Urban villages as transfer stations for dengue fever epidemic: A case study in the Guangzhou, China.

Background Numerous urban villages (UVs) and frequent infectious disease outbreaks are major environmental and public health concerns in highly urbanized regions, especially in developing countries. However, the spatial and quantitative associations between UVs and infections remain little understoo...

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Bibliographic Details
Published in:PLOS Neglected Tropical Diseases
Main Authors: Hongyan Ren, Wei Wu, Tiegang Li, Zhicong Yang
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2019
Subjects:
Online Access:https://doi.org/10.1371/journal.pntd.0007350
https://doaj.org/article/1c1b7dd790fd4f45b09b812b60e04113
Description
Summary:Background Numerous urban villages (UVs) and frequent infectious disease outbreaks are major environmental and public health concerns in highly urbanized regions, especially in developing countries. However, the spatial and quantitative associations between UVs and infections remain little understood on a fine scale. Methodology and principal findings In this study, the relationships between reported dengue fever (DF) epidemics during 2012-2017, gross domestic product (GDP), the traffic system (road density, bus and/or subway stations), and UVs derived from high-resolution remotely sensed imagery in the central area of Guangzhou, were explored using geographically weighted regression (GWR) models based on a 1 km × 1 km grid scale. Accounting for 16.53%-18.07% of residential area and 16.84%-18.02% of population, UVs possessed 28.55%-38.24% of total reported DF cases in the core area of Guangzhou. The density of DF cases and the DF incidence rates in UVs were 1.81-3.13 and 1.82-3.06 times of that of normal construction land. Approximately 90% of the total cases were concentrated in the UVs and their buffering zones of radius ranged from 0 to 500 m. Significantly positive associations were observed between gridded DF incidence rates and UV area (r = 0.33, P = 0.000), the number of bus stops (r = 0.49, P = 0.000) and subway stations (r = 0.27, P = 0.000), and road density (r = 0.39, P = 0.000). About 60% of spatial variations in the gridded DF incidence rates were interpreted by the different variables of GDP, UVs, and bus stops integrated in GWR models. Conclusions UVs likely acted as special transfer stations, receiving and/or exporting DF cases during epidemics. This work increases our understanding of the influences of UVs on vector-borne diseases in highly urbanized areas, supplying valuable clues to local authorities making targeted interventions for the prevention and control of DF epidemics.