Dataset Information

Ascertaining the impact of public rapid transit system on spread of dengue in urban settings.

ABSTRACT: Urbanization is an important factor contributing to the global spread of dengue in recent decades, especially in tropical regions. However, the impact of public transportation system on local spread of dengue in urban settings remains poorly understood, due to the difficulty in collecting relevant locality, transportation and disease incidence data with sufficient detail, and in suitably quantifying the combined effect of proximity and passenger flow. We quantify proximity and passenger traffic data relating to 2014-2015 dengue outbreaks in Kaohsiung, Taiwan by introducing a "Risk Associated with Metro Passengers Presence" (RAMPP), which considers the passenger traffic of stations located within a fixed radius, giving more weight to the busier and/or closer stations. In order to analyze the contagion risk associated with nearby presence of one or more Kaohsiung Rapid Transit (KRT) stations, we cluster the Li's (the fourth level administrative subdivision in Taiwan) of Kaohsiung based on their RAMPP value using the K-means algorithm. We then perform analysis of variance on distinct clusterings and detect significant differences for both years. The subsequent post hoc tests (Dunn) show that yearly incidence rate observed in the areas with highest RAMPP values is always significantly greater than that recorded with smaller RAMPP values. RAMPP takes into account of population mobility in urban settings via the use of passenger traffic information of urban transportation system, that captures the simple but important idea that large amount of passenger flow in and out of a station can dramatically increase the contagion risk of dengue in the neighborhood. Our study provides a new perspective in identifying high-risk areas for transmissions and thus enhances our understanding of how public rapid transit system contributes to disease spread in densely populated urban areas, which could be useful in the design of more effective and timely intervention and control measures for future outbreaks.

SUBMITTER: Sanna M

PROVIDER: S-EPMC7112089 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Ascertaining the impact of public rapid transit system on spread of dengue in urban settings.

Sanna Mattia M Hsieh Ying-Hen YH

The Science of the total environment 20170508

Urbanization is an important factor contributing to the global spread of dengue in recent decades, especially in tropical regions. However, the impact of public transportation system on local spread of dengue in urban settings remains poorly understood, due to the difficulty in collecting relevant locality, transportation and disease incidence data with sufficient detail, and in suitably quantifying the combined effect of proximity and passenger flow. We quantify proximity and passenger traffic ...[more]

PMID: 28499330

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Project description:Infectious disease outbreaks often occur in the aftermath of catastrophic events, either natural or man-made. While natural disasters such as typhoons/hurricanes, flooding and earthquakes have been known to increase the risk of infectious disease outbreak, the impact of anthropogenic disasters is less well-understood. Kaohsiung City is located in southern Taiwan, where most dengue outbreaks had occurred in the past two decades. It is also the center of petrochemical industry in Taiwan with pipelines running underneath city streets. Multiple underground gas explosions occurred in Kaohsiung in the evening of July 31, 2014 due to chemical leaks in the pipelines. The explosions caused 32 deaths, including five firefighters and two volunteer firefighters, and injured 321 persons. Historically, dengue outbreaks in southern Taiwan occurred mostly in small numbers of around 2000 cases or less, except in 2002 with over 5000 cases. However, in the months after the gas explosions, the city reported 14528 lab-confirmed dengue cases from August to December. To investigate the possible impact, if any, of the gas explosions on this record-breaking dengue outbreak, a simple mathematical model, the Richards model, is utilized to study the temporal patterns of the spread of dengue in the districts of Kaohsiung in the proximity of the explosion sites and to pinpoint the waves of infections that had occurred in each district in the aftermath of the gas explosions. The reproduction number of each wave in each district is also computed. In the aftermath of the gas explosions, early waves occurred 4-5 days (which coincides with the minimum of human intrinsic incubation period for dengue) later in districts with multiple waves. The gas explosions likely impacted the timing of the waves, but their impact on the magnitude of the 2014 outbreak remains unclear. The modeling suggests the need for public health surveillance and preparedness in the aftermath of future disasters.

Project description:BACKGROUND: Dengue infection spread in naive populations occurs in an explosive and widespread fashion primarily due to the absence of population herd immunity, the population dynamics and dispersal of Ae. aegypti, and the movement of individuals within the urban space. Knowledge on the relative contribution of such factors to the spatial dimension of dengue virus spread has been limited. In the present study we analyzed the spatio-temporal pattern of a large dengue virus-2 (DENV-2) outbreak that affected the Australian city of Cairns (north Queensland) in 2003, quantified the relationship between dengue transmission and distance to the epidemic's index case (IC), evaluated the effects of indoor residual spraying (IRS) on the odds of dengue infection, and generated recommendations for city-wide dengue surveillance and control. METHODS AND FINDINGS: We retrospectively analyzed data from 383 DENV-2 confirmed cases and 1,163 IRS applications performed during the 25-week epidemic period. Spatial (local k-function, angular wavelets) and space-time (Knox test) analyses quantified the intensity and directionality of clustering of dengue cases, whereas a semi-parametric Bayesian space-time regression assessed the impact of IRS and spatial autocorrelation in the odds of weekly dengue infection. About 63% of the cases clustered up to 800 m around the IC's house. Most cases were distributed in the NW-SE axis as a consequence of the spatial arrangement of blocks within the city and, possibly, the prevailing winds. Space-time analysis showed that DENV-2 infection spread rapidly, generating 18 clusters (comprising 65% of all cases), and that these clusters varied in extent as a function of their distance to the IC's residence. IRS applications had a significant protective effect in the further occurrence of dengue cases, but only when they reached coverage of 60% or more of the neighboring premises of a house. CONCLUSION: By applying sound statistical analysis to a very detailed dataset from one of the largest outbreaks that affected the city of Cairns in recent times, we not only described the spread of dengue virus with high detail but also quantified the spatio-temporal dimension of dengue virus transmission within this complex urban environment. In areas susceptible to non-periodic dengue epidemics, effective disease prevention and control would depend on the prompt response to introduced cases. We foresee that some of the results and recommendations derived from our study may also be applicable to other areas currently affected or potentially subject to dengue epidemics.

Dataset Information

Ascertaining the impact of public rapid transit system on spread of dengue in urban settings.

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Ascertaining the impact of public rapid transit system on spread of dengue in urban settings.

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