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

INTRODUCTION: Field trials and modelling studies suggest that elimination of dengue transmission may be possible through widespread release of Aedes aegypti mosquitoes infected with the insect bacterium Wolbachia pipientis (wMel strain), in conjunction with routine dengue control activities. This st...

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Autores principales: Bannister-Tyrrell, Melanie, Hillman, Alison, Indriani, Citra, Ahmad, Riris Andono, Utarini, Adi, Simmons, Cameron P, Anders, Katherine L, Sergeant, Evan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660636/
https://www.ncbi.nlm.nih.gov/pubmed/37989350
http://dx.doi.org/10.1136/bmjgh-2023-013313
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author Bannister-Tyrrell, Melanie
Hillman, Alison
Indriani, Citra
Ahmad, Riris Andono
Utarini, Adi
Simmons, Cameron P
Anders, Katherine L
Sergeant, Evan
author_facet Bannister-Tyrrell, Melanie
Hillman, Alison
Indriani, Citra
Ahmad, Riris Andono
Utarini, Adi
Simmons, Cameron P
Anders, Katherine L
Sergeant, Evan
author_sort Bannister-Tyrrell, Melanie
collection PubMed
description INTRODUCTION: Field trials and modelling studies suggest that elimination of dengue transmission may be possible through widespread release of Aedes aegypti mosquitoes infected with the insect bacterium Wolbachia 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 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. 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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spelling pubmed-106606362023-11-20 Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach Bannister-Tyrrell, Melanie Hillman, Alison Indriani, Citra Ahmad, Riris Andono Utarini, Adi Simmons, Cameron P Anders, Katherine L Sergeant, Evan BMJ Glob Health Original Research INTRODUCTION: Field trials and modelling studies suggest that elimination of dengue transmission may be possible through widespread release of Aedes aegypti mosquitoes infected with the insect bacterium Wolbachia 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 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. 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. BMJ Publishing Group 2023-11-20 /pmc/articles/PMC10660636/ /pubmed/37989350 http://dx.doi.org/10.1136/bmjgh-2023-013313 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Research
Bannister-Tyrrell, Melanie
Hillman, Alison
Indriani, Citra
Ahmad, Riris Andono
Utarini, Adi
Simmons, Cameron P
Anders, Katherine L
Sergeant, Evan
Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title_full Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title_fullStr Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title_full_unstemmed Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title_short Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach
title_sort utility of surveillance data for planning for dengue elimination in yogyakarta, indonesia: a scenario-tree modelling approach
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660636/
https://www.ncbi.nlm.nih.gov/pubmed/37989350
http://dx.doi.org/10.1136/bmjgh-2023-013313
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