Nonlinear Modelling for Predicting Patient Presentation Rates for Mass Gatherings

Arbon, Paul; Bottema, Murk J.; Zeitz, Kathryn; Lund, Adam; Turris, Sheila A.; Anikeeva, Olga; Steenkamp, Malinda

doi:10.1017/s1049023x18000493

Cited by 13 publications

(30 citation statements)

References 12 publications

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“…Three studies, conducted on data from a mixture of mass gathering manifestations, found crowd size to be positively associated with the total number of patient presentations [15,26,31] whereas attendance was not associated with PPR in one study [16].…”

Section: Plos Onementioning

confidence: 99%

“…Ten multivariable regression models to predict patient presentation (rate) were developed. The following predictor variables were included in these models: weather conditions (in 8 models), crowd size (in 4 models), type of the manifestation (in 8 models), venue accommodation (in 4 models), time of the manifestation (in 3 models), free water availability (in 1 model), https://doi.org/10.1371/journal.pone.0234977.g001 Weather conditions were found to be a significant factor to predict patient presentation (rate): humidity [15,26], temperature [21], heat index (i.e. a combination of air temperature and relative humidity) [18,24] and dew point [27] were positively associated with the number or rate of patient presentation at first aid posts.…”

Section: Factors That Predict Patient Presentation (Rate)mentioning

confidence: 99%

“…In one of our included studies, temperature (i.e. <23.5˚C vs �23.5˚C and <25.5˚C vs �25.5˚C) was included in a non-linear regression tree model with a lower total number of patient presentations in case of higher temperatures [26]. One study conducted in the USA found that the presence of air conditioning in a mixture of indoor mass gatherings (sport spectator manifestations, concerts, public exhibitions) was linked to a lower patient presentation rate [17].…”

Section: Factors That Predict Patient Presentation (Rate)mentioning

confidence: 99%

“…One multivariate model to predict PPR at 405 music concerts in the USA showed that indoor versus outdoor manifestations was not a statistically significant predictor [16]. Two Australian studies found that manifestations organised during both day and night resulted in a higher PPR compared to manifestations organized during the day or night [15,26]. One model to predict PPR at 403 music concerts found that day of the week was not a statistical significant predictor [24].…”

Section: Plos Onementioning

confidence: 99%

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Prediction modelling studies for medical usage rates in mass gatherings: A systematic review

et al. 2020

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Background Mass gathering manifestations attended by large crowds are an increasingly common feature of society. In parallel, an increased number of studies have been conducted that developed and/or validated a model to predict medical usage rates at these manifestations. Aims To conduct a systematic review to screen, analyse and critically appraise those studies that developed or validated a multivariable statistical model to predict medical usage rates at mass gatherings. To identify those biomedical, psychosocial and environmental predictors that are associated with increased medical usage rates and to summarise the predictive performance of the models. Method We searched for relevant prediction modelling studies in six databases. The predictors from multivariable regression models were listed for each medical usage rate outcome (i.e. patient presentation rate (PPR), transfer to hospital rate (TTHR) and the incidence of new injuries). The GRADE methodology (Grades of Recommendation, Assessment, Development and Evaluation) was used to assess the certainty of evidence. Results We identified 7,036 references and finally included 16 prediction models which were developed (n = 13) or validated (n = 3

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Section: Plos Onementioning

confidence: 99%

Section: Factors That Predict Patient Presentation (Rate)mentioning

confidence: 99%

Section: Factors That Predict Patient Presentation (Rate)mentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

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Prediction modelling studies for medical usage rates in mass gatherings: A systematic review

et al. 2020

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“…There is a positive correlation between environmental factors. Modeling can be useful for predicting patient presentation numbers not only for planned mass gatherings but for unplanned mass security events [135].…”

Section: Modeling and Simulation For Global Health Security Preparednessmentioning

confidence: 99%

Simulation and Modeling Applications in Global Health Security

French

2020

Advanced Sciences and Technologies for Security Applications

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Global health security (GHS) is dependent upon having an adequate and prepared health security workforce. There are currently numerous challenges in establishing and maintaining a health security workforce. The frequency and magnitude of disasters have increased significantly over the past 30 years. Current and future GHS threats, both manmade and natural, require a prepared and flexible healthcare provider workforce ready to respond to current or emerging GHS threats [1]. Developing and maintaining GHS -specific skills in the healthcare workforce is a tremendous logistical challenge. Innovative education technologies, including simulation and digital learning, can be leveraged to achieve preparedness for GHS threats [2].Ebola Virus Disease (EVD), Middle East Respiratory Syndrome (MERS) and other emerging infectious diseases (EID) are also concerns for GHS. The world faces increasing challenges related to natural and manmade disasters as the frequency and magnitude of disasters have increased significantly over the past 30 years. Healthcare workers protect the well-being of people around the world by preventing, detecting, and responding to public health threats. Current and future GHS threats, both manmade and natural, require a prepared and flexible healthcare provider workforce ready to respond to current or emerging threats [3].There is a global public health workforce shortage. The WHO tracks healthcare workforce data on 186 countries, and 57 were insufficient in healthcare provider availability and accessibility [4]. The 2013-2016 African EVD epidemic revealed WHO organizational deficiencies in coordinating responses to public health emergencies and a shifting of priorities away from global health security threats [5]. It Providing initial and sustainment training to the diverse GHS healthcare workforce is expensive and inefficient utilizing the traditional classroom model. Greater demands have been placed on disaster medicine educators. There is a need to develop innovative methods to educate healthcare providers in the ever-expanding body of disaster medicine knowledge [22].Many of these challenges can be met with gaming and simulation technologies new generations of GHS responders have embraced. Simulation-based training (SBT) has been demonstrated to provide effective learning and is increasingly being integrated into healthcare provider education [23]. The advantages of SBT may be summarized as follows: (1) safety-simulated lives and health can be jeopardized to any extent required for training without harming any people; (2) economy-simulated material and equipment can be used, misused, and expended;(3) visibility-simulation can provide visibility in two ways; you can make the invisible visible and control the visibility of details allowing the learner to discern the forest from the trees or the trees from the forest as needed; (4) time control -simulator time can be sped up, slowed down, or stopped. It can also be completely reversed, allowing learners to replicate specific problems, events, or opera...

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Medical management of mass gatherings

Smith¹,

Tataris²

2021

Emergency Medical Services

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Nonlinear Modelling for Predicting Patient Presentation Rates for Mass Gatherings

Cited by 13 publications

References 12 publications

Prediction modelling studies for medical usage rates in mass gatherings: A systematic review

Prediction modelling studies for medical usage rates in mass gatherings: A systematic review

Simulation and Modeling Applications in Global Health Security

Medical management of mass gatherings

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