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Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations.

Riley P, Ben-Nun M, Linker JA, Cost AA, Sanchez JL, George D, Bacon DP, Riley S - PLoS Comput. Biol. (2015)

Bottom Line: The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time.These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both.This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

View Article: PubMed Central - PubMed

Affiliation: Predictive Science Inc., San Diego, California, United States of America.

ABSTRACT
The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: pC, 0.0133-0.150 and R0, 1.09-2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with pC approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R0 and pC could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

No MeSH data available.


Related in: MedlinePlus

Transmissibility and severity of pandemic influenza.a Relationship between the total number of individuals infected and the basic reproductive number R0. Arrows show the non-linear effect of a 20% reduction in transmission: at lower reproductive numbers, the same intervention is much more effective. b Severity pyramid for infectious disease. The strength of symptoms and ability to detect cases increases with each level in the pyramid. c Conceptual two-dimensional classification of pandemics in terms of basic reproductive number (R0) and severity (pC), illustrating the likely impact of interventions, depending on where the outbreak falls in this parameter space (see main text).
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pcbi.1004392.g001: Transmissibility and severity of pandemic influenza.a Relationship between the total number of individuals infected and the basic reproductive number R0. Arrows show the non-linear effect of a 20% reduction in transmission: at lower reproductive numbers, the same intervention is much more effective. b Severity pyramid for infectious disease. The strength of symptoms and ability to detect cases increases with each level in the pyramid. c Conceptual two-dimensional classification of pandemics in terms of basic reproductive number (R0) and severity (pC), illustrating the likely impact of interventions, depending on where the outbreak falls in this parameter space (see main text).

Mentions: The transmissibility of an emergent strain in a particular population is quantified by the basic reproductive number R0, defined to be the average number of secondary cases generated by one typically infectious individual in an otherwise susceptible population [12]. If interventions are in place before the arrival of a new virus, as they are likely to be for many populations during a moderate or severe pandemic, their transmission-blocking efficacy can be thought of as proportional reduction in R0. The same proportionate decrease in R0 is much more effective in reducing the overall cumulative attack rate (CAR) for lower absolute values of R0 than for higher absolute values (Fig 1A). Thus, estimates of R0 for pandemic influenza in the range 1.5 to 3 [13, 14] are important because they imply a high population efficacy for interventions that reduce R0 by only modest proportions [9, 15], even if containment [16, 17] is not achieved.


Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations.

Riley P, Ben-Nun M, Linker JA, Cost AA, Sanchez JL, George D, Bacon DP, Riley S - PLoS Comput. Biol. (2015)

Transmissibility and severity of pandemic influenza.a Relationship between the total number of individuals infected and the basic reproductive number R0. Arrows show the non-linear effect of a 20% reduction in transmission: at lower reproductive numbers, the same intervention is much more effective. b Severity pyramid for infectious disease. The strength of symptoms and ability to detect cases increases with each level in the pyramid. c Conceptual two-dimensional classification of pandemics in terms of basic reproductive number (R0) and severity (pC), illustrating the likely impact of interventions, depending on where the outbreak falls in this parameter space (see main text).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4581836&req=5

pcbi.1004392.g001: Transmissibility and severity of pandemic influenza.a Relationship between the total number of individuals infected and the basic reproductive number R0. Arrows show the non-linear effect of a 20% reduction in transmission: at lower reproductive numbers, the same intervention is much more effective. b Severity pyramid for infectious disease. The strength of symptoms and ability to detect cases increases with each level in the pyramid. c Conceptual two-dimensional classification of pandemics in terms of basic reproductive number (R0) and severity (pC), illustrating the likely impact of interventions, depending on where the outbreak falls in this parameter space (see main text).
Mentions: The transmissibility of an emergent strain in a particular population is quantified by the basic reproductive number R0, defined to be the average number of secondary cases generated by one typically infectious individual in an otherwise susceptible population [12]. If interventions are in place before the arrival of a new virus, as they are likely to be for many populations during a moderate or severe pandemic, their transmission-blocking efficacy can be thought of as proportional reduction in R0. The same proportionate decrease in R0 is much more effective in reducing the overall cumulative attack rate (CAR) for lower absolute values of R0 than for higher absolute values (Fig 1A). Thus, estimates of R0 for pandemic influenza in the range 1.5 to 3 [13, 14] are important because they imply a high population efficacy for interventions that reduce R0 by only modest proportions [9, 15], even if containment [16, 17] is not achieved.

Bottom Line: The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time.These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both.This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

View Article: PubMed Central - PubMed

Affiliation: Predictive Science Inc., San Diego, California, United States of America.

ABSTRACT
The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: pC, 0.0133-0.150 and R0, 1.09-2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with pC approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R0 and pC could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

No MeSH data available.


Related in: MedlinePlus