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  5. Spatiotemporal variability in dengue transmission intensity in Jakarta, Indonesia
 
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Spatiotemporal variability in dengue transmission intensity in Jakarta, Indonesia
File(s)
journal.pntd.0008102.pdf (2.9 MB)
Published version
Author(s)
O'Driscoll, Megan
Imai, Natsuko
Ferguson, Neil
Hadinegoro, Sri Rezeki
Satari, Hindra Irawan
more
Type
Journal Article
Abstract
Background
Approximately 70% of the global burden of dengue disease occurs on the Asian continent, where many large urban centres provide optimal environments for sustained endemic transmission and periodic epidemic cycles. Jakarta, the capital of Indonesia, is a densely populated megacity with hyperendemic dengue transmission. Characterization of the spatiotemporal distribution of dengue transmission intensity is of key importance for optimal implementation of novel control and prevention programmes, including vaccination. In this paper we use mathematical models to provide the first detailed description of spatial and temporal variability in dengue transmission intensity in Jakarta.

Methodology/Principal findings
We applied catalytic models in a Bayesian framework to age-stratified dengue case notification data to estimate dengue force of infection and reporting probabilities in 42 subdistricts of Jakarta. The model was fitted to yearly and average annual data covering a 10-year period between 2008 and 2017. We estimated a long-term average annual transmission intensity of 0.130 (95%CrI: 0.129–0.131) per year in Jakarta province, ranging from 0.090 (95%CrI: 0.077–0.103) to 0.164 (95%CrI: 0.153–0.174) across subdistricts. Annual average transmission intensity in Jakarta province during the 10-year period ranged from 0.012 (95%CrI: 0.011–0.013) in 2017 to 0.124 (95%CrI: 0.121–0.128) in 2016.

Conclusions/Significance
While the absolute number of dengue case notifications cannot be relied upon as a measure of endemicity, the age-distribution of reported dengue cases provides valuable insights into the underlying nature of transmission. Our estimates from yearly and average annual case notification data represent the first detailed estimates of dengue transmission intensity in Jakarta’s subdistricts. These will be important to consider when assessing the population-level impact and cost-effectiveness of potential control and prevention programmes in Jakarta province, such as the controlled release of Wolbachia-carrying mosquitoes and vaccination.

Author summary
Characterization of the spatiotemporal distribution of dengue transmission intensity, a key measure of population infection risk, can inform the optimal use and deployment of control and prevention programmes. Jakarta, the capital of Indonesia, is a large urban centre with hyperendemic dengue transmission. We fitted catalytic models to age-stratified dengue surveillance data reported in Jakarta’s subdistricts from 2008 to 2017. We estimated a long-term average annual transmission intensity of 0.130 (95%CrI: 0.129–0.131) per year in Jakarta province, which varied across subdistricts from 0.090 (95%CrI: 0.077–0.103) per year in Sawah Besar to 0.164 (95%CrI: 0.153–0.174) per year in Pasar Rebo. We observed significant spatiotemporal variation and clustering of transmission intensity in Jakarta. Our estimates obtained from the analysis of yearly and cumulative case-notification data reported between 2008 and 2017 represent the first detailed estimates of average dengue transmission intensity, which will be key to assess the potential impact of future control and prevention programmes in Jakarta province.
Date Issued
2020-03-06
Date Acceptance
2020-01-30
Citation
PLoS Neglected Tropical Diseases, 2020, 14 (3)
URI
http://hdl.handle.net/10044/1/77382
DOI
https://www.dx.doi.org/10.1371/journal.pntd.0008102
ISSN
1935-2727
Publisher
Public Library of Science
Journal / Book Title
PLoS Neglected Tropical Diseases
Volume
14
Issue
3
Copyright Statement
© 2020 O’Driscoll 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.
Sponsor
Bill & Melinda Gates Foundation
Medical Research Council
Medical Research Council (MRC)
Wellcome Trust
Grant Number
OPP1092240
MR/R015600/1
MR/R015600/1
213494/Z/18/Z
Subjects
06 Biological Sciences
11 Medical and Health Sciences
Tropical Medicine
Publication Status
Published
Article Number
ARTN e0008102
Date Publish Online
2020-03-06
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