Relationship between Neighborhood Characteristics and Demand for Emergency Health Service Vehicles: A Poisson Hurdle Regression Modeling Approach

Habib, Muhammad Ahsanul; Olajide, Babatope; Terashima, Mikiko; Campbell, S. Duke

doi:10.1177/0361198118797459

Cited by 4 publications

(3 citation statements)

References 28 publications

(53 reference statements)

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“…Such models can determine both spatial and temporal factors within the same framework. For instance, it has been shown that residential areas have more demand during morning hours, commercial areas create more ambulance demand during afternoon hours, and areas with higher population density, a larger proportion of individuals older than 40 years, and more heterogenous land use create more ambulance demand (Habib et al, 2018).…”

Section: Demand Forecastingmentioning

confidence: 99%

Models for Dispatch of Volunteers in Daily Emergency Response

Matinrad

2022

Linköping Studies in Science and Technology. Dissertations

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Sufficient emergency resources are essential for emergency services to provide timely help to affected people and to minimize damage to public and private assets and the environment. Emergency services, however, face resource shortages and increasing demand over time. As a result, their response times increase, resulting in lower survival chances of affected people and more severe damage to properties and the environment. Thus, emergency services need to utilize and effectively manage all their available resources. These can be divided into traditional resources, such as ambulances, and new and emerging resources, such as volunteers. Models and methods developed using operations research (OR) methodologies can facilitate the management of these resources. However, despite a rich literature on OR-based models and methods focusing on traditional resources, the literature on new and emerging resources, and specifically volunteers, is scarce.The aim of this thesis is to develop models and methods for task assignment and dispatch of volunteers to daily medical emergencies. This also includes forecasting models for future emergencies. The developed models and methods consider volunteer programs in Sweden and the Netherlands, employing real historical data.The aim has been addressed through three studies, one main study and two substudies, the results of which are presented in the six included papers. The main study focuses on the development of models, methods, and strategies for task assignment and dispatch of volunteers to out-of-hospital cardiac arrest (OHCA) cases using OR.To evaluate the survival rates of these patients, the most important health outcome of a response process, survival functions have been used in the development of these models and strategies. The results of this study are presented in Papers Ⅱ-Ⅴ. The first sub-study investigates different types of new and emerging resources used in daily medical emergency response, and the results are presented as an overview of the literature in Paper Ⅰ. The second sub-study focuses on the forecast of medical emergency demand, and its outcomes are presented in Paper Ⅵ.The overall conclusion is that the use of OR-based models and methods can contribute to improved outcomes and increased survival probabilities compared to the strategies and techniques used in the existing systems. vi vii This PhD journey has been a roller coaster ride with many ups and downs. At times, the upward stretches were long and slow while the downward ones were deep, feeling as though they would never end. Despite all the challenges along the way, it was a very enjoyable experience, giving me the opportunity to learn many lessons and grow. It would not have been possible to finish this roller coaster ride and write this thesis alone; I have been lucky to have had many people with me throughout this time, cheering me on, helping me, and supporting me, to whom I am sincerely grateful.First and foremost, I would like to thank my supervisors, Tobias Andersson Granberg, Jan Lundgren, and Anna ...

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Section: Demand Forecastingmentioning

confidence: 99%

Models for Dispatch of Volunteers in Daily Emergency Response

Matinrad

2022

Linköping Studies in Science and Technology. Dissertations

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“…Furthermore, ignoring excess zeros in the modeling framework might result in biased and inconsistent parameter estimates and poor prediction accuracy ( 24 ). This demands an extension of the conventional Poisson/NB model into advanced techniques such as zero-inflated ( 24 – 26 ) and hurdle ( 27 , 28 ) models.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling the Demand for Shared E-Scooter Services

Orvin

Bachhal

Fatmi

2021

Transportation Research Record

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This paper presents the findings on modeling the demand for shared e-scooter services (SES); specifically, spatio-temporal variation of SES demand. A zero-inflated negative binomial (ZINB) model is developed using the count data of trip origins at the dissemination area level from Kelowna, Canada. The motivation for adopting the ZINB model is the presence of excess zeros in the count data. ZINB has two components: the zero-inflated component accounts for excess zeros, and the count component accounts for the over-dispersion characteristics of data resulting from excess zeros. In addition to the ZINB, several other count models including hurdle models are estimated. The goodness-of-fit measures suggest that the ZINB model outperforms other methods. The model results confirm the effects of temporal, weather, transportation infrastructure, land use, and neighborhood characteristics. For example, the count model results reveal that SES demand is more likely to be higher during summer, mid-day on weekends, afternoons of weekdays, and days without rainfall. Furthermore, higher e-scooter index, higher density of cycle tracks, heterogeneous land use, urban centers, lower elevation, and neighborhoods with higher density of hotels and younger population might induce higher demand. The zero component results of the model are consistent with the findings revealed by the count component. The model is validated using a hold-out sample, and the validation results confirm that the prediction performance of the model is reasonably satisfactory. The findings of this study provide important insights into when and where the demand is higher, which will assist in effective policy-making supporting e-scooter use.

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“…They used a timestratified case-crossover design and concluded that an hourly temperature of more than 27 Centigrade increases ambulance demand. Habib et al (2018) have examined the effects of neighborhood characteristics on ambulance demand. For this purpose, they used and compared a Poisson regression model with a Poisson hurdle regression model.…”

Section: Demandmentioning

confidence: 99%

An Operations Research Approach for Daily Emergency Management

Matinrad

2019

Linköping Studies in Science and Technology. Licentiate Thesis

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Emergency services play a vital role in society by providing help to affected people and minimizing damage to public and private assets as well as the environment during emergencies. However, these organizations deal with problems of increasing demand uncertainty and resource shortage over time. These problems lead to the creation of many other problems, such as longer response times, lower survivability of victims and patients, and more severe damage to properties and the environment. Acquiring more information about future emergency demand, such as factors affecting this demand, can contribute to reduction of the effects of increasing demand uncertainty. The introduction of volunteers as a new type of emergency resource, which has gained attention in the past few years, can be a solution to the problem of increasing resource shortage. My PhD journey started when I joined the KTS-division of Communication and Transport Systems, Department of Science and Technology. While this journey, so far, has been the most enjoyable trip I have ever taken in my life, it has not been an easy one all the time. A journey, full of ups and downs, many lessons learned, and many more to come to learn. During this period, many people have helped and supported me, to whom I am sincerely grateful. First and foremost, I would like to thank my supervisors, Tobias Andersson Granberg, Jan Lundgren, and Anna Fredriksson, for their patient guidance, feedback, comments, and the invaluable time and effort they spent sharing their knowledge with me. I am grateful to Tobias for continuously supporting me in every step of my research and studies, being there when needed for guidance, discussion, and developing ideas, and never losing his patience or belief in me. I am deeply grateful to all three of you and very happy to have you as my supervisors. Without your help, this thesis simply would not have turned out as it is now. Also, I would like to extend my gratitude to all my colleagues at KTS for discussions, sharing knowledge and experiences, and creating a friendly working environment. I am especially grateful to both my office mates, Alan and Therese; thank you for all our scientific and non-scientific discussions, it is always a pleasure talking to you two. A special thanks to both my formal and informal mentors, Fahimeh and Ellen; your kind support and talks helped me get through especially my first year as a PhD student. Thanks also to Kriss for always generously, and without any hesitance, sharing your time and knowledge with me. A special thank you to Viveka Nilson; your help with everything, with high positivity and spirit, is invaluable. And thanks to the PhD body of KTS for all PhD fikas, serious meetings, and after works; it is always nice to spend time with you. This research was financed by The Swedish Civil Contingency Agency (Myndigheten för samhällsskydd och beredskap, MSB), and has been part of the Center for Advanced Research in Emergency Response (CARER), for which I am very grateful. Additionally, I would like to thank my w...

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Relationship between Neighborhood Characteristics and Demand for Emergency Health Service Vehicles: A Poisson Hurdle Regression Modeling Approach

Cited by 4 publications

References 28 publications

Models for Dispatch of Volunteers in Daily Emergency Response

Models for Dispatch of Volunteers in Daily Emergency Response

Modeling the Demand for Shared E-Scooter Services

An Operations Research Approach for Daily Emergency Management

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