Hostname: page-component-7bb8b95d7b-495rp Total loading time: 0 Render date: 2024-09-26T18:02:00.552Z Has data issue: false hasContentIssue false

Quantitative Metrics in Mass-Gathering Studies: A Comprehensive Systematic Review

Published online by Cambridge University Press:  05 April 2024

Cüneyt Çalışkan
Affiliation:
Department of Disaster Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Türkiye Department of Emergency Aid and Disaster Management, Hamidiye Faculty of Health Sciences, University of Health Sciences, Istanbul, Türkiye
Ahmet Doğan Kuday*
Affiliation:
Department of Disaster Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Türkiye
Tuğba Özcan
Affiliation:
Department of Disaster Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Türkiye
Nihal Dağ
Affiliation:
Department of Disaster Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Türkiye Department of Emergency Aid and Disaster Management, Hamidiye Faculty of Health Sciences, University of Health Sciences, Istanbul, Türkiye
Kerem Kınık
Affiliation:
Department of Disaster Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Türkiye Department of Emergency Aid and Disaster Management, Hamidiye Faculty of Health Sciences, University of Health Sciences, Istanbul, Türkiye
*
Correspondence: Ahmet Doğan Kuday Department of Disaster Medicine Hamidiye Institute of Health Sciences University of Health Sciences Istanbul, Türkiye E-mail: dogankuday@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Introduction:

Mass gatherings are events where many people come together at a specific location for a specific purpose, such as concerts, sports events, or religious gatherings, within a certain period of time. In mass-gathering studies, many rates and ratios are used to assess the demand for medical resources. Understanding such metrics is crucial for effective planning and intervention efforts. Therefore, this systematic review aims to investigate the usage of rates and ratios reported in mass-gathering studies.

Methods:

In this systematic review, the PRISMA guidelines were followed. Articles published through December 2023 were searched on Web of Science, Scopus, Cochrane, and PubMed using the specified keywords. Subsequently, articles were screened based on titles, abstracts, and full texts to determine their eligibility for inclusion in the study. Finally, the articles that were related to the study’s aim were evaluated.

Results:

Out of 745 articles screened, 55 were deemed relevant for inclusion in the study. These included 45 original research articles, three special reports, three case presentations, two brief reports, one short paper, and one field report. A total of 15 metrics were identified, which were subsequently classified into three categories: assessment of population density, assessment of in-event health services, and assessment of out-of-event health services.

Conclusion:

The findings of this study revealed notable inconsistencies in the reporting of rates and ratios in mass-gathering studies. To address these inconsistencies and to standardize the information reported in mass-gathering studies, a Metrics and Essential Ratios for Gathering Events (MERGE) table was proposed. Future research should promote consistency in terminology and adopt standardized methods for presenting rates and ratios. This would not only enhance comparability but would also contribute to a more nuanced understanding of the dynamics associated with mass gatherings.

Type
Systematic Review
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of World Association for Disaster and Emergency Medicine

Introduction

Perhaps there is no universally accepted definition of a mass gathering in the literature, but a mass gathering typically refers to the coming together of many people at a specific location for a common purpose or event. Reference Koçak and Tuncay1 Although this definition does not specify the number of attendees, a mass gathering typically involves many attendees, ranging from several thousand to several million. These events can take various forms such as concerts, festivals, sporting events, political rallies, religious meetings, and more. Mass gatherings often play a substantial role in uniting attendees, fostering a sense of community, enriching social interaction, promoting artistic and cultural engagement, and providing valuable contributions to the local economy. However, these spontaneous or planned (recurring or one-time) events can also strain the planning and intervention resources of the host community, city, or country. 2

Mass gatherings may present various challenges, including crowd management, security concerns, public health issues, and logistical matters. Reference Yezli and Alotaibi3 Organizers and authorities often need to plan and implement measures to ensure the safety and well-being of attendees, address potential security risks, and manage the overall logistics of the event. Especially due to the potential spread of infectious diseases in crowded environments, mass gatherings can pose significant public health risks. Reference Memish, Steffen and White4 To overcome these challenges, organizers and authorities need to take proactive measures for public health surveillance and monitoring to prevent, detect, and control infectious diseases.

Effectively managing risks in mass gatherings is a complex and multifaceted undertaking that requires a comprehensive strategy. Reference Aitsi-Selmi, Murray and Heymann5 At the core of this comprehensive approach lies the creation of a robust risk assessment tool that serves as a fundamental mechanism for identifying potential health hazards. Reference Sharma, Desikachari and Sarma6 This tool facilitates the systematic evaluation of various factors contributing to the overall risk environment. Moreover, estimating medical resource utilization within this framework is crucial. This estimation process is complex and greatly influenced by factors such as the nature and duration of the event, attendance levels, prevailing weather conditions, venue factors, crowd mood and density, as well as alcohol and drug consumption. Reference Milsten, Maguire and Bissell7 Event organizers and authorities can enhance their capacity to anticipate, mitigate, and effectively respond to potential health and safety issues during mass gatherings by considering these various factors.

In mass-gathering studies, the use of rates and ratios is crucial for assessing the demand on medical resources and providing a quantitative perspective on the health aspects of mass gatherings. Such metrics play an important role in developing targeted interventions and resource allocation strategies. As the risk environment evolves, a nuanced understanding of these metrics contributes to enhancing the overall resilience and preparedness of stakeholders involved in organizing and managing mass gatherings. Despite significant variations depending on the nature, scale, and purpose of mass gatherings, there are several metrics and formulas in the literature. However, significant differences were observed in the results of studies in the literature. Reference De Lorenzo8 Recent literature has highlighted a notable risk of inaccuracies in calculating medical usage rates (MURs) using different models in various contexts. Reference Van Remoortel, Scheers and De Buck9 Therefore, a systematic analysis of rates and ratios related to mass gatherings was conducted in this study, to lay the groundwork for the development and implementation of more effective strategies for future mass-gathering events.

Methods

Definitional Concepts

This study conducted a systematic review of articles that presented rates and ratios related to mass-gathering events. An integrative review approach was used in this study because of its ability to bring together different perspectives on the topic. Reference Whittemore and Knafl10 The review process included stages such as defining the problem, conducting a literature review, selecting and collecting data, analyzing the quality of evidence, and presenting the data. Although no specific protocol or record outlining inclusion criteria and methods of analysis has been established for this study, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines have been followed.

The research question has been determined as follows: “What are the rates and ratios derived for mass-gatherings events?” Within the scope of the defined question, the “participants” of this study consisted of all types of mass gatherings, such as sports events, music concerts, and festivals (Participation). The rates and ratios derived for mass gatherings were examined (Intervention). A comparative analysis was performed on the derived rates and ratios (Comparison). Rates and ratios obtained from different articles constituted the outcomes of the research (Outcomes). All studies published in English with accessible full texts were included in the research (Study Design).

Databases and Search Strategies

Database searching was conducted with the combination of the relevant keywords as follows: (mass gathering*) AND (rate* OR ratio*). For the selection of key terms, experts in the disaster medicine field were consulted and the consensus of four researchers was taken into consideration. A comprehensive search was conducted on PubMed (National Center for Biotechnology Information, National Institutes of Health; Bethesda, Maryland USA); Scopus (Elsevier; Amsterdam, Netherlands); Web of Science (Clarivate Analytics; London, United Kingdom); and Cochrane (Wiley; Hoboken, New Jersey USA) databases, and articles published through December 1, 2023 were obtained for relevant studies.

Eligibility Criteria

Inclusion Criteria—The inclusion criteria consisted of the following:

  1. 1. Articles that address rates or ratios derived from mass-gathering events;

  2. 2. Articles that are accessible and free of charge; and

  3. 3. Articles written in English.

Exclusion Criteria—The exclusion criteria consisted of the following:

  1. 1. Articles that do not address rates or ratios derived from mass-gathering events;

  2. 2. Articles that are not accessible and free of charge;

  3. 3. Articles not written in English;

  4. 4. Articles that report the incidence and prevalence of infectious diseases, such as COVID-19; and

  5. 5. Articles that include only simple percentages.

Study Selection and Data Extraction

Two researchers (ADK and TÖ) independently screened the titles and abstracts of all references obtained in the search results. Subsequently, the full text of each article potentially meeting the eligibility criteria was obtained. After the full-text assessment, studies that did not meet the selection criteria were excluded. Disagreements between researchers were resolved through consensus or consultation with a third referee (CC). For each included study, reference lists were scanned for relevant additional records. The Mendeley Reference Manager (Mendeley Ltd.; London, UK) app was used to manage scanned references and eliminate duplicate entries. Data obtained from the reviewed studies were extracted using a form created by the authors. All extracted data were reviewed by members of the research team to confirm accuracy and completeness. The following information was recorded to describe the findings: author(s), country, study type, event type, event duration, number of attendees, and outcome metrics.

Quality Appraisal

In this study, the Mixed Methods Appraisal Tool (MMAT) 2018 version was used to assess the quality of the included articles. The MMAT is a comprehensive appraisal tool that allows the evaluation of various research designs, including quantitative, qualitative, and mixed methods studies. It consists of five categories, each with five specific criteria: the qualitative set, randomized controlled trials set, non-randomized studies set, observational descriptive studies set, and mixed methods set. Reference Hong, Fàbregues and Bartlett11 In the process of quality assessment, two researchers (ADK & TÖ) scrutinized each article for potential biases according to MMAT categories. Any disparities were addressed through discussion or consultation with a third author. The outcomes of the quality assessment using MMAT 2018 in this systematic review encompass articles meeting three to five criteria (out of five). Reference Kuday, Özcan and Çalışkan12

Results

Included Studies Characteristics

Following the search, a total of 745 publications were identified from the Web of Science, Scopus, Cochrane, and PubMed databases. After eliminating duplicate articles, 567 publications remained. Among these, the abstracts of 440 studies did not meet the inclusion criteria, and the full texts were not reviewed. The full texts of the remaining 127 studies were read, and 72 of them were excluded. Of these, 61 of them were not relevant, eight were of low quality, the full text of two could not be accessed, and one was not in English. As a result, 55 articles were included in the study findings (Figure 1). The publication dates of the 55 studies included in the research findings ranged from 1990 through 2023. Among them, 45 were original research, three were special reports, three were case reports, two were brief reports, one was a short paper, and one was a report from the field (Table 1 Reference Alassaf13Reference Zeitz, Haghighi and Burstein67 ).

Figure 1. Flow Diagram of Study Identification and Selection Process.

Table 1. Characteristics of the Included Articles

Abbreviations: ATR, ambulance transfer rate; EHP, event-to-host-population ratio; In-PPR, intra-venue PPR; MARR, mutual aid request rate; METH, medical center to hospital; MG, mass gathering; MTR, medical transfer rate; MUR, medical usage rate; OHCA, out-of-hospital cardiac arrest; Out-PPR, out-of-venue PPR; PDR, pre-diagnosis rate; PPR, patient presentation rate; RTHR, referrals-to-hospital rate; TTHR, transport-to-hospital rate; USFMP, using start-finish medical post; VAR, venue accommodation rate.

Descriptive Analysis of Documents

As a result of the systematic review, a total of 15 metrics were obtained, including event-to-host-population ratio (EHP), venue accommodation rate (VAR), injury/season injury rate, rates of out-of-hospital cardiac arrest (OHCA), pre-diagnosis rate (PDR), attack rate, patient presentation rate (PPR), rate of using Start-Finish Medical Post (USFMP), MUR, ambulance transfer rate (ATR), medical service to hospital (METH), mutual aid request rate (MARR), transfer-to-hospital rate (TTHR), referral-to-hospital rate (RTHR), and medical transfer rate (MTR). These 15 metrics have been categorized into three groups: assessment of population density, in-event health services, and out-of-event health services. The formulas for the rate and ratios used in mass gatherings are presented in Table 2, and detailed information regarding these metrics is elaborated below.

Table 2. Formulas for the Metrics Used in Mass-Gathering Events

Abbreviations: ATR, ambulance transfer rate; EHP, event-to-host-population ratio; In-PPR, intra-venue PPR; MARR, mutual aid request rate; METH, medical center to hospital; MTR, medical transfer rate; MUR, medical usage rate; OHCA, out-of-hospital cardiac arrest; Out-PPR, out-of-venue PPR; PDR, pre-diagnosis rate; PPR, patient presentation rate; RTHR, referral-to-hospital rate; TTHR, transport-to-hospital rate; USFMP, using start-finish medical post; VAR, venue accommodation rate.

Assessment of Population Density

Event-to-Host-Population Ratio (EHP)—The EHP ratio refers to the ratio of the number of attendees in a mass-gathering event to the host population during the event. Reference Spaepen, Haenen and Kaufman54 Derived by dividing attendees by the host population, it guides resource planning, aiding organizers in ensuring event success without overwhelming infrastructure. Additionally, the EHP ratio anticipates health care demand, serving as a proactive tool for preparedness.

Venue Accommodation Rate (VAR)—The crowd density affects the volume of patients treated at an event, and the VAR serves as an indicator of this density. Reference Milsten, Maguire and Bissell7 It is defined as the rate of the actual number of spectators per event to the maximum capacity for attendees, expressed as a percentage. Reference Morimura, Katsumi and Koido47 A high rate suggests that the actual number of attendees per event is approaching or exceeding the maximum capacity, indicating a densely populated venue. On the other hand, a low rate suggests that there is still considerable capacity available in the venue, indicating a lower crowd density.

Assessment of In-Event Health Services

Injury Rate/Season Injury Rate—The injury rate is a metric that measures the frequency of injuries in a specific population or context and is commonly reported in mass-gathering events. The calculation of the injury rate involves dividing the total number of injuries by the overall number of attendees, typically presenting the result as a percentage. In addition, the season injury rate illustrates the cumulative injury rate occurring over one year, obtained by dividing the total injury rates within a year by 12 months. Reference Rabb and Coleby51 A higher injury rate indicates a greater frequency of injuries relative to the population or exposure, while a lower rate suggests a lower incidence of injuries.

Rate of Out-of-Hospital Cardiac Arrest (OHCA)—While OHCA is not a metric specific to mass gatherings, it signifies the unexpected cessation of an individual’s heart activity, typically occurring outside the hospital. The OHCA rate is calculated by dividing the number of OHCA cases during the event by the total number of attendees and then multiplying the result by a factor, often expressed per 100,000 attendees. Reference Goldberg, Battistini and Cash29 Even though not explicitly stated as OHCA in the literature, there are also studies providing the incidence rate of cardiopulmonary arrest per 10,000 attendees. Reference Bock, Cordell and Hawk18,Reference Tajima, Takazawa and Yamada59 A high OHCA rate or incidence rate of cardiopulmonary arrest in mass-gathering events suggests a high demand for emergency medical interventions and services such as responding to heart attacks. On the other hand, a low rate suggests a lower demand for emergency health care services during the event, and organizers may require fewer emergency resources.

Pre-Diagnosis Rate (PDR)—Injuries and illnesses like trauma, acute gastroenteritis, headache, myalgia, and sunburn are usually presented by frequency or percentage in mass-gathering events. In the literature, a few studies have provided PDR or the incidence rates of patient diagnosis/symptoms. Reference Spaite, Meislin and Valenzuela58 The PDR or rates of patient diagnosis/symptoms are employed to evaluate the incidence of specific diagnoses among patients or injured individuals. It is calculated by dividing the count of diagnoses by the total number of attendees and then multiplying the result by a factor, often expressed per 1,000 attendees. Reference Koçak, Çalışkan and Sönmezler37 A high diagnosis rate suggests an increased incidence of specific conditions among attendees in mass gatherings, indicating potential health issues before a formal diagnosis. This information assists event planners, health care professionals, and public health authorities in customizing their services. On the flip side, a lower rate of diagnosis might suggest an attendee population that is generally healthier; however, factors such as the type of event, demographics, and pre-existing conditions observed should be taken into account.

Attack Rate—Attack rate is a term typically used to measure the speed of the spread of an outbreak or disease. It is calculated by dividing the total number of cases that occur during a specific period or in a specific situation by the total population, often expressed as a percentage. While not exclusive to mass gatherings, it is a crucial metric for understanding the dynamics of the spread of outbreaks and diseases, informing preventive measures, and guiding the implementation of public health strategies in mass gatherings. Reference Rajakrishnan, Hafiz Ismail and Jamalulail52 It plays a significant role, particularly in the control of infectious diseases and the management of outbreak situations.

Patient Presentation Rate (PPR)—The PPR is a metric used to assess the number of patient presentations to a health care facility or service during a specific period within a mass-gathering event. In the literature, it is also observed that the PPR is analyzed in two separate categories for mass-gathering events: “Intra-venue PPR (In-PPR)” and “Out-of-venue PPR (Out-PPR).” In-PPR refers to presentations within the event venue, while Out-PPR pertains to presentations outside the venue. Reference Morimura, Katsumi and Koido47 However, it is often reported as PPR in the literature. The PPR is calculated by dividing the total number of patient presentations during the event by the overall number of attendees, and the result is often multiplied by a coefficient such as 10,000 for standardized reporting. Reference Arbon, Bridgewater and Smith17 A heightened PPR typically indicates a heightened demand for health care services, suggesting an escalation in health-related concerns during mass gatherings and signaling a potential necessity for emergency interventions. Conversely, a lower PPR generally signifies reduced demand for health care services, indicating that anticipated health issues during mass gatherings are limited, thereby reducing the need for emergency interventions.

Rate of Using Start-Finish Medical Post (USFMP)—Start-Finish Medical Post (SFMP) is a facility located at the start and finish lines of mass gatherings like marathons or cycling races. Its purpose is to provide prompt medical assistance to attendees facing emergencies, serving as a central hub with personnel and resources. The rate of USFMP is a metric that indicates the frequency or ratio of attendees seeking medical assistance or services at the SFMP during an event. It is calculated by dividing the number of individuals who utilize the SFMP services by the total number of attendees, often expressed per 10,000 attendees. Reference Ussahgij, Kotruchin and Osotthanakorn62 Although it yields the same output as PPR, USFMP is commonly used in sports events.

Medical Usage Rate (MUR)—The MUR, as also known overall usage rate, refers to the rate of utilization or demand for medical services or resources during a mass-gathering event. Reference Milsten, Maguire and Bissell7,Reference Burton, Corry and Lewis20 The MUR is calculated by dividing the number of individuals seeking medical care by the total attendance for that event and is typically reported as a rate in patients per 10,000 (PPTT). Reference Hostettler-Blunier, Müller and Haltmeier34,Reference Sabra, Cabañas and Bedolla53,Reference Thierbach, Wolcke and Piepho60 The PPR also is referred to as the MUR, but PPR may be limited in some studies to presentations to medical services and exclude first aid and other prehospital care presentations. Reference Arbon68 Therefore, it can be said that MUR encompasses the total patient presentations, including all presentations delivered by first aid providers and professional health care workers.

Assessment of Out-of-Event Health Services

Ambulance Transfer Rate (ATR)—The ATR typically refers to the rate of individuals at a mass-gathering event who require transportation to a health care facility via ambulance. This rate is calculated by dividing the number of individuals transferred by ambulance to a medical facility by the total number of attendees in the mass gathering, often expressed as per 1,000 attendees. Reference Gutman, Lund and Turris31,Reference Lund and Turris41 The ATR is an important metric in assessing the need for Emergency Medical Services and the overall health and safety considerations during large events. It provides insights into the demand for ambulance services, the severity of incidents, and the effectiveness of medical response strategies in the context of mass gatherings.

Medical Center to Hospital (METH)—The METH metric refers to individuals who, after receiving on-site medical services at a medical center or medical station located at an event, are transferred to a hospital for further medical treatment. The rate of METH is calculated by dividing the number of individuals evacuated to the hospital by the total number of cases or individuals. Reference Bortolin, Ulla and Bono19 Similar to ATR, METH provides the rate of patients transported by ambulance; however, METH is usually presented as a percentage.

Mutual Aid Request Rate (MARR)—In general terms, mutual aid refers to cooperation and assistance provided by one organization or group to another, often in emergency or challenging situations. The MARR represents the rate of mutual aid requests made during a mass gathering, and it is defined as the ratio of patients transported to the hospital by ambulance, excluding ambulances stationed on campus for the event, to every 1,000 attendees. Reference Friedman, O’Connor and Munro27

Transport-to-Hospital Rate (TTHR)—The TTHR is a metric that measures the rate at which individuals are transported to a hospital after seeking emergency services or another health care unit in mass-gathering events. It is calculated by dividing the total number of patients transported to the hospital during the event by the overall number of attendees, and the result is often multiplied by a coefficient such as 10,000 for standardized reporting. Reference Arbon, Bridgewater and Smith17 Similar to METH and ATR, TTHR typically presents the rate of patients transported by ambulance and may not include patients who were transferred to the hospital using their own means. This rate, typically provided alongside PPR, is used to assess the severity of out-of-event health care services during mass-gathering events, to ensure patients’ access to appropriate treatment, and to allocate health resources effectively. Reference Scheers, Van Remoortel and Lauwers69 A high TTHR may indicate increased out-of-event health care services needs and more serious patient conditions in mass gatherings, implying a higher demand for emergency medical intervention. Conversely, a low TTHR suggests milder health issues and lower demand for out-of-event health care services.

Referral-to-Hospital Rate (RTHR)—Transport generally refers to the conveyance of an individual to a health care facility, typically facilitated by an ambulance. The TTHR specifically encompasses referrals to the hospital through ambulances, and it indicates how many individuals were transported to the hospital via ambulances during a mass-gathering event. Referral, on the other hand, signifies directing an individual to a more specialized health care unit or a specialized doctor, and it encompasses all methods. This includes individuals referred to the hospital by health care professionals, ambulance, or different methods. Reference Ranse and Hutton70 In this context, RTHR measures the frequency of individuals being referred to specialized health care services during mass gatherings, indicating the likelihood of referral based on incident severity. The calculation involves dividing the total hospital-referred patients by the overall attendee count during the event, and the outcome is frequently scaled by a coefficient like 10,000 for standardized reporting. Reference Crabtree, Mo and Ong24

Medical Transfer Rate (MTR)—The ATR specifically pertains to the frequency of emergency ambulance responses and transfers, specifically related to emergency calls, throughout the event. On the other hand, MTR comprises all external referrals, encompassing ambulance transfers and other forms of medical transportation. Reference Gutman, Lund and Turris31 To elaborate, the ATR is narrowly focused on the occurrence of emergency ambulance responses and subsequent transfers, whereas the MTR encompasses a broader spectrum of medical transfers, accounting for various modes of transportation that may not necessarily involve public ambulance services. In short, it can be said that it produces the same output as RTHR and encompasses all total referrals.

Discussion

Most articles on mass gatherings are inherently descriptive, and these studies often include rates related to venue-specific disease, injuries, and patient transfers. In this study, the rates and ratios reported in mass-gathering studies were examined and tried to be gathered in a framework. The 15 metrics obtained in this study help to evaluate the effectiveness of health care services, to understand the demand for emergency services, and to monitor the number of individuals seeking medical assistance during mass gatherings within a specific time frame. Reference Anikeeva, Arbon and Zeitz16 However, it is important to note that the interpretation of these metrics depends on the characteristics of the mass-gathering event, the organization of health care services, and other relevant factors.

Inconsistencies Detected in the Literature

Unfortunately, a review of the literature revealed inconsistencies among the reported rates and ratios, missing values in some metrics, and rates were represented by different terminologies. Many studies included values such as the number of injuries, deaths, and hospitalizations; however, many studies were also found that did not provide these values. Reference Hostettler-Blunier, Müller and Haltmeier34,Reference Thierbach, Wolcke and Piepho60,Reference Agar, Pickard and Bhangu71Reference Chan and Quinn73 In a study conducting a retrospective analysis of patient admissions over seven years, the number of attendees attending each year was provided, but the total number of attendees was not given. Moreover, PPR and TTHR values were provided on average, but they were not detailed for each specific year. Reference Zeitz, Schneider and Jarrett65 In addition, in a study conducted at six shopping malls in Ankara, Türkiye, it was reported that out of 4,634 treated patients, 189 were transported to the hospital by ambulance, and 299 patients were self-referred to hospitals. The fact that the TTHR value was provided while the RTHR value was not given is noteworthy. Reference Ceyhan and Demir22

In the methods section of a study conducted at an outdoor music concert, the MUR was stated to be calculated per thousand attendees, but it was presented as PPTT in the results section. Moreover, it is noteworthy that while the total transport numbers were available, the calculation of TTHR was not conducted. Reference Westrol, Koneru and Mcintyre63 Even though Ussahgij’s study was recent, it did not provide a value commonly found in the literature, such as MUR or PPR. Instead, the USFMP ratio was utilized for a study conducted at a sports event. Moreover, despite reporting that two individuals were admitted to the hospital, no ratios such as TTHR or MTR had been provided. Reference Ussahgij, Kotruchin and Osotthanakorn62 In the findings of another study conducted at a large university stadium, it was written that the injury/illness rate in 1983 was 29.5 per 10,000 attendees, but in the table, this rate was shown as 2.95. Reference Spaite, Meislin and Valenzuela58

Recommendation for Standardization

Although various names were used for rates and ratios in the literature, they essentially calculated the same things. However, the use of different names for these rates and the lack of values for some metrics may hinder standardization and complicate the comparison of studies. For example, PPR and MUR have often been used interchangeably in the literature. At this point, it should be noted that PPR may be limited to medical service presentations, and may not encompass first aid presentations. Therefore, if the data are appropriate, PPR should be presented separately from the first aid rate (FAR), and their sum should constitute MUR (FAR + PPR = MUR). The same issue existed in the ratios used for the evaluation of out-of-event health services. While METH, ATR, and TTHR typically indicate the ratio of patients transported by ambulance, they may not include patients transported to the hospital by their own means. The MARR, on the other hand, also indicates the ratio of patients transported by ambulance, but it signifies collaboration and assistance provided from one organization or group to another. Both MTR and RTHR encompass a wider range of medical transfers by considering various modes of transportation, which may not necessarily include ambulance services. At this point, it would be more understandable to report separately the patients transported by ambulance, those directed to the hospital by their own means, and the total number of transfers. Therefore, patients transported by ambulance should be given as TTHR, patients directed to the hospital should be given as RTHR, and the total transfer should be given as MTR (TTHR + RTHR = MTR). The MARR is not widely used in the literature, however, if available, this ratio should also be added to the MTR.

Another crucial point for standardization is the necessity of expressing ratios per how many attendees. Essentially, this situation can vary based on the number of attendees. For instance, in an event with 10,000 attendees, the PPR may appear smaller when expressed as a percentage but larger when expressed per 10,000. Therefore, ratios can be multiplied by 100, 1,000, or 10,000 to make them more understandable and comparable, allowing for easier comparison of different events or situations. Upon examining studies in the literature, it was observed that PPR values were often given using a coefficient of 1,000, Reference Alassaf13,Reference Ceyhan, Demir and Güler21,Reference Zeitz, Zeitz and Arbon66 but some researchers used 10,000 instead. Reference Locoh-Donou, Yan and Berry39,Reference Milsten, Bradley and Hill45,Reference Milsten and Ness46 Similarly, from the perspective of TTHR, a coefficient of 1,000 was predominantly used, Reference Arbon, Bridgewater and Smith17,Reference Chang, Chang and Huang23,Reference Imbriaco, Flauto and Bussolari35,Reference Zeitz, Schneider and Jarrett65 but some researchers used 10,000 instead. Reference Goldberg, Battistini and Cash29,Reference Hardcastle, Samlal and Naidoo32,Reference Milsten, Tennyson and Weisberg44 In addition, MUR was generally presented as PPR in the literature. However, some studies referred only to MUR without using PPR. Some studies reported MUR per 10,000 attendees Reference Burton, Corry and Lewis20,Reference Milsten, Seaman and Liu43,Reference Milsten, Tennyson and Weisberg44,Reference Ussahgij, Kotruchin and Osotthanakorn62Reference Yazawa, Kamijo and Sakai64 while others reported it per 1,000 attendees, Reference Hostettler-Blunier, Müller and Haltmeier34 and yet others presented it as a percentage. Reference Piat, Minniti and Traversi50 In light of this information, especially when documenting multiple studies conducted in the past, it is crucial to accurately report rates that vary based on the number of attendees. For example, if in one study the PPR value is five per 1,000 attendees, and in another study it is ten per 10,000 people, stating that the PPR value ranges from five to ten would be incorrect. It is necessary to specify that the PPR varies between one-to-five per 1,000 attendees or 10-50 per 10,000 attendees. As a result, taking the coefficient as 1,000 or 10,000 does not pose a problem; however, the coefficient value must be reported accurately, and caution should be exercised when making comparisons.

As a result, many studies lacked clear statements regarding the number of attendees, failed to provide rates for patient presentations and total transfers, and reported rates under different names. This situation makes it challenging to compare between studies, leads to incomplete or inconsistent data, and results in a lack of overall standardization. Therefore, to facilitate comparability between studies and ensure standardization, the use of the Metrics and Essential Ratios for Gathering Events (MERGE) table is recommended, which has been developed by including the minimum information that needs to be reported (Table 3). The MERGE table should minimally include VAR, FAR, PPR, MUR, TTHR, RTHR, MTR, and mortality rates. Although PDR is a value commonly reported in mass-gathering events, it is not included in the MERGE table. It would be more sensible to present a separate table containing PDR values related to injuries and illnesses.

Table 3. Metrics and Essential Ratios for Gathering Events (MERGE) Table

Abbreviations: FAR, first aid rate; MTR, medical transport rate; MUR, medical usage rate; PPR, patient presentation rate; RTHR, referral-to-hospital rate; TTHR, transport-to-hospital rate; VAR, venue accommodation rate.

a Patient per 10,000.

b Patient per 100,000.

The MERGE table developed in this study may not be universally applicable to every mass-gathering event, but it serves as a starting point to promote standardization in data reporting. It is essential to adapt this table to the specific characteristics of the mass-gathering events. For instance, consider a flash mob event organized in a public square, where attendees assemble suddenly and briefly perform a coordinated action before dispersing. In such spontaneous events, accurately estimating the total number of attendees can be challenging due to the rapid and unpredictable nature of the gathering. Therefore, some changes can be made to the table based on the number and type of incidents. In addition, presenting values related to personnel, materials, and equipment usage will also enrich the table. The number of attendees for each metric given in the table should be shown below it.

Limitations

This study is subject to certain limitations, as is common in most reviews. Firstly, there is no specific protocol or record outlining the inclusion criteria and analysis methods employed in this study. Additionally, the effectiveness of the selected keywords and the potential exclusion of relevant articles may have impacted the comprehensiveness of the review. Finally, the study is confined to open-access and English language literature, thereby not encompassing all potential articles published on the research topic.

Conclusion

The extensive analysis of 55 relevant studies spanning from 1990 through 2023 provides nuanced insights into the health dynamics associated with mass gatherings. Density metrics assist in proactive resource planning and crowd density management, while in-event health service metrics help assess health care demand and tailor services to prevalent health issues. Out-of-event health service metrics provide critical information regarding the severity of incidents and the demand for Emergency Medical Services. As the growth of mass-gathering events continues to be witnessed, these metrics serve as a foundation for future research and the development of effective health management strategies in mass-gathering settings. However, it has been observed in the literature that various terminologies and percentage expressions are used for similar ratios. To facilitate meaningful comparisons in future research, standardization is crucial. The MERGE table provided in this study serves as an example of a framework for standardizing reporting, emphasizing the need for a unified approach. This standardization would not only enhance the consistency of reporting, but it would also foster a more cohesive understanding of health metrics in mass gatherings across diverse studies.

Conflicts of interest

None declared.

Author Contributions

CC: Conceptualization, methodology, project administration, supervision. ADK: Resources, investigation, formal analysis, writing - review & editing, writing - original draft. TÖ: Resources, investigation, formal analysis, writing - review & editing, writing - original draft. ND: Resources, investigation, writing - review & editing, writing - original draft. KK: Conceptualization, methodology, project administration, supervision.

Supplementary Materials

To view supplementary material for this article, please visit https://doi.org/10.1017/S1049023X2400027X

References

Koçak, H, Tuncay, İ. Evaluation of trauma cases in different types of mass gathering events. Ulus Travma Acil Cerrahi Derg. 2022;28(6):781789.Google ScholarPubMed
World Health Organization. Public health for mass gatherings: key considerations. 2015. https://www.who.int/publications-detail-redirect/public-health-for-mass-gatherings-key-considerations. Accessed November 22, 2023.Google Scholar
Yezli, S, Alotaibi, B. Mass gatherings and mass gatherings health. Saudi Med J. 2016;37(7):729730.CrossRefGoogle ScholarPubMed
Memish, ZA, Steffen, R, White, P, et al. Mass gatherings medicine: public health issues arising from mass gathering religious and sporting events. Lancet. 2019;393(10185):20732084.CrossRefGoogle ScholarPubMed
Aitsi-Selmi, A, Murray, V, Heymann, D, et al. Reducing risks to health and wellbeing at mass gatherings: the role of the Sendai Framework for Disaster Risk Reduction. Int J Infect Dis. 2016;47:101104.CrossRefGoogle ScholarPubMed
Sharma, U, Desikachari, BR, Sarma, S. Protocol for development of a risk assessment tool for planning and management of religious mass-gathering events of India—a health system-strengthening initiative. Pilot Feasibility Stud. 2019;5(1):83.CrossRefGoogle ScholarPubMed
Milsten, AM, Maguire, BJ, Bissell, RA, et al. Mass-gathering medical care: a review of the literature. Prehosp Disaster Med. 2002;17(3):151162.CrossRefGoogle ScholarPubMed
De Lorenzo, RA. Mass gathering medicine: a review. Prehosp Disaster Med. 1997;12(1):6872.CrossRefGoogle ScholarPubMed
Van Remoortel, H, Scheers, H, De Buck, E, et al. Prediction modelling studies for medical usage rates in mass gatherings: a systematic review. PLoS One. 2020;15(6):e0234977.CrossRefGoogle ScholarPubMed
Whittemore, R, Knafl, K. The integrative review: updated methodology. J Adv Nurs. 2005;52(5):546553.CrossRefGoogle ScholarPubMed
Hong, QN, Fàbregues, S, Bartlett, G, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information. 2018;34(4):285291.CrossRefGoogle Scholar
Kuday, AD, Özcan, T, Çalışkan, C, et al. Challenges faced by medical rescue teams during disaster response: a systematic review study. Disaster Med Public Health Prep. 2023;17:e548.CrossRefGoogle ScholarPubMed
Alassaf, WI. EMS Coverage of a female-only event with 10,000 attendees: preparation and implementation in one week. Prehosp Disaster Med. 2017;32(6):694698.CrossRefGoogle ScholarPubMed
Allen, TL, Jolley, SJ, Cooley, VJ, et al. The epidemiology of illness and injury at the alpine venues during the Salt Lake City 2002 Winter Olympic Games. J Emerg Med. 2006;30(2):197202.CrossRefGoogle Scholar
Allgaier, RL, Shaafi-Kabiri, N, Romney, CA, et al. Use of predictive modeling to plan for special event medical care during mass gathering events. Disaster Med Public Health Prep. 2019;13(5-6):874879.CrossRefGoogle ScholarPubMed
Anikeeva, O, Arbon, P, Zeitz, K, et al. Patient presentation trends at 15 mass-gathering events in South Australia. Prehosp Disaster Med. 2018;33(4):368374.CrossRefGoogle ScholarPubMed
Arbon, P, Bridgewater, FH, Smith, C. Mass gathering medicine: a predictive model for patient presentation and transport rates. Prehosp Disaster Med. 2001;16(3):150158.CrossRefGoogle ScholarPubMed
Bock, HC, Cordell, WH, Hawk, AC, et al. Demographics of emergency medical care at the Indianapolis 500-mile race (1983-1990). Ann Emerg Med. 1992;21(10):12041207.CrossRefGoogle ScholarPubMed
Bortolin, M, Ulla, M, Bono, A, et al. Holy shroud exhibition 2010: health services during a 40-day mass-gathering event. Prehosp Disaster Med. 2013;28(3):239244.CrossRefGoogle ScholarPubMed
Burton, JO, Corry, SJ, Lewis, G, et al. Differences in medical care usage between two mass-gathering sporting events. Prehosp Disaster Med. 2012;27(5):458462.CrossRefGoogle ScholarPubMed
Ceyhan, MA, Demir, GG, Güler, GB. Evaluation of health care services provided in political public meetings in Turkey: a forgotten detail in politics. Prehosp Disaster Med. 2018;33(6):607613.CrossRefGoogle Scholar
Ceyhan, MA, Demir, GG. Health care services in shopping centers: a routine mass-gathering event. Prehosp Disaster Med. 2020;35(6):669675.CrossRefGoogle Scholar
Chang, WH, Chang, KS, Huang, CS, et al. Mass gathering emergency medicine: a review of the Taiwan experience of long-distance swimming across Sun-Moon Lake. Int J Gerontol. 2010;4(2):5368.CrossRefGoogle Scholar
Crabtree, N, Mo, S, Ong, L, et al. Retrospective analysis of patient presentations at the Sydney (Australia) Royal Easter Show from 2012 to 2014. Prehosp Disaster Med. 2017;32(2):187194.CrossRefGoogle ScholarPubMed
Dutch, MJ, Senini, LM, Taylor, DJ. Mass gathering medicine: the Melbourne 2006 Commonwealth Games experience. Emerg Med Australas. 2008;20(3):228233.CrossRefGoogle ScholarPubMed
Friedman, MS, Plocki, A, Likourezos, A, et al. A prospective analysis of patients presenting for medical attention at a large electronic dance music festival. Prehosp Disaster Med. 2017;32(1):7882.CrossRefGoogle Scholar
Friedman, NMG, O’Connor, EK, Munro, T, et al. Mass-gathering medical care provided by a collegiate-based first response service at an annual college music festival and campus-wide celebration. Prehosp Disaster Med. 2019;34(1):2529.CrossRefGoogle ScholarPubMed
Goldberg, SA, Maggin, J, Molloy, MS, et al. The Gillette Stadium experience: a retrospective review of mass gathering events from 2010 to 2015. Disaster Med Public Health Prep. 2018;12(6):752758.CrossRefGoogle ScholarPubMed
Goldberg, SA, Battistini, V, Cash, RE, et al. A retrospective review of out of hospital cardiac arrest at Gillette Stadium: 10 years of experience at a large sports venue. Resusc Plus. 2023;14.Google Scholar
Grant, WD, Nacca, NE, Prince, LA, et al. Mass-gathering medical care: retrospective analysis of patient presentations over five years at a multi-day mass gathering. Prehosp Disaster Med. 2010;25(2):183187.CrossRefGoogle Scholar
Gutman, SJ, Lund, A, Turris, SA. Medical support for the 2009 world police and fire games: a descriptive analysis of a large-scale participation event and its impact. Prehosp Disaster Med. 2011;26(1):3339.CrossRefGoogle Scholar
Hardcastle, TC, Samlal, S, Naidoo, R, et al. A redundant resource: a pre-planned casualty clearing station for a FIFA 2010 stadium in Durban. Prehosp Disaster Med. 2012;27(5):409415.CrossRefGoogle ScholarPubMed
Ho, WH, Koenig, KL, Quek, LS. Formula one night race in Singapore: a 4-year analysis of a planned mass gathering. Prehosp Disaster Med. 2014;29(5):489493.CrossRefGoogle Scholar
Hostettler-Blunier, S, Müller, N, Haltmeier, T, et al. Public medical preparedness at the “Swiss Wrestling and Alpine Games 2013”: descriptive analysis of 1,533 patients treated at the largest 3-day sporting event in Switzerland. Emerg Med Int. 2017;2017:9162095.CrossRefGoogle ScholarPubMed
Imbriaco, G, Flauto, A, Bussolari, T, et al. Mass gathering emergency medicine organization for the Union of European Football Associations’ under-21 championship 2019 in Bologna, Italy. Disaster Med Public Health Prep. 2022;16(1):405408.CrossRefGoogle ScholarPubMed
Johnsson, KMC, Örtenwall, PA, Kivi, ALH, et al. Medical support during the European Union Summit in Gothenburg, Sweden, June 2001. Prehosp Disaster Med. 2006;21(4):282285.CrossRefGoogle ScholarPubMed
Koçak, H, Çalışkan, C, Sönmezler, , et al. Analysis of medical responses in mass gatherings: the commemoration ceremonies for the 100th anniversary of the Battle of Gallipoli. Prehosp Disaster Med. 2018;33(3):288292.CrossRefGoogle ScholarPubMed
Kocak, H, Tuncay, I. Comparison of emergency medical services cases in different types of mass gathering events held between 2015-2018 in Turkey. Eurasian J Emerg Med. 2022;21(2):9399.CrossRefGoogle Scholar
Locoh-Donou, S, Yan, G, Berry, T, et al. Mass gathering medicine: event factors predicting patient presentation rates. Intern Emerg Med. 2016;11(5):745752.CrossRefGoogle ScholarPubMed
Lonnee, M, Andersen, KG, Stagelund, S, et al. Use of medical supplies at the Roskilde Festival 2016: a prospective observational study. Prehosp Disaster Med. 2021;36(3):306312.CrossRefGoogle ScholarPubMed
Lund, A, Turris, SA. Mass-gathering medicine: risks and patient presentations at a 2-day electronic dance music event. Prehosp Disaster Med. 2015;30(3):271278.CrossRefGoogle Scholar
Maleczek, M, Rubi, S, Fohringer, C, et al. Medical care at a mass gathering music festival: retrospective study over 7 years (2011-2017). Wien Klin Wochenschr. 2022;134(7-8):324331.CrossRefGoogle Scholar
Milsten, AM, Seaman, KG, Liu, P, et al. Variables influencing medical usage rates, injury patterns, and levels of care for mass gatherings. Prehosp Disaster Med. 2003;18(4):334346.CrossRefGoogle ScholarPubMed
Milsten, AM, Tennyson, J, Weisberg, S. Retrospective analysis of mosh-pit-related injuries. Prehosp Disaster Med. 2017;32(6):636641.CrossRefGoogle ScholarPubMed
Milsten, A, Bradley, WF, Hill, M, et al. Foul ball rates and injuries at Major League Baseball games: a retrospective analysis of data from three stadiums. Prehosp Disaster Med. 2022;37(2):277283.CrossRefGoogle Scholar
Milsten, A, Ness, J. Hockey puck strike rates and injuries at National Hockey League games: a retrospective analysis of data from six seasons. Prehosp Disaster Med. 2022;37(3):397400.CrossRefGoogle Scholar
Morimura, N, Katsumi, A, Koido, Y, et al. Analysis of patient load data from the 2002 FIFA World Cup Korea/Japan. Prehosp Disaster Med. 2004;19(3):278284.CrossRefGoogle ScholarPubMed
Munn, MB, Lund, A, Golby, R, et al. Observed benefits to on-site medical services during an annual 5-day electronic dance music event with harm reduction services. Prehosp Disaster Med. 2016;31(2):228234.CrossRefGoogle ScholarPubMed
Pakravan, AH, West, RJ, Hodgkinson, DW. Suffolk Show 2011: prehospital medical coverage in a mass-gathering event. Prehosp Disaster Med. 2013;28(5):529532.CrossRefGoogle Scholar
Piat, SC, Minniti, D, Traversi, D, et al. Torino 2006 Winter Olympic Games: highlight on health services organization. J Emerg Med. 2010;39(4):454461.CrossRefGoogle ScholarPubMed
Rabb, H, Coleby, J. Hurt on the hill: a longitudinal analysis of obstacle course racing injuries. Orthop J Sports Med. 2018;6(6):2325967118779854.CrossRefGoogle Scholar
Rajakrishnan, S, Hafiz Ismail, MZ, Jamalulail, SH, et al. Investigation of a foodborne outbreak at a mass gathering in Petaling District, Selangor, Malaysia. Western Pac Surveill Response J. 2022;13(1):15.CrossRefGoogle Scholar
Sabra, JP, Cabañas, JG, Bedolla, J, et al. Medical support at a large-scale motorsports mass-gathering event: the inaugural formula one united states grand prix in Austin, Texas. Prehosp Disaster Med. 2014;29(4):392398.CrossRefGoogle Scholar
Spaepen, K, Haenen, WAP, Kaufman, L, et al. Validation of a Belgian prediction model for patient encounters at music mass gatherings. Prehosp Disaster Med. 2020;35(5):561566.CrossRefGoogle ScholarPubMed
Spaepen, K, Arno, G, Kaufman, L, et al. Validation of a Belgian prediction model for patient encounters at Belgium’s largest public cultural mass gathering. Disaster Med Public Health Prep. 2022;16(3):11281133.CrossRefGoogle ScholarPubMed
Spaepen, K, Lauwaert, D, Kaufman, L, et al. Validation of a Belgian prediction model for patient encounters at football mass gatherings. Prehosp Disaster Med. 2021;36(6):724729.CrossRefGoogle ScholarPubMed
Spaepen, K, Cardinas, R, Haenen, WAP, et al. The impact of in-event health services at Europe’s largest electronic dance music festival on EMS and ED in the host community. Int J Environ Res Public Health. 2023;20(4):3207.CrossRefGoogle ScholarPubMed
Spaite, DW, Meislin, HW, Valenzuela, TD, et al. Banning alcohol in a major college stadium: impact on the incidence and patterns of injury and illness. J Am Coll Health Assoc. 1990;39(3):125128.CrossRefGoogle Scholar
Tajima, T, Takazawa, Y, Yamada, M, et al. Spectator medicine at an international mega sports event: Rugby World Cup 2019 in Japan. Environ Health Prev Med. 2020;25(1):72.CrossRefGoogle ScholarPubMed
Thierbach, AR, Wolcke, BB, Piepho, T, et al. Medical support for children’s mass gatherings. Prehosp Disaster Med. 2003;18(1):1419.CrossRefGoogle ScholarPubMed
Turris, SA, Callaghan, CW, Rabb, H, et al. On the way out: an analysis of patient transfers from four large-scale north American music festivals over two years. Prehosp Disaster Med. 2019;34(1):3845.CrossRefGoogle ScholarPubMed
Ussahgij, W, Kotruchin, P, Osotthanakorn, P, et al. Analysis of medical interventions at the Start-Finish Medical Post of an international running event in rural Thailand. Prehosp Disaster Med. 2022;37(1):8489.CrossRefGoogle ScholarPubMed
Westrol, MS, Koneru, S, Mcintyre, N, et al. Music genre as a predictor of resource utilization at outdoor music concerts. Prehosp Disaster Med. 2017;32(3):289296.CrossRefGoogle ScholarPubMed
Yazawa, K, Kamijo, Y, Sakai, R, et al. Medical care for a mass gathering: the Suwa Onbashira festival. Prehosp Disaster Med. 2007;22(5):431435.CrossRefGoogle ScholarPubMed
Zeitz, KM, Schneider, DPA, Jarrett, D, et al. Mass gathering events: retrospective analysis of patient presentations over seven years. Prehosp Disaster Med. 2002;17(3):147150.CrossRefGoogle ScholarPubMed
Zeitz, KM, Zeitz, CJ, Arbon, P. Forecasting medical work at mass-gathering events: predictive model versus retrospective review. Prehosp Disaster Med. 2005;20(3):164168.CrossRefGoogle ScholarPubMed
Zeitz, K, Haghighi, PD, Burstein, F, et al. Understanding the drivers on medical workloads: an analysis of spectators at the Australian Football League. Australian Health Review. 2013;37(3):402406.CrossRefGoogle ScholarPubMed
Arbon, P. The development of conceptual models for mass-gathering health. Prehosp Disaster Med. 2004;19(3):208212.CrossRefGoogle ScholarPubMed
Scheers, H, Van Remoortel, H, Lauwers, K, et al. Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model. BMC Public Health. 2022;22(1):173.CrossRefGoogle ScholarPubMed
Ranse, J, Hutton, A. Minimum data set for mass-gathering health research and evaluation: a discussion paper. Prehosp Disaster Med. 2012;27(6):543550.CrossRefGoogle ScholarPubMed
Agar, C, Pickard, L, Bhangu, A. The tough guy prehospital experience: patterns of injury at a major UK endurance event. Emerg Med J. 2009;26(11):826830.CrossRefGoogle Scholar
Wetterhall, SF, Coulombier, DM, Herndon, JM, et al. Medical care delivery at the 1996 Olympic games. JAMA. 1998;279(18):14631468.CrossRefGoogle ScholarPubMed
Chan, SB, Quinn, JE. Outcomes in EMS-transported attendees from events at a large indoor arena. Prehosp Emerg Care. 2003;7(3):332335.CrossRefGoogle Scholar
Figure 0

Figure 1. Flow Diagram of Study Identification and Selection Process.

Figure 1

Table 1. Characteristics of the Included Articles

Figure 2

Table 2. Formulas for the Metrics Used in Mass-Gathering Events

Figure 3

Table 3. Metrics and Essential Ratios for Gathering Events (MERGE) Table

Supplementary material: File

Çalışkan et al. supplementary material 1

Çalışkan et al. supplementary material
Download Çalışkan et al. supplementary material 1(File)
File 20.4 KB
Supplementary material: File

Çalışkan et al. supplementary material 2

Çalışkan et al. supplementary material
Download Çalışkan et al. supplementary material 2(File)
File 28.3 KB