Fine-scale estimation of effective reproduction numbers for dengue surveillance

The effective reproduction number Rt is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used Rt as a measure to inform public health operations and policy f...

Full description

Saved in:
Bibliographic Details
Main Authors: Ong, Janet, Soh, Stacy, Ho, Soon Hoe, Seah, Annabel, Dickens, Borame Sue, Tan, Ken Wei, Koo, Joel Ruihan, Cook, Alex R., Richards, Daniel R., Gaw, Leon Yan-Feng, Ng, Lee Ching, Lim, Jue Tao
Other Authors: School of Biological Sciences
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/163304
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-163304
record_format dspace
spelling sg-ntu-dr.10356-1633042023-02-28T17:12:57Z Fine-scale estimation of effective reproduction numbers for dengue surveillance Ong, Janet Soh, Stacy Ho, Soon Hoe Seah, Annabel Dickens, Borame Sue Tan, Ken Wei Koo, Joel Ruihan Cook, Alex R. Richards, Daniel R. Gaw, Leon Yan-Feng Ng, Lee Ching Lim, Jue Tao School of Biological Sciences National Environment Agency Engineering::Environmental engineering Virus-Infection Vector Control The effective reproduction number Rt is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010-2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R2EpiEstim = 0.95, R2EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE EpiEstim = 1.23, MASEEpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response. Published version 2022-11-30T08:18:51Z 2022-11-30T08:18:51Z 2022 Journal Article Ong, J., Soh, S., Ho, S. H., Seah, A., Dickens, B. S., Tan, K. W., Koo, J. R., Cook, A. R., Richards, D. R., Gaw, L. Y., Ng, L. C. & Lim, J. T. (2022). Fine-scale estimation of effective reproduction numbers for dengue surveillance. PLoS Computational Biology, 18(1), e1009791-. https://dx.doi.org/10.1371/journal.pcbi.1009791 1553-734X https://hdl.handle.net/10356/163304 10.1371/journal.pcbi.1009791 35051176 2-s2.0-85123303715 1 18 e1009791 en PLoS Computational Biology © 2022 Ong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Virus-Infection
Vector Control
spellingShingle Engineering::Environmental engineering
Virus-Infection
Vector Control
Ong, Janet
Soh, Stacy
Ho, Soon Hoe
Seah, Annabel
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Cook, Alex R.
Richards, Daniel R.
Gaw, Leon Yan-Feng
Ng, Lee Ching
Lim, Jue Tao
Fine-scale estimation of effective reproduction numbers for dengue surveillance
description The effective reproduction number Rt is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010-2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R2EpiEstim = 0.95, R2EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE EpiEstim = 1.23, MASEEpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.
author2 School of Biological Sciences
author_facet School of Biological Sciences
Ong, Janet
Soh, Stacy
Ho, Soon Hoe
Seah, Annabel
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Cook, Alex R.
Richards, Daniel R.
Gaw, Leon Yan-Feng
Ng, Lee Ching
Lim, Jue Tao
format Article
author Ong, Janet
Soh, Stacy
Ho, Soon Hoe
Seah, Annabel
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Cook, Alex R.
Richards, Daniel R.
Gaw, Leon Yan-Feng
Ng, Lee Ching
Lim, Jue Tao
author_sort Ong, Janet
title Fine-scale estimation of effective reproduction numbers for dengue surveillance
title_short Fine-scale estimation of effective reproduction numbers for dengue surveillance
title_full Fine-scale estimation of effective reproduction numbers for dengue surveillance
title_fullStr Fine-scale estimation of effective reproduction numbers for dengue surveillance
title_full_unstemmed Fine-scale estimation of effective reproduction numbers for dengue surveillance
title_sort fine-scale estimation of effective reproduction numbers for dengue surveillance
publishDate 2022
url https://hdl.handle.net/10356/163304
_version_ 1759857005302906880