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Surveillance of low pathogenic novel H7N9 avian influenza in commercial poultry barns: detection of outbreaks and estimation of virus introduction time.

Pinsent A, Blake IM, White MT, Riley S - BMC Infect. Dis. (2014)

Bottom Line: We accurately estimated the day of virus introduction in isolation with weekly and 2-weekly sampling.A strong sampling effort would be required to infer both the day of virus introduction and R0.Such a sampling effort would not be required to estimate the day of virus introduction alone once R0 was known, and sampling N sample = 50 of birds in the flock on a weekly or 2 weekly basis would be sufficient.

View Article: PubMed Central - PubMed

Affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London, UK. amy.pinsent07@imperial.ac.uk.

ABSTRACT

Background: Both high and low pathogenic subtype A avian influenza remain ongoing threats to the commercial poultry industry globally. The emergence of a novel low pathogenic H7N9 lineage in China presents itself as a new concern to both human and animal health and may necessitate additional surveillance in commercial poultry operations in affected regions.

Methods: Sampling data was simulated using a mechanistic model of H7N9 influenza transmission within commercial poultry barns together with a stochastic observation process. Parameters were estimated using maximum likelihood. We assessed the probability of detecting an outbreak at time of slaughter using both real-time polymerase chain reaction (rt-PCR) and a hemagglutinin inhibition assay (HI assay) before considering more intense sampling prior to slaughter. The day of virus introduction and R0 were estimated jointly from weekly flock sampling data. For scenarios where R0 was known, we estimated the day of virus introduction into a barn under different sampling frequencies.

Results: If birds were tested at time of slaughter, there was a higher probability of detecting evidence of an outbreak using an HI assay compared to rt-PCR, except when the virus was introduced <2 weeks before time of slaughter. Prior to the initial detection of infection N sample = 50 (1%) of birds were sampled on a weekly basis once, but after infection was detected, N sample = 2000 birds (40%) were sampled to estimate both parameters. We accurately estimated the day of virus introduction in isolation with weekly and 2-weekly sampling.

Conclusions: A strong sampling effort would be required to infer both the day of virus introduction and R0. Such a sampling effort would not be required to estimate the day of virus introduction alone once R0 was known, and sampling N sample = 50 of birds in the flock on a weekly or 2 weekly basis would be sufficient.

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The likelihood of identifying day of virus introduction (Ts) and basic reproduction number (R0) simultaneously with and without varying degrees of reactive sampling.A-D the contour of the log likelihood surface around the true values of R0 and Ts. Reactive sampling of Nsample = 50, 500, 1000, and 2000 birds for A, B, C and D respectively. For illustration purposes an R0 = 7 and Ts = 7 were used. Different colours represent how close each estimate of the likelihood is to the maximum value. Blue indicates greater than 1.92 from the maximised true estimate, green indicates less than 1.92 likelihood point from the maximised true estimate (corresponding to the 95% confidence intervals), yellow indicates less than 1.0 likelihood point from the maximised true estimate and red indicates less than 0.5 points away from the maximised true estimate.
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Fig3: The likelihood of identifying day of virus introduction (Ts) and basic reproduction number (R0) simultaneously with and without varying degrees of reactive sampling.A-D the contour of the log likelihood surface around the true values of R0 and Ts. Reactive sampling of Nsample = 50, 500, 1000, and 2000 birds for A, B, C and D respectively. For illustration purposes an R0 = 7 and Ts = 7 were used. Different colours represent how close each estimate of the likelihood is to the maximum value. Blue indicates greater than 1.92 from the maximised true estimate, green indicates less than 1.92 likelihood point from the maximised true estimate (corresponding to the 95% confidence intervals), yellow indicates less than 1.0 likelihood point from the maximised true estimate and red indicates less than 0.5 points away from the maximised true estimate.

Mentions: Birds within the barn were sampled and tested for infection using an rt-PCR test on a weekly basis to estimate Ts and R0, whilst assuming all other parameters were known (parameters are described in Table 1). In the absence of reactive sampling (an increase in the number of birds sampled at the next time point following the detection of infection), it was difficult to accurately obtain an estimate for Ts and R0. Here a wide range of different values of Ts gave comparable likelihoods for a fixed value of R0 (Figure 3A). We increased the number of birds sampled after the initial detection of infection in the following manner: Nsample = 50, Nsample = 500, Nsample = 1000 and Nsample = 2000, (Figure 3 A, B, C, D, respectively). The increase in number of birds sampled improved the accuracy of the estimates of R0 and Ts (Figure 3). Of the regimes tested the best accuracy arose from sampling 2,000 birds (40%) after detection of infection (Figure 3D). Anything lower resulted in highly variable estimates of Ts and R0 across different stochastic observations, therefore this was the sampling regime used for all estimates presented. We assumed that in the relatively rare event of such an outbreak resources would be extended to accommodate this sampling regime.Figure 3


Surveillance of low pathogenic novel H7N9 avian influenza in commercial poultry barns: detection of outbreaks and estimation of virus introduction time.

Pinsent A, Blake IM, White MT, Riley S - BMC Infect. Dis. (2014)

The likelihood of identifying day of virus introduction (Ts) and basic reproduction number (R0) simultaneously with and without varying degrees of reactive sampling.A-D the contour of the log likelihood surface around the true values of R0 and Ts. Reactive sampling of Nsample = 50, 500, 1000, and 2000 birds for A, B, C and D respectively. For illustration purposes an R0 = 7 and Ts = 7 were used. Different colours represent how close each estimate of the likelihood is to the maximum value. Blue indicates greater than 1.92 from the maximised true estimate, green indicates less than 1.92 likelihood point from the maximised true estimate (corresponding to the 95% confidence intervals), yellow indicates less than 1.0 likelihood point from the maximised true estimate and red indicates less than 0.5 points away from the maximised true estimate.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4129106&req=5

Fig3: The likelihood of identifying day of virus introduction (Ts) and basic reproduction number (R0) simultaneously with and without varying degrees of reactive sampling.A-D the contour of the log likelihood surface around the true values of R0 and Ts. Reactive sampling of Nsample = 50, 500, 1000, and 2000 birds for A, B, C and D respectively. For illustration purposes an R0 = 7 and Ts = 7 were used. Different colours represent how close each estimate of the likelihood is to the maximum value. Blue indicates greater than 1.92 from the maximised true estimate, green indicates less than 1.92 likelihood point from the maximised true estimate (corresponding to the 95% confidence intervals), yellow indicates less than 1.0 likelihood point from the maximised true estimate and red indicates less than 0.5 points away from the maximised true estimate.
Mentions: Birds within the barn were sampled and tested for infection using an rt-PCR test on a weekly basis to estimate Ts and R0, whilst assuming all other parameters were known (parameters are described in Table 1). In the absence of reactive sampling (an increase in the number of birds sampled at the next time point following the detection of infection), it was difficult to accurately obtain an estimate for Ts and R0. Here a wide range of different values of Ts gave comparable likelihoods for a fixed value of R0 (Figure 3A). We increased the number of birds sampled after the initial detection of infection in the following manner: Nsample = 50, Nsample = 500, Nsample = 1000 and Nsample = 2000, (Figure 3 A, B, C, D, respectively). The increase in number of birds sampled improved the accuracy of the estimates of R0 and Ts (Figure 3). Of the regimes tested the best accuracy arose from sampling 2,000 birds (40%) after detection of infection (Figure 3D). Anything lower resulted in highly variable estimates of Ts and R0 across different stochastic observations, therefore this was the sampling regime used for all estimates presented. We assumed that in the relatively rare event of such an outbreak resources would be extended to accommodate this sampling regime.Figure 3

Bottom Line: We accurately estimated the day of virus introduction in isolation with weekly and 2-weekly sampling.A strong sampling effort would be required to infer both the day of virus introduction and R0.Such a sampling effort would not be required to estimate the day of virus introduction alone once R0 was known, and sampling N sample = 50 of birds in the flock on a weekly or 2 weekly basis would be sufficient.

View Article: PubMed Central - PubMed

Affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London, UK. amy.pinsent07@imperial.ac.uk.

ABSTRACT

Background: Both high and low pathogenic subtype A avian influenza remain ongoing threats to the commercial poultry industry globally. The emergence of a novel low pathogenic H7N9 lineage in China presents itself as a new concern to both human and animal health and may necessitate additional surveillance in commercial poultry operations in affected regions.

Methods: Sampling data was simulated using a mechanistic model of H7N9 influenza transmission within commercial poultry barns together with a stochastic observation process. Parameters were estimated using maximum likelihood. We assessed the probability of detecting an outbreak at time of slaughter using both real-time polymerase chain reaction (rt-PCR) and a hemagglutinin inhibition assay (HI assay) before considering more intense sampling prior to slaughter. The day of virus introduction and R0 were estimated jointly from weekly flock sampling data. For scenarios where R0 was known, we estimated the day of virus introduction into a barn under different sampling frequencies.

Results: If birds were tested at time of slaughter, there was a higher probability of detecting evidence of an outbreak using an HI assay compared to rt-PCR, except when the virus was introduced <2 weeks before time of slaughter. Prior to the initial detection of infection N sample = 50 (1%) of birds were sampled on a weekly basis once, but after infection was detected, N sample = 2000 birds (40%) were sampled to estimate both parameters. We accurately estimated the day of virus introduction in isolation with weekly and 2-weekly sampling.

Conclusions: A strong sampling effort would be required to infer both the day of virus introduction and R0. Such a sampling effort would not be required to estimate the day of virus introduction alone once R0 was known, and sampling N sample = 50 of birds in the flock on a weekly or 2 weekly basis would be sufficient.

Show MeSH
Related in: MedlinePlus