A qualitative approach in comparing six cities toward a resilient response plan: COVID-19 and inequalities

Abstract

COVID-19 has dramatically affected financial markets, economies, and societies worldwide and exposed pre-existing inequalities in cities. This work aims to understand the inequalities in some cities worldwide, their reasons and circumstances, and impacts to drive lessons for future prevention, intervention, and post-catastrophe/ hazard plans such as COVID-19 that would raise resilience and decrease damages. Six major cities were included in the analysis and contrasted based on specific assessment criteria. The study included the impact of the pandemic on the economy and the government's responses global crisis. Additionally, newfound measures and technologies developed to control the hazard, including the community's response and cooperation to solving the issue were explored. The outcomes of this work shed a light on problems to be addressed in the future towards enhances the resilience of cities pre- and post- global crisis. Through the comparisons made in this paper, conclusions regarding the cities' successful combat against COVID-19 were drawn. According to the comparative analysis, it became apparent that poverty, culture, and governance are primary factors that control the success of states under emergency. Moreover, it is understood that technology is a significant factor in combating pandemics and health emergencies as large as COVID-19, especially for tracking and monitoring.

Introduction

The emergence of the COVID-19 pandemic, even if not the highest in death tolls throughout history, resulted in the largest distributional consequences in the history of pandemics (Cabral and Xu 2021). Consequently, many researchers have studied the environmental and socio-economic impacts, management, and governance of the crisis caused by the pandemic (Sharifi and Khavarian-Garmsir 2020), These studies established that the old socio-economic inequalities, such as healthcare, unemployment, and housing, already existing in major cities became more exposed as a result of the pandemic (Sharifi and Khavarian-Garmsir 2020).

Inequality exists in various forms, such as, between rural and urban areas, majority and minority of a community (Visagie and Turok 2021), or in vulnerable areas with poor living conditions with limited accessibility to basic infrastructure (de Groot and Lemanski 2020). The factors leading up to such inequalities can be reduced to poverty, culture, and, more importantly, governance. Therefore, the inclusion of these factors ahead of time is determinantal to the success of prevention, rehabilitation, or control measures plans, implemented in the time of national or international crisis.

The fundamental understanding of culture is paramount for proper assessment and communication of the global response to COVID-19, taking into consideration factors such as individualism vs. collectivism, cultural identity, diversity of nationalities, and cultural background (Airhihenbuwa et al. 2020). Furthermore, a cultural framework for community engagement is essential to ensure a global communication response to COVID -19 and a collaboration with the government (Cruz et al. 2020).

The role of technology cannot be ignored in tracking, monitoring, and supporting COVID-19 control measures. The Information and Communication Technologies and Big Data analysis assisted in the resilience of cities throughout the duration of the pandemic (Linkov et al. 2021). However, the use of technology may highlight the inequalities caused by COVID-19 (Madianou 2020), citizens within the poverty limits or poor urban areas are incapable of easily accessing technology. Another measure that can slow down the spread of COVID-19 but also accentuates the inequalities is the lockdown that limits the mobility of vulnerable areas and people (Gozzi et al. 2021). Hence, governments should prioritize the systematic elimination of inequalities to ensure proper and fair future pandemics prevention or mitigation plans accessible to all citizens across different social classes (Sharifi and Khavarian-Garmsir 2020).

Notwithstanding, inequalities detrimental to the success or failure of pandemic preventive measures and resilience of cities are not limited to minorities, poverty rate, culture, or urban vs. rural areas. They also encompass gained experience in combatting previous hazard/catastrophe or governance. Therefore, it can be said that a city with a low poverty rate does not automatically mean more resilient toward the COVID-19 crisis. Likewise, a city with less experience combatting such pandemics is not necessarily less resilient.

In this contribution, we aim to demonstrate the effect of some cases of inequalities between different cities in combatting the spread of the pandemic. The examined inequalities span across different factors such as, (1) spatial and temporal factors in diagnosis, treatment, and rehabilitation of COVID-19, (2) inequalities of the use of digital infrastructure for monitoring, tracking, and supporting the COVID-19 control measures, as well as (3) inequalities in governance practices on COVID-19 health risks, prevention, and intervention. In this regard, six cities were selected and studied to understand their inequalities based on the aforementioned criteria. Finally, a qualitative approach was followed to make a comparison in order to identify the success of each city’s prevention plans or responses to the COVID-19 crisis.

Methodology

City selection

Towards assessing the effect of inequalities on the success rate for a given country in mitigating a global crisis, a cause-and-effect relationship was established though collecting secondary data. Using previous research, journals, newspapers, and government records; the necessary data was collected to assess the success rates of the cities being studied.

Six major cities were selected, including Abu Dhabi (UAE), Amman (Jordan), Sao Paulo (Brazil), New York state (United States), Bengaluru (India), and Shanghai (China). Additionally, for the sake of establishing a fair comparison, each two cities were paired and compared based on a specific shared criterion that influenced their response to the pandemic, as such:

Abu Dhabi and Amman were compared due to their similar geographical locations in the Gulf region, along with being affected by the pandemic at a later time than other major cities.

Sao Paulo and New York state were compared due to their similar population densities.

Bengaluru and Shanghai were compared owing to their effective implementation of various technologies throughout the pandemic.

The cities mentioned above were compared based on three criteria: (1) the impact of governance practice, (2) the spatial and temporal inequality, and (3) the impact of digital infrastructure on monitoring and tracking COVID-19. The impact of governance practice denotes the government's response and actions in halting the progression of the pandemic in their respective cities. On the other hand, spatial and temporal inequalities are focused on the lack of recourses, supplies, and infrastructure in cities leading to difficulties in mitigating the COVID-19 crisis. Conversely, the impact of digital infrastructure on monitoring and tracking encompasses the diverse range of technologies used in the efforts against the novel coronavirus.

To assure the reliability and objectivity of the data collected, several methods were applied. First, the data gathered from a variety of sources was normalized to insure it does not contain any inconsistencies and was uniform. To review the scientific literature, a thorough understanding of bias and how it affects study results was vital. For instance, the sources used focused on both the positives and negatives of the city being analyzed, with an objective point of view. Sources that failed to adequately point out the reasoning behind criticizing the city or the government were eliminated.

Through the comparisons made in this paper, conclusions regarding the cities' successful combat against COVID-19 were drawn. These conclusions establish different tools and initiatives that are vital to learn from and recognize governance weaknesses to ensure preparedness for future pandemics or equivalent unforeseen events.

Case studies

Case of Abu Dhabi, UAE

Abu Dhabi was one of the lucky cities to be hit by the virus later than most countries, giving it a sufficient span of time to learn and prepare efficient methods to deal with the possible outbreak. Abu Dhabi is the capital of UAE, with a population of 1,511,768 (World City Populations 2021, 2021); and occupying 972 km² of UAE. Even with a large population, Abu Dhabi citizens showed an excellent response to the outbreak, due to the government's constant awareness and prevention campaigns. Similar to the case of Shanghai, the local GDP per capita grew by 2.4% as of 2021, resulting in a GDP of US $ 98,000 (Abbas 2021).

Case of Amman, Jordan

Amman is one of the cities that faced problems handling the COVID-19 pandemic. As of 2021, the city has a total population of 2,182,151 (Amman Population 2021 Demographics, Maps, Graphs, 2021), with an area of 1680 km², making it the largest city in Jordan. Due to the pandemic, the GDP of Jordan in 2020 decreased by 3.76% reaching 43.70 billion US Dollars (Trading Economics 2020). Moreover, the GDP per capita in 2019 was 4,426$US, decreasing to 4,259$ US in 2020 due to the government’s late response to the pandemic (Jordan GDP per Capita, 1980–2020—Knoema, 2021).

Case of New York State, USA

New York state is ranked as the fourth most populated state in the United States, with a total population of 19,299,981 as of 2021, and a total area of 783.8 km² (U.S. States by Size in Square Miles 2020).

As such, the population density of the city is 38,242 people per square kilometre, making it the densest city in the United States (New York Population 2021 Demographics, Maps, Graphs, 2021). By the year 2020, the total gross domestic product (GDP)of the United States decreased by 2.3% reaching US $ 20.93 trillion $ (Gross Domestic Product, 4th Quarter and Year 2020 (Advance Estimate) | U.S. Bureau of Economic Analysis (BEA), 2021). This was a larger drop for the state of New York due to COVID-19 and the governments' restrictions, declining by 36% in the second quarter of 2020 (New York’s Economy and Finances in the COVID-19 Era 2020).

In USA, The GDP per capita in 2019 was recorded to be US $ 65,254, with a change of 3.49% from the preceding year, however, in 2020 the GDP per capita decreased to US $ 63,416, changing by − 2.82% (United States of America GDP per Capita, 1980–2020—Knoema.Com, 2021).

Case of Sao Paulo, Brazil

The city of Sao Paulo is the largest among all cities in Brazil. As of 2021, Sao Paulo has a total population of 22,237,472 and an area of 1,521 km², with a density of 7,216.3 people per square kilometer (Sao Paulo Population 2021 Demographics, Maps, Graphs, 2021). Owing to its position as the foremost industrial center in Latin America, the Brazilian federal government has to initiate actions and programs that guarantee corporate income and business durability. The COVID-19 emergency assistance program has reached 66 million people, with payments of 50.7 billion US $, or close to 3.9% of GDP. In total, the federal government spent around 111 billion US$, nearly 8.6% of GDP. The central bank has also supported credit expansion in the financial system, which underpinned a rise of over 37%, equal to 1.7% of GDP. Overall, monetary and lending measures of around 12% of GDP were allocated to the COVID-19 response. As an outcome of these resources, more than 50% of the Brazilian population obtained support to counteract the fall in their income resulting from 10 million job losses in the first four months of the pandemic (ECLAC 2020).

Case of Bengaluru, India

As of 2021, Bengaluru is the capital and largest city in Karnataka state in India, with a total population of 12,764,935 (Bangalore Population 2021 Demographics, Maps, Graphs, 2021), and a total area of 709 km². It is also dubbed as the "IT capital of India", as it houses a multitude of Indian IT companies. Due to the pandemic, India's GDP growth rate was one of the slowest among emerging economies (currently $1.956 Trillion), with the number of poor people increasing by nearly 7.5 scores. According to the Pew Research Center, the pandemic pushed 32 million people into poverty in India last year, taking into consideration the majority of the 54 million people globally falling-out from the middle social class (Singh and Kumar 2021).

India's coronavirus cases and deaths have broken world records reporting 314,835 new cases on one day, surpassing the previous one-day high reported in the United States (297,430) in January 2021 (India—COVID-19 Overview—Johns Hopkins, 2021a). However, working with the assumption that the pandemic has worsened inequality in India, hence, the increase in poverty would have been far greater than predicted, along with the likelihood of shrinking the middle class (Das 2021).

Case of Shanghai, China

China was one of the first countries to be affected by COVID-19, positioning the country at the frontline of combating the pandemic as the virus emerged from the city of Wuhan. While the virus was still being investigated, Shanghai was one of the first cities to implement COVID-19 preventive measures.

Shanghai is the most populous city in China and the world, with a population of 26,317,104, in a total area of 6,340 km² (World City Populations 2021, 2021), along with being deemed as a central financial hub. As of 2020, the local GDP Per Capita is 24,046.23$US, which surprisingly has increased by 1.7% due to the government cutting taxes, which later proved helpful in keeping unemployment rates below 4.4%. Furthermore, the city encouraged digital enterprise development, allowing significant economy growth by 17.6%. This encouragement, in turn, gave the city a chance to recover from the losses occurring due to the pandemic (Global Times 2021).

Comparative analysis

Case study findings

To facilitate a fair comparison and identify common factors among the selected cities, this research examines significant inequalities in each city and their impact on their response to the crisis. In Table 1, we provide general information about these cities, including their population, area, GDP as of 2019–20, and the number of COVID-19 cases and deaths as of July 20, 2021, sourced from the World Health Organization (WHO).

Table 1 General information of selected cities and number of COVID-19 cases and deaths (Ritchie 2020)

Key percentages to consider are the proportion of COVID-19 cases relative to each city's population. Bengaluru and New York exhibit higher percentages at approximately 31.76% and 31.19%, respectively. In contrast, cities like Shanghai and Abu Dhabi have notably lower percentages of cases, at approximately 0.42% and 6.73%, respectively.

For the percentage of total deaths in relation to the population, Amman has a relatively high percentage of cases, approximately 79.67%, compared to its population. In contrast, other cities like New York show lower percentages of deaths relative to their populations, with New York at approximately 0.37%.

These percentages reveal the varying impact of COVID-19 in each city, highlighting the different degrees of effect on their populations.

The following figures represent the significant dates in the pandemic; first confirmed cases, case peak, first death, death peak, and lockdown implementation and lifting, to further understand the situation each city.

Figure 1. shows the first case and peak in each compared city; the figure indicates that cities like Abu Dhabi, Amman, and New York state took the longest to reach their daily case peak. However, New York is the highest number of cases out of the three. Moreover, Sao Paolo, since the start of the pandemic, reached its peak and amounted up to 20,483 cases in one day.

Fig. 1

Abu Dhabi, Amman, New York state, Sao Paolo, Shanghai, and Bengaluru first confirmed cases of COVID-19 and peak timeline peak timeline (Ritchie 2020; Timeline: WHO's COVID-19 Response 2020)

Figure 2. The following figure presents the first confirmed death and peak in each city that was chosen to compare. In addition, the death toll has also been included, where the highest death count of 1,082 was in Sao Paulo in late May, and the lowest was Shanghai having a peak of one death in a day.

Fig. 2

Abu Dhabi, Amman, New York state, Sao Paolo, Shanghai, and Bengaluru first confirmed death from COVID-19 and peak timeline (Ritchie 2020; Timeline: WHO's COVID-19 Response 2020)

Figure 3. represents the dates and the duration of the city-wide lockdown imposed as an emergency response to COVID-19. Amman, New York, Sao Paulo, and Bengaluru had a similar range in their implemented lockdown, where it generally lasted from 3 to 4 months. It can be noted that Abu Dhabi sustained the most extended lockdown of the compared cities. In contrast, Shanghai did not impose a lockdown but instead opted to enforce a 14-day quarantine period on anyone entering the city on 25th Jan 2020. Other cities later implemented this measure to reopen while maintaining infection rates.

Fig. 3

Emergency COVID-19 lockdown timeline for Abu Dhabi, Amman, New York state, Sao Paolo, Shanghai, and Bengaluru (Ritchie 2020; Timeline: WHO's COVID-19 Response 2020)

Analysis of comparative study between Abu Dhabi and Amman

Provided in Table 2 are the major findings of the comparative analysis of Abu Dhabi and Amman cities based on the three criteria highlighted in "Case studies" section

Table 2 Comparative study between Abu Dhabi and Amman

Based on the governance impact criterion in Table 2, both capitals' governmental restrictions and rules were similar. They followed the policies listed by the World Health Organization (WHO); however, with different implementation approaches. The major factor assisting Abu Dhabi throughout the pandemic timeline was its pre-existing emergency response system run by National Crisis and Emergency Management Authority (NCEMA). This enabled the city to be vigilant in detecting the virus, even issuing the first alert of the pandemic before it was announced as an international level public health emergency by WHO (al Hosany et al. 2021).

Abu Dhabi government practiced excellent risk communication with its public through a platform named "Weqaya" by NCEMA, catering to various groups in the community, while providing detailed awareness campaigns and updates on the status of the pandemic. Additionally, the city pushed the social distancing regulations standards set by WHO from 1 to 2 m, practiced the use of face masks before it was issued as a policy by WHO (al Hosany et al. 2021). Moreover, the city has closed public gathering spaces without entirely limiting the circulation in the capital except for the specific curfew hours of 8 pm–6 am. However, access from other cities in the UAE was entirely restricted. Additionally, the government of Abu Dhabi during the lockdown duration ensured mental health and safety for all its citizens by launching awareness campaigns, postponing fees, reducing bills, and providing aid to the elderly. They have also launched a National Disinfection Program to disinfect the city from the virus (al Hosany et al. 2021).

On the other hand, in the case of Amman, the governmental regulations restricted movement without any exceptions for an extended period, with the effects of prolonged confinement being damaging to mental health (Jordan: The Toughest Lockdown in the World | KfW Development Bank 2021).

Amman’s forced lockdown permitted citizens movement only when shopping for necessities to neighbouring supermarkets (Jordan: The Toughest Lockdown in the World | KfW Development Bank 2021). In addition, bread and water were distributed to houses with buses and vehicles. Still, the service caused overcrowding in some neighbourhoods in the capital (BBC News 2020).

On the other hand, Abu Dhabi has created many field hospitals, transformed large spaces, formed screening centres, and dedicated hospitals for COVID-19 patients in various parts of the city (AlQutob et al. 2020). They have enough medical gear and equipment to supply different medical facilities to help accommodate patients (al Hosany et al. 2021). However, Amman had several field hospitals and hospitals that accept Coronavirus patients. Abu Dhabi was prepared to control the pandemic with its resources, citizens' cooperation, and preparedness plans (Abu Dhabi Government Incentives in Light of COVID-19 in Can Be Viewed Here. 2021). According to Table 2, Amman struggled with managing the disease due to the citizens' response and minimal resources. Abu Dhabi also launched a disinfection program to prevent the spread of the disease and ensure safety for all citizens and was careful to label it as a "Disinfection program" in lieu of lockdown to manage panic and provide a sense of security that extended for months till the outbreak subdued (Smart Solutions to Fight COVID-19-The Official Portal of the UAE Government 2020).

Similarly, Amman had a disinfection program for a short period to sanitize terminals, buses, stores, and streets (Constructionweekonline 2020). Moreover, both capitals used virtual learning during the outbreak through various platforms and applications. Additionally, they have both created applications that monitor and track COVID-19 cases. Nevertheless, Abu Dhabi had a wider variety of applications that catered to many users like senior citizens and Abu Dhabi citizens abroad, as depicted in Table 2. Furthermore, Abu Dhabi extended its technology by utilizing drones and robots to disinfect and monitor people breaking social distancing laws or going outside curfew hours (Smart Solutions to Fight COVID-19-The Official Portal of the UAE Government 2020).

Based on Table 2, the delay in receiving the wave of the COVID-19 pandemic has played in favour of both cities. However, Abu Dhabi's strong economy and emergency plans enabled them to withstand the lockdown for a more extended period and carry out its response swiftly with the cooperation of the residents. On the contrary, Amman started strong yet did not have enough resources to carry out their lockdown since it risked the livelihood of the citizens; the circumstances forced them to return to their jobs. This comparison proves that a delay in the wave only helps learn how other cities respond to the emergency. However, it is almost impossible to sustain that response without enough resources.

Table 2 shows the comparison of the capitals Abu Dhabi and Amman. Both cities have similar geographic locations in which they are in the Gulf region. Additionally, Abu Dhabi and Amman received a delay in the wave of the coronavirus long after a significant number of cities got hit by it. The capitals dealt with the outbreak in different ways through governmental restrictions and the supply of medical gear. However, they had similar approaches by following the policies set by WHO and monitoring the spread through applications and websites.

Analysis of comparative study between Sao Paulo and New York State

Both Sao Paulo and New York faced terrible times due to the substantial rise of COVID-19 cases. Although each city struggled to mitigate the outbreak, they had a plan to control the spread by enforcing lockdowns. The government requested people to stay home, limiting the capacity at non-essential businesses and setting a national curfew. All these prevention measures are effective; however, they were not successful in these cases as demonstrated from the analysis shown in Table 3.

Table 3 Comparative study between Sao Paulo and New York

Both presidents represented a failed model for their citizens by spreading false information about the virus, demeaning the level of threat COVID-19 had on people's lives, and dismissing any safety precautions issued by the world's health organization (WHO).

As shown in Table 3, Sao Paulo had Bolsonaro shunning masks, advocating for fake healing methods, and favouring the economy over the safety of his people. The citizens of Sao Paulo were influenced by their leader, thus ignoring the safety rules enforced to minimize virus spread. In addition, New Yorkers also had to witness Former President Trump belittle the Coronavirus, which caused them to disregard precautions.

The adverse reactions of Former President Trump and Bolsonaro reduced their credibility in the publics’ eyes due to not showing any concern for the safety of their people. Furthermore, both failed to demonstrate any understanding of the situation's risks and ramifications, resulting in a consistently high infection rate and shortage of medical resources.

Although New York and Sao Paulo had a similar outcome to COVID-19, there were special measures that New York state has implemented to control the transmission of the virus. New York has transformed various public spaces into COVID-19 testing centres and field hospitals; this was an effort to treat more patients. Moreover, New York transformed dorms, nursing homes, ships, large public spaces, centres, and hotels for quarantine purposes and medical treatment of COVID-19 patients; this is undoubtedly a preventative measure that Sao Paulo could have implemented to manage the excessive numbers of patients. As the COVID-19 pandemic continues to grow, cities must adopt ways to have a plan of action to build resilience against any shortcomings.

Sao Paulo and New York lacked medical equipment at crucial times. In both cases, oxygen supplies were rationed, ICU beds were fully occupied, and both staff and equipment were lacking. Additionally, hospitals experienced overcrowding, due to the high number of cases. However, local manufacturers in New York contributed to resolving the issue through producing a sufficient number of medical equipment to cover the city's needs.

Ultimately, these two cases showed a failed example of governance where leaders were supposed to direct and help solve the problem. As such, unfortunately, both New York's and Sao Paulo's leaders were part of the problem, causing great panic and promoting negligence, contributing to the increased number of cases.

This table draws a comparison between two major cities around the world; Sao Paulo and New York. These two cities have a similar density. The table illustrates many ways in which the governments of each city had a drawback, whether it was a shortage in supplies, response, and digital infostructure and monitoring.

Analysis of comparative study between Shanghai and Bengaluru

Both cities were one of the few cities that were hit by the pandemic in its first stages, however, with different approaches towards containing its progression, as highlighted from the analysis included in Table 4. Shanghai was more proactive in solving the COVID-19 problem than Bengaluru. Since China had prior experience with the SARS pandemic, they implemented the most effective solution being the "suppression strategy," by hunting down the virus instead of resisting it to cut the transmission levels to zero. This strategy gave Shanghai a more explicit goal in creating technologies that helped track high transmission areas. Using satellites and GNSS constellations like the BeiDou and GAOFin, created maps showing the geographical location distribution of new confirmed cases, cumulative diagnoses, and recovered cases as shown in Table 4.

Table 4 Comparative study between Shanghai and Bengaluru

As mentioned in the spatial and temporal inequality, Shanghai and Bengaluru faced the issue of slums and closed dormitory-style housing, which made social distancing impossible. The In Urban world policy issued by the UN (Policy Brief: COVID-19 in an Urban World 2020) dictated that adequate housing is paramount to adhering to the coronavirus social distancing and hygiene guidelines; therefore, the lack of it is an inequality of itself leading to the high rates of COVID-19 cases in poor and rural areas. Nonetheless, Shanghai evicted some of those areas, which helped lessen the congestion. Unfortunately, Bengaluru could not do the same and still suffered from the large outbreak in those areas; especially those where most residents were poor and could not afford to move to different areas. In addition, the disregard for the dangers of the pandemic resulted in a significant shortage in medical supplies, a pre-existing problem in Bengaluru, yet worsened with the second wave with the number of COVID-19 cases reaching 2 million as shown in Table 1. This issue was mitigated by countries sending relief of supplies and helping them build more field hospitals to increase their bed capacity and oxygen supplies.

Bengaluru, though it had to suffer from the two waves of the coronavirus pandemic, the city managed to successfully create tracking technologies to deal with the growing outbreak. They utilized GIS and GPS to map and track patients, while also using heat mapping to locate congested areas and draw up containment plans. In addition, both cities used surveillance technologies, with Bengaluru using the BBMP Contain app, drones, and closed-circuit televisions (CCTVs), while Shanghai utilizing robots and drones as well as satellites.

Overall, Shanghai's approach to technology was much more rounded due to prior experience with pandemics. This enabled Shanghai to act early and focus on terminating the source of the problem, as opposed to the high level of negligence seen in the case of Bengaluru.

This table represents a comparison between two major Asian cities: Bengaluru and Shanghai. The cities' response to the COVID-19 pandemic was technology-centred; however, each utilized it to suit their demands. While Bengaluru centred on information technology and Shanghai was more versatile in its approach and took on both information technology and biotechnology, both cities provide excellent examples of the latest smart tools that can mitigate and control the intensity of coronavirus.

These cities demonstrate the vital role of technology in fighting against emergencies and pandemics to ensure the safety of their communities.

Conclusion for the analysis and comparison of the case

According to the comparative analysis, it became apparent that poverty, culture, and governance are primary factors that control the success of states under emergency. Moreover, it is understood that technology is a significant factor in combating pandemics and health emergencies as large as COVID-19, especially for tracking and monitoring. Each city had a different approach in utilizing the technology, thus proving its versatility and usefulness. Furthermore, it is noticeable that the cities that understood their inequalities and weak points were the most successful examples, like Abu Dhabi and Shanghai.

In the case of how the governance practice impacted the cities' response, inequalities were discovered, such as time, resources, and response speed. For example, cities like Amman implemented proper measures against the pandemic but failed to sustain it for long durations due to their economic standing and lack of resources. Moreover, the case of Sao Paulo, New York, and Bengaluru showed that unless the community cooperates, any implemented initiatives will fail.

In successful examples like Abu Dhabi and Shanghai, both had a different type of advantage. Abu Dhabi received the pandemic wave later than other cities, ensuring they had enough time to prepare for the outbreak and develop their technologies with their government-funded emergency response team. On the other hand, Shanghai already experienced the SARS outbreak in 2002, giving them enough knowledge and prior experience to control the spread and progression of such pandemics.

Despite the geographical location and circumstances (criteria) of the six case studies, the factors that were more influential in the creation of spatial and temporal inequality were primarily governance negligence and a lack of resources. In the case of Amman, it suffered from a shortage of beds, forcing them to rely on aids. COVID-19's impact has united with existing socio-economic vulnerabilities (Cities Policy Responses 2020). The crucial factor in the crisis was not the urban density but rather the urbanization quality and structural inequalities, hence disproportionately affecting unprotected populations and minorities like immigrants, POC, poor, the homeless, women, and the elderly(Cities Policy Responses 2020).New York and Sao Paulo were at a significant disadvantage when it came to the lack of medical resources and the overflow of patients; nevertheless, New York chose to manufacture more supplies and build field hospitals. On the other hand, Shanghai's government implemented an initiative to return immigrant workers to their villages. In addition, it urged international students to stay in their countries to lessen the density and solve the issue of overpopulation in the region. The same issue was faced in Bengaluru, since the city housed many settlement-like buildings; however, the government took no action to solve this overcrowding issue. Therefore, as a measure to solve those inequalities, post-pandemic urban design adapted must respect social distancing rules (Culture Shock: COVID-19 and the Cultural and Creative Sectors 2020).

Finally, the paper also focused on the impact of digital infrastructure on monitoring and tracking, displaying how cities utilized technology to fight the pandemic. For example, the standard utilization of technology in Amman, New York, and Sao Paulo was focused on monitoring and tracking patients and assessing the infection rates. However, Shanghai prioritized locating the sources of the infection rather than its spread, giving them the advantage in terminating the sources of infection in that region. Further, cities like Abu Dhabi, Bengaluru, and Shanghai provided a comprehensive approach using technology, as they used it in the medical aspect of the pandemic, which later helped them create solutions to combat the virus. Although, the variety in utilization gives varied results. Monitoring was needed to track and understand the level of damage being done to the city. In contrast, a comprehensive approach provided the cities with a better grip on the pandemic to understand it and resolve it.

Factors and recommendations

Through the analysis and comparison conducted in this work, we conclude that it is essential for governments to work together with local and international NGOs and accept and fairly distribute international aids for the common interest of the public. On the other hand, governments should refrain from using their national power and influence to provide or receive aid, as this can create inequalities in responses to COVID-19 and hinder international collaboration. (Ryan 2020). Good governance that targets resilience should call for a multi-layer collaboration (Sharifi and Khavarian-Garmsir 2020).

It is clear that if the inequalities in cities persist, public health could be threatened since enforcing protective measures will become difficult (Sharifi and Khavarian-Garmsir 2020). Hence, identifying and stopping such inequalities is necessary, and each government should prioritize the city recovery plan from the pandemic (Florida et al. 2021). However, this cannot be done without policies that protect the most vulnerable areas (Du et al. 2020).

Finally, and for future research, we recommend exploring the social changes that COVID 19 may bring in both short and long terms in the structure and morphology of cities, suburbs, metropolitan, and regions at different geographical scales (Airhihenbuwa et al. 2020).

Limitations

Due to the immediacy of the topic the authors referred, while starting this research, to news and references on websites. Later references have been updated and peer-reviewed journals and reliable reports from United Nations and OECD have been considered and added. The data gathered in this paper are subjective to change due the ongoing pandemic and new results and reports that are produced and published daily. Therefore, everchanging numbers of cases and deaths are undeniably anticipated. Furthermore, this paper adopted certain criteria for the comparisons that were made between each two cities. However, there are additional measures that can be used for drawing conclusions.