The Geographies of COVID-19

This chapter provides a historical and geographical overview of the use of geospatial tools and technologies to address pandemics in general, COVID-19 specifically, and longer-term adaptation to extreme events. Situating such events in place and time emphasizes the importance of these tools and how they shape the stories we tell. What is meant by “the geographies of the pandemic?” How have maps and geography contributed to understanding the pandemic and what have we learned from past events? A key theme of the pandemic is the exposure of inequality around the world not only exacerbated by the virus but also compounded by the government and social responses. This has exposed vulnerable populations (who are they?) and the landscape of inequity (where are they?), revealing how geography and geospatial technologies can contribute to future solutions and adaptations.

The COVID-19 pandemic has infected hundreds of millions around the world and led to the deaths of millions of people globally. It has also generated multiple and cascading effects that have led to economic shocks, disrupted education, limited mobility, forced migration, and hindered the provision of health care. Throughout the pandemic, maps have helped us to understand the spread of the virus and visualize rapidly changing information about its impacts. The objective of this chapter is to define first- and second-order impacts of the COVID-19 pandemic and describe their relationships to geospatial approaches for examining these impacts. Examples and cases from published research are presented to identify the limitations and challenges associated with geospatial applications, such as time, space, and scale. The conceptual framework includes a description of the first-order impacts of the pandemic (i.e., disease cases, hospitalizations, deaths) and a discussion of how human and societal responses generate second-order impacts, including social and economic effects. The combination of first- and second-order impacts results in increasing inequality and rising numbers of vulnerable populations. An examination of the emerging literature is provided to identify and describe how maps have been used to measure the impacts of the pandemic.

This chapter reviewed the role of quantitative geographical approaches in COVID-19 research. We particularly focused on two types of COVID-19 research: (1) studies on first-order impacts that investigate immediate health-related impacts of the COVID-19 pandemic (e.g., virus transmission, confirmed cases, and deaths) and (2) studies on second-order impacts that examine COVID-19’s secondary impacts, including social, economic, and environmental aspects. We focused on 331 papers that adopted quantitative geospatial approaches. We selected these papers from 45 journals in geography, GIScience, and urban and regional planning. Regarding studies on COVID-19 first-order impacts, we identified three research themes: (1) investigating geographical disparities in COVID-19 cases and deaths as well as the accessibility to COVID-19 relevant facilities such as testing and vaccination sites, (2) examining various factors that affect COVID-19 cases and deaths and building a model to predict those in the future, and (3) other topics that are relatively less studied than the aforementioned two themes. We observed fewer papers on second-order impacts than on first-order impacts. Moreover, the topic of human mobility was investigated the most, followed by health and well-being and the environment. This chapter contributes to the literature as it provides a comprehensive review of the role of quantitative geospatial approaches in COVID-19 research and highlights important future research directions.

Mobile location data became a center point of debate in the midst of the COVID-19 pandemic. Unlike pandemics of the past, the advancement of cellular phone technology and its adoption by a large proportion of the world population caused many governments, health authorities, and companies to explore how phone-based geospatial data could be applied to prevent disease transmission. This chapter examines the values and ethics involved in the debates over whether and/or how to apply mobile location data to prevention efforts through contact tracing, quarantine enforcement, symptom checking, and flow modelling. Questions over the efficacy of these programs and their appropriateness to the public health crisis remain. The rollout of mandatory location-tracking applications in South Korea, Israel, and Taiwan, as well as the participation of data brokers in supplying governments and researchers with widespread location data, challenge the values of privacy, freedom of movement, and informed consent. The precedents set during the COVID-19 pandemic for the use of personal geospatial data and the infrastructure established to support its collection will follow us into the next world challenge.

The rapid spread of the COVID-19 pandemic in 2020 to cities across the world illuminated the need to understand the distribution of resources across urban areas. Urban geographies are complex and interdimensional. Unfortunately, the data needed to understand these critical socio-economic relationships is infrequently available, particularly in the lower- and middle-income countries. Human geography data applied in developing urban areas during the COVID-19 pandemic offers an understanding of how populations are dependent upon the infrastructure around them and the limitations of both data and infrastructure to support vulnerable populations. Using local knowledge to enhance and improve human geography data for analysis to mitigate COVID-19 impacts emphasizes the practical need for geospatial capacity and participatory mapping partnerships among stakeholders to support community recovery and resilience. The Cities’ COVID Mitigation Mapping (C2M2) Program led by the U.S. Department of State from summer 2020 through fall 2021 illustrates the reach of participatory mapping partnerships applied to second-order impacts of the COVID-19 pandemic, and the geospatial model used offers lessons applicable for recovery from the pandemic as well as a wide range of issues that will continue to impact developing cities, to include resilience and sustainability.

The Cities COVID Mitigation and Mapping (C2M2) Ulaanbaatar project was implemented to mitigate the secondary health impacts of the COVID-19 pandemic by facilitating access to health services, via making information about health services available and easily accessible to the public. The project started in October 2020 when Mongolia still had not reported any case of community outbreak of the COVID-19 virus. The WHO and the international media praised and exemplified Mongolia’s efforts in containing the virus, thanks to swift and strict measures to close its borders, suspend local travel, and enforce lock down measures – that is until November of 2020. Almost a year later, Mongolia has one of the worst daily COVID-19 cases, hospitalization rates, and deaths despite close to 70% vaccination rate. The full swing of the pandemic put an immense pressure on the health infrastructure evidenced by the lack of non-COVID-19-related health services and national shortage of health workers. The pre-pandemic challenge of accessing healthcare has primarily been due to lack of reliable information about available health services and limited word of mouth. Our efforts focused on creating an up-to-date health service information portal to facilitate the process of finding information about the needed health services online easily, especially during lock-down measures. The project also worked to promote the use of geospatial data to support policy and decision-making by creating and sharing open data and developing a vulnerability analysis of urban and health service access. While the project has been successful in collecting data and creating the key tools, stakeholder and public outreach remains a key step in achieving the intended results.

The COVID-19 pandemic has led to significant disruptions in all aspects of societies. Amidst the COVID-19 pandemic, systemic inequities and implicit biases have become more visible, as many pieces of evidence reveal that the US population is disproportionately harmed physically, socially, emotionally, economically, and educationally. This chapter aims to summarize relevant studies that reveal, analyze, and discuss the long-standing inequity issues in the US that have been emerging during the COVID-19 pandemic from three different perspectives: (1) inequity in COVID-19 testing rates, confirmed cases, and mortality, (2) inequity in stay-at-home compliance and short-/long-term recovery, and (3) inequity in vaccination tendency, vaccine allocation, and vaccination rate. The observed inequities from these three perspectives can be attributed mainly to the disparity of demographics and socioeconomic status of the population. Such a disparity may further widen the gap between advantaged and disadvantaged groups and cause unequal economic and health consequences that disproportionately affect vulnerable groups. By summarizing the analytical approaches, experimental settings, and statistical findings, we provide evidence that unravels the role of demographic and socioeconomic status in observed inequities during the COVID-19 pandemic. In addition, we discuss the strategies that can be adopted to reduce the inequity induced by future epidemics.

How are the stories geographers look for, especially during health crises like COVID-19, limited by the language we use in our data collection? In the Latine research community, an ongoing discussion of the limits of data collection focusing on those who are “Hispanic”, “Latinx”, “Latino/a”, or “Latine” has been ongoing. This conversation, led by Black and Indigenous Latine researchers, critically questions our usage of these terms when seeking to capture the complex stories of Latine people, especially when past research has ignored the Black and Indigenous Latine populations in the United States. Regional differences in identity formation throughout the United States, immigration and Latin American origins, and language all contribute to unique Latine identities and experiences, especially regarding health and healthcare access. How have various Latinx communities throughout the United States coped with the impacts of COVID-19? What are the COVID-19 survival barriers they have experienced? This chapter summarizes the current discussions on this issue and discusses which stories of the Latine community in the COVID-19 pandemic we do know. This chapter also offers potential avenues for better understanding Latine populations throughout the United States with examples from targeted interventions.

COVID-19 severely impacted Nepal’s economy. The tourism industry, a major contributor to Nepal’s gross domestic product (GDP), has been one of the major sectors to bear the secondary impact due to COVID-19. This chapter provides an overview of the economic and non-economic impact of COVID-19 on the tourism sector. The discussion centers around two major stakeholders: businesses and workers. It also elaborates on the major stakeholders’ expectations on the government to withstand and recover from the economic shock.

Under the Cities COVID Mitigation Management (C2M2) project (Cites’ COVID Mitigation Mapping, MapGive, https://​mapgive.​state.​gov/​c2m2/​), facility-based data was collected in several cities in Africa (Bukavu in the Democratic Republic of Congo, Nairobi and Kericho in Kenya, and Pemba in Mozambique). The data included geospatial information on water access points, healthcare, and education-related facilities in these cities. In addition, for each facility, data was collected around service availability, service capacity, and service readiness. The need for data to drive decision support was clearly illustrated through feedback from local populations, i.e., a Kibera resident shared the following: “When you go to the water point, sometimes you find long lines of water jerry cans, so you have to wait for hours or even go home without water; the fact that we needed more water during the corona pandemic was very demanding physically and financially. Quite often, we had to go fetch water from far places since there is no water in our area”. In this chapter, we discuss the facility-based data model and how the data collection process, metrics, and dashboards can be used to measure impact and prepare for and mitigate the impacts of any future natural or human-made disasters.

The COVID-19 pandemic has produced different second-order effects that go beyond the health outcome. One of these cascading effects is the increase in domestic violence. The objectives of this study are twofold: (a) to explore the temporal and spatial patterns of domestic violence formal complaints, across the city of Quito before, during, and after the confinement caused by the COVID-19 pandemic, and (b) to determine the demographic and socioeconomic factors that explain the reporting of domestic violence during these periods. Specifically, we want to explore if the lockdown affected domestic violence reporting. Different degrees of restrictions in movement, including a complete lockdown, across different socioeconomic sectors generated different spatial patterns of domestic violence. This study uses individual geocoded crimes of domestic violence in Quito, between 2018 and 2021, from the Attorney General’s Office (FGE), to generate spatial and statistical analysis. This study shows that there are different spatial patterns before and after lockdown and statistical models find that mobility restrictions are strongly related to the level of domestic violence reporting. Additionally, employment, education, distance to complaint units, poverty, and overcrowding are important effects on domestic violence. In general, we find that there is a combination of factors that during the pandemics decreased the level of reporting of domestic violence affecting the more vulnerable people in vulnerable places.

Many studies applying geospatial analysis to communicable diseases simply borrowed methods developed for chronic diseases, e.g., cluster detection based on the incidence rate. However, such use of rate has a fundamental assumption, the disease has a base rate in the population at risk, which does not hold for an acute human-to-human communicable disease like COVID-19. Moreover, a human-to-human communicable disease may be highly related to the population density besides the size, which makes the incidence rate of such diseases less indicative. To verify this understanding, using the COVID-19 data in China at the city and provincial levels and corresponding population data, we evaluated the associations of the case count and transmission ability of COVID-19 with the population size and population density. We found that there is hardly any detectable association between the disease and the population size ordensity, which is likely due to the highly strict prevention measures and limited case counts in China. The results indicate that the geospatial analyses based on the incidence rate of COVID-19 may not be informative about the pandemic in China. We suggest mapping with case count or case-reproduction ratio R_t instead.

The COVID-19 pandemic continues to have unprecedented impacts on people and places globally, challenging the ability of both government and citizens to respond. The use of Nonpharmaceutical Interventions (NPIs) has been widespread in attempting to curtail the spread of COVID-19. However, there were important distinctions in how governments chose to use the public health tools at their disposal. We focus on the experience of Aotearoa New Zealand (NZ), a jurisdiction that has been featured as arguably one of the most successful and stringent in attempts to eliminate COVID-19 from the population. We also explore and examine the social and spatial patterns that exist and have widened within NZ as the pandemic has unfolded, exposing the underlying social structures and fractures that now exist and persist in many countries. Initially, a geographic approach was absent, but as the pandemic progressed, this became a key aspect of the public health response. This chapter explores a range of data sources from the ongoing pandemic in NZ. We conclude by discussing an emerging syndemic, concluding the chapter with policy implications and potential future research directions.

This chapter draws on the Aboriginal and Torres Strait Islander experience of the COVID-19 pandemic in Australia, with a focus on the spatial differences in urban and rural health outcomes and responses. We explore cultural, socioeconomic, and place-based dimensions of COVID-19 among Aboriginal peoples including inequity around transmission, infection, and severity; the spatiality of public health restrictions, community-controlled health service responses, and grassroots relief efforts; control of remote community borders and movements; and the framing of these in the context of cultural diversity and sovereignty, and ongoing colonization

We examined the impacts of the COVID-19 lockdown on the livelihoods of commercial male Boda-Boda motorists in Uganda. The objectives of the study were to (1) characterize social services within the working environment of Boda-Boda motorists and (2) explore the perceived impacts of COVID-19 lockdown on the livelihood of Boda-Boda motorists and their families. The study utilized qualitative and quantitative methods of data collection. Quantitatively, ArcGIS 10.4 and Global Positioning System were used to determine the distribution and distances to social services. Proximity analyses were carried out using near tool and buffer analysis tool to determine how far the different social services were from the different Boda-Boda stages. Qualitatively, the study collected data from four focus group discussion and four key informants. The study revealed the existence of fairly distributed administrative and social services. However, due to lockdown movement restrictions, Boda-Boda motorists were not allowed to transport passengers, the primary users of such services. This caused Boda-Boda motorists to lose their employment, income, and provisioning role. Boda-Boda motorists suffered economic, psychological, and physical violence from their female partners due to failure to provide for their families. Protective systems, services, policy reform, and awareness to address domestic violence against men are required.

Using evidence of the spatial trajectory of the virus in the past can help us predict spatial patterns in the future. Geospatial analysis and GIS (Geographical Information Systems) may accelerate the spatial analysis of virus spatial trajectories. The different types of transportation have accelerated the transmission of the virus. One way to find it is by using special applications within Geographical Information Systems (GIS). Generally, GIS methods are used for spatial analyses – among these, the analysis of traffic patterns. In this research a few spatial and numerical methods were used. The common methods are zonal statistics, buffer, interpolation used to better explain COVID-19 spatial trajectories. The data included in this research were obtained from various sources. The data for traffic connections were from a free and open-source database (https://​www.​naturalearthdata​.​com/​). The data for air traffic routes were from the official page of the International Air Transport Association (https://​www.​iata.​org/​). COVID-19 cases across the world were collected from the Worldometer database (https://​www.​worldometers.​info/​coronavirus/​). Methods and algorithms used in this research such as the vector spatial trajectories of the virus and numerical analysis make this research interdisciplinary. This study covers the whole world and aims to improve our understanding of the relation between traffic networks and the spatial trajectories of COVID-19. In our analysis, we found a high risk for the virus through the geographic areas on traffic routes. Four types of traffic – airplanes, railroad, road and ship – were analysed too. These data used from 2021 year. Airplanes displayed a high risk of viral transmission, cars and trains a medium risk and ships the lowest risk. The traffic was analysed by data of total connection per year. The possibility of transmission is relatively lower on railroad lines, followed by marine traffic, road and then air traffic. As they are the most connected, we believe that road and railroad traffic could produce new hotspots of coronavirus cases. Large and densely populated areas in the world, areas with big urban communities, large traffic infrastructure and a large number of traffic connection points have been greatly affected by COVID-19. Only areas which are not densely populated, with underdeveloped and small or poor traffic connections and networks, as well as isolated island territories appear to be less affected by the pandemic. This can be changed by the necessity of inhabitants in these regions to go to other regions for supplies.

Over the past decades, digital technologies have been exploited to supply traditional measures employed to trace people’s behavior. This chapter aims to discuss the current field of actual surveillance and the age of surveillance capitalism with its contradictions. The main focus is on the Italian technology solutions deployed to tackle the spread of COVID-19. This chapter analyzes the interaction between the procedures shaped by the Italian surveillance technologies implemented to discipline (e.g., social distancing) and control (e.g., prescribing spatial behavior) forms of governmentality. Another aspect of this research explores the very complex stratification of public and private spaces producing new spatiality during the pandemic. A preliminary analysis of surveillance technologies deployed to struggle COVID-19 is reviewed and their biopolitical power in the current exceptional state discussed in the specific case of Italy. Two perspectives, a biopolitical one and data justice, provide an essential lens of reading to understand the effects of surveillance technologies in the Italian society during the pandemic, leading to a further progress in the phenomenon of surveillance capitalism to which we have all been subjected for a long time.

The contribution of the urban informal sector (UIS) to national economies and local livelihoods in sub-Saharan Africa cannot be overstated. Unfortunately, this sector is vulnerable to political, economic, social, and environmental uncertainties such as those presented by the COVID-19 pandemic in 2020. For example, government-instituted containment and mitigation measures employed to curb the initial spread of COVID-19 threatened the very existence of the UIS. Whether it was the mandatory lockdowns, closure of schools and businesses, stay-in-place orders, social distancing guidelines, or the closure of national borders, the sector appeared destined for collapse. However, despite the lack of social protections and direct financial support from the government, the UIS demonstrated an unlikely resilience. This study examines the relative resilience of the UIS in the face of COVID-19-imposed lockdowns in the first 2 years of the global pandemic. A survey of literature is followed by analysis of published material, media content, Internet sources, government reports, and other official and nonofficial government sources. Study findings show that the flexible nature of operation and activities involved in the USI, its community orientation and deep social networks, and the low capital outlay required to restart – all made reentry into the sector relatively manageable.

Water in both built and natural environments is fundamentally important to humans, with the health and sustainability of freshwater ecosystems critical to the stability of human social systems. The complex and often sensitive relationships between human activities and freshwater resources have been highlighted during the COVID-19 pandemic, providing unique insights into how humans interact with freshwater resources, both in terms of impacts and dependencies on these systems. In particular, mandated lockdowns in several areas of the world have resulted in relatively rapid improvements in water quality due to limited human activity, suggesting the resilience of natural systems. However, the need and challenges of providing clean water in both rural and urban areas were also highlighted by restrictions associated with the COVID-19 pandemic, often resulting in clean water shortages in already struggling communities. Ongoing changes in climate, particularly related to precipitation, have also likely contributed to water-related issues during the COVID-19 pandemic. In some areas, fisheries experienced increased pressures as food distribution systems and local economies were disrupted, thus requiring members of local communities to rely more directly on natural resources. The combination of COVID-19 restrictions, regional climatic variability, and varying levels of social and economic stability suggest the need for preemptive approaches to ensure water availability and access to freshwater resources in all areas of the world in the coming decades.

It is inevitably better to prevent a pandemic than have to control one, and Earth observations (EO) will play a critical role in predicting and preventing disease incidence in the future. Most new, emerging diseases are zoonotic in origin, meaning they spill over from animal species to infect humans. Therefore, it is critical to take a One Health approach in further disease studies: we must investigate these animals (reservoir species), the environments they inhabit, and their interactions with humans in order to reduce the probability of spillover events. EO data is useful in all three of these areas and can be integrated with other data to develop a more comprehensive and multifaceted view of disease transmission and prevention. For example, the levels of vector-borne diseases carried by insects such as mosquitos and ticks can be predicted with weather and climate data from satellites in combination with data on human population characteristics. For other diseases that have their hosts in vertebrates like bats or chimpanzees, habitat data are particularly useful. Satellites can measure the degree of habitat destruction and human incursion to estimate the probability of human-wildlife interactions that could spread disease. Preventing the next pandemic will require us to stay ahead of the disease curve, and EO data provides an avenue that can help us stop disease before it starts.

The US National Science Foundation (NSF) has a history of supporting urgently needed, ephemeral data collection for research on major disruptive events, often addressing first-order impacts. NSF has communicated the availability of rapidly accessible research funds through Dear Colleague Letters (DCLs) 14 times from 2010 to 2020 to address health hazards, earthquakes, hurricanes, and man-made hazardous events in and out of the United States. In response to the COVID-19 pandemic, three Dear Colleague Letters were published, and approximately USD 162.4 million was distributed to researchers for 991 unique NSF projects in fiscal year (FY) 2020, as considered in this chapter. The research community led the charge in defining the research agenda to address the pandemic, with the first COVID-19-related proposals coming into NSF months before COVID-19 was declared a pandemic. To understand how the research community prioritized the initial research topics to address the pandemic, we qualitatively evaluated FY 2020-funded projects to reveal 11 categories which includ (1) biology of the virus and zoonosis, (2) human infection, (3) transmission, (4) effects on and tools for healthcare systems, (5) human distancing behavior, (6) public policy, (7) risk perception, (8) information access and misinformation, (9) supply chain and food security, (10) education, and (11) impact on ecosystems, environment, and infrastructure. Awarded projects address a broad range of topics, many of which included geospatial approaches, with overlap across categories. One key observation is the cross-societal implications and inter- and transdisciplinary perspectives emphasized across projects. The response to COVID-19 reinforced the need to bring diverse researchers and disciplines together to solve interwoven challenges during times of rapid change and urgent need.

The preparation of this volume is bracketed by two events: first, the global pandemic that continues to this day, and second, the emerging conflict in Ukraine where Russia has invaded a sovereign nation. This juxtaposition of global and regional events demonstrates the need to understand the geography of places and consider how geospatial approaches can inform policy and solutions. To address the pandemic, the national governments have put into practice place-based procedures and policies to protect and save lives; we now enter a phase of global uncertainty where conflict upends those policies and lives are lost. The coincidence of the pandemic and conflict compounds the global health emergency particularly in fragile states exposed to conflict and violence where provisioning basic services (such as food, water, and shelter) is essential (Richardson, Chap. 3). As the Ukraine invasion unfolds, we observe in real time the impact of conflict and the emergence of the Ukrainian diaspora and consider the hidden toll the virus will take in concert with violent loss of life. This conflict will hinder and complicate public health responses and this is only one example of a nation-state, Russia advancing a specific agenda with the continued pandemic as a backdrop. Armed conflict results in people on the move and this means the virus will also be on the move. The UN reports that 24 million of the 98 million confirmed to have contracted the virus live in countries facing humanitarian or refugee crises (UN Press Release, 2021), and this number is sure to increase as the conflict rages and expands.