Characteristics of automated external defibrillator coverage in Philadelphia, PA, based on land use and estimated risk

Chrisinger, Benjamin W.; Grossestreuer, Anne V.; Laguna, Meredith C; Griffis, Heather; Branas, Charles C.; Wiebe, Douglas J.; Merchant, Raina M.

doi:10.1016/j.resuscitation.2016.09.021

Cited by 11 publications

(7 citation statements)

References 24 publications

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“…Twenty observational studies 25,50,[59][60][61][62][63][64][65][67][68][69][70][71][72][73][74][75][76][77] and three surveys [53][54]66 reported on the availability and accessibility of public-access AEDs.…”

Section: Availability and Accessibilitymentioning

confidence: 99%

Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: a systematic review

Smith

Keung

Khan

et al. 2017

European Heart Journal - Quality of Care and Clinical Outcomes

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Public access defibrillation initiatives make automated external defibrillators available to the public. This facilitates earlier defibrillation of out-of-hospital cardiac arrest victims and could save many lives. It is currently only used for a minority of cases. The aim of this systematic review was to identify barriers and facilitators to public access defibrillation. A comprehensive literature review was undertaken defining formal search terms for a systematic review of the literature in March 2017. Studies were included if they considered reasons affecting the likelihood of public access defibrillation and presented original data. An electronic search strategy was devised searching MEDLINE and EMBASE, supplemented by bibliography and related-article searches. Given the low-quality and observational nature of the majority of articles, a narrative review was performed. Sixty-four articles were identified in the initial literature search. An additional four unique articles were identified from the electronic search strategies. The following themes were identified related to public access defibrillation: knowledge and awareness; willingness to use; acquisition and maintenance; availability and accessibility; training issues; registration and regulation; medicolegal issues; emergency medical services dispatch-assisted use of automated external defibrillators; automated external defibrillator-locator systems; demographic factors; other behavioural factors. In conclusion, several barriers and facilitators to public access defibrillation deployment were identified. However, the evidence is of very low quality and there is not enough information to inform changes in practice. This is an area in urgent need of further high-quality research if public access defibrillation is to be increased and more lives saved. PROSPERO registration number CRD42016035543.

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Section: Availability and Accessibilitymentioning

confidence: 99%

Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: a systematic review

Smith

Keung

Khan

et al. 2017

European Heart Journal - Quality of Care and Clinical Outcomes

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“…For instance, Shawul and Chakma have used this method to analysis the conversion of land use types in different periods 45 . The kernel density analysis could effectively identify the spatial agglomeration area of an event and was widely used in geographic, medical event analysis and case analysis 46 . The advantage of the Getis-Ord Gi* analysis is to judge the hot spots of high and low values at the same time and to analyze the evolution trend of hot spots of high and low values.…”

Section: Discussionmentioning

confidence: 99%

Coupling ITO3dE model and GIS for spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing in China

Zhu

Yang

Huang

et al. 2021

Sci Rep

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To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an ‘Input-Translate-Output’ three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40–2.28, 0.41–2.57, and 0.41–2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of ‘no-risk no-change’, ‘low-risk no-change’, and ‘medium-risk no-change’ were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.

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“…and Chakma have used this method to analysis the conversion of land use types in different periods (Shawul and Chakma, 2019). The kernel density analysis could effectively identify the spatial agglomeration area of an event and was widely used in geographic, medical event analysis and case analysis (Chrisinger et al, 2016). The advantage of the Getis-Ord Gi* analysis is to judge the hot spots of high and low values at the same time and to analyze the evolution trend of hot spots of high and low values.…”

Section: Geographical Methods Were Well Applied In the Field Of Agricmentioning

confidence: 99%

Spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing, China, based on the ITO3dE model and GIS

Zhu¹,

Yang²,

Huang³

et al. 2020

Preprint

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To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an ‘Input-Translate-Output’ three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40–2.28, 0.41–2.57, and 0.41–2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of ‘no-risk no-change’, ‘low-risk no-change’, and ‘medium-risk no-change’ were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1,110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.

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Characteristics of automated external defibrillator coverage in Philadelphia, PA, based on land use and estimated risk

Cited by 11 publications

References 24 publications

Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: a systematic review

Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: a systematic review

Coupling ITO3dE model and GIS for spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing in China

Spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing, China, based on the ITO3dE model and GIS

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