Spatial mapping of temporal risk characteristics to improve environmental health risk identification: A case study of a dengue epidemic in Taiwan

Wen, Tzai‐Hung; Lin, Neng-Yu; Lin, Chun-Hung A.; King, Chwan-Chuen; Su, Ming-Daw

doi:10.1016/j.scitotenv.2006.02.009

Cited by 71 publications

(96 citation statements)

References 13 publications

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“…However, it was based on the number of cases recorded daily as follows: for one or more confirmed DF cases per day, the occurrence for that day would be 1, while it would be 0 if no cases were found (Giesecke, 2001, Wen et al, 2006. We defined the index as ED/TD, where ED is the total number of days in which one or more cases occurred during the period and TD is the total number of days during the period (TD).…”

Section: Data Organization and Analysismentioning

confidence: 99%

“…Earnest et al (2005) and Zeger et al (2006) used autoregressive integrated moving average (ARIMA) models to forecast the spread of uneven cases and predict incidence values, but this and other similar approaches had difficulties identifying the spatial risk. Wen et al (2006) proposed a spatio-temporal risk approach to map uneven events based on temporally defined indices. In their study, three temporal risk indices were introduced and a local spatial auto-correlation index to identify areas at risk was proposed.…”

Section: Introductionmentioning

confidence: 99%

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Modeling spatio-temporal risk changes in the incidence of dengue fever in Saudi Arabia: a geographical information system case study

2011

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Abstract. The aim of this study was to use geographical information systems to demonstrate the Dengue fever (DF) risk on a monthly basis in Jeddah, Saudi Arabia with the purpose to provide documentation serving to improve surveillance and monitor the Aedes aegypti mosquito vector. Getis-Ord Gi* statistics and a frequency index covering a five-year period (2006)(2007)(2008)(2009)(2010) were used to map DF and model the risk spatio-temporally. The results show that monthly hotspots were mainly concentrated in central Jeddah districts and that the pattern changes considerably with time. For example, on a yearly basis, for the month of January, the Burman district was identified as a low risk area in 2006, a high-risk area in 2007, medium risk in 2008, very low risk in 2009 and low risk in 2010. The results demonstrate that it would be useful to follow the monthly DF pattern, based on the average weekly frequency, as this can facilitate the allocation of resources for the treatment of the disease, preventing its prevalence and monitoring its vector.

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Section: Data Organization and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling spatio-temporal risk changes in the incidence of dengue fever in Saudi Arabia: a geographical information system case study

2011

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“…Risk assessment examines the severity or magnitude of risk to human health posed by contaminants [22]. A risk assessment report can be either quantitative or qualitative.…”

Section: Introductionmentioning

confidence: 99%

Physical Risk Assessment for Urban Water Supply in a Developing Country: A Case of Mega City Dhaka

Shams

Ahsan

Al‐Mamun

et al. 2016

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Abstract. Water supply access in many developing countries is yet to fulfill Millennium Development Goals. Many local governments are incapable of managing their water resources either due to funding constrains or lack of adequate work force. This often results into poor services with low quality, insufficient and inconsistent delivery of water, leakage and wastage creating water shortages. The water stress resulting from urbanization is more acute in terms of Dhaka city due to its capital city-centric development strategies attracting rural-urban migration, which have resulted into an unplanned horizontal and vertical expansion of the city without having facilities for relevant infrastructures. Therefore, it is important to carry out a risk assessment on existing water supply distribution systems to address the challenges of frequent leaks contributing to cross contamination and system loss arising from unplanned development and aging of pipes. The objective of this study is to identify the physical risk for various zones under Dhaka City based on existing distribution systems and its susceptibility to leakage. The assessment requires analyses of distribution system, its length, number of leaks in the pipes detected every month, population density, number of consumers, characteristics of areas whether industrial or residential areas, low lying and vulnerable to flooding. The study finds that Zone IV possesses a very high risk due to an average leak of 93 per month with 1,571,960 people are exposed to vulnerability while Zone II, III, V, VI having average monthly leaks of 39, 36, 26, and 34 respectively are high risk zones.

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“…Nonetheless, they could be useful to confi rm the existence of case clusters and spatial correlation. In addition, Wen et al (2006) 13 state that the exclusive utilization of incidence rates to assess the occurrence of diseases provide limited results, and thus propose a temporal-spatial risk model to map geographic distribution of cases. This model is based on three risk measures in the geographic space -frequency, duration and intensity, and was applied in Taiwan in 2002, where it was considered adequate to identify high-risk areas.…”

mentioning

confidence: 99%

“…Following the example of the model proposed by Wen et al (2006), 13 the present study aimed to apply the temporal-spatial model to assess high-risk areas for the occurrence of dengue fever. The geocoding process was obtained by combining addresses where there had been dengue fever cases with a map of street segments provided by São José do Rio Preto's municipal government, by using the software ArcGIS 9.…”

mentioning

confidence: 99%

Modelo de risco tempo-espacial para identificação de áreas de risco para ocorrência de dengue

Galli¹,

Neto²

2008

Rev. Saúde Pública

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OBJECTIVE:To apply the temporal-spatial model to assess high-risk areas for the occurrence of dengue fever. METHODS:A total of 11,989 confi rmed, autochthonous dengue fever cases, geocoded by address in the city of São José do Rio Preto (Southeastern Brazil), between September of 2001 and August of 2006, were included in the study. Frequency, duration and intensity indices were used to assess the severity and magnitude of transmission. The local indicator of spatial association was adopted to identify signifi cant spatial clusters (p-value<0.05). The values of the three indices were considered high in a spatial unit when their standard values were positive and the respective local indicator of spatial association values were signifi cant. RESULTS:Of all the geocoded dengue fever cases, 38.1% occurred in the urban spatial units, classifi ed as highest-risk: 19.4% in 2001-2002, 13.9% in 2002-2003, 2.8% in 2003-2004, 16.7% in 2004-2005, and 21.3% in 2005-2006. The utilization of three risk measures enabled to identify higher-risk areas for the occurrence of dengue fever, concentrated in the city's northern region. Even though case notifi cation data are subject to bias, this information is available in the health services and can lead to important conclusions, recommendations and hypotheses. CONCLUSIONS:The non-complex, notifi cation-based procedures adopted in the study could be routinely used by services that are responsible for dengue fever surveillance and control to identify high-risk areas.

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Spatial mapping of temporal risk characteristics to improve environmental health risk identification: A case study of a dengue epidemic in Taiwan

Cited by 71 publications

References 13 publications

Modeling spatio-temporal risk changes in the incidence of dengue fever in Saudi Arabia: a geographical information system case study

Modeling spatio-temporal risk changes in the incidence of dengue fever in Saudi Arabia: a geographical information system case study

Physical Risk Assessment for Urban Water Supply in a Developing Country: A Case of Mega City Dhaka

Modelo de risco tempo-espacial para identificação de áreas de risco para ocorrência de dengue

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