Estimating population sensitivity and confidence of freedom from highly pathogenic avian influenza in the Victorian poultry industry using passive surveillance

Sergeant, E.; Dries, Leanna R.; Moore, Karen; Salmon, Sally E.

doi:10.1016/j.prevetmed.2022.105622

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…Another source of bias in field studies is the expected stochasticity in the context of outbreaks; some subtypes might have had better conditions for spread than others, by chance. For instance, housing style has previously been considered to be a risk factor, and likely differs between studies, countries and species (Sergeant et al 2022, Scott et al 2018).…”

Section: Discussionmentioning

confidence: 99%

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A review of estimated transmission parameters for the spread of avian influenza viruses

Kirkeby

Ward

2022

Transbounding Emerging Dis

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Avian influenza poses an increasing problem in Europe and around the world. Simulation models are a useful tool to predict the spatiotemporal risk of avian influenza spread and evaluate appropriate control actions. To develop realistic simulation models, valid transmission parameters are critical. Here, we reviewed published estimates of the basic reproduction number (R0), the latent period and the infectious period by virus type, pathogenicity, species, study type and poultry flock unit. We found a large variation in the parameter estimates, with highest R0 estimates for H5N1 and H7N3 compared with other types; for low pathogenic avian influenza compared with high pathogenic avian influenza types; for ducks compared with other species; for estimates from field studies compared with experimental studies; and for within‐flock estimates compared with between‐flock estimates. Simulation models should reflect this observed variation so as to produce more reliable outputs and support decision‐making. How to incorporate this information into simulation models remains a challenge.

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Section: Discussionmentioning

confidence: 99%

“…For instance, housing style has previously been considered to be a risk factor, and likely differs between studies, countries and species (Sergeant et al. 2022 , Scott et al. 2018 ).…”

Section: Discussionmentioning

confidence: 99%

A review of estimated transmission parameters for the spread of avian influenza viruses

Kirkeby

Ward

2022

Transbounding Emerging Dis

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“…Model calculations used or adapted standard formulae as described by [16] and subsequent methodological developments [18,26,29,30], as follows:…”

Section: Methodsmentioning

confidence: 99%

“…Design prevalence was set at a single dengue case in the population and converted to a proportion (P * ) of the total population. Model calculations used or adapted standard formulae as described by [16] and subsequent methodological developments [18,26,29,30], as follows:…”

Section: Surveillance Sensitivitymentioning

confidence: 99%

Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario tree modelling approach

Bannister-Tyrrell

Hillman

Indriani

et al. 2023

Preprint

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Introduction Field trials and mathematical modelling studies suggest that elimination of dengue transmission may be possible through widespread release ofAedes aegyptimosquitoes infected with the insect bacteriumWolbachia pipientis(wMel strain), in conjunction with routine dengue control activities. This study aimed to develop a modelling framework to guide planning for the potential elimination of locally-acquired dengue in Yogyakarta, a city of almost 400,000 people in Java, Indonesia. Methods A scenario tree modelling approach was used to estimate the sensitivity of the dengue surveillance system (including routine hospital-based reporting and primary-care based enhanced surveillance), and time required to demonstrate elimination of locally-acquired dengue in Yogyakarta city, assuming the detected incidence of dengue decreases to zero in the future. Age and gender were included as risk factors for dengue, and detection nodes included the probability of seeking care, probability of sample collection and testing, diagnostic test sensitivity, and probability of case notification. Parameter distributions were derived from health system data or estimated by expert opinion. Alternative simulations were defined based on changes to key parameter values, separately and in combination. Results For the default simulation, median surveillance system sensitivity was 0.131 (95% PI 0.111 - 0.152) per month. Median confidence in dengue elimination reached 80% after a minimum of 13 months of zero detected dengue cases and 90% confidence after 25 months, across different scenarios. The alternative simulations investigated produced relatively small changes in median system sensitivity and time to elimination. Conclusion This study suggests that with a combination of hospital-based surveillance and enhanced clinic-based surveillance for dengue, an acceptable level of confidence (80% probability) in the elimination of locally acquired dengue can be reached within 2 years. Increasing the surveillance system sensitivity could shorten the time to first ascertainment of elimination of dengue and increase the level of confidence in elimination.

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“…Model calculations used or adapted standard formulae as described by15 and subsequent methodological developments,17 27 30 31 as follows:…”

Section: Methodsmentioning

confidence: 99%

Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach

Bannister-Tyrrell,

Hillman,

Indriani

et al. 2023

BMJ Glob Health

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IntroductionField trials and modelling studies suggest that elimination of dengue transmission may be possible through widespread release ofAedes aegyptimosquitoes infected with the insect bacteriumWolbachia pipientis(wMel strain), in conjunction with routine dengue control activities. This study aimed to develop a modelling framework to guide planning for the potential elimination of locally acquired dengue in Yogyakarta, a city of almost 400 000 people in Java, Indonesia.MethodsA scenario-tree modelling approach was used to estimate the sensitivity of the dengue surveillance system (including routine hospital-based reporting and primary-care-based enhanced surveillance), and time required to demonstrate elimination of locally acquired dengue in Yogyakarta city, assuming the detected incidence of dengue decreases to zero in the future. Age and gender were included as risk factors for dengue, and detection nodes included the probability of seeking care, probability of sample collection and testing, diagnostic test sensitivity and probability of case notification. Parameter distributions were derived from health system data or estimated by expert opinion. Alternative simulations were defined based on changes to key parameter values, separately and in combination.ResultsFor the default simulation, median surveillance system sensitivity was 0.131 (95% PI 0.111 to 0.152) per month. Median confidence in dengue elimination reached 80% after a minimum of 13 months of zero detected dengue cases and 90% confidence after 25 months, across different scenarios. The alternative simulations investigated produced relatively small changes in median system sensitivity and time to elimination.ConclusionThis study suggests that with a combination of hospital-based surveillance and enhanced clinic-based surveillance for dengue, an acceptable level of confidence (80% probability) in the elimination of locally acquired dengue can be reached within 2 years. Increasing the surveillance system sensitivity could shorten the time to first ascertainment of elimination of dengue and increase the level of confidence in elimination.

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Estimating population sensitivity and confidence of freedom from highly pathogenic avian influenza in the Victorian poultry industry using passive surveillance

Cited by 4 publications

References 17 publications

A review of estimated transmission parameters for the spread of avian influenza viruses

A review of estimated transmission parameters for the spread of avian influenza viruses

Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario tree modelling approach

Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach

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