza emergence. PLoS Comput Biol 2017; 13:e1005749. [PMID: 29049288 PMCID: PMC5654262 DOI: 10.1371/journal.pcbi.1005749] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 08/30/2017] [Indexed: 11/18/2022] Open
Abstract
Influenza pandemics can emerge unexpectedly and wreak global devastation. However, each of the six pandemics since 1889 emerged in the Northern Hemisphere just after the flu season, suggesting that pandemic timing may be predictable. Using a stochastic model fit to seasonal flu surveillance data from the United States, we find that seasonal flu leaves a transient wake of heterosubtypic immunity that impedes the emergence of novel flu viruses. This refractory period provides a simple explanation for not only the spring-summer timing of historical pandemics, but also early increases in pandemic severity and multiple waves of transmission. Thus, pandemic risk may be seasonal and predictable, with the accuracy of pre-pandemic and real-time risk assessments hinging on reliable seasonal influenza surveillance and precise estimates of the breadth and duration of heterosubtypic immunity.
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Affiliation(s)
- Spencer J. Fox
- Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
- * E-mail:
| | - Joel C. Miller
- Mathematical Sciences, Monash University, Frankston, Victoria, Australia
- The Institute for Disease Modeling, Bellevue, Washington, United States of America
| | - Lauren Ancel Meyers
- Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
- The Santa Fe Institute, Santa Fe, New Mexico, United States of America
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11
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Klepac P, Megiddo I, Grenfell BT, Laxminarayan R. Self-enforcing regional vaccination agreements. J R Soc Interface 2016; 13:20150907. [PMID: 26790996 PMCID: PMC4759795 DOI: 10.1098/rsif.2015.0907] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
In a highly interconnected world, immunizing infections are a transboundary problem, and their control and elimination require international cooperation and coordination. In the absence of a global or regional body that can impose a universal vaccination strategy, each individual country sets its own strategy. Mobility of populations across borders can promote free-riding, because a country can benefit from the vaccination efforts of its neighbours, which can result in vaccination coverage lower than the global optimum. Here we explore whether voluntary coalitions that reward countries that join by cooperatively increasing vaccination coverage can solve this problem. We use dynamic epidemiological models embedded in a game-theoretic framework in order to identify conditions in which coalitions are self-enforcing and therefore stable, and thus successful at promoting a cooperative vaccination strategy. We find that countries can achieve significantly greater vaccination coverage at a lower cost by forming coalitions than when acting independently, provided a coalition has the tools to deter free-riding. Furthermore, when economically or epidemiologically asymmetric countries form coalitions, realized coverage is regionally more consistent than in the absence of coalitions.
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Affiliation(s)
- Petra Klepac
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - Itamar Megiddo
- Center for Disease Dynamics, Economics and Policy, Washington, DC 20036, USA
| | - Bryan T Grenfell
- Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ramanan Laxminarayan
- Center for Disease Dynamics, Economics and Policy, Washington, DC 20036, USA Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA Public Health Foundation of India, New Delhi 110070, India
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12
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Neher RA, Bedford T, Daniels RS, Russell CA, Shraiman BI. Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses. Proc Natl Acad Sci U S A 2016; 113:E1701-9. [PMID: 26951657 PMCID: PMC4812706 DOI: 10.1073/pnas.1525578113] [Citation(s) in RCA: 117] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny.
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MESH Headings
- Amino Acid Sequence
- Antigenic Variation/genetics
- Antigens, Viral/genetics
- Antigens, Viral/immunology
- Computer Graphics
- Computer Simulation
- Evolution, Molecular
- Forecasting
- Hemagglutinin Glycoproteins, Influenza Virus/genetics
- Hemagglutinin Glycoproteins, Influenza Virus/immunology
- Humans
- Influenza A Virus, H1N1 Subtype/genetics
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines
- Influenza, Human/epidemiology
- Influenza, Human/prevention & control
- Betainfluenzavirus/genetics
- Betainfluenzavirus/immunology
- Models, Immunological
- Molecular Sequence Data
- Phenotype
- Phylogeny
- Seasons
- Software
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Affiliation(s)
- Richard A Neher
- Evolutionary Dynamics and Biophysics, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109
| | - Rodney S Daniels
- Worldwide Influenza Centre, The Francis Crick Institute, London NW7 1AA, United Kingdom
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom
| | - Boris I Shraiman
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106
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13
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Chan CHS, Sanders LP, Tanaka MM. Modelling the role of immunity in reversion of viral antigenic sites. J Theor Biol 2015; 392:23-34. [PMID: 26723535 DOI: 10.1016/j.jtbi.2015.12.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Revised: 12/14/2015] [Accepted: 12/16/2015] [Indexed: 12/22/2022]
Abstract
Antigenic sites in viral pathogens exhibit distinctive evolutionary dynamics due to their role in evading recognition by host immunity. Antigenic selection is known to drive higher rates of non-synonymous substitution; less well understood is why differences are observed between viruses in their propensity to mutate to a novel or previously encountered amino acid. Here, we present a model to explain patterns of antigenic reversion and forward substitution in terms of the epidemiological and molecular processes of the viral population. We develop an analytical three-strain model and extend the analysis to a multi-site model to predict characteristics of observed sequence samples. Our model provides insight into how the balance between selection to escape immunity and to maintain viability is affected by the rate of mutational input. We also show that while low probabilities of reversion may be due to either a low cost of immune escape or slowly decaying host immunity, these two scenarios can be differentiated by the frequency patterns at antigenic sites. Comparison between frequency patterns of human influenza A (H3N2) and human RSV-A suggests that the increased rates of antigenic reversion in RSV-A is due to faster decaying immunity and not higher costs of escape.
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Affiliation(s)
- Carmen H S Chan
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia; Evolution & Ecology Research Centre, University of New South Wales, Sydney, NSW, Australia.
| | - Lloyd P Sanders
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia; Evolution & Ecology Research Centre, University of New South Wales, Sydney, NSW, Australia; Computational Social Science, ETH, Zürich, Switzerland
| | - Mark M Tanaka
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia; Evolution & Ecology Research Centre, University of New South Wales, Sydney, NSW, Australia
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14
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Kucharski AJ, Andreasen V, Gog JR. Capturing the dynamics of pathogens with many strains. J Math Biol 2015; 72:1-24. [PMID: 25800537 PMCID: PMC4698306 DOI: 10.1007/s00285-015-0873-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Revised: 03/05/2015] [Indexed: 12/20/2022]
Abstract
Pathogens that consist of multiple antigenic variants are a serious public health concern. These infections, which include dengue virus, influenza and malaria, generate substantial morbidity and mortality. However, there are considerable theoretical challenges involved in modelling such infections. As well as describing the interaction between strains that occurs as a result cross-immunity and evolution, models must balance biological realism with mathematical and computational tractability. Here we review different modelling approaches, and suggest a number of biological problems that are potential candidates for study with these methods. We provide a comprehensive outline of the benefits and disadvantages of available frameworks, and describe what biological information is preserved and lost under different modelling assumptions. We also consider the emergence of new disease strains, and discuss how models of pathogens with multiple strains could be developed further in future. This includes extending the flexibility and biological realism of current approaches, as well as interface with data.
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Affiliation(s)
- Adam J Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
| | - Viggo Andreasen
- Department of Mathematics and Physics, Roskilde University, 4000, Roskilde, Denmark
| | - Julia R Gog
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge, UK
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15
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de Vos MGJ, Poelwijk FJ, Battich N, Ndika JDT, Tans SJ. Environmental dependence of genetic constraint. PLoS Genet 2013; 9:e1003580. [PMID: 23825963 PMCID: PMC3694820 DOI: 10.1371/journal.pgen.1003580] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2012] [Accepted: 05/04/2013] [Indexed: 11/25/2022] Open
Abstract
The epistatic interactions that underlie evolutionary constraint have mainly been studied for constant external conditions. However, environmental changes may modulate epistasis and hence affect genetic constraints. Here we investigate genetic constraints in the adaptive evolution of a novel regulatory function in variable environments, using the lac repressor, LacI, as a model system. We have systematically reconstructed mutational trajectories from wild type LacI to three different variants that each exhibit an inverse response to the inducing ligand IPTG, and analyzed the higher-order interactions between genetic and environmental changes. We find epistasis to depend strongly on the environment. As a result, mutational steps essential to inversion but inaccessible by positive selection in one environment, become accessible in another. We present a graphical method to analyze the observed complex higher-order interactions between multiple mutations and environmental change, and show how the interactions can be explained by a combination of mutational effects on allostery and thermodynamic stability. This dependency of genetic constraint on the environment should fundamentally affect evolutionary dynamics and affects the interpretation of phylogenetic data.
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Alfaro-Murillo JA, Towers S, Feng Z. A deterministic model for influenza infection with multiple strains and antigenic drift. JOURNAL OF BIOLOGICAL DYNAMICS 2013; 7:199-211. [PMID: 23701386 PMCID: PMC3780334 DOI: 10.1080/17513758.2013.801523] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2012] [Revised: 04/29/2013] [Indexed: 06/02/2023]
Abstract
We describe a multiple strain Susceptible Infected Recovered deterministic model for the spread of an influenza subtype within a population. The model incorporates appearance of new strains due to antigenic drift, and partial immunity to reinfection with related circulating strains. It also includes optional seasonal forcing of the transmission rate of the virus, which allows for comparison between temperate zones and the tropics. Our model is capable of reproducing observed qualitative patterns such as the overall annual outbreaks in the temperate region, a reduced magnitude and an increased frequency of outbreaks in the tropics, and the herald wave phenomenon. Our approach to modelling antigenic drift is novel and further modifications of this model may help improve the understanding of complex influenza dynamics.
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Wikramaratna PS, Sandeman M, Recker M, Gupta S. The antigenic evolution of influenza: drift or thrift? Philos Trans R Soc Lond B Biol Sci 2013; 368:20120200. [PMID: 23382423 PMCID: PMC3678325 DOI: 10.1098/rstb.2012.0200] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
It is commonly assumed that antibody responses against the influenza virus are polarized in the following manner: strong antibody responses are directed at highly variable antigenic epitopes, which consequently undergo 'antigenic drift', while weak antibody responses develop against conserved epitopes. As the highly variable epitopes are in a constant state of flux, current antibody-based vaccine strategies are focused on the conserved epitopes in the expectation that they will provide some level of clinical protection after appropriate boosting. Here, we use a theoretical model to suggest the existence of epitopes of low variability, which elicit a high degree of both clinical and transmission-blocking immunity. We show that several epidemiological features of influenza and its serological and molecular profiles are consistent with this model of 'antigenic thrift', and that identifying the protective epitopes of low variability predicted by this model could offer a more viable alternative to regularly update the influenza vaccine than exploiting responses to weakly immunogenic conserved regions.
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Bedford T, Rambaut A, Pascual M. Canalization of the evolutionary trajectory of the human influenza virus. BMC Biol 2012; 10:38. [PMID: 22546494 PMCID: PMC3373370 DOI: 10.1186/1741-7007-10-38] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2012] [Accepted: 04/30/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. However, despite strong pressure to evolve away from human immunity and to diversify in antigenic phenotype, H3N2 influenza shows paradoxically limited genetic and antigenic diversity present at any one time. Here, we propose a simple model of antigenic evolution in the influenza virus that accounts for this apparent discrepancy. RESULTS In this model, antigenic phenotype is represented by a N-dimensional vector, and virus mutations perturb phenotype within this continuous Euclidean space. We implement this model in a large-scale individual-based simulation, and in doing so, we find a remarkable correspondence between model behavior and observed influenza dynamics. This model displays rapid evolution but low standing diversity and simultaneously accounts for the epidemiological, genetic, antigenic, and geographical patterns displayed by the virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. CONCLUSIONS Selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable. In the model, the influenza population shows a 1- to 2-year timescale of repeatability, suggesting a window in which evolutionary dynamics could be, in theory, predictable.
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Affiliation(s)
- Trevor Bedford
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
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