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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

Characterization of overall severity and individual base fits.a Estimates of R0 versus pC for top-50 military installations. The ten installations with the largest number of ILI cases are colored red, installations 11 through 20 are colored blue, and the remaining 30 bases are colored cyan. The grey box denotes the 40 installations with the smallest area in pC-R0 space. The histograms along the top and right show the distribution of pC and R0 values, respectively. b-e Incidence rates for four military installations (red line), with model fits overlaid (blue line), illustrating: b a two-peak profile; c a single-peak profile; d an anomalously high and narrow profile; and e a complex profile. The green line shows the value of the basic reproduction number and the horizontal dashed grey line marks the critical value of 1.0. The inset in each panel shows the cumulative attack rate for the same time period.
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pcbi.1004392.g002: Characterization of overall severity and individual base fits.a Estimates of R0 versus pC for top-50 military installations. The ten installations with the largest number of ILI cases are colored red, installations 11 through 20 are colored blue, and the remaining 30 bases are colored cyan. The grey box denotes the 40 installations with the smallest area in pC-R0 space. The histograms along the top and right show the distribution of pC and R0 values, respectively. b-e Incidence rates for four military installations (red line), with model fits overlaid (blue line), illustrating: b a two-peak profile; c a single-peak profile; d an anomalously high and narrow profile; and e a complex profile. The green line shows the value of the basic reproduction number and the horizontal dashed grey line marks the critical value of 1.0. The inset in each panel shows the cumulative attack rate for the same time period.

Mentions: To describe the key features of the lower portion of the severity pyramid, we extended a previous mechanistic model of influenza transmission in these MPZs [25]. In our earlier work, we assumed a value of pC, the proportion of infections that resulted in ILI, and fitted only R0. Here, we estimate pC and R0 jointly, by using known approximate size for each population (see MATERIALS AND METHODS, Fig 2, S2 Table). As expected, estimates for the basic reproduction number R0 were similar to those in our previous work [25], although there were some exceptions. Seven of the ten largest MPZs formed a distinct cluster within the R0-pC space, within the ranges: R0 between 1.12–1.53 and pC between 0.052–0.15. Visually, the fit of these models to ILI incidence data was good (S2 Fig).


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)

Characterization of overall severity and individual base fits.a Estimates of R0 versus pC for top-50 military installations. The ten installations with the largest number of ILI cases are colored red, installations 11 through 20 are colored blue, and the remaining 30 bases are colored cyan. The grey box denotes the 40 installations with the smallest area in pC-R0 space. The histograms along the top and right show the distribution of pC and R0 values, respectively. b-e Incidence rates for four military installations (red line), with model fits overlaid (blue line), illustrating: b a two-peak profile; c a single-peak profile; d an anomalously high and narrow profile; and e a complex profile. The green line shows the value of the basic reproduction number and the horizontal dashed grey line marks the critical value of 1.0. The inset in each panel shows the cumulative attack rate for the same time period.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi.1004392.g002: Characterization of overall severity and individual base fits.a Estimates of R0 versus pC for top-50 military installations. The ten installations with the largest number of ILI cases are colored red, installations 11 through 20 are colored blue, and the remaining 30 bases are colored cyan. The grey box denotes the 40 installations with the smallest area in pC-R0 space. The histograms along the top and right show the distribution of pC and R0 values, respectively. b-e Incidence rates for four military installations (red line), with model fits overlaid (blue line), illustrating: b a two-peak profile; c a single-peak profile; d an anomalously high and narrow profile; and e a complex profile. The green line shows the value of the basic reproduction number and the horizontal dashed grey line marks the critical value of 1.0. The inset in each panel shows the cumulative attack rate for the same time period.
Mentions: To describe the key features of the lower portion of the severity pyramid, we extended a previous mechanistic model of influenza transmission in these MPZs [25]. In our earlier work, we assumed a value of pC, the proportion of infections that resulted in ILI, and fitted only R0. Here, we estimate pC and R0 jointly, by using known approximate size for each population (see MATERIALS AND METHODS, Fig 2, S2 Table). As expected, estimates for the basic reproduction number R0 were similar to those in our previous work [25], although there were some exceptions. Seven of the ten largest MPZs formed a distinct cluster within the R0-pC space, within the ranges: R0 between 1.12–1.53 and pC between 0.052–0.15. Visually, the fit of these models to ILI incidence data was good (S2 Fig).

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