key: cord-0905583-8oxix4yl
authors: Rosenkrantz, Leah; Schuurman, Nadine; Bell, Nathaniel; Amram, Ofer
title: The need for GIScience in mapping COVID-19
date: 2020-07-01
journal: Health Place
DOI: 10.1016/j.healthplace.2020.102389
sha: 8ddcc229ba4c62c0e2a4b547194576ecae6a1efc
doc_id: 905583
cord_uid: 8oxix4yl

Since first being tracked in late 2019 in China, the effects of the COVID-19 coronavirus have shaped global patterns of morbidity and mortality as well as exposed the strengths and limitations of health care systems and social safety nets. Without question, reporting of its impact has been bolstered in large part through near real-time daily mapping of cases and fatalities. Though these maps serve as an effective political and social tool in communicating disease impact, most visualizations largely over-emphasize their usefulness for tracking disease progression and appropriate responses. Messy and inconsistent health data are a big part of this problem, as is a paucity of high-resolution spatial data to monitor health outcomes. Another issue is that the ease of producing out-of-the box products largely out paces the response to the core challenges inherent in the poor quality of most geo-referenced data. Adopting a GIScience approach, and in particular, making use of location-based intelligence tools, can improve the shortcomings in data reporting and more accurately reveal how COVID-19 will have a long-term impact on global health.

have shaped global patterns of morbidity and mortality as well as exposed the strengths and 26

limitations of health care systems and social safety nets. Without question, reporting of its impact 27 has been bolstered in large part through near real-time daily mapping of cases and fatalities. 28

Though these maps serve as an effective political and social tool in communicating disease 29 impact, most visualizations largely over-emphasize their usefulness for tracking disease 30 progression and appropriate responses. Messy and inconsistent health data are a big part of this 31 problem, as is a paucity of high-resolution spatial data to monitor health outcomes. Another issue 32

is that the ease of producing out-of-the box products largely out paces the response to the core 33 challenges inherent in the poor quality of most geo-referenced data. Adopting a GIScience 34 approach, and in particular, making use of location-based intelligence tools, can improve the 35 shortcomings in data reporting and more accurately reveal how COVID-19 will have a long-term 36 impact on global health. The global understanding of the impact of COVID-19 has grown proportionately with the 48 use of mapping applications across the public and private sectors, most notable of which are 49 daily publications by news agencies or near-real time online dashboards ("Johns Hopkins 50

Coronavirus Resource Center," n.d.; Times, n.d.). Although these maps provide an important 51 visual representation of its impact on morbidity and mortality and serve as an effective political 52 and social tool in communicating disease impact, most illustrations are over-emphasizing their 53 usefulness for tracking the progression of the disease and developing appropriate responses. For 54 instance, many maps have far too low a spatial resolution to inform prevention or mitigation 55 efforts at the local level, while others misrepresent entire areas by inappropriately using 56 choropleth maps to illustrate absolute data instead of relative data ("A heat map of coronavirus 57 cases in Canada -Macleans.ca," n.d.; "Canada Coronavirus (COVID-19) Tracker Map | 58

AccuWeather," n.d.; "Map," n.d.; "Mapping the Covid-19 Outbreak Globally," n.d.; Brackley, 59 2020; "City releases Toronto neighbourhood map of COVID-19 infections," 2020). At issue is 60 that the rise of open-source cartographic software has made map making accessible to just about 61 anyone with a computer and some technical know-how. While this is ultimately positive, the 62 proliferation of "out of the box" interactive maps (e.g., ArcGIS online, Tableau) is making 63 certain kinds of mapping of COVID events (e.g. choropleth maps, graduated symbols) more 64 ubiquitous than ever. The result has been a plethora of mediocre maps of COVID-19 that serve 65 little to no real benefit, some of which distort reality whether intentionally or not ("From 66 coronavirus to bushfires, misleading maps are distorting reality," 2020). 67

There are two reasons for concern, and both have to do with the underlying data that 68 power them. The first is that the available data are often messy and inconsistent. Changes in testing capacity, reporting discrepancies around fatalities, and overall differences in 70 methodologies have made interpreting data a challenge, especially when trying to compare one 71 geographic region or time period to another (Abbott, 2020) . The second is that securing geo-72 located health data at a high enough spatial resolution to detect meaningful patterns has proven 73 challenging due to privacy constraints. In North America, health data is predominantly being 74 reported at the county, city, or state level ("LA County Department of Public Health," n.d.; 75 nychealth/coronavirus-data, 2020; "PHSKC COVID-19 Outbreak Summary Dashboard," n.d.). 76

While this is a start, people are not static beings and cannot be neatly summarized to a single 77 point location or polygon as is often the case in data reported by health authorities. Furthermore, 78 most researchers have yet to gain access to individual trajectory data of infected individuals as 79 they move about their daily lives. 80 81 Putting GIScience to work: 82

As health geographers, we know that maps can play a larger role in the toolkit of policy 83 analysts, decision makers, and the public in building a long-term response to COVID-19. 84

Adopting a GIScience approach, and in particular, making use of location-based intelligence 85 tools, can help researchers and policy makers address the shortcomings in the data and lead to 86 more nuanced spatial analyses of the disease. Two separate efforts can meet these needs. 87

The first is a top-down, "Big Brother" effort in which government surveillance can make 88 use of smartphone apps that collect a user's cell phone location data (by way of GPS, cell phone 89 towers, and/or WiFi), electronic wrist bands, credit card transactions, and closed-circuit 90 television (CCTV) systems to track disease spread and, in some cases, enforce social isolation 91 measures (Fig 1) . This surveillance method is a comprehensive and rapid way to collect data on people's movement and health status. China for example, is using a government-backed app that 93 collects a user's name, national ID number and health information among other data, and 94 requires them to scan their phone at various checkpoints to track user movement. The app then 95 generates a personal infection risk rating to determine whether they are allowed passage through 96 the checkpoint (Calvo et al., 2020) . Similarly, at the start of the pandemic the Israeli government 97 also adopted population level surveillance, authorizing the repurposing of an anti-terrorist phone- concern over privacy and infringement on civil liberties. Calvo, Deterding, and Ryan (2020) further raise the alarm over issues of "surveillance creep" when it comes to these new 139 government measures (Calvo et al., 2020) . On the other hand, the bottom-up approach struggles 140 to ensure enough data is collected to be accurately used for cartographic or analytic purposes. 141

Given that this data is volunteered, it takes longer to reach a minimum sample size than 142 mandated top-down measures. 143 144

Whatever the method of collection, the increase of higher resolution and dynamic geo-146 located data on COVID-19 can allow researchers to go beyond the simple maps of present to tell 147 a much bigger, more detailed story. For example, geo-located data can allow a more explicit 148 understanding of its impact on near-and long-term health and social conditions within 149 communities. At issue, particularly in the United States, is that trends in COVID-19 events are 150 highlighting deeply rooted health disparities across the country along ethnic and racial lines. 151

Early reports of COVID-19 testing have shown that physicians are less likely to refer African 152

Americans for testing when they show up for care with signs of infection than other races (28). 153

These trends mirror long-standing findings that race directly (e.g., by providers) and indirectly 154 (e.g. providers locating outside of minority neighborhoods) leads to discrimination in health care 155 access (Farmer, 2020) . 156

At the same time, disparities in access to testing highlight only part of the picture. 157

Reports have also emerged that both federal and state governments are not collecting data on 158 race or ethnicity (Akilah Johnson and Buford, 2020). Nor has there been systemic testing and 159 coding of mortality-related events, which is likely leading to substantial undercounts of events 160 ("Fatal Flaws: Covid-19's death toll appears higher than official figures suggest," 2020).

Combined, the current limitations in data coding lay the groundwork for GIS Scientists to 162 monitor changes in the underlying causes of death and search for abnormal patterns of mortality 163 that could be attributed to racial disparities in care access during the outbreak. While it is a 164 precarious time for the most vulnerable, we are unlikely to grasp the true significance of 165 COVID-19 on long-term changes in population health outcomes without also harnessing the data 166 linkage and analysis properties of GIS to overcome limitations in current data reporting and 167 release statistics. 168

In a similar vein, investigations will be needed to assess whether the likelihood of 169 receiving treatment, as well as ensuing social and economic interventions, varies by community, 170 particularly those that were already experiencing the brunt of other disease burdens. Well 171 established geospatial methods can be used to investigate this. For instance, one method to 172 model these effects could be through distance decay analyses, a technique which could both help 173 uncover selection bias in community recovery evaluations as well as variations in outcomes 174 attributed to resource access. Another is through multinomial classification models based on 175 overlapping spatial clusters of recovery and socioeconomic conditions. Such models become 176 particularly important for revealing familiar patterns of racial and economic bias in light of 177 COVID-19 effects and could also reveal which communities recovered well in spite of these 178 factors, leading to new hypotheses associated with the role of community cohesion during 179 periods of isolation. 180

Finally, as society begins to transition back to 'normal', high resolution geo-located data 181 will also play a critical role in managing COVID19 outbreaks until the virus can be controlled. 182

The current non-pharmaceutical intervention (NPI) measures being implemented to curb the 183 spread of the virus (e.g. social isolation, lockdowns, etc.) are effective tools at our disposal but, due to resulting economic slowdown, they cannot be utilized for long periods of time. In the near 185 future, the easing of these measures to allow increased economic activity will be a critical step, 186 and real-time surveillance of COVID19 outbreaks will be essential to implementing targeted NPI volunteered GIS) strategy is essential for conducting the types of analyses we need to address the 202 multiple social, economic, and health care challenges brought on by the disease, and develop a 203 more considered response. Access to these data by spatial analysts is the basis for informed, 204 evidence-based decision making as well as maintaining social order via clear communication to 205 the public. 206

The authors received no financial support for the research, authorship, and/or publication of this 209 article. 

A heat map of coronavirus cases in Canada

States Are Reopening With No Clear Picture of U.S. Coronavirus 224 Cases

Early Data Shows African Americans Have Contracted and 226 Died of Coronavirus at an Alarming Rate

What are maps really saying about COVID-19 in Canada?

Health surveillance during covid-19 pandemic

COVID-19) Tracker Map, n.d. URL 233

Coronavirus: When the police knock at your door. BBC News. 235 City releases Toronto neighbourhood map of COVID-19 infections

COVID Symptom Tracker-Help slow the spread of COVID-19

The Coronavirus Doesn't Discriminate, But U.S. Health Care Showing 242 Familiar Biases

Fatal Flaws: Covid-19's death toll appears higher than official figures suggest, 2020. The 244 Economist

From coronavirus to bushfires, misleading maps are distorting reality

Citizens as sensors: the world of volunteered geography

To Track Coronavirus, Israel Moves to Tap 253 Secret Trove of Cellphone Data. The New York Times

Israel bans use of tracking app used to quarantine coronavirus patients

Use of surveillance to fight coronavirus raises concerns about government 260 power after pandemic ends

Let's Beat COVID-19

Map: Here's where coronavirus cases have been confirmed, n.d. . NBC News

Mapping the Covid-19 Outbreak Globally

Restrictions Are Slowing Coronavirus Infections, New Data Suggest. 271 The New York Times

Apple and Google Team Up to 'Contact Trace' the 273 Coronavirus. The New York Times

NYC Department of Health and Mental Hygiene. 275 PHSKC COVID-19 Outbreak Summary Dashboard, n.d. Tableau Software

Private Kit: Safe Paths; Privacy-by-Design Contact Tracing using GPS+Bluetooth

Cellphone tracking could help stem the spread of

trajectory data can be used to identify the recent locations of infectious patients and warn others 308 who were potentially exposed at these locations to self-isolate. On the right, Bluetooth 309 technology can be used to identify individuals who have come in close proximity to each other. 310While the use of this technology does not allow identification of the location of these users, it 311can track users who have come into close contact with each other. Coupled with other location 312 data, such as GPS or the use of cell phone towers, Bluetooth technology can play an important 313 role in identifying if individuals have come into close contact with someone infected by COVID-31419. 315

• Maps have played a large role in communicating the impact of COVID-19.• Most maps, however, have over-emphasized their usefulness for tracking disease progression and appropriate responses due to messy health data and low-resolution spatial data. • Adopting a GIScience approach can improve the shortcomings in data reporting and map making for COVID-19.