Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.

BACKGROUND:Dengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human...

Full description

Bibliographic Details
Published in:PLOS Neglected Tropical Diseases
Main Authors: Guanghu Zhu, Jiming Liu, Qi Tan, Benyun Shi
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2016
Subjects:
Online Access:https://doi.org/10.1371/journal.pntd.0004633
https://doaj.org/article/bfc35b3669734ec09613383c50cd2267
id ftdoajarticles:oai:doaj.org/article:bfc35b3669734ec09613383c50cd2267
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:bfc35b3669734ec09613383c50cd2267 2023-05-15T15:12:48+02:00 Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China. Guanghu Zhu Jiming Liu Qi Tan Benyun Shi 2016-04-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0004633 https://doaj.org/article/bfc35b3669734ec09613383c50cd2267 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC4841561?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004633 https://doaj.org/article/bfc35b3669734ec09613383c50cd2267 PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004633 (2016) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2016 ftdoajarticles https://doi.org/10.1371/journal.pntd.0004633 2022-12-31T11:54:57Z BACKGROUND:Dengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human mobility. The purpose of this study is to detect dengue transmission patterns and identify the disease dispersion dynamics in Guangzhou, China. METHODOLOGY:We conducted surveys in 12 districts of Guangzhou, and collected daily data of Breteau index (BI) and reported cases between September and November 2014 from the public health authority reports. Based on the available data and the Ross-Macdonald theory, we propose a dengue transmission model that systematically integrates entomologic, demographic, and environmental information. In this model, we use (1) BI data and geographic variables to evaluate the spatial heterogeneities of Aedes mosquitoes, (2) a radiation model to simulate the daily mobility of humans, and (3) a Markov chain Monte Carlo (MCMC) method to estimate the model parameters. RESULTS/CONCLUSIONS:By implementing our proposed model, we can (1) estimate the incidence rates of dengue, and trace the infection time and locations, (2) assess risk factors and evaluate the infection threat in a city, and (3) evaluate the primary diffusion process in different districts. From the results, we can see that dengue infections exhibited a spatial and temporal variation during 2014 in Guangzhou. We find that urbanization, vector activities, and human behavior play significant roles in shaping the dengue outbreak and the patterns of its spread. This study offers useful information on dengue dynamics, which can help policy makers improve control and prevention measures. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 10 4 e0004633
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
Guanghu Zhu
Jiming Liu
Qi Tan
Benyun Shi
Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
topic_facet Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
description BACKGROUND:Dengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human mobility. The purpose of this study is to detect dengue transmission patterns and identify the disease dispersion dynamics in Guangzhou, China. METHODOLOGY:We conducted surveys in 12 districts of Guangzhou, and collected daily data of Breteau index (BI) and reported cases between September and November 2014 from the public health authority reports. Based on the available data and the Ross-Macdonald theory, we propose a dengue transmission model that systematically integrates entomologic, demographic, and environmental information. In this model, we use (1) BI data and geographic variables to evaluate the spatial heterogeneities of Aedes mosquitoes, (2) a radiation model to simulate the daily mobility of humans, and (3) a Markov chain Monte Carlo (MCMC) method to estimate the model parameters. RESULTS/CONCLUSIONS:By implementing our proposed model, we can (1) estimate the incidence rates of dengue, and trace the infection time and locations, (2) assess risk factors and evaluate the infection threat in a city, and (3) evaluate the primary diffusion process in different districts. From the results, we can see that dengue infections exhibited a spatial and temporal variation during 2014 in Guangzhou. We find that urbanization, vector activities, and human behavior play significant roles in shaping the dengue outbreak and the patterns of its spread. This study offers useful information on dengue dynamics, which can help policy makers improve control and prevention measures.
format Article in Journal/Newspaper
author Guanghu Zhu
Jiming Liu
Qi Tan
Benyun Shi
author_facet Guanghu Zhu
Jiming Liu
Qi Tan
Benyun Shi
author_sort Guanghu Zhu
title Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
title_short Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
title_full Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
title_fullStr Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
title_full_unstemmed Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.
title_sort inferring the spatio-temporal patterns of dengue transmission from surveillance data in guangzhou, china.
publisher Public Library of Science (PLoS)
publishDate 2016
url https://doi.org/10.1371/journal.pntd.0004633
https://doaj.org/article/bfc35b3669734ec09613383c50cd2267
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004633 (2016)
op_relation http://europepmc.org/articles/PMC4841561?pdf=render
https://doaj.org/toc/1935-2727
https://doaj.org/toc/1935-2735
1935-2727
1935-2735
doi:10.1371/journal.pntd.0004633
https://doaj.org/article/bfc35b3669734ec09613383c50cd2267
op_doi https://doi.org/10.1371/journal.pntd.0004633
container_title PLOS Neglected Tropical Diseases
container_volume 10
container_issue 4
container_start_page e0004633
_version_ 1766343441962237952