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The Impact of Mass Gatherings on Emergency Department Patient Presentations with Communicable Diseases Related to Syndromic Indicators: An Integrative Review

Published online by Cambridge University Press:  19 February 2020

Yunjing (Shirley) Qiu Open the ORCID record for Yunjing (Shirley) Qiu [Opens in a new window] ,
Julia Crilly ,
Peta-Anne Zimmerman  and
Jamie Ranse
Yunjing (Shirley) Qiu*
Affiliation:
School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia
Julia Crilly
Affiliation:
School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia Department of Emergency Medicine, Gold Coast Health, Gold Coast, Queensland, Australia
Peta-Anne Zimmerman
Affiliation:
School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia Department of Infection Control, Gold Coast Health, Gold Coast, Queensland, Australia
Jamie Ranse
Affiliation:
School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia Department of Emergency Medicine, Gold Coast Health, Gold Coast, Queensland, Australia
*
Correspondence: Yunjing Qiu, RN, School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia, E-mail: shirley.shirley28@gmail.com
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Abstract

Background:

Mass-gathering events (MGEs) are commonly associated with a higher than average rate of morbidity. Spectators, workers, and the substantial number of MGE attendees can increase the spread of communicable diseases. During an MGE, emergency departments (EDs) play an important role in offering health care services to both residents of the local community and event attendees. Syndromic indicators (SIs) are widely used in an ED surveillance system for early detection of communicable diseases.

Aim:

This literature review aimed to develop an understanding of the effect of MGEs on ED patient presentations with communicable diseases and their corresponding SIs.

Method:

An integrative literature review methodology was used. Online databases were searched to retrieve relevant academic articles that focused on MGEs, EDs, and SIs. Inclusion/exclusion criteria were applied to screen articles. The Standard Quality Assessment Criteria for Evaluating Primary Research (QualSyst) assessment tool was used to assess the quality of included papers.

Results:

Eleven papers were included in this review; all discussed the impact of an MGE on patient presentations with communicable diseases at EDs/hospitals. Most included studies used the raw number of patients who presented or were admitted to EDs/hospitals to determine impact. Further, the majority of studies focused on either respiratory infections (n = 4) or gastrointestinal infections (n = 2); two articles reported on both. Eight articles mentioned SIs; however, such information was limited. The quality of evidence (using QualSyst) ranged from 50% to 90%.

Conclusions:

Limited research exists on the impact of MGEs on ED presentations with communicable diseases and related SIs. Recommendations for future MGE studies include assessing differences in ED presentations with communicable diseases regarding demographics, clinical characteristics, and outcomes before, during, and after the event. This would benefit health care workers and researchers by offering more comprehensive knowledge for application into practice.

Keywords

communicable diseaseemergency departmentmass gathering
Type
Systematic Review
Information
Prehospital and Disaster Medicine , Volume 35 , Issue 2 , April 2020 , pp. 206 - 211
Copyright
© World Association for Disaster and Emergency Medicine 2020

Background

Mass-gathering events (MGEs) refer to large events that frequently occur internationally and can include sports tournaments, music festivals, and religious activities. ArbonReference Arbon1 defines MGEs as events that can attract many people gathering in one place during a specific period for the same purpose, which may delay the response of health services to emergency situations due to limited access to patients or the location of event(s). Given the number of MGE attendees can range from 1,000Reference Locoh-Donou, Yan and Berry2 to 8.8 million,Reference Gautret and Steffen3 it is essential to understand the potential effects on emergency health care services.

Health services available for participants of MGEs include in-event health services, such as first aid and/or medical tents, and external health services, such as local ambulance services and hospitals.Reference Ranse, Hutton and Keene4 Emergency departments (EDs) play an important role not only in offering health care services to residents of the local community and visitors, but in managing the increased health demand from MGE attendees.Reference Turris and Lund5 A systematic review by Ranse, et alReference Ranse, Hutton and Keene4 reported the number of patients transported to EDs can range from one to 190 during an MGE. Emergency departments already confronted by issues of over-crowding may struggle to cope with managing the possible increase in patient load during MGEsReference Lowthian, Curtis, Jolley, Stoelwinder, McNeil and Cameron6,Reference Welzel, Koenig, Bey and Visser7 if plans are not in place for practical prevention measures to mitigate the workload. These considerations are required alongside understanding characteristics of the event, such as the nature of the event (planned/unplanned), the demographic characteristics of event attendees (young/old), and possible influencing confounders, such as if alcohol is sold at the event and the weather.

Public health structures and personnel play a key role in the planning, detection, and monitoring of potential health threats during MGEs to prevent outbreaks of communicable disease, therefore limiting the impact on EDs.Reference Colón-González, Lake, Morbey, Elliot, Pebody and Smith8 Emergency department sentinel surveillance systems can be operationalized during MGEs (and at other times) to assist with this monitoring by using a wide-range of syndromic indicators (SIs). Syndromic indicators refer to a specific set of signs and symptoms (such as influenza-like illness) used to capture abnormal health events (such as thunderstorm asthma or communicable disease outbreaks).Reference Morbey, Elliot, Charlett, Verlander, Andrews and Smith9

At MGEs, the surge in the local population and the concentration of people may increase the spread of communicable diseases, which can place a strain on local emergency health care services.Reference Gautret and Steffen3,Reference Elliot, Hughes and Hughes10 Communicable diseases can result from infectious agents, such as human immunodeficiency virus (HIV) and measles, are contagious, and can be transferred from person-to-person.11 While research has emerged regarding outbreaks of communicable diseases,Reference Gautret and Steffen3,Reference Abubakar, Gautret and Brunette12,Reference Memish, Zumla and Alhakeem13 the characteristics of ED presentations, and the use of ED resources during MGEs,Reference Ranse, Hutton and Keene4,Reference DeMott, Hebert, Novak, Mahmood and Peksa14 there is sparse literature regarding the impact of MGEs on ED presentations with communicable diseases related to SIs.

By examining current academic literature, this review aims to answer the question: What is the impact of an MGE on ED patient presentations with communicable diseases related to SIs?

Methods

Design

This literature review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statementReference Liberati, Altman and Tetzlaff15 and followed Whittemore and Knafl’sReference Whittemore and Knafl16 methodology for conducting integrative reviews.

Data Collection

Online databases MEDLINE (Medical Literature Analysis and Retrieval System Online; US National Library of Medicine, National Institutes of Health; Bethesda, Maryland USA); CINAHL (Cumulative Index to Nursing and Allied Health Literature; EBSCO Information Services; Ipswich, Massachusetts USA); PubMed (National Center for Biotechnology Information; Bethesda, Maryland USA); EBSCO (EBSCO Information Services; Ipswich, Massachusetts USA); and ProQuest (ProQuest LLC; Ann Arbor, Michigan) were used to search available literature, limited to the 10-year period between 2008 and 2018. The keywords listed in Table 1 were used to locate and obtain peer-reviewed academic papers, published in the English language, that were related to the question. The linking word “or” was used between keywords listed in each row, while “and” was used between keywords listed in each column. The inclusion and exclusion criteria for the review are presented in Table 2.

Table 1. Keywords and MeSH Terms used in Article Selection

Abbreviations: ICD-10, International Classification of Diseases 10th Revision; MeSH, Medical Subject Heading.

Table 2. Inclusion and Exclusion Criteria

Abbreviations: ED, emergency department; MGE, mass-gathering event.

After title and abstract screening (YQ), full-text articles were retrieved and reviewed for relevance (YQ). References of related articles were also screened for additional relevant papers. Clarification of article inclusions (when required) was made with other authors (JR, PAZ, and JC). The PRISMA Guidelines, checklist, and flow diagramReference Liberati, Altman and Tetzlaff15 were used to guide the article inclusion process.

Data Analysis

Data extracted from included studies and entered into a Microsoft Word (Microsoft Corp.; Redmond, Washington USA) table were: author, MGE type, MGE location, duration of the MGE, the number of MGE attendees, study design, level of evidence, study aim, reported communicable diseases, related SIs, key findings, and limitations. The Standard Quality Assessment Criteria for Evaluating Primary Research (QualSyst) assessment tool was used to determine the quality of the research reviewed.Reference Kmet, Lee and Cook17 Using the QualSyst assessment tool, the quality of each article was scored independently by two authors (YQ and PAZ) on a range from 0% to 100% where over 80% reflects strong quality; 71%-80% reflects good quality; 50%-70% reflect adequate quality; and less than 50% reflect limited quality.Reference Lee, Packer, Tang and Girdler18 The final score of each article was the sum of scores obtained from each question listed on the checklist for assessing the quality of studies divided by the total possible score.Reference Kmet, Lee and Cook17 A quality score of ≥50% was the threshold for articles to be included in this review.

Results

In total, 11 articles met the inclusion criteria and were included in this review (Table 3). The PRISMA flow diagram provides information on the number of articles excluded and included in each step, and the reason for exclusion (Figure 1). The QualSyst assessment quality score for the 11 included articles ranged from 50% to 90%, indicating adequate to strong levels of evidence (Table 3). Both independent reviewers assigned the same score to four papers with small discrepancies for the remaining seven papers. Articles that were assigned different scores were discussed by both reviewers reaching consensus on the final score of these articles.

Table 3. Summary of Literature on Communicable Disease in MGEs and the Impact on ED

Abbreviations: CD, communicable disease; ED, emergency department; LOE, level of evidence; MGE, mass-gathering event; NS, not specified; PPR, patient presentation rate; SIs, syndromic indicators.

Abbreviations: ED, emergency department; MGE, mass-gathering event; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Figure 1. PRISMA Flow Diagram, Adapted from Liberati, et al.Reference Liberati, Altman and Tetzlaff15

Communicable Diseases in Past MGEs

Within the 11 studies on MGEs and communicable diseases, the type of events included religious events (five studies), sporting events (four studies), and other outdoor MGEs (two studies). Specific to communicable diseases, seven studies discussed respiratory infections, one study discussed gastrointestinal infections, and another reported both respiratory and gastrointestinal communicable diseases. Two studies discussed neurological infection and zoonotic diseases separately.

Measurement of ED Activities during MGEs

Variation existed in the studies regarding the impact of MGEs on local hospitals. Eight studies reported a raw number of patients who presented or were admitted to EDs/hospitals, (ranging from three to 401),Reference Al-Lami, Al-Fatlawi and Bloland19,Reference Brockmann, Piechotowski and Bock-Hensley20 while the other three studies reported either the rate of patient presentations to EDs (0.005/1000)Reference Smith, Fulde and Hendry21 or hospital administration rate (3.6-102/1000).Reference Botelho-Nevers, Gautret, Benarous, Charrel, Felkai and Parola22,Reference Zepeda-Lopez, Perea-Araujo and Miliar-García23

Syndromic Indicators used in EDs for Communicable Diseases

Most studies (n = 7; 64%) mentioned the use of a surveillance system based on patients’ signs and symptoms. Of these seven studies, three presented specific syndromes (which included febrile, acute respiratory symptom, rash at least three days, and sore throat)Reference Zepeda-Lopez, Perea-Araujo and Miliar-García23-Reference Lim, Cutter, Lim, Ee, Wong and Tay25 for detecting communicable diseases, whereas the remaining four only briefly mentioned the role of SIs in the surveillance system during MGE periods.

Discussion

From the literature reviewed, despite a growing body of knowledge about MGEs, EDs, and SIs, there is a lack of evidence regarding the effects of MGEs on ED attendances with communicable diseases.

Communicable Diseases in Past MGEs

There is evident diversity in the type of communicable disease(s) that may occur during an MGE, which place certain challenges on the ED. With the influx of a large population and rapid population movement, MGEs greatly facilitate the transmission of communicable diseases.Reference Chowell, Nishiura and Viboud26 Of the 11 studies included in this review, respiratory and gastrointestinal communicable diseases were the most common type of communicable diseases reported. However, other uncommon communicable diseases such as Type B Neisseria meningitidis and Leptospirosis were also noted.Reference Brockmann, Piechotowski and Bock-Hensley20,Reference Cummiskey, Borrione, Bachl, Ergen and Pigozzi27 It is therefore essential to review communicable diseases that occur during MGEs to enhance ED syndromic surveillance systems.

Another challenge with communicable diseases evident from the literature reviewed is that they may have long incubation periods resulting in secondary communicable disease cases that are delayed in detection, and sometimes result in further transmission in other countries.Reference Botelho-Nevers, Gautret, Benarous, Charrel, Felkai and Parola22-Reference Chen, Kutty and Lowe24,Reference Grgicˇ-Vitek, Frelih and Ucakar28-Reference Verhoef, Duizer and Vennema30 Due to the immense scope for travel and advanced transportation technologies, the number of international participants at MGEs is gradually increasing world-wide.Reference David and Roy31,Reference Yanagisawa, Wada, Spengler and Sanchez-Pina32 Along with the growing number of foreign visitors, infectious pathogens can be carried by these international travelers to other countries within a few days, which requires considerable attention from the host and home countries.Reference David and Roy31,Reference Yanagisawa, Wada, Spengler and Sanchez-Pina32 This illustrates the importance of good history taking by medical and nursing staff, especially for people arriving in the ED who have recently travelled.

Measurement of ED Activities during MGEs

Variation exists in the literature regarding the impact of MGEs on EDs. While the hosting of an MGE can increase patient volumes in local EDs, sometimes by as much as 400 patients/day,Reference Al-Lami, Al-Fatlawi and Bloland19 the actual number, demographic, clinical characteristics, and outcomes of patients presenting to EDs tend to vary by the type of MGE. This information, although limited, may be helpful to inform the planning of future MGEs that are similar in nature. None of the included studies examined the impact on the ED over time (ie, before, during, and after the MGE) in terms of clinical characteristics or outcomes of ED presentations. The absence of more detailed information about actual ED presentations makes it difficult to prospectively determine the impact of MGEs on EDs and the resources required to care for this cohort, not only during the MGE, but potentially after the event proper has finished.

Syndromic Indicators used in EDs for Communicable Diseases

Syndromic indicators have been widely used in the emergency system for public health surveillance. Syndromic indicators are helpful to measure prospectively as they can predict the incidence of communicable diseases, as well as potential increases in health care resource requirements.Reference Malik, Gumel, Thompson, Strome and Mahmud33 Previous studies have reported some syndromes used to detect communicable diseases during MGEs, such as fever, rash, and abdominal pain, indicating diseases such as measles, influenza, and respiratory tract infections.Reference Zepeda-Lopez, Perea-Araujo and Miliar-García23-Reference Lim, Cutter, Lim, Ee, Wong and Tay25 However, information as to the exact SIs and corresponding diagnosis codes (ie, International Classification of Diseases 10th Revision [ICD-10]) used to detect the impact of communicable diseases on EDs in MGE is still very limited,Reference Smith, Fulde and Hendry21,Reference Verhoef, Duizer and Vennema30 which makes comparative research and recommendations for standardized prospective data collection difficult. Future research in this area is thus recommended to inform a minimum data set, as recommended by Ranse and Hutton.Reference Ranse and Hutton34

Limitations

This review only included peer-reviewed articles published in English. Therefore, some articles, such as media reports, academic forum discussion papers, and articles published in other languages were not included. The title and abstract of articles were screened by one author (as part of an honors thesis). Final clarifications regarding final articles included in this review were however made with another author (PAZ). Furthermore, the quality of included studies was assessed by two authors.

Conclusion

Few studies exist that identify the impact on EDs from communicable diseases that may emerge during MGEs. Various type of communicable diseases can arise during and after MGEs based on varying incubation periods. Research is also limited in noting specific syndromic symptoms, indicators, or standard diagnostic codes (ie, ICD-10) used in ED surveillance systems. As such, future research is needed that uses patient-level data to identify and evaluate the impact on EDs before, during, and after an MGE. This information will not only address gaps in current literature, but will also provide in-depth information on improving the performance and preparation of existing emergency care systems for future MGEs.

Conflicts of interest

none

References

Arbon, P. Mass-gathering medicine: a review of the evidence and future directions for research. Prehosp Disaster Med. 2007;22(2):131–135.10.1017/S1049023X00004507CrossRefGoogle ScholarPubMed
Locoh-Donou, S, Yan, G, Berry, T, et al. Mass gathering medicine: event factors predicting patient presentation rates. Intern Emerg Med. 2016;11(5):745–752.10.1007/s11739-015-1387-1CrossRefGoogle ScholarPubMed
Gautret, P, Steffen, R. Communicable diseases as health risks at mass gatherings other than Hajj: what is the evidence? Int J Infect Dis. 2016;47:46–52.10.1016/j.ijid.2016.03.007CrossRefGoogle ScholarPubMed
Ranse, J, Hutton, A, Keene, T, et al. Health service impact from mass gatherings: a systematic literature review. Prehosp Disaster Med. 2017;32(1):71–77.10.1017/S1049023X16001199CrossRefGoogle ScholarPubMed
Turris, SA, Lund, A. Triage during mass gatherings. Prehosp Disaster Med. 2012;27(5):531–535.10.1017/S1049023X12001446CrossRefGoogle ScholarPubMed
Lowthian, JA, Curtis, AJ, Jolley, DJ, Stoelwinder, JU, McNeil, JJ, Cameron, PA. Demand at the emergency department front door: 10-year trends in presentations. Med J Aust. 2012;196:128–132.10.5694/mja11.10955CrossRefGoogle ScholarPubMed
Welzel, TB, Koenig, KL, Bey, T, Visser, E. Effect of hospital staff surge capacity on preparedness for a conventional mass casualty event. West J Emerg Med. 2010;11(2):189–196.Google ScholarPubMed
Colón-González, FJ, Lake, IR, Morbey, RA, Elliot, AJ, Pebody, R, Smith, GE. A methodological framework for the evaluation of syndromic surveillance systems: a case study of England. BMC l Public Health. 2018;18(1):544–557.10.1186/s12889-018-5422-9CrossRefGoogle ScholarPubMed
Morbey, RA, Elliot, AJ, Charlett, A, Verlander, NQ, Andrews, N, Smith, GE. The application of a novel ‘rising activity, multi-level mixed effects, indicator emphasis’ (RAMMIE) method for syndromic surveillance in England. J Bioinform. 2015;31(22):3660–3665.Google ScholarPubMed
Elliot, AJ, Hughes, HE, Hughes, TC, et al. Establishing an emergency department syndromic surveillance system to support the London 2012 Olympic and Paralympic Games. Emerg Med J. 2012;29(12):954–960.10.1136/emermed-2011-200684CrossRefGoogle ScholarPubMed
World Health Organization. Communicable disease alert and response for mass gatherings: key considerations. http://www.who.int/csr/Mass_gatherings2.pdf. Published 2008. Accessed August 10, 2018.Google Scholar
Abubakar, I, Gautret, P, Brunette, GW, et al. Global perspectives for prevention of infectious diseases associated with mass gatherings. Lancet Infect Dis. 2012;12(1):66–74.10.1016/S1473-3099(11)70246-8CrossRefGoogle ScholarPubMed
Memish, ZA, Zumla, A, Alhakeem, RF, et al. Hajj: infectious disease surveillance and control. The Lancet. 2014;383(9934):2073–2082.10.1016/S0140-6736(14)60381-0CrossRefGoogle ScholarPubMed
DeMott, JM, Hebert, CL, Novak, M, Mahmood, S, Peksa, GD. Characteristics and resource utilization of patients presenting to the ED from mass gathering events. Am J Emerg Med. 2018;36(6):983–987.10.1016/j.ajem.2017.11.006CrossRefGoogle ScholarPubMed
Liberati, A, Altman, DG, Tetzlaff, J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):1–34.10.1016/j.jclinepi.2009.06.006CrossRefGoogle ScholarPubMed
Whittemore, R, Knafl, K. The integrative review: updated methodology. J Adv Nurs. 2005;52(5):546–553.10.1111/j.1365-2648.2005.03621.xCrossRefGoogle ScholarPubMed
Kmet, LM, Lee, RC, Cook, LS. Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Edmonton, Alberta, Canada: Alberta Heritage Foundation for Medical Research (AHFMR). AHFMR - HTA Initiative #13.Google Scholar
Lee, L, Packer, TL, Tang, SH, Girdler, S. Self-management education programs for age-related macular degeneration: a systematic review. Australas J Ageing. 2008;27(4):170–176.Google ScholarPubMed
Al-Lami, F, Al-Fatlawi, A, Bloland, P, et al. Pattern of morbidity and mortality in Karbala hospitals during Ashura mass gathering at Karbala, Iraq 2010. East Mediterr Health J. 2013;19(2):S13–S18.10.26719/2013.19.Supp2.S13CrossRefGoogle ScholarPubMed
Brockmann, S, Piechotowski, I, Bock-Hensley, O, et al. Outbreak of leptospirosis among triathlon participants in Germany, 2006. BMC Infect Dis. 2010;10(1):1–5.10.1186/1471-2334-10-91CrossRefGoogle ScholarPubMed
Smith, MWH, Fulde, GWO, Hendry, PM. World Youth Day 2008: did it stress Sydney hospitals? Med J Aust. 2008;189(11-12):630–632.CrossRefGoogle ScholarPubMed
Botelho-Nevers, E, Gautret, P, Benarous, L, Charrel, R, Felkai, P, Parola, P. Travel-related influenza A/H1N1 infection at a rock festival in Hungary: one virus may hide another one. J Travel Med. 2010;17(3):197–198.10.1111/j.1708-8305.2010.00410.xCrossRefGoogle Scholar
Zepeda-Lopez, HM, Perea-Araujo, L, Miliar-García, A, et al. Inside the outbreak of the 2009 influenza A (H1N1) virus in Mexico. PLoS One. 2010:5(10):e13256.10.1371/journal.pone.0013256CrossRefGoogle ScholarPubMed
Chen, TH, Kutty, P, Lowe, LE, et al. Measles outbreak associated with an international youth sporting event in the United States, 2007. Pediatr Infect Dis J. 2010;29(9):794–800.CrossRefGoogle ScholarPubMed
Lim, HC, Cutter, J, Lim, WK, Ee, A, Wong, YC, Tay, BK. The influenza A (H1N1-2009) experience at the inaugural Asian Youth Games Singapore 2009: mass gathering during a developing pandemic. Br J Sports Med. 2010;44(7):528–532.CrossRefGoogle ScholarPubMed
Chowell, G, Nishiura, H, Viboud, C. Modeling rapidly disseminating infectious disease during mass gatherings. BMC Med. 2012;10:159.10.1186/1741-7015-10-159CrossRefGoogle ScholarPubMed
Cummiskey, J, Borrione, P, Bachl, N, Ergen, E, Pigozzi, F. Report of a serious reportable communicable disease at a major sporting event. J Sports Med Phys Fitness. 2008:48(2):125–128.Google Scholar
Grgicˇ-Vitek, M, Frelih, T, Ucakar, V, et al. An outbreak of measles associated with an international dog show in Slovenia, November 2014. Euro Surveill. 2015;20(3):1–4.Google Scholar
Pfaff, G, Lohr, D, Santibanez, S, et al. Spotlight on measles 2010: measles outbreak among travelers returning from a mass gathering Germany, September to October 2010. Euro Surveill. 2010;15(50):1–4.Google Scholar
Verhoef, L, Duizer, E, Vennema, H, et al. Import of norovirus infections in the Netherlands and Ireland following pilgrimages to Lourdes, 2008: preliminary report. Euro Surveill. 2008;13(44):1–2.Google ScholarPubMed
David, S, Roy, N. Public health perspectives from the biggest human mass gathering on earth: Kumbh Mela, India. Int J Infect Dis. 2016;47:42–45.10.1016/j.ijid.2016.01.010CrossRefGoogle ScholarPubMed
Yanagisawa, N, Wada, K, Spengler, JD, Sanchez-Pina, R. Health preparedness plan for dengue detection during the 2020 summer Olympic and Paralympic games in Tokyo. PLoS Negl Trop Dis. 2018;12(9):e0006755.CrossRefGoogle ScholarPubMed
Malik, MT, Gumel, A, Thompson, LH, Strome, T, Mahmud, SM. “Google flu trends” and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba. Canadian Journal of Public Health. 2011;102(4):294–297.10.1007/BF03404053CrossRefGoogle Scholar
Ranse, J, Hutton, A. Minimum data set for mass gathering health research and evaluation: a discussion paper. Prehosp Disaster Med. 2012;27(6):543–550.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Keywords and MeSH Terms used in Article Selection

Figure 1

Table 2. Inclusion and Exclusion Criteria

Figure 2

Table 3. Summary of Literature on Communicable Disease in MGEs and the Impact on ED

Figure 3

Figure 1. PRISMA Flow Diagram, Adapted from Liberati, et al.15

Abbreviations: ED, emergency department; MGE, mass-gathering event; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.