Assessing pandemic era stadium events and infections using mobile phone based population mobility data: An exploratory study from Ireland,2021

Abstract

Mass gathering events (MGEs) attracting local, national, or international crowds presented particular challenges in the context of the coronavirus disease 2019 (COVID-19) pandemic. Sporting, religious, music and other cultural events held during the early months of the pandemic, without social distancing or other safeguards, have been regarded as so-called ‘super spreader’ events. By the summer of 2020, MGEs were generally banned or subject to severe restrictions. Regular European sporting fixtures such as England’s Football Association and Germany’s Bundesliga matches began to return in the autumn with protective measures in place, such as matches initially held behind closed doors, and later with sub-capacity crowd limits and mandatory social distancing [1, 2, 3, 4, 5].

With protective measures in place, and proof of COVID-19 vaccination or recovery required for entry, a series of six sporting MGEs, ‘the All-Ireland Finals’ were held in the Republic of Ireland’s largest stadium, Croke Park in Dublin, during August-September 2021. This study draws on a high-resolution human population mobility dataset to quantify journeys to/from the stadium area on MGE days by destination. The anonymised, aggregated, data used is based on mobile phone usage, and consists of a series of fine-grained geographical origin-destination matrices presenting daily estimates of area to area journey numbers. With mobility from the stadium area serving as a proxy for MGE attendance, this study explores associations between MGE attendance numbers and local COVID-19 infections over subsequent five week periods. No evidence was found of association between attendance at any of the six 2021 All-Ireland MGEs and COVID-19 infections over subsequent five week periods. This finding contrasts with studies of comparable MGEs in 2020, such as English Association Football matches held during spring 2020, and German Bundesliga football matches held during autumn 2020. These differing outcomes may point to the effectiveness of transmission mitigation policies and behaviours.

Keywords

Mobile data human population mobility COVID-19 mass gathering events mobile phone data

1. Introduction

Figure 1.

Republic of Ireland daily COVID-19 infections February 2020–May 2022.

On 30 ${}^{\text{th}}$ January 2020, the World Health Organization (WHO) declared the outbreak of a novel coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV-2), to be a public health emergency of international concern (PHEIC). Initially thought to be viral pneumonia, the illness had first been reported from Wuhan, Hubei Province, People’s Republic of China in late December 2020, and had already spread to eighteen other countries across the Americas, Asia, and Europe. Cases continued to spread and multiply rapidly over the following weeks, and on 11 ${}^{\text{th}}$ March, the WHO declared COVID-19, the disease caused by SARS-CoV-2, to be a pandemic, calling ‘for countries to take urgent and aggressive action’ [6].

In the Republic of Ireland, as elsewhere around the world, non-pharmaceutical interventions including mandatory social distancing, stay at home orders, closure of educational and cultural facilities, and of businesses or amenities deemed non-essential, formed a major aspect of the COVID-19 policy response. The first COVID-19 case in Ireland was confirmed on 29 ${}^{\text{th}}$ February 2020, and over the next twelve months the disease spread on a pattern similar to that of European countries. Three ‘waves’ of increasing severity rose during spring, autumn, and winter, each eventually subsiding as restrictions on personal mobility and contact were imposed [6, 7, 8, 9, 10, 11, 12]. Ireland’s COVID-19 vaccination programme was launched on 29 ${}^{\text{th}}$ December 2020, and mandatory testing and quarantine rules for incoming travellers were introduced in late February 2021. After the third wave peak at the turn of 2021, daily infection rates fell sharply over January-February, before tapering down more gently over the following four months. However, daily case numbers began to rise again in late June, which marked the beginning of an accelerating upward trend over the remainder of the year, punctuated only by a brief dip in September before rising to a fourth wave of unprecedented height over the December 2021–January 2022 holiday season [11] (Fig. 1).

Table 1

Croke Park All-Ireland events August–September 2021

Date	Event	Total CP attendance	CP capacity	Team A	Team B
7 ${}^{\text{th}}$ Aug	Hurling semi-final	24,000	28.9%	Limerick	Waterford
8 ${}^{\text{th}}$ Aug	Hurling semi-final	24,000	28.9%	Cork	Kilkenny
14 ${}^{\text{th}}$ Aug	Football semi-final	24,000	28.9%	Dublin	Mayo
22 ${}^{\text{nd}}$ Aug	Hurling final	40,000	47.6%	Cork	Limerick
28 ${}^{\text{th}}$ Aug	Football semi-final	24,000	28.9%	Kerry	Tyrone
11 ${}^{\text{th}}$ Sep	Football final	41,150	50%	Mayo	Tyrone

CP – Croke Park.

The Irish government responded to steadily declining daily case numbers during the first half of 2021 with a phased relaxation of restrictions. By the beginning of August, most smaller indoor leisure venues, such as pubs, restaurants, cinemas, gyms, indoor sports and gaming facilities, were permitted to open subject to reduced patron capacity, social distancing, and/or patron’s proof of COVID-19 vaccination or recovery. Larger attendances had generally been capped at one hundred for indoor performances and events, and five hundred for outdoor events hosted in stadia with a maximum capacity of at least five thousand. However, a ‘pilot’ programme of sixteen outdoor events held in June accepted larger audiences under mandatory safeguarded conditions including advance communication with attendees, contact tracing, venues operating at reduced patron capacity, physical distancing, mask wearing and hand hygiene [13, 30]. On 30 ${}^{\text{th}}$ July, Minister of State for Sport Jack Chambers declared the pilot programme a success and announced that ‘increased attendances’ would be permitted at the Gaelic Athletic Association (GAA) All-Ireland Senior Football and Hurling Championship semi-final and final matches, (the ‘All-Ireland Finals’). After some rescheduling, the 2021 All-Ireland Finals were held in their traditional venue, Croke Park in north inner city Dublin, with sub capacity crowds attending [14].

These MGEs were thus authorised and scheduled in a context of falling COVID-19 cases, but actually held during what proved to be a six-month a period of rising daily case numbers. The analysis presented below considers the question of whether the 2021 All-Ireland Finals MGEs contributed to or accelerated the rising daily COVID-19 case numbers experienced in the Republic of Ireland during autumn 2021.

2. Materials and methods

2.1 Overview

The All-Ireland inter-county sporting competitions are contested annually by teams representing the Republic of Ireland’s twenty-six counties, plus Northern Ireland’s six counties, competing in two sports, football and hurling. Two semi-finals and one final match for each sport, for a total of six MGEs, collectively referred to as the ‘All-Ireland Finals’, are traditionally hosted in the GAA’s flagship stadium, Croke Park in north inner city Dublin. With a maximum spectator capacity of 82,300, Croke Park is among Europe’s largest stadia, attracting fans from across Ireland [15]. Each MGE pits two county teams against one another, with attending crowds including substantial numbers of fans making round trip journeys from the competing counties on match days. The 2021 All-Ireland Finals were held on this traditional format, but with sub-capacity stadium attendance. Crowds of 24,000 fans attended the hurling and football semi-finals on 7 ${}^{\text{th}}$ , 8 ${}^{\text{th}}$ , 14 ${}^{\text{th}}$ , and 20 ${}^{\text{th}}$ August. 40,000 fans attended the hurling final on 22 ${}^{\text{nd}}$ August, and 41,500 attended the football final on 11 ${}^{\text{th}}$ September (Table 1).

All-Ireland Finals MGEs have a slightly different structure to typical team sporting league or national tournament fixtures. Rather than a home team hosting a visiting team in a local stadium, with the visiting team and supporters travelling, All-Ireland final Fixtures are all hosted in the same neutral stadium, Croke Park. Thus, with the exception of Dublin county teams, all teams are effectively visiting teams when playing in Croke Park. The population mobility associated with assembling the large crowds attending these MGEs can be envisaged on a hub and spoke pattern, with Croke Park acting as the hub, attracting round trip journeys from countrywide. Large proportions of crowds attending the All-Ireland Finals are drawn from finalist/semi-finalist counties, as GAA fans make the round trip journey from their ‘home’ counties to support their county team on the day. Representation levels of each ‘spoke’, i.e. crowd composition by geography, vary according to the specific event, but unlike home team vs. visiting team scenarios, visiting team vs. visiting team mobility patterns are directly comparable, relatively unimpeded by the noise from regular daily mobility in the host city. Increased hub-spoke round trip journeys on match days can thus serve as a strong proxy for MGE attendance, and can be used to disaggregate attending crowds by geographical pre-match origin and post-match destination. The 2021 All-Ireland Finals present a unique set of conditions for exploring the extent to which MGE attendance levels from defined ‘spoke’ areas impacted on subsequent COVID-19 infections in those localities.

2.2 Data

The Republic of Ireland’s electoral geography is structured on a three-level nested hierarchy of 26 counties, subdivided into 166 local electoral areas (LEAs), further subdivided into 3,409 electoral divisions (EDs) (Fig. 2). The mobility data used in this study is comprised of a series of daily ED-to-ED contact origin-destination matrices covering the period 1 ${}^{\text{st}}$ April–31 ${}^{\text{st}}$ October 2021. Each daily matrix is populated with estimated counts of people who spent 30 min or more in one ED, and then 30 min or more in another ED during the same day (i.e. daily numbers of journeys from ED ‘A’ to ED ‘B’ throughout the country).

Figure 2.

Republic of Ireland counties, local electoral areas, and electoral districts.

The origin-destination matrices are based on statistical analysis of anonymised, aggregated, mobile phone activity records from one of Ireland’s three major mobile network operator (MNO) companies, which holds approximately 30% market share. This high volume, high detailed data provides reliable geographically disaggregated high resolution estimates of daily population mobility, without any compromises of personal privacy. Anonymised data is aggregated to ED level and scaled up to estimates of ED-to-ED movement. To preserve anonymity, cells containing five or less estimated movements are populated with zeroes. For the purposes of this study, a random estimate from zero to five was substituted in such cases. Cases of ‘true zero’, i.e. no detected/estimated movement, are not populated in the matrices. As the contact matrices are compiled at the lower ED level, ED estimates can be easily aggregated to LEA or county level estimates, provided three levels of administrative zone available for analysis.

Ireland’s Central Statistics Office (CSO) published weekly new COVID-19 case numbers by LEA during 2021, week ending Monday. Both case counts and case rates per 100,000 of population are published, with figures $<$ 10 supressed to preserve anonymity. The LEA level is the principle geographic level of analysis of this study, as the LEA level is suitable for assessing community trends. COVID-19 case numbers during the period of study were zero in most EDs, and the ED level is so fine grained as to cut across communities, obfuscating trends and generating excessive noise. Conversely, while aggregating to county level is useful in assessing general impacts of events on wider mobility, the county level is too broad to capture local community trends.

Eight counties (Cork, Dublin, Kerry, Kilkenny, Limerick, Mayo, Tyrone, and Waterford) were involved in six 2021 All-Ireland Final events over six dates, as seen in Table 1. However, while Dublin competed in the football semi-final on 14 ${}^{\text{th}}$ August, and Tyrone competed in the football semi-final on 28 ${}^{\text{th}}$ August and final on 11 ${}^{\text{th}}$ September, data from Dublin or Tyrone are not included in this study. County Tyrone is not situated within the Republic of Ireland, but in Northern Ireland, a region within the United Kingdom of Great Britain and Northern Ireland (UK). As Tyrone is not subject to the Republic of Ireland’s electoral geography and not covered directly by the Republic’s mobile network operators, data related to Tyrone journeys is not included in the contact matrices, and therefore not available for this study. Dublin data is available, but as Croke Park MGE attendance movements are not easily isolated from other intra-capital movements, the data is excessively noisy in comparison with data from other competing counties. Intra Dublin movement is thus omitted from the analysis.

The one hundred and fifty-five LEAs throughout the Republic of Ireland, excluding Dublin, make up the study population. This study uses journeys from the ‘Croke Park area’ (CPA) to LEAs on All-Ireland Finals match dates to proxy for MGE attendance. The CPA, shown in Fig. 3, is defined as the ED where Croke Park resides, Ballybough B (coloured in dark blue) and surrounding and nearby EDs which tend to display increased mobility levels on match days (coloured in orange) (Fig. 3). CPA-LEA journey numbers are assumed to represent post-MGE movements, and used to disaggregate MGE attending crowds by LEA.

Figure 3.

Dublin electoral district map with ‘Croke Park area’ EDs highlighted.

Studies of MGEs and COVID-19 have argued that mobility associated with MGE-related travel in itself is not necessarily a major factor in increasing transmission rates, but that risks are increased by activities associated with MGE celebration, such as visiting crowds’ tendencies to congregate in confined spaces, to be closely packed together when queuing, and to engage in behaviours such as singing, dancing, chanting, and loud conversation. In the context of socially distanced outdoor sporting MGEs, heightened risks of COVID-19 transmission are not necessarily while actually spectating the event itself, but in corridors and on concourses during ingress and egress from the stadia, and during celebration before and afterwards in nearby bars, restaurants, and other shared spaces [1, 2, 3, 4, 5, 18, 19, 20]. Given these scenarios, event day journeys to/from MGE locations can serve as a strong proxy for potential exposure or for participation in risk behaviours associated with MGE attendance.

2.3 Statistical analysis

This study frames the 2021 Croke Park All-Ireland MGEs as a series of discrete events, and explores associations between MGE attendance and COVID-19 infections by LEA over subsequent five week periods. The two hurling semi-finals which took place over the same weekend are treated as a single event occurring during the week ending Monday 9 ${}^{\text{th}}$ August for the purposes of statistical analysis, using the higher mobility figures from the two days included for each LEA, and disregarding the lower. LEA Higher mobility corresponded to match day in the cases of all LEAs located in the counties competing in the hurling semi-finals: the 7 ${}^{\text{th}}$ of August in Limerick and Waterford, and the 8 ${}^{\text{th}}$ of August in Cork and Kilkenny.

The timeframe of each analysis begins with the event week, and extends for five weeks thereafter. The Delta variant, which was the dominant COVID-19 strain during the study period, has an average incubation period of 4.8–7.4 days and serial interval of 4–8 days [21, 22, 23]. A five week timeframe allows for extreme incubation periods of up fourteen days and an additional three weeks allowing for household and community transmission, and also for lags in testing. Two statistical methods are employed: regression of COVID-19 cumulative infections onto MGE attendance counts by LEA, and; analysis of variance of infection rates across ordinal mobility levels by LEA.

The two techniques offer slightly different perspectives. The regression analysis is based on a simple linear equation regressing cumulative COVID-19 cases since week ending 7 ${}^{\text{th}}$ June 2021 by LEA $a$ onto estimated MGE attendance $M$ by LEA $a$ :

$\displaystyle I_{a}\approx A+\beta M_{a}+\epsilon$

The first week in June is chosen as the base week for cumulative COVID-19 infections as this was at the end of the period of relatively stable low case numbers and the beginning of a period of rising daily cases. This was the context in which the 2021 All-Ireland Finals MGEs were held, and the key question at issue here is whether infections increased more rapidly in LEAs to which All-Ireland Finals attendees travelled after the MGEs.

Estimated MGE attendance, posited as the treatment variable $M$ , is calculated by subtracting mean non-match day CPA-LEA daily journeys from MGE day journeys. Negative numbers are treated as zero, indicating no MGE attendees from this LEA. The test of the hypothesis that All-Ireland Finals MGEs acted to spread the virus is whether $\beta>$ 0. Regression is applied separately to each of the five weeks subsequent to the MGE, testing the five hypotheses that MGE attendances precipitated increased COVID-19 infections one, two, three, four and five weeks after the event.

(Negative numbers are not an indication that the MGE deterred travel! Rather, some LEAs, particularly those in closer proximity to Dublin, tend to have higher weekday than weekend journeys associated with commuter patterns. In the absence of an LEA-relevant event attracting increased weekend journeys, subtracting a specific weekend date’s journeys from an overall mean is likely to produce a negative number, which, for current purposes, is noise).

Rather than focus on direct association between MGE journeys and COVID-19 infections, the second mode of analysis offers a broader perspective, using two custom metrics, Event Day Factor (EDF) and Indexed Infection Rate (IIR) to compare post-MGE LEA infection rates across event day mobility levels. EDF, a metric of MGE day CPA-LEA journeys relative to typical (non-MGE) journeys daily journeys, is calculated by dividing match day journeys by mean daily journeys on non-match day (days when no All-Ireland Finals event was held match at Croke Park) over the period 1 ${}^{\text{st}}$ July–31 ${}^{\text{st}}$ September 2021. This generic metric provides a measure of MGE impact on mobility relative to typical daily mobility, and offers direct comparability across LEAs of differing population sizes and different distances and numbers of journeys from Dublin, which is helpful for tabulation and visualisation. Choropleths mapping EDF ordinal bands for each event are included with supplementary materials.

Indexed Infection Rate (IIR) IIR is calculated by dividing the infection rate posted for the week of the event into the five subsequent weekly infection rates, thus compiling a weekly index number series, indexed to the event week. Again this provides a generic measure of how LEA infection rates changed in the weeks after the MGE, comparable across LEAs of different sizes and circumstances.

Example: The mean of estimated daily journeys from the Croke Park area to Cappamore-Kilmallock LEA-7 in county Limerick on non-match days during period 1 ${}^{\text{st}}$ July 2021–31 ${}^{\text{st}}$ September 2021 is 16.4. An estimated 460 persons travelled from the Croke Park area on 7 ${}^{\text{th}}$ August 2021, the date of the Limerick vs. Waterford All-Ireland Hurling final. Cappamore-Kilmallock LEA-7 EDF on 7 ${}^{\text{th}}$ August 2021 $=$ 460 $\div$ 16.4 $=$ 28.05.

Cappamore-Kilmallock LEA-7 posted a COVID-19 infection rate of 324.5 per 100,000 week ending 9 ${}^{\text{th}}$ August 2021, the week during which the All-Ireland Hurling semi-finals were held. Rates of 350.4, 485.3, 468.1, 333.1, and 215.4 per 100,000 were posted over the following five weeks. Dividing each of these by the event week infection rate, 324.5, produces the IIR series 1.08, 1.5, 1.44, 1.03, 0.66 over the period week ending 16 ${}^{\text{th}}$ Aug 2021–week ending 13 ${}^{\text{th}}$ Sep 2021.

Table 2
CPA journeys by All-Ireland finalist counties

Event date	County	Population	Non-match day Avg to CPA	Match day to CPA	To CPA county EDF	Non-match day Avg from CPA	Match day from CPA	From CPA county EDF
07 ${}^{\text{th}}$ Aug 2021	Limerick	194899	145	2166	14.9	115	1710	14.9
07 ${}^{\text{th}}$ Aug 2021	Waterford	116176	99	1885	19.0	79	1492	18.9
08 ${}^{\text{th}}$ Aug 2021	Cork	542868	229	3557	15.5	192	2652	13.8
08 ${}^{\text{th}}$ Aug 2021	Kilkenny	99232	233	2550	10.9	173	1977	11.4
14 ${}^{\text{th}}$ Aug 2021	Mayo	130507	71	1191	16.8	54	147	2.7
22 ${}^{\text{nd}}$ Aug 2021	Cork	542868	229	4336	18.9	192	3857	20.1
22 ${}^{\text{nd}}$ Aug 2021	Limerick	194899	145	3776	26.0	115	2947	25.6
28 ${}^{\text{th}}$ Aug 2021	Kerry	179000	57	689	12.1	38	405	10.7
11 ${}^{\text{th}}$ Sep 2021	Mayo	130507	71	2704	38.1	54	1409	26.1

CPA – Croke Park Area; EDF – Event Day Factor.

As weighted metrics, EDF and IIR facilitate direct comparison across LEAs of differing population sizes and levels of daily mobility from Dublin. Testing the hypothesis of no difference in LEA infection rates across ordinal ranks of MGE-related mobility presents a different perspective from the regression, offering insight as to whether critical masses of mobility might be associated with increased infection rates, irrespective of any direct linear relationship. A Kruskal-Wallis analysis of variance on ranks is used to compare IIRs across ordinal EDF bands of $<$ 2, 2–4.9, 5–9.9, 10–14.9, 15–19.9, and 20 $+$ (the Kruskal-Wallis analysis of variance was selected instead of a parametric ANOVA because parametric ANOVA required assumptions were not met in all cases – details in Appendix). The $<$ 2 band, i.e. no more than double typical daily mobility is regarded as comparable to typical non-MGE day mobility, while the higher bands represent increasing levels of mobility relative to typical daily movements. The null hypothesis of no difference between IIR over EDF levels states that:

Let $\mu$ be IIR over EDF level: $H_{0}:\mu_{1}=\mu_{2}=\mu_{3}=\mu_{4}=\mu_{5}$

With the hurling finals considered as a single event, analyses are applied to five MGEs overall. Tables presenting regression results, LEA counts by EDF level, the results of tests for normal distribution (required for ANOVA) of IIR scores by week and EDF level, and ANVOA results are presented in Appendix 1, with accompanying notes. Three visualisations pertaining to each event are included in Appendix II. The first of each set is a choropleth displaying EDF by LEA, providing a geographically disaggregated, easily understood view of MGE-related mobility. The second of each set, intended as visual aid to the regression analyses, is a scatterplot, faceted by week, of cumulative COVID cases plotted against estimated MGE attendance. The third, intended as a visual aid to ANOVA, is a boxplot faceted by week, plotting IIR scores by EDF levels.

3. Results

Figure 4 and Table 2 below shows daily estimated journeys to/from the Croke Park area (CPA) by selected county (All-Ireland 2021 finalist/semi-finalist counties) over the period 1 ${}^{\text{st}}$ July–30 ${}^{\text{th}}$ September 2021. As expected, substantial increases over regular daily traffic are evident on match days. Movements into the CPA from competing counties on All-Ireland match days increased by factors ranging from 10.9 (Kilkenny, Hurling semi-final, 8 ${}^{\text{th}}$ August) to 38.1 (Mayo, football final, 11 ${}^{\text{th}}$ September), while movements from the CPA to competing counties increased by factors ranging from 10.7 (Kerry, football semi-final, 28 ${}^{\text{th}}$ August) to 26.1 (Mayo, football final, 22 ${}^{\text{nd}}$ August). These substantial county level increases in mobility reflect increased aggregate mobility at the lower LEA and ED levels, as explored in more detail below.

Figure 4.

Daily journeys to/from Croke Park.

The 2021 All Senior Championship Hurling semi-finals were contested in Croke Park between Limerick and Waterford on the Saturday, 7 ${}^{\text{th}}$ August 2021, and between Cork and Kilkenny on Sunday 8 ${}^{\text{th}}$ August 2021. Croke Park hosted a crowd of 24,000, or 28.9% of maximum capacity, for each match. Regression results do not show any significant association between CPA-LEA travel and cumulative infections by LEA over the five weeks subsequent to match week, week ending 16 ${}^{\text{th}}$ August 2021–week ending 13 ${}^{\text{th}}$ September 2021. Kruskal-Wallis one-way analysis of variance showed no significant differences in IIR across EDF levels over the period (details in Appendix 1.1).

The first All-Ireland Senior Championship Football semi-final match was contested between Dublin and Mayo in Croke Park on Saturday 14 ${}^{\text{th}}$ August 2021, with a sub-capacity crowd of 24,000 fans attending. However, intra-Dublin mobility data is not included in this study, as discussed in section 3.1. Regression results do not show any significant association between CPA-LEA travel and cumulative infections by LEA over the five weeks subsequent to match week, week ending 23 ${}^{\text{rd}}$ August 2021–week ending 20 ${}^{\text{th}}$ September 2021. As available data was unsuitable for ANOVA (details in Appendix 1.2), a $t$ -test was used to compare LEAs across two EDF categories of $\leqslant$ 2, 2 $+$ . No significant difference was found.

The All-Ireland Senior Championship Hurling final was contested between Cork and Limerick in Croke Park on Sunday 22 ${}^{\text{nd}}$ August 2021, with a crowd of 40,000 fans, or 47.6% capacity, attending. While substantial numbers travelled from both counties, infection numbers remained stable over the subsequent five weeks. Regression results do not show any significant association between CPA-LEA travel and cumulative infections by LEA over the five weeks subsequent to match week, week ending 30th August 2021–week ending 27th September 2021. Kruskal-Wallis one-way analysis of variance showed no significant differences in IIR across EDF levels over the period (details in Appendix 1.3).

The second 2021 All-Ireland Senior Championship football semi-final was contested between Kerry and Tyrone in Croke Park on Saturday 28 ${}^{\text{th}}$ August 2021, with a crowd of 40,000 fans, or 47.6% capacity attending. Regression results show significant association between CPA-LEA travel and cumulative infections by LEA over each of the five weeks subsequent to match week, week ending 6 ${}^{\text{th}}$ September 2021–week ending 4 ${}^{\text{th}}$ October 2021. However the R squared in each case is negligibly low in all cases, ranging from 0.036 to just 0.031, meaning that less than 4% of variation is explained by MGE attendance. Kruskal-Wallis one-way analysis of variance showed no significant differences in IIR across EDF levels over the period (details in Appendix 1.4).

The last of the 2021 All-Ireland Finals MGEs, the Football Senior Championship Final, was contested between Mayo and Tyrone in Croke Park on 11 ${}^{\text{th}}$ September 2021, with a 50% capacity crowd of 41,150 fans attending. Tyrone journey data is unavailable, as explained in Section 3.1. Regression results do not show any significant association between CPA-LEA travel and cumulative infections by LEA over the five weeks subsequent to match week, week ending 13 ${}^{\text{th}}$ September 2021. Kruskal-Wallis one-way analysis of variance showed no significant differences in IIR over EDF levels over the period (details in Appendix 1.5).

4. Discussion

Studies of sporting MGES during spring 2020 in England and during autumn 2020 in Germany both found that the events precipitated minor increases in local COVID-19 infections. Olczak et al. estimated that each football match held across England during March-April 2020 increased local COVID-19 cases by 6 per 100,000 people on average, and may also have impacted on infection rates in areas from which visiting teams and their supporters travelled [1]. Similarly, Fischer et al.’s analysis of European professional football matches held from 10 ${}^{\text{th}}$ August–10 ${}^{\text{th}}$ November 2020, when the pandemic second wave swept over Europe, found that matches increased infection rates in the hosting area by 3.6–6.4 cases per 100,000 of population over the subsequent three weeks [2].

By contrast, this exploratory study, which investigated how a series of stadium MGEs held in Dublin during late summer 2021, did not find any association between MGE attendance and COVID-19 infections. Although the 2021 All-Ireland Finals MGEs were held in August and early September, a time when the dominant strain was the Delta variant, which was more transmissible (though less virulent) than previously dominant strains, and just a few weeks into a period of rising case numbers, no association was found between MGE-related mobility from/to specific LEAs and COVID-19 infection rates in those LEAs over subsequent five week periods. No evidence that the 2021 All-Ireland Finals MGEs contributed to COVID-19 infection rates was found.

While contrasting with earlier studies findings on how comparable sporting MGEs impacted on infection rates during the pandemic’s earlier stages, this study supports the consensus that association between mobility in of itself and infections weakened after the pandemic’s initial stages. Drawing on mobility metrics derived from MNO data, studies by Gatelo et al. [16] and Madden et al. [17] found that high mobility levels were associated with high infection rates during the earlier months of the pandemic, up to May 2020, and that the sharply decreased mobility imposed by ‘lockdowns’ did curb infection rates. However, mobility-infection correlations associations weakened after the initial stage of the pandemic. These studies argue that behavioural changes such as mask wearing in shared spaces, social distancing, and appropriate hand hygiene were likely more important in reducing case numbers than mobility restrictions alone. Scenarios where these behaviours were relaxed or absent are associated with increased case numbers. A retrospective cohort study linked a COVID-19 outbreak in Castellon, Spain to attendance at feast and dance MGEs associated with the Falles festival held in Castellon’s Borriana municipality in late February and early March 2020 [18]. Malaysia suffered the highest numbers of COVID-19 cases and deaths in Southeast Asia in the first quarter of 2020, with over 35% cases directly linked to the Sri Petaling religious MGE attracting members of the Tablighi Muslim missionary movement from across the region [19]. Iran came to be regarded as the ‘second epicentre’ of COVID-19 pandemic when an epidemic spread from Qom, a city of 1.2 m inhabitants which attracts 20 million Shite Muslim pilgrims from the Middle Eastern, Afghanistan, and Pakistan [20]. Madden et al. note that Ireland’s 2020 festive period, during which restrictions on indoor social gathering were relaxed, precipitated a wave of unprecedented daily COVID-19 case numbers [17]. This pattern was repeated in more intensified form over the following year’s festive season.

These studies of a diverse range of MGEs and social occasions are aligned in emphasised the role communal activities in spreading infections. These include activities general to many forms of MGEs such as congregation and loud conversation, shared dining, dancing, singing and/or chanting, and also event specific activities such as shared sleeping at religious pilgrimage MGEs and alcohol consumption, which is associated with risk behaviours at sporting and music events. Near universal cancellation or significant modification of MGEs is widely held to have forestalled or mitigated further COVID-19 outbreaks. The All-Ireland MGEs examined in this study were held in an outdoor venue during late summer 2021, with sub-capacity attendance and mandatory social distancing, in a context of high degrees of awareness of infection mitigation behaviours, such as wearing face covers and practising appropriate hand hygiene, and where the overwhelming majority of Ireland’s adult population were vaccinated against COVID-19, with proof of vaccination or recovery required to enter the stadium or hospitality venues such as pubs and restaurants. These factors may explain the difference between the relatively modest effect on case rates detected by studies of earlier comparable stadium MGES and the lack of effect found here. Contrasting the circumstances, policy context, and epidemiological outcomes of the All-Ireland Finals MGEs in 2021 and comparable football MGEs held in England and Germany in 2020, the evidence presented here does appear to support the Irish government’s claims of success with it’s ‘pilot’ approach. Controlled experimentation with scaling up attendances at a series of safeguarded events with carefully monitored post-hoc contact tracing did provide sufficient evidence for greater outdoor MGE attendance increases, and might provide a template for future MGE management under similar circumstances.

Mobile phone network data is recognised as the gold standard for analysis of human population mobility, and has proved a valuable resource in analysing mobility disruptions and restructuring around the world caused by the COVID-19 pandemic, underpinning analyses of population mobility responses in national and situational contexts such as studies examining mobility trends and the spread of COVID-19 in the Republic of Ireland [17], quantifying migration from cities towards rural areas in Finland, where many families maintain a second home, during periods of government stay at home orders [24], and modelling the effects of mobility restrictions on the spread of COVID-19 in Shenzhen, China [25].

However, few studies of MGEs in the pandemic context have used origin-destination matrices [28, 29]. Fischer uses mobility metrics based on estimates of match day percentage point increases in general mobility in home and visiting counties relative to a 2019 reference period, rather than considering visiting county to home county journeys directly. Olczak et al. also consider home and visiting team areas separately, but do not include mobility metrics in their analysis. This exploratory study took a simpler, more direct approach, facilitated by the high resolution mobility data. The linear formula employed estimates of mobility from the stadium ‘hub’ area to LEA ‘spokes’ as a proxy for MGE attendance, while the analysis of variance considered MGE journeys relative to typical mobility levels. A 2020 Lancet article on effective analytical use of mobile phone data for monitoring travel and physical distancing interventions recommended that ‘data must be optimised to an actionable spatial boundary, such as an administrative zone or grid square, and on a timescale that can provide epidemiologically relevant information’ [26]. The analysis of the pandemic-era MGEs presented here is based on mobility data fitting this framework.

While the mobility data used is of high quality, there are some caveats around interpretation. MGE attendance is inferred from mobility proxies, which do not offer direct observation of individual or group behaviours such as social distancing observance or face covering wearing. And as the dataset is anonymised and aggregated, demographic details on mobile carriers are unavailable. Rather than the more fully realised predictive models incorporating variables representing local demographic conditions, or more detailed representation of local epidemiological conditions factoring in hospitalisations and excess deaths presented in many other studies, here COVID infections numbers by LEA were regressed onto MGE attendance with a straightforward linear equation. This admittedly narrow approach was chosen to highlight and explore the potential of the high resolution mobility data in understanding mobility associated with and attendance at specific events, and in producing granular, localised analysis of their epidemiological impacts. More broadly it demonstrates how high detail, high volume privately held data can be leveraged for statistical analysis or official statistics without compromising personal privacy or digital rights. Future work could incorporate high-resolution mobility data into more holistic and sophisticated models, or on the other hand, present more straightforward aggregates and indicators, such as the EDF and IIR metrics as bases for official statistics.

This paper presents formal statistical analysis, but the key finding that the MGEs did draw large crowds and did occasion substantial increases in mobility, but did not precipitate increases in COVID-19 infections, is intimated by the maps and plots included, and can be understood intuitively at a glance. The graphs, maps and tables presented here are produced by parameterised software routines, which can be embedded in desktop based or web based ‘dashboard’ style interfaces. The work presented here provides an example of the types of tools techniques which can be made available to leverage high volume, high detail data to generate insights into specific policy issues or questions and capability to provide information and analytical/visual tools available to non-expert, non-technical users, such as policy makers, media, or members of the general public, in timely fashion, as official statistics. While the focus here is on a specific series of sporting MGEs taking place at single, a similar approach could be employed to analyse mobility associated with many events and locations.

5. Conclusion

Framing the 2021 All-Ireland Finals as a series of discrete natural experiments, this study found that while the events caused localised mobility spikes, they did not precipitate increases in local COVID-19 infection rates over the following five weeks. In addition to these specific findings, the study has demonstrated how mobility datasets derived from mobility network operators can be leveraged for insights into or official statistics on population mobility and COVID-19 infection patterns, without compromises of privacy or personal data rights.

Footnotes

Supplementary data

The supplementary files are available to download from https://dx-doi-org.web.bisu.edu.cn/10.3233/SJI-220045.

Appendix 1

References

Olczak

Reade

Yeo

. Mass outdoor events and the spread of an airborne virus: English football and COVID-19. 2020 Aug 27. Available at SSRN 3682781.

Fischer

. Thinning out spectators: Did football matches contribute to the second COVID-19 wave in Germany. 2021 Feb 26. Available at SSRN 3793379.

Drury

Rogers

Marteau

Yardley

Reicher

Stott

. Re-opening live events and large venues after Covid-19 ‘lockdown’: Behavioural risks and their mitigations. Safety Science. 2021 Jul 1; 139: 105243.

Corsini

Bisciotti

Eirale

Volpi

. Football cannot restart soon during the COVID-19 emergency! A critical perspective from the Italian experience and a call for action. British Journal of Sports Medicine. 2020 Oct 1; 54(20): 1186-7.

McCloskey

Zumla

Ippolito

Blumberg

Arbon

Cicero

Endericks

Lim

Borodina

. Mass gathering events and reducing further global spread of COVID-19: a political and public health dilemma. The Lancet. 2020 Apr 4; 395(10230): 1096-9.

Listings of WHO’s response to COVID-19. https://www.who.int/news/item/29-06-2020-covidtimeline, accessed 4

{}^{\text{th}}

Jan 2020.

Timeline and detail of public health restrictive measures advised by NPHET in response to the COVID-19 pandemic. NPHET Policy Unit, Department of Health, 13 January 2021.

Coronavirus in Ireland – a timeline. https://www.rte.ie/news/2020/0320/1124382-covid-19-ireland-timeline/, accessed 5

{}^{\text{th}}

January 2022.

Resilience and Recovery 2020-2021: Plan for Living with COVID-19. Department of the Taoiseach, Government of Ireland, 15

{}^{\text{th}}

September 2021.

10.

https://www.gov.ie/en/publication/e5175-resilience-and-recovery-2020-2021-plan-for-living-with-covid-19/, accessed 5

{}^{\text{th}}

January 2022.

11.

Ireland’s COVID-19 Data Hub. Government of Ireland. https://covid19ireland-geohive.hub.arcgis.com/, accessed 5

{}^{\text{th}}

January 2022.

12.

Speech by Taoiseach Micheál Martin from Government Buildings. Department of the Taoiseach, Government of Ireland, Friday, 28

{}^{\text{th}}

May 2021. https://www.gov.ie/en/speech/f2b3c-speech-by-taoiseach-micheal-martin-from-government-buildings-friday-28-may-2021/, accessed 5 January 2022.

13.

Minister Chambers publishes guidelines for safe return of spectators to sports events. Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media, Government of Ireland, Published on 7

{}^{\text{th}}

June 2021. https://www.gov.ie/en/press-release/70663-minister-jack-chambers-publishes-updated-guidelines-for-safe-return-of-spectators-to-sports-events/, accessed 5

{}^{\text{th}}

January 2022.

14.

Attendance of 40,000 to be permitted at GAA All-Ireland Finals in Croke Park. Irish Times. 30 July 2021. Available at: https://www.irishtimes.com/news/ireland/irish-news/attendance-of-40-000-to-be-permitted-at-gaa-all-ireland-finals-in-croke-park-1.4635098.

15.

https://crokepark.ie/stadium/about.

16.

Gatalo

Tseng

Hamilton

Lin

Klein

. Associations between phone mobility data and COVID-19 cases. The Lancet Infectious Diseases. 2021 May 1; 21(5): e111.

17.

Madden

Teljeur

Gleeson

Walsh

McGrath

. Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland. International Journal of Environmental Research and Public Health. 2021 Jan; 18(12): 6285.

18.

Domènech-Montoliu

Pac-Sa

Vidal-Utrillas

Latorre-Poveda

Del Rio-González

Ferrando-Rubert

Ferrer-Abad

Sánchez-Urbano

Aparisi-Esteve

Badenes-Marques

Cervera-Ferrer

. Mass gathering events and COVID-19 transmission in Borriana (Spain): A retrospective cohort study. PloS One. 2021 Aug 26; 16(8): e0256747.

19.

Mat

Edinur

Razab

Safuan

. A single mass gathering resulted in massive transmission of COVID-19 infections in Malaysia with further international spread. Journal of Travel Medicine. 2020 Apr 1.

20.

Ebrahim

Memish

. COVID-19 – the role of mass gatherings. Travel Medicine and Infectious Disease. 2020 Mar 1; 34: 101617.

21.

McAloon

Collins Á Hunt

Barber

Byrne

Butler

Casey

Griffin

Lane

McEvoy

Wall

. Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research. BMJ open. 2020 Aug 1; 10(8): e039652.

22.

Health Protection Surveillance Centre. Summary of COVID-19 virus variants in Ireland Report. Health Service Executive, 2022 Jan 1.

23.

Park

Cook

Lim

Sun

Dickens

. A systematic review of COVID-19 epidemiology based on current evidence. Journal of Clinical Medicine. 2020 Apr; 9(4): 967.

24.

Willberg

Järv

Väisänen

Toivonen

. Escaping from cities during the covid-19 crisis: Using mobile phone data to trace mobility in finland. ISPRS International Journal of Geo-information. 2021 Feb; 10(2): 103.

25.

Zhou

Yue

Xia

. Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: a modelling study using mobile phone data. The Lancet Digital Health. 2020 Aug 1; 2(8): e417-24.

26.

Kishore

Kiang

Engø-Monsen

Vembar

Schroeder

Balsari

Buckee

. Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis. The Lancet Digital Health. 2020 Sep 1.

27.

Oliver

Lepri

Sterly

Lambiotte

Deletaille

De Nadai

Letouzé

Salah

Benjamins

Cattuto

Colizza

. Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Science Advances. 2020 Jun 1; 6(23): eabc0764.

28.

Wesolowski

Eagle

Tatem

Smith

Noor

Snow RW Buckee

. Quantifying the impact of human mobility on malaria. Science. 2012; 338: 267-270.

29.

Csáji

Browet

Traag

Delvenne

Huens E Van Dooren

Blondel

. Exploring the mobility of mobile phone users. Physics A. 2013:392; 1459-1473.

30.

Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media. Minister Chambers publishes guidelines for safe return of spectators to sports events. 2020 Jun 7. Available at: https://www.gov.ie/en/press-release/70663-minister-jack-chambers-publishes-updated-guidelines-for-safe-return-of-spectators-to-sports-events/.

Assessing pandemic era stadium events and infections using mobile phone based population mobility data: An exploratory study from Ireland,2021

Abstract

Keywords

1. Introduction

2.1 Overview

2.2 Data

Table 2 CPA journeys by All-Ireland finalist counties

5. Conclusion

Footnotes

Supplementary data

Appendix 1

References

Table 2
CPA journeys by All-Ireland finalist counties