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Virulence attenuation during an influenza A/H5N1 pandemic.

Boni MF, Nguyen TD, de Jong MD, van Doorn HR - Philos. Trans. R. Soc. Lond., B, Biol. Sci. (2013)

Bottom Line: Evolutionary theory dictates that pathogens should evolve to be relatively benign, depending on the magnitude of the correlation between a pathogen's virulence and its transmissibility.Because the case fatality of H5N1 infections in humans is currently 60 per cent, it is doubtful that the current viruses are close to their evolutionary optimum for transmission among humans.We discuss two main epidemiological-evolutionary features of this system (i) the delaying or slowing of an epidemic which results in a majority of hosts experiencing an attenuated virulence phenotype and (ii) the strong evolutionary pressure for lower virulence experienced by the virus during a period of intense social distancing.

View Article: PubMed Central - PubMed

Affiliation: Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam. mboni@oucru.org

ABSTRACT
More than 15 years after the first human cases of influenza A/H5N1 in Hong Kong, the world remains at risk for an H5N1 pandemic. Preparedness activities have focused on antiviral stockpiling and distribution, development of a human H5N1 vaccine, operationalizing screening and social distancing policies, and other non-pharmaceutical interventions. The planning of these interventions has been done in an attempt to lessen the cumulative mortality resulting from a hypothetical H5N1 pandemic. In this theoretical study, we consider the natural limitations on an H5N1 pandemic's mortality imposed by the virus' epidemiological-evolutionary constraints. Evolutionary theory dictates that pathogens should evolve to be relatively benign, depending on the magnitude of the correlation between a pathogen's virulence and its transmissibility. Because the case fatality of H5N1 infections in humans is currently 60 per cent, it is doubtful that the current viruses are close to their evolutionary optimum for transmission among humans. To describe the dynamics of virulence evolution during an H5N1 pandemic, we build a mathematical model based on the patterns of clinical progression in past H5N1 cases. Using both a deterministic model and a stochastic individual-based simulation, we describe (i) the drivers of evolutionary dynamics during an H5N1 pandemic, (ii) the range of case fatalities for which H5N1 viruses can successfully cause outbreaks in humans, and (iii) the effects of different kinds of social distancing on virulence evolution. We discuss two main epidemiological-evolutionary features of this system (i) the delaying or slowing of an epidemic which results in a majority of hosts experiencing an attenuated virulence phenotype and (ii) the strong evolutionary pressure for lower virulence experienced by the virus during a period of intense social distancing.

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Contour plots in phenotype space showing (a) R0 value and (b) log10 case fatality for the different phenotypes in the model. The axes show affinity for α2,6 receptors (j index, horizontal axis) and level of viral replication (k index, vertical axis) and are scaled from 0 to 1. The basic reproductive number R0 is calculated from equations (2.3)–(2.8) (see the electronic supplementary material), and the case fatality is calculated from equation (2.9). The white circles in the top-left of each graph (a,b) show the approximate phenotypic position of current H5N1 viruses, low affinity for α2,6 receptors and a high level of viral replication. The white circles in the right of each graph (a,b) show the approximate phenotype position of seasonal human influenza viruses (i.e. subtypes H3N2 and H1N1); these viruses have a high affinity for α2,6 receptors and what we surmise to be an average level of viral replication. The white arrow in (a) shows the probable evolutionary path under the assumption that R0 is a good proxy for viral fitness. The white arrow in (b) shows the optimal evolutionary path from a public health perspective, i.e. the path that results in the most rapid virulence attenuation. R0,max = 1.82.
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RSTB20120207F2: Contour plots in phenotype space showing (a) R0 value and (b) log10 case fatality for the different phenotypes in the model. The axes show affinity for α2,6 receptors (j index, horizontal axis) and level of viral replication (k index, vertical axis) and are scaled from 0 to 1. The basic reproductive number R0 is calculated from equations (2.3)–(2.8) (see the electronic supplementary material), and the case fatality is calculated from equation (2.9). The white circles in the top-left of each graph (a,b) show the approximate phenotypic position of current H5N1 viruses, low affinity for α2,6 receptors and a high level of viral replication. The white circles in the right of each graph (a,b) show the approximate phenotype position of seasonal human influenza viruses (i.e. subtypes H3N2 and H1N1); these viruses have a high affinity for α2,6 receptors and what we surmise to be an average level of viral replication. The white arrow in (a) shows the probable evolutionary path under the assumption that R0 is a good proxy for viral fitness. The white arrow in (b) shows the optimal evolutionary path from a public health perspective, i.e. the path that results in the most rapid virulence attenuation. R0,max = 1.82.

Mentions: The case fatality for a given virus is , and the ω parameters are defined by2.9where CFmax is the maximum allowable case fatality in the model. Thus, we assume that case fatality is directly proportional to LRT burden. Figure 2 shows the case fatality and R0 values in phenotype space, the optimal evolutionary path of the virus, and the optimal evolutionary path from a public health perspective. In these two phenotype-space maps, we see that αj has the biggest impact on the invading virus's R0, and thus that evolution should favour more rapid change in αj than in βk. From a public health perspective, evolutionary change in both the α- and β-dimensions would be optimal as this would result in the most rapid reduction in case fatality. The white arrows in these graphs show, in phenotype space, the directions of maximal change in R0 and maximal change in case fatality.Figure 2.


Virulence attenuation during an influenza A/H5N1 pandemic.

Boni MF, Nguyen TD, de Jong MD, van Doorn HR - Philos. Trans. R. Soc. Lond., B, Biol. Sci. (2013)

Contour plots in phenotype space showing (a) R0 value and (b) log10 case fatality for the different phenotypes in the model. The axes show affinity for α2,6 receptors (j index, horizontal axis) and level of viral replication (k index, vertical axis) and are scaled from 0 to 1. The basic reproductive number R0 is calculated from equations (2.3)–(2.8) (see the electronic supplementary material), and the case fatality is calculated from equation (2.9). The white circles in the top-left of each graph (a,b) show the approximate phenotypic position of current H5N1 viruses, low affinity for α2,6 receptors and a high level of viral replication. The white circles in the right of each graph (a,b) show the approximate phenotype position of seasonal human influenza viruses (i.e. subtypes H3N2 and H1N1); these viruses have a high affinity for α2,6 receptors and what we surmise to be an average level of viral replication. The white arrow in (a) shows the probable evolutionary path under the assumption that R0 is a good proxy for viral fitness. The white arrow in (b) shows the optimal evolutionary path from a public health perspective, i.e. the path that results in the most rapid virulence attenuation. R0,max = 1.82.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675429&req=5

RSTB20120207F2: Contour plots in phenotype space showing (a) R0 value and (b) log10 case fatality for the different phenotypes in the model. The axes show affinity for α2,6 receptors (j index, horizontal axis) and level of viral replication (k index, vertical axis) and are scaled from 0 to 1. The basic reproductive number R0 is calculated from equations (2.3)–(2.8) (see the electronic supplementary material), and the case fatality is calculated from equation (2.9). The white circles in the top-left of each graph (a,b) show the approximate phenotypic position of current H5N1 viruses, low affinity for α2,6 receptors and a high level of viral replication. The white circles in the right of each graph (a,b) show the approximate phenotype position of seasonal human influenza viruses (i.e. subtypes H3N2 and H1N1); these viruses have a high affinity for α2,6 receptors and what we surmise to be an average level of viral replication. The white arrow in (a) shows the probable evolutionary path under the assumption that R0 is a good proxy for viral fitness. The white arrow in (b) shows the optimal evolutionary path from a public health perspective, i.e. the path that results in the most rapid virulence attenuation. R0,max = 1.82.
Mentions: The case fatality for a given virus is , and the ω parameters are defined by2.9where CFmax is the maximum allowable case fatality in the model. Thus, we assume that case fatality is directly proportional to LRT burden. Figure 2 shows the case fatality and R0 values in phenotype space, the optimal evolutionary path of the virus, and the optimal evolutionary path from a public health perspective. In these two phenotype-space maps, we see that αj has the biggest impact on the invading virus's R0, and thus that evolution should favour more rapid change in αj than in βk. From a public health perspective, evolutionary change in both the α- and β-dimensions would be optimal as this would result in the most rapid reduction in case fatality. The white arrows in these graphs show, in phenotype space, the directions of maximal change in R0 and maximal change in case fatality.Figure 2.

Bottom Line: Evolutionary theory dictates that pathogens should evolve to be relatively benign, depending on the magnitude of the correlation between a pathogen's virulence and its transmissibility.Because the case fatality of H5N1 infections in humans is currently 60 per cent, it is doubtful that the current viruses are close to their evolutionary optimum for transmission among humans.We discuss two main epidemiological-evolutionary features of this system (i) the delaying or slowing of an epidemic which results in a majority of hosts experiencing an attenuated virulence phenotype and (ii) the strong evolutionary pressure for lower virulence experienced by the virus during a period of intense social distancing.

View Article: PubMed Central - PubMed

Affiliation: Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam. mboni@oucru.org

ABSTRACT
More than 15 years after the first human cases of influenza A/H5N1 in Hong Kong, the world remains at risk for an H5N1 pandemic. Preparedness activities have focused on antiviral stockpiling and distribution, development of a human H5N1 vaccine, operationalizing screening and social distancing policies, and other non-pharmaceutical interventions. The planning of these interventions has been done in an attempt to lessen the cumulative mortality resulting from a hypothetical H5N1 pandemic. In this theoretical study, we consider the natural limitations on an H5N1 pandemic's mortality imposed by the virus' epidemiological-evolutionary constraints. Evolutionary theory dictates that pathogens should evolve to be relatively benign, depending on the magnitude of the correlation between a pathogen's virulence and its transmissibility. Because the case fatality of H5N1 infections in humans is currently 60 per cent, it is doubtful that the current viruses are close to their evolutionary optimum for transmission among humans. To describe the dynamics of virulence evolution during an H5N1 pandemic, we build a mathematical model based on the patterns of clinical progression in past H5N1 cases. Using both a deterministic model and a stochastic individual-based simulation, we describe (i) the drivers of evolutionary dynamics during an H5N1 pandemic, (ii) the range of case fatalities for which H5N1 viruses can successfully cause outbreaks in humans, and (iii) the effects of different kinds of social distancing on virulence evolution. We discuss two main epidemiological-evolutionary features of this system (i) the delaying or slowing of an epidemic which results in a majority of hosts experiencing an attenuated virulence phenotype and (ii) the strong evolutionary pressure for lower virulence experienced by the virus during a period of intense social distancing.

Show MeSH
Related in: MedlinePlus