COVID-19 and urban vulnerability in India

Age, gender and household infrastructural inequality in COVID-19: Contextual analysis of Mamelodi

BACKGROUND

 Age, gender and household infrastructure are important social determinants affecting health inequalities. This study aims to assess the ways that age and gender of the household head and household infrastructure intersect to create relative advantage and disadvantage in COVID-19 vulnerability.

METHODS

 Using household primary care survey data from Mamelodi, Gauteng, headed households were sorted into three risk categories for each of the relevant infrastructural determinants of COVID-19. Bivariate ordinal logistic regression was used to determine the odds of households falling into each risk category. The proportion of high-risk (HR) categories and dwelling types was also calculated.

RESULTS

 Households headed by someone ≥ 65 years were less likely to be in all HR categories and more frequently had formal houses. Male-head households were more likely to be HR for water, sanitation and hygiene infrastructure and indoor pollution; however, female-headed households (FHHs) were at higher risk for crowding. In Mamelodi, households headed by ≥ 65 years olds were relatively infrastructurally protected, likely because of pro-equity housing policy, as were FHHs, except for crowding. The care load on FHHs results in their infrastructural protection benefiting more community members, while simultaneously incurring risk.

CONCLUSION

 Infrastructural support based on the household head's age and gender could improve targeting and the effectiveness of health interventions. These results demonstrate the importance of a contextual understanding of gender and age inequalities and tailoring public health support based on this understanding.Contribution: This research describes patterns of health-related infrastructural inequality, identifies ways to improve health interventions, and demonstrates the importance of equity-focused policy in an African context.

Urban Health Scholarship and Practice in the Post-Pandemic Era

The COVID-19 pandemic highlighted several challenges that cities face that can affect the health of urban populations. These challenges are an opportunity for sharpening of our urban health scholarship, to rethink the questions the field should be asking, and how the answers to those questions should guide practice. The central role of inequities in cities, the politics of urban health, communication for health, the deployment of health care, and the future of urban living are all areas that merit attention by scholars and practitioners in the field in coming decades.

Preparing for the next outbreak: A review of indices measuring outbreak preparedness, vulnerability, and resilience

The COVID-19 pandemic has highlighted the need for relevant metrics describing the resources and community attributes that affect the impact of communicable disease outbreaks. Such tools can help inform policy, assess change, and identify gaps to potentially reduce the negative outcomes of future outbreaks. The present review was designed to identify available indices to assess communicable disease outbreak preparedness, vulnerability, or resilience, including articles describing an index or scale developed to address disasters or emergencies which could be applied to addressing a future outbreak. This review assesses the landscape of indices available, with a particular focus on tools assessing local-level attributes. This systematic review yielded 59 unique indices applicable to assessing communicable disease outbreaks through the lens of preparedness, vulnerability, or resilience. However, despite the large number of tools identified, only 3 of these indices assessed factors at the local level and were generalizable to different types of outbreaks. Given the influence of local resources and community attributes on a wide range of communicable disease outcomes, there is a need for local-level tools that can be applied broadly to various types of outbreaks. Such tools should assess both current and long-term changes in outbreak preparedness with the intent to identify gaps, inform local-level decision makers, public policy, and future response to current and novel outbreaks.

Pandemic vulnerability index of US cities: A hybrid knowledge-based and data-driven approach

Cities become mission-critical zones during pandemics and it is vital to develop a better understanding of the factors that are associated with infection levels. The COVID-19 pandemic has impacted many cities severely; however, there is significant variance in its impact across cities. Pandemic infection levels are associated with inherent features of cities (e.g., population size, density, mobility patterns, socioeconomic condition, and health & environment), which need to be better understood. Intuitively, the infection levels are expected to be higher in big urban agglomerations, but the measurable influence of a specific urban feature is unclear. The present study examines 41 variables and their potential influence on the incidence of COVID-19 infection cases. The study uses a multi-method approach to study the influence of variables, classified as demographic, socioeconomic, mobility and connectivity, urban form and density, and health and environment dimensions. This study develops an index dubbed the pandemic vulnerability index at city level (PVI-CI) for classifying the pandemic vulnerability levels of cities, grouping them into five vulnerability classes, from very high to very low. Furthermore, clustering and outlier analysis provides insights on the spatial clustering of cities with high and low vulnerability scores. This study provides strategic insights into levels of influence of key variables upon the spread of infections, along with an objective ranking for the vulnerability of cities. Thus, it provides critical wisdom needed for urban healthcare policy and resource management. The calculation method for the pandemic vulnerability index and the associated analytical process present a blueprint for the development of similar indices for cities in other countries, leading to a better understanding and improved pandemic management for urban areas, and more resilient planning for future pandemics in cities across the world.

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

INTRODUCTION

Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.

METHODS

Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R₀), daily reproduction number (R_e), and case doubling time. Based on pre-restriction and Phase 1 R₀, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis.

RESULTS

The estimated median R₀ during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, -15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, -204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83).

CONCLUSION

Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.

Striving for wellbeing digitally in the city amidst the pandemic: Solidarity through Twitter in Ankara

This article elaborates on the utilization of social media for practices of interaction in the city during the COVID-19 pandemic and discusses its potential in providing for the wellbeing of urban communities. During the early periods of the pandemic when preventative measures were taken intensively to decrease contamination, communities lacked physical relationships with and within cities. Interactions realized in physical spaces in normal conditions were compensated with practices in social media. While such shift can be perceived to have decreased the meaning of cities in the pursuit of daily life and interactions, efforts which were localized upon physical human settlements yet were realized in the digital realm seem to have opened alternative paths for connection among residents. Within this context, we explore Twitter data through three hashtags which were promoted by the local government of Ankara and used densely by the residents in the early periods of the pandemic. Considering that social connection is one of the fundamental enablers of wellbeing, we aim to provide insights into the strive for wellbeing in times of crises where ruptures in physical interaction prevail. The patterns we observe in the expressions that gather around the selected hashtags shed a light on the ways the cities, their people and local governments are positioned in the struggles pursued in digital realm. Our findings support our arguments that social media has significant potential in contributing to the wellbeing of people especially in times of crisis, local governments can increase the quality of life of their citizens with modest actions, and the cities hold significant meanings for people as loci of communities and thus of wellbeing. Through the discussions we pursue, we seek to contribute to the stimulation of research, policies, and community actions that aim at the enhancement of wellbeing of urban individuals and communities.

Vulnerability, neglect, and collectivity in Brazilian favelas: Surviving the threats of the COVID-19 pandemic and the state's necropolitics

The COVID-19 pandemic has deepened existing inequities and injustices in Brazil, seen in the disproportionately detrimental impacts on favelas. State policy responses to the pandemic have disregarded favela residents' experiences. Recommendations such as 'shelter-in-place' ignore the reality of over 11.4 million favela residents who cannot work from home or afford to stop working, nor practise physical distancing from others. This study investigates the discourse of community organisations in favelas as they respond to the threats of the COVID-19 pandemic and the state's necropolitics. Community organisations in favelas have taken action to protect their residents from the virus, unemployment and hunger. I assess organisations' (1) justification to act as a collective in their communities, and (2) stances about the government's responses to the crisis. Through content analysis of social media, websites and media appearances of eight favela organisations and collectives in São Paulo and Rio de Janeiro, this study finds three main themes through which organisations justify their actions: vulnerability, neglect, and collectivity and care. More than survival strategies, the actions of favela organisations are counter-political acts as they oppose the decrepit necropolitics of the state by collectively enduring in the Brazilian context of the COVID-19 pandemic. Understanding favela organisations' actions in response to the pandemic is fundamental. It further illuminates the impact of public health emergencies in the lives of informal settlements' residents and the governance of public health emergencies in these communities.

Mitigating the impacts of the COVID-19 pandemic on vulnerable populations: Lessons for improving health and social equity

The COVID-19 pandemic had an inequitable and disproportionate impact on vulnerable populations, reversing decades of progress toward healthy populations and poverty alleviation. This study examines various programmatic tools and policy measures used by governments to support vulnerable populations during the pandemic. A comparative case study of 15 countries representing all World Health Organization's regions offers a comprehensive picture of countries with varying income statuses, health system arrangements and COVID-19 public health measures. Through a systematic desk review and key informant interviews, we report a spectrum of mitigation strategies deployed in these countries to address five major types of vulnerabilities (health, economic, social, institutional and communicative). We found a multitude of strategies that supported vulnerable populations such as migrant workers, sex workers, prisoners, older persons and school-going children. Prioritising vulnerable populations during the early phase of COVID-19 vaccination campaigns, direct financial subsidies and food assistance programmes were the most common measures reported. Additionally, framing public health information and implementing culturally sensitive health promotion interventions helped bridge the communication barriers in certain instances. However, these measures remain insufficient to protect vulnerable populations comprehensively. Our findings point to the need to expand fiscal space for health, enlarge healthcare coverage, incorporate equity principles in all policies, leverage technology, multi-stakeholder co-production of policies and tailored community engagement mechanisms.

Urban resilience to socioeconomic disruptions during the COVID-19 pandemic: Evidence from China

The COVID-19 pandemic and the associated restrictions have raised the awareness of building pandemic-resilient cities. Prior studies often evaluated the resilience of one type of urban system while lacking a comparison across various urban subsystems. This study fills this gap by measuring and comparing the adaptive resilience to the pandemic of various urban subsystems in Chinese cities. We propose a novel outcome measurement of the pandemic's socioeconomic impacts on cities, i.e., the citizens' complaints data, and use its temporal changes to measure cities' adaptive resilience to the pandemic. We find a wide range of urban subsystems were severely shocked by the pandemic, including the urban economy, construction-and-housing sector, welfare system, and education system. Different urban subsystems exhibit divergent degrees of adaptive resilience to the pandemic. Using cluster analysis, we also identify three types of cities with different patterns of adaptive resilience: cities whose general economies were the least resilient, cities whose construction-and-housing system was the least resilient, and cities that were mostly affected by restriction measures. Our findings contribute to the understanding of the pandemic's socioeconomic costs and help identify the divergent resilience of different urban subsystems so as to develop targeted policy interventions to improve cities' resilience to the pandemic.

No going back: COVID-19 disease threat perception and male migrants' willingness to return to work in India

This paper explores the causal link between the likelihood of re-migration to cities and the perceived threat of contracting COVID-19 using novel data on male reverse migrant workers in India. We find that reverse-migrants who believe there is a significant chance of contracting COVID-19 display a significantly lower likelihood of returning to their urban workplaces, regardless of their duration of migration. On the other hand, longer-duration migrants display a lower perceived chance of contracting COVID-19 than shorter-duration migrants. We also contribute to the migration literature by linking behavioural attributes to the decision to migrate. We find that more impatient individuals display a heightened belief regarding contracting COVID-19 and a higher projected likelihood of returning to work. Finally, we find that while both loss and risk-averse individuals have a lower projected likelihood of returning to urban workplaces, only loss-averse individuals perceive that their chance of contracting COVID-19 is lower.

Impact of COVID-19 pandemic on cultural ecosystem services from urban green spaces: a case from English Bazar Urban Agglomeration, Eastern India

Urban green space (UGS) provides multiple cultural ecosystem services (CES) and enhances people's physical and mental well-being. The importance of UGS was more critical during crisis periods such as the COVID-19 pandemic. Recently, UGS has been under severe threats due to rapid urban expansion and climate change. Particularly, the cities in developing countries have experienced a dramatic loss of green spaces due to land use and land cover (LULC) change. This study aims to assess the impact of the COVID-19 pandemic on CES perception obtained from two public UGS, i.e., Subhankar Sishu Uddyan (SSU) and Bandh Road (BR) in English Bazar Urban Agglomeration (EBUA), Eastern India. A survey was performed to assess the valuation of CES, CES obtained from UGS, and the use of CES difference during partial (unlock phases) and after lockdown periods. The non-parametric tests were carried out to understand the significant differences between CES and UGS perceived by the respondents. Explanatory factor analysis was also performed to find the association among CES for each UGS. The results reported substantial variations of UGS use during partial and after lockdown periods. During the after-lockdown period, the UGS mainly were used for social relations (51%), spending time with relatives and friends (25%), spending time with children (11%) in SSU and walking (25%), spending time with relatives and friends (21%), and physical activities (17%) in BR. During the partial lockdown period, a significant difference between SSU and BR was recorded from social relations and health value among all CES. After the full lockdown period, a significant difference was observed in recreation, social relations, health, and aesthetic value. The frequency and duration of UGS use during partial lockdown periods substantially increased. About 12% of the total visitor visited UGS daily after the lockdown, whereas it was 4% during the partial lockdown. The study's findings will assist urban planners and policymakers in understanding the need for UGS to promote the well-being of the citizens.

A scoping review of the impacts of COVID-19 physical distancing measures on vulnerable population groups

Most governments have enacted physical or social distancing measures to control COVID-19 transmission. Yet little is known about the socio-economic trade-offs of these measures, especially for vulnerable populations, who are exposed to increased risks and are susceptible to adverse health outcomes. To examine the impacts of physical distancing measures on the most vulnerable in society, this scoping review screened 39,816 records and synthesised results from 265 studies worldwide documenting the negative impacts of physical distancing on older people, children/students, low-income populations, migrant workers, people in prison, people with disabilities, sex workers, victims of domestic violence, refugees, ethnic minorities, and people from sexual and gender minorities. We show that prolonged loneliness, mental distress, unemployment, income loss, food insecurity, widened inequality and disruption of access to social support and health services were unintended consequences of physical distancing that impacted these vulnerable groups and highlight that physical distancing measures exacerbated the vulnerabilities of different vulnerable populations.

A neighborhood-level analysis of association between social vulnerability and COVID-19 in ahvaz, Iran

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.

Film as a pedagogical tool for geography during the pandemic induced virtual classes

Film has always been an important medium to disseminate social issues through imageries and imaginaries. The present paper examines the importance of film in understanding contextual, geographical concept-metaphors through virtual classes that can unearth the potential of the teaching-learning process in the COVID-19 induced lockdown situation. Qualitative techniques are used here to analyze landscapes, communication and actions to reveal the importance of a film from Bollywood, the world's largest film producing hub, in the context of teaching geographical concepts via online digital-mode classes in the ongoing pandemic scenario. Besides, Bollywood film has a wider and strong subliminal effect on the human mind. In this connection, the present work shows how a teachers' team use geographic media literacy as a pedagogical tool to enhance their students' cognition in online classes. It further shows that film acts as a geographic teaching tool for making students aware of the subjective understanding of Geography through a sub-branch wise explanation of cinematic components. It is observed that, even in the absence of classroom activity, if the lecture/study materials are interlinked with film, it would render a good understanding of the required geographical know-how. This article thus introduces a new scope for devising a better and more resilient online teaching process that promises to enrich geographical studies' digital pedagogy.

A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran

Social vulnerability is related to the differential abilities of socio-economic groups to withstand and respond to the adverse impacts of hazards and stressors. COVID-19, as a human risk, is influenced by and contributes to social vulnerability. The purpose of this study was to examine the association between social vulnerability and the prevalence of COVID-19 infection in the counties of Khuzestan province, Iran. To determine the social vulnerability of the counties in the Khuzestan province, decision-making techniques and geographic information systems were employed. Also, the Pearson correlation was used to examine the relationship between the two variables. The findings indicate that Ahvaz county and the province's northeastern counties have the highest levels of social vulnerability. There was no significant link between the social vulnerability index of the counties and the rate of COVID-19 cases (per 1000 persons). We argue that all counties in the province should implement and pursue COVID-19 control programs and policies. This is particularly essential for counties with greater rates of social vulnerability and COVID-19 cases.

Community resilience to pandemics: An assessment framework developed based on the review of COVID-19 literature

The COVID-19 outbreak in 2019 and the challenges it posed to communities around the world, demonstrated the necessity of enhancing the resilience of communities to pandemics. In this regard, assessment frameworks can play an essential role and guide resilience-building efforts. However, the lack of a comprehensive assessment framework has led to a focus on sectoral evaluation. This study aims to propose an integrated framework for assessing the pandemic resilience of communities. For this purpose, we rely on a systematic review of literature indexed in major academic databases. We have thoroughly analyzed a total number of 115 related documents to extract relevant criteria. Findings show that many criteria and factors affect community resilience to pandemics. By inductive content coding in MAXQDA software, we have categorized these criteria into five dimensions of Institutional, Social, Economic, Infrastructural, and Demographic. Good leadership and management, insurance and governmental support, planning and preparation, expertise and labor, and available equipment and technologies are the most important institutional criteria. Communication and collective identity, mutual support, public safety and protection, public awareness, and social justice are the influential social criteria. Economic sustainability and resource availability are criteria of economic resilience. Sufficiency of services, public spaces, housing tenure, and transportation system are the main criteria related to the built environment and infrastructural dimension. Finally, demographic resilience includes physical health, psychological well-being, life quality, and hygiene. Based on these criteria, this study develops an integrated evaluation framework that researchers can implement along with conventional assessment and ranking methods to determine the level of community resilience to pandemics.

Institutional development and the government response to COVID-19 in China

As COVID-19 is pervasive across the globe, governments in different countries face the dilemma of restricting the transmission risk of the virus by social distancing while yet maintaining economic activity. Inadequate social distancing policies lead to more infection cases and deaths, while over stringent social distancing policies have significant economic cost implications. This study investigates the role of local government institutions in striking the balance between saving lives and economic recovery. We based our study on a sample of 28 provincial governments in China during the early outbreak of 2020 when the emergency responses of local governments were synchronous. The findings show that local governments in those provinces with lower degrees of marketization, which were accustomed to directly intervene in the social system, mandatorily quarantined many more close contacts for each confirmed case than those in the more market-oriented provinces whose social distancing policies took economic considerations into account. The 'overdone' (over stringent) social distancing policies in the more state-oriented provinces led to lower human mobility and economic growth. This study highlights the importance of taking economic considerations into account when adopting policies and strategies to combat the spread of COVID-19 and how different institution management cultures lead to different outcomes.

Implications of the COVID-19 pandemic for urban informal housing and planning interventions: Evidence from Singapore

The outbreak of the COVID-19 pandemic revealed the crucial role of social distancing and hygiene practices in reducing virus transmission and thus revealed the high risk of infection in urban informal housing. Through an empirical study of Singapore's infectious situation and antiepidemic measures, this paper shows that the number of infected migrant workers living in dormitories was three hundred times greater than the number of infected local urban residents, not only because of the migrants' 'vulnerable' position but also because their living conditions fostered widespread transmission of the virus. The dwelling conditions of migrant dormitories, such as overcrowded living spaces, widely shared sanitation facilities, and poor hygiene practices, present great challenges to standard prevention strategies and control measures. Adverse health impacts resulting from the lockdown of dormitories during the COVID-19 pandemic suggest the importance of planning intervention in the dwelling conditions of informal housing, and indicate a need for the governments' active reforms of building codes and health care systems to promote the health of disadvantaged groups and then create more inclusive and healthy cities for all the society.

Neighborhood, built environment and resilience in transportation during the COVID-19 pandemic

COVID-19 has swept the world, and the unprecedented decline in transit ridership has been noticed. However, little attention has been paid to the resilience of the transportation system, particularly in medium-sized cities. Drawing upon a light rail ridership dataset in Salt Lake County from 2017 to 2021, we develop a novel method to measure the vulnerability and resilience of transit ridership using a Bayesian structure time series model. The results show that government policies have a more significant impact than the number of COVID-19 cases on transit ridership. Regarding the built environment, a highly compact urban design might reduce the building coverage ratio and makes transit stations more vulnerable and less resilient. Furthermore, the high rate of minorities is the primary reason for the drops in transit ridership. The findings are valuable for understanding the vulnerability and resilience of transit ridership to pandemics for better coping strategies in the future.

Preferred hospitalization of COVID-19 patients using intuitionistic fuzzy set-based matching approach

Preferable hospitalization of COVID-19 patients has become an urgent and challenging task to save lives amidst the unexpected rising of the 3rd wave, where fuzzy set and matching techniques are considered due to their inherent capability to deal with uncertain suitable pair selection. The matching technique has been widely used to solve decision-making problems due to its capability to determine the suitable pair between the objects of two disjoint sets, whereas fuzzy set is well known to manage uncertain situations. This paper extends the matching technique using fuzzy set and proposes a novel fuzzy matching approach to solve uncertain decision-making problems. We also extend the fuzzy matching approach in the framework of an intuitionistic fuzzy set. A relation between the matching technique and fuzzy set theory is established by developing the preference sequence of the elements. The fuzzy entropy is used to measure the closeness among the elements between two distinct sets. Applicability of the proposed approach is measured by providing an illustrative case study concerned with the preferred hospitalization of the COVID-19 patients. Finally, a comparative study is given to analyze the effectiveness of the proposed approach, where the intuitionistic fuzzy set-based matching approach shows better performance compared to fuzzy and conventional matching based approach. For experimentation purpose, this study uses 9424 patients and 234 hospitals with a total available capacity of 18,024 beds.

Investigating the impacts of COVID-19 safety measures and related uncertainties among socially vulnerable groups in Lagos megacity

The emergence of the unique coronavirus disease (COVID-19), associated safety measures and impacts have been experienced differently across various sociodemographic and livelihood groups. As a result of the impacts of the COVID-19 restrictions, this study examined experiences and livelihood uncertainties from socially vulnerable groups. One hundred and fifty responses (150) were recorded from residents in Iwaya, and Makoko areas within Lagos Mainland Local Government Area of Lagos state. Complete lockdown or stay-at-home orders, compulsory face masks in public spaces, curfews, physical and social distancing and restriction of inter-state movements are some of the precautionary/safety measures introduced by the Government and enforced by security agents. The findings show that curfews and restriction of inter-state movements were two of the safety measures that had no or reduced impact (p-values > 0.01) on the respondents’ means of livelihood. Our results reveal that because a larger percentage of male participants are self-employed and owned personal businesses they were more affected by COVID-19 restrictions than females. 42.7% (64) of females and 57.3% (86) of males reported COVID-19-related anxieties and stress from fear of starvation, and contracting the virus, to impacts on money/finances, slow sales and businesses, food supply, job loss, erratic power supply affecting work from home options. 54.7% of respondents had more than 5 people living together, while 84.7% of housing types (128) are bungalows with several rooms inhabited by an average of three to four people per household. Increased stress, fear of hunger, loss of jobs and source of income were some of the negative impacts resulting from the introduction of the COVID-19 safety measures which adversely affected occupations like traders, people engaged in fishing activities, painters, carpenters, hairdressers and barbers, printers and bricklayers. Our work provides insights into the effects of the COVID-19-safety measures and subjective impact across vulnerable groups and occupations.

Evaluating the risk of accessing green spaces in COVID-19 pandemic: A model for public urban green spaces (PUGS) in London

The pandemic caused by SARS-CoV-2 (COVID-19) at the beginning of 2020 has restricted the human population indoor with some allowance for recreation in green spaces for social interaction and daily exercise. Understanding and measuring the risk of COVID-19 infection during public urban green spaces (PUGS) visits is essential to reduce the spread of the virus and improve well-being. This study builds a data-fused risk assessment model to evaluate the risk of visiting the PUGS in London. Three parameters are used for risk evaluation: the number of new cases at the middle-layer super output area (MSOA) level, the accessibility of each public green space and the Indices of Multiple Deprivation at the lower-layer super output area (LSOA) level. The model assesses 1357 PUGS and identifies the risk in three levels, high, medium and low, according to the results of a two-step clustering analysis. The spatial variability of risk across the city is demonstrated in the evaluation. The evaluation of risk can provide a better metric to the decision-making at both the individual level, on deciding which green space to visit, and the borough level, on how to implement restricting measures on green space access.

Are High-Altitude Residents More Susceptible to Covid-19 in India? Findings and Potential Implications for Research and Policy

In this paper, we study the incidence of COVID-19 and the associated fatality with altitude using high frequency, district level data from India. To understand the implications of the nationwide lockdown after the outbreak, we use data for about four months- two from the lockdown period starting from March 25 till May 31, 2020 and about two months after unlocking was initiated (June 1-July 26, 2020). The multivariate regression result indicates slower growth in average rate of infection during the lockdown period in hilly regions, the gains of which attenuated after the unlocking was initiated. Despite these early gains, the rate of fatalities is significantly higher during the lockdown period in comparison to the plains. The findings remain robust to multiple alternative specifications and methods including one that accounts for confounding possibilities via unobservable and provides consistent estimates of bias adjusted treatment effects. The evidence supports the need for provisioning of public health services and infrastructure upgradation, especially maintenance of adequate stock of life support devices, in high altitude regions. It also underscores the necessity for strengthening and revising the existing Hill Areas Development Programme and integrating important aspects of public health as part of this policy.

Infrastructural Inequality and Household COVID-19 Vulnerability in a South African Urban Settlement

COVID-19 has highlighted the importance of household infrastructure in containing the spread of SARS-CoV-2, with Global South urban settlements particularly vulnerable. Targeted interventions have used area or dwelling type as proxies for infrastructural vulnerability, potentially missing vulnerable households. We use infrastructural determinants of COVID-19 (crowding, water source, toilet facilities, and indoor pollution) to create an Infrastructural Vulnerability Index using cross-sectional household data (2018-2019) from Mamelodi, a low-income urban settlement in South Africa. Households were stratified into vulnerability groups by index results; sociodemographic variables were assessed as predictors of index scores; and inequality analysis and decomposition were conducted. Thirty-three percent of households fell in the lowest risk group, 32% in the second, 21% in the third, and 14% in the highest. Dwelling type and geographical ward were associated with changes in index scores, with a shack (adjusted β (aβ) = 3.45, CI = 3.39-3.51) associated with highest increase compared to a house. Wards in more developed areas were not consistently associated with lower index scores in the final regression model. The infrastructural vulnerability of the top 10% of households was greater than the bottom 40%, and inequality was predominantly within (80%) rather than between (20%) wards, and more between (60%) than within (40%) dwelling types. Our results show a minority of households account for the majority of infrastructural vulnerability, with its distribution only partially explained by area and dwelling type. Efforts to contain COVID-19 can be improved by using local-level data, and a vulnerability index, to target infrastructural support to households in greatest need.

Impacts of COVID-19 Pandemic on Micro and Small Enterprises: Evidence From Rural Areas of Iran

Since 2020, the outbreak of the COVID-19 crisis has caused a great deal of social and economic damages to micro and small-scale enterprises (MSEs). This research examined the most common damages of this crisis in active and inactive rural MSEs and also assessed different kind of responses the managers and owners of theses MSEs have received dealing with these damages. The sample population of this study consisted of all managers of 72 active and 38 closed rural MSEs in the Dastjerd village, Hamedan, Iran. These MSEs were mainly garment small factories. This research utilized a mixed approach (quantitative-qualitative) to study the research objectives in depth. First, in qualitative part, semi-constructed interviews and field visits were done. Then, using quantitative, results of the qualitative section, previous studies and the existing literature, a researcher-made questionnaire was created. Based on qualitative part information through interviews, damages of rural MSEs during COVID-19 pandemic were categorized into three classes, including damages related to production, and financial and marketing issues. Also, two categories of managers' responses that could be labeled as passive and adaptive behavior were identified. Findings showed that active rural MSEs have taken more adaptive measures and tried to find appropriate ways to reduce or overcome damages. Active MSEs were mainly owned and managed collaboratively by more literate and experienced managers. Also results revealed that rural MSEs' managers reacted to different kinds of damages based on their ability, knowledge, and experience. Based on research results, managers' knowledge and skills can help them find more adaptive solutions to keep the firms stable and overcome damages. It can be concluded that COVID-19 pandemic has a great impact on rural MSEs and they need more financial support and managerial advice to overcome this kind of crisis situation.

Corona was scary, lockdown was worse: A mixed-methods study of community perceptions on COVID-19 from urban informal settlements of Mumbai

The COVID-19 pandemic has magnified the multiple vulnerabilities of people living in urban informal settlements globally. To bring community voices from such settlements to the center of COVID-19 response strategies, we undertook a study in the urban informal settlements of Dharavi, Mumbai, from September 2020-April 2021. In this study, we have examined the awareness, attitudes, reported practices, and some broader experiences of the community in Dharavi with respect to COVID-19. We have used a mixed-methods approach, that included a cross-sectional survey of 468 people, and in-depth interviews and focus group discussions with 49 people living in this area. Data was collected via a mix of phone and face-to-face interviews. We have presented here the descriptive statistics from the survey and the key themes that emerged from our qualitative data. People reported high levels of knowledge about COVID-19, with television (90%), family and friends (56%), and social media (47%) being the main sources of information. The knowledge people had, however, was not free of misconceptions and fear; people were scared of being forcefully quarantined and dying alone during the early days of COVID-19. These fears had negative repercussions in the form of patient-related stigma and hesitancy in seeking healthcare. A year into the pandemic, however, people reported a shift in attitudes from 'extreme fear to low fear' (67% reported perceiving low/no COVID risk in October 2020), contributing to a general laxity in following COVID-appropriate behaviors. Currently, the community is immensely concerned about the revival of livelihoods, that have been adversely impacted due to the lockdown in 2020 as well as the continued 'othering' of Dharavi for being a COVID hotspot. These findings suggest that urban informal settlements like Dharavi need community-level messaging that counters misinformation and denial of the outbreak; local reinforcement of COVID-appropriate behaviours; and long-term social protection measures.

Rethinking urban density, vitality and healthy environment in the post-pandemic city: The case of Istanbul

The present study aims to examine the relationship between urban vitality, healthy environment and density through the city of Istanbul, which is going through the Covid-19 outbreak. In this context, an online survey was conducted to measure the assessments of the residents living in districts with different density categories regarding the neighborhoods and the city they live in. The evaluations made by the citizens in the dimensions of vitality, mobility, safety, healthiness, cleanliness, orderliness were reduced to two main factors as "urban vitality" and "healthy environment" using Principal Components Analysis. Then, the evaluations regarding these six variables and two factors were subjected to cross-inquiries with the personal, residential and district characteristics. Urban residents were also asked to evaluate the city life before and after the Covid-19 outbreak. The main findings of the study reveal that there is a statistically significant difference between the density levels of the districts in terms of the perception of urban vitality and some sub-variables of healthy environment. Also, there is an observed change in the thoughts about urban life in Istanbul due to the outbreak.

An Innovative Index for Evaluating Urban Vulnerability on Pandemic Using LambdaMART Algorithm

The COVID-19 pandemic has significantly changed urban life and increased attention has been paid to the pandemic in discussions of urban vulnerability. There is a lack of methods to incorporate dynamic indicators such as urban vitality into evaluations of urban pandemic vulnerability. In this research, we use machine learning to establish an urban Pandemic Vulnerability Index (PVI) that measures the city’s vulnerability to the pandemic and takes dynamic indicators as an important aspect of this. The proposed PVI is constructed using 140 statistic variables and 10 dynamic variables, using data from 47 prefectures of Japan. Factor Analysis is used to extract factors from variables that may affect city vulnerability, and the LambdaMART algorithm is used to aggregate factors and predict vulnerability. The results show that the proposed PVI can predict the relative seriousness of the COVID-19 pandemic in two weeks with a precision of more than 0.71, which is meaningful for taking controlling measures in advance and shaping the society’s response. Further analysis revealed the key factors affecting urban pandemic vulnerability, including city size, transit station vitality, and medical facilities, emphasizing precautions for public transport systems and new planning concepts such as the compact city. This research explores the application of machine learning techniques in the indicator establishment and incorporates dynamic factors into vulnerability assessments, which contribute to improvements in urban vulnerability assessments and the planning of sustainable cities while facing the challenges of the COVID-19 pandemic.

Are leading urban centers predisposed to global risks- A analysis of the global south from COVID-19 perspective

COVID-19 initially spread among prominent global cities and soon to the urban centers of countries across the globe. While cities are the hotbeds of activities, they also seem highly exposed to global risks including the pandemic. Using the case of COVID-19 and the World Risk Index framework, this paper examines if the leading cities from the global south are inherently vulnerable and exposed to global risks and can they exacerbate the overall risk of their respective nations. Compared against their respective national averages, most of the 20 cities from 10 countries analyzed in this paper, have higher exposure, lower adaptive capacity, higher coping capacity and varied susceptibility. As this relative understanding is based on respective national averages which are often lower than the global standards, even high performance on certain indicators may still result in elevated predisposition. This paper concludes that the leading urban centers from the global south are highly likely to be predisposed to global risks due to their inherent vulnerability and exposure, and many of the drivers of this predisposition are related to the process of urbanization itself. This predisposition can enhance the overall exposure and vulnerability of the nation in which they are located.

A decision support system for prioritised COVID-19 two-dosage vaccination allocation and distribution

This study proposes a decision support system (DSS) that integrates GIS, analytics, and simulation methods to help develop a priority-based distribution of COVID-19 vaccines in a large urban setting. The methodology applies novel hierarchical heuristic-simulation procedures to create a holistic algorithm for prioritising the process of demand allocation and optimising vaccine distribution. The Melbourne metropolitan area in Australia with a population of over five million is used as a case study. Three vaccine supply scenarios, namely limited, excessive, and disruption, were formulated to operationalise a two-dose vaccination program. Vaccine distribution with hard constraints were simulated and then further validated with sensitivity analyses. The results show that vaccines can be prioritised to society's most vulnerable segments and distributed using the current logistics network with 10 vehicles. Compared with other vaccine distribution plans with no prioritisation, such as equal allocation of vaccines to local government areas based on population size or one on a first-come-first-serve basis, the plans generated by the proposed DSS ensure prioritised vaccination of the most needed and vulnerable population. The aim is to curb the spread of the infection and reduce mortality rate more effectively. They also achieve vaccination of the entire population with less logistical resources required. As such, this study contributes to knowledge and practice in pandemic vaccine distribution and enables governments to make real-time decisions and adjustments in daily distribution plans. In this way any unforeseen disruptions in the vaccine supply chain can be coped with.

Immune status determined as per guidelines of Ayurveda found associated with clinical outcomes of COVID-19 disease - Results of a cross-sectional pilot study

BACKGROUND

A key public health priority during the emergence of a novel pathogen is probing the factors contributing in clinical severity of the disease COVID-19. Moreover, analysis of the determined clinical outcomes is required and thus, modifiable predictor values need to identified. In Ayurveda, outcome of a disease is a multivariate function and this exploratory work is an attempt to identify one such factor "Vyadhiksamatwa" (immune status).

MATERIALS AND METHODS

A questionnaire-based, cross-sectional study was conducted in fifty diagnosed cases of COVID-19. Study participants were subjected to a questionnaire to assess relationship between the three determinants of the disease - exposure, clinical severity, and Vyadhiksamatwa.

RESULTS

Clinical severity was found strongly correlated with Vyadhiksmatwa with the value of Pearson Correlation - 0.740 significant at the 0.01 level (2-tailed).

CONCLUSION

In the determination of clinical severity of disease, there are two epidemiological factors responsible - extrinsic (exposure) and intrinsic (Vyadhiksamatwa). It has been observed that higher the value of Vyadhiksamatwa of an individual, lesser will be the clinical severity of the disease in that individual. Vyadhiksamatwa can alter the host response to infections.

Geographical Appraisal of COVID-19 in West Bengal, India

Study shows that COVID-19 cases, deaths and recoveries vary in macro level. Geographical phenomena may act as potential controlling factor. The present paper investigates spatial pattern of COVID-19 cases and deaths in West Bengal (WB), India and assumes Kolkata is the source region of this disease in WB. Thematic maps on COVID related issues are prepared with the help of QGIS 3.10 software. As on 15th January 2021, WB has 564032 number of COVID-19 cases which is 0.618% to the total population of the state. However, the COVID-19 case for India is 0.843% and for world is 1.341% to its total population. Lorenz Curve shows skewed distribution of the COVID-19 cases in WB. 17 (90%) districts hold 84.11% of the total population and carry 56.30% of the total COVID-19 cases. However, the remaining two districts-Kolkata and North 24 Parganas-hold remaining 43.70% COVID-19 cases. Correlation coefficient with COVID-19 cases and Population Density, Urban Population and Concrete Roof of their house are significant at 1% level of significance.

Planning for pandemic resilience: COVID-19 experience from urban slums in Khulna, Bangladesh

COVID-19 worsened urban slum dwellers' pre-existing vulnerabilities. Maintaining WHO-suggested physical distancing/isolation made planning more challenging in slums. The scenarios hint at the urgency to investigate whether these resource-scarce communities – already susceptible to climate change, poverty, health services, infrastructure, and space constraints, could build resilience against COVID-19. What lack of resources/assets made communities vulnerable there, and what adaptation measures were taken? What planning/management practices were adopted there, and to what extent could WHO's IPC guidelines (on transmission prevention and control) be followed? Findings show that pre-COVID economic, infrastructural, and health-related issues had affected slum dwellers' COVID-time vulnerabilities. While poor infrastructure and sanitation, informal employment, livelihood diversity, superstition, and comorbidities remained the key ‘internal’ issues, lack of institutional preparedness and safety-net programs, discontinued municipal services and inaccessible/untrustworthy healthcare services and corruption/bias/non-coordination in beneficiary selection remained the key ‘external’ issues. Information sharing, openness to pandemic knowledge, and active participation in awareness/training programs have been the most adopted measures. Aid schemes, despite criticisms, saved dwellers from starvation. Therefore, this proved to be a critical coping element. However, NGOs systematic monetary aid gave dwellers the most flexibility in spending. On top, NGOs proved to be the most vital external stakeholder in all sectors except for built environment/planning. To increase adaptive capacity, scopes remain in maximizing the use of community infrastructure in future events. Simultaneously, spatial aspects, alongside the non-spatial, seemed crucial in tackling complex poverty profiles, resource-scarcity, and vulnerabilities of slums. Findings are based on NGO BRAC's existing dataset and fieldwork between April–August 2020 on 29 slums in Khulna, Bangladesh, using a qualitative methodology. The study contributes to a growing body of knowledge and practice on resilient planning for COVID-19 (and similar future pandemics), especially for slums, while addressing its overlooked spatial dimensions.

The role of pre-pandemic teleworking and E-commerce culture in the COVID-19 dispersion in Europe

The threats of the coronavirus have shifted the workplace of many people from office to home and also made e-commerce the primary medium for purchases. While these changes were made in an effort to mitigate contagion, there are no studies, to the best of our knowledge, that address if teleworking and e-commerce culture prior to the pandemic influenced the dispersion of the virus. In our study we examine whether pre-existing teleworking practices and e-commerce activity have played an important role in the COVID-19 dispersion in Europe. Based on a set of data from all European countries, the present study employs the Philips & Sul methodology to explore corona convergence patterns. Our findings suggest that pre-existing e-commerce activity and teleworking practices had little to no effect in reducing the initial opportunities of individuals to contract the virus leading to the conclusion that other social interactions must have played a more important role.

Habitat vulnerability in slum areas of India - What we learnt from COVID-19?

UN-Habitat identified the present COVID-19 pandemic as 'city-centric'. In India, more than 50% of the total cases were documented in megacities and million-plus cities. The slums of cities are the most vulnerable due to its unhygienic environment and high population density that requires an urgent implementation of public healthcare measures. This study aims to examine habitat vulnerability in slum areas to COVID-19 in India using principal component analysis and Fuzzy AHP based technique to develop slum vulnerability index to COVID-19 (SVI_covid-19). Four slum vulnerability groups (i.e. principal components) were retained with eigen-values greater than 1 based on Kaiser criterion - poor slum household status; lack of social distance maintenance; high concentrations of slum population and towns and mobility of the households. This study also mapped composite SVI_covid-19 on the basis of PCA and Fuzzy AHP method at the state level for a better understanding of spatial variations. The result shows that slums located in the eastern and central parts of India (particularly Uttar Pradesh, Bihar, Jharkhand, Odisha, West Bengal) were more vulnerable to COVID-19 transmission due to lack of availability as well as accessibility to the basic services and amenities to slum dwellers. Thus, the findings of the study may not only help to understand the habitat vulnerability in slum areas to COVID-19 but it will also teach a lesson to implement effective policies for enhancing the quality of slum households (HHs) and to reduce the health risk from any infectious disease in future.

Spatial priority for COVID-19 vaccine rollout against limited supply

The COVID-19 vaccines are limited in supply which requires vaccination by priority. This study proposes a spatial priority-based vaccine rollout strategy for Bangladesh. Demographic, economic and vulnerability, and spatial connectivity - these four types of factors are considered for identifying the spatial priority. The spatial priority is calculated and mapped using a GIS-based analytic hierarchy process. Our findings suggest that both demographic and economic factors are keys to the spatial priority of vaccine rollout. Secondly, spatial connectivity is an essential component for defining spatial priority due to the transmissibility of COVID-19. A total of 12 out of 64 districts were found high-priority followed by 22 medium-priorities for vaccine rollout. The proposed strategy by no means suggests ending mass vaccination by descending age groups but an alternative against limited vaccine supply. The spatial priority of the vaccine rollout strategy proposed in this study might help to curb down COVID-19 transmission and to keep the economy moving. The inclusion of granular data and contextual factors can significantly improve the spatial priority identification which can have wider applications for other infectious and transmittable diseases and beyond.

A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020

COVID-19 has infected over 163 million people and has resulted in over 3.9 million deaths. Regarding the tools and strategies to research the ongoing pandemic, spatial analysis has been increasingly utilized to study the impacts of COVID-19. This article provides a review of 221 scientific articles that used spatial science to study the pandemic published from June 2020 to December 2020. The main objectives are: to identify the tools and techniques used by the authors; to review the subjects addressed and their disciplines; and to classify the studies based on their applications. This contribution will facilitate comparisons with the body of work published during the first half of 2020, revealing the evolution of the COVID-19 phenomenon through the lens of spatial analysis. Our results show that there was an increase in the use of both spatial statistical tools (e.g., geographically weighted regression, Bayesian models, spatial regression) applied to socioeconomic variables and analysis at finer spatial and temporal scales. We found an increase in remote sensing approaches, which are now widely applied in studies around the world. Lockdowns and associated changes in human mobility have been extensively examined using spatiotemporal techniques. Another dominant topic studied has been the relationship between pollution and COVID-19 dynamics, which enhance the impact of human activities on the pandemic's evolution. This represents a shift from the first half of 2020, when the research focused on climatic and weather factors. Overall, we have seen a vast increase in spatial tools and techniques to study COVID-19 transmission and the associated risk factors.

Employment Loss in Informal Settlements during the Covid-19 Pandemic: Evidence from Chile

The Covid-19 pandemic has reached almost every corner of the world. Despite the historical development, approval, and distribution of vaccines in some countries, non-pharmaceutical interventions will remain an essential strategy to control the pandemic until a substantial proportion of the population has immunity. There is increasing evidence of the devastating social and economic effects of the pandemic, particularly on vulnerable communities. Individuals living in urban informal settlements are in a structurally disadvantaged position to cope with a health crisis such as the Covid-19 pandemic. Estimates of this impact are needed to inform and prioritize policy decisions and actions. We study employment loss in informal settlements before and during the Covid-19 pandemic in Chile, using a longitudinal panel study of households living in Chile's informal settlements before and during the health crisis. We show that before the pandemic, 75% of respondents reported being employed. There is a decrease of 30 and 40 percentage points in May and September 2020, respectively. We show that the employment loss is substantially higher for individuals in informal settlements than for the general population and has particularly affected the immigrant population. We also show that the pandemic has triggered neighborhood cooperation within the settlements and that targeted government assistance programs have reached these communities in a limited way. Our results suggest that individuals living in informal settlements are facing severe hardship as a consequence of the pandemic. In addition to providing much-needed support, this crisis presents a unique opportunity for long-term improvements in these marginalized communities.

Reconsidering the criteria of the healthy house's interior design during crises: COVID-19 pandemic as an example

Purpose

The advent of the COVID-19 pandemic brought various and radical changes at the worldwide level. Globally, severe preventive measures were imposed to respond to the crisis such as lockdowns which forced the people to quarantine themselves inside their houses for longer periods. This issue stressed the crucial role of healthy houses in providing the various needs of residents during crises.

Design/methodology/approach

This study methodology adopted both inductive approach and a Study Application Model to define the Healthy House Criteria and fulfill the study objectives. Under the inductive approach a holistic literature review was undertaken while the Study Application Model implied defining the conception of the overall Criteria of the Healthy House's interior design under the COVID-19.

Findings

The finding of the study showed some areas needed to improve current healthy house's criteria in terms of its interior design that may be used to cope with potential crises such as the COVID-19. Based on the revealed findings, the researcher suggested a conceptual framework for healthy house's criteria and further research areas.

Originality/value

The current research may provide applicable framework for both interior designers and households in terms of how to design and implement a healthy house, which is valid to accommodate residents during potential crises such as the COVID-19.

Geospatial modelling of COVID-19 vulnerability using an integrated fuzzy MCDM approach: a case study of West Bengal, India

COVID-19 is a worldwide transmitted pandemic that has brought a threatening challenge to Indian society and the economy. The disease has become a public health disaster, which has no effective medication. However, proper management and planning, which includes understanding the transmitting pattern, number of containment zones, vulnerable factors, and level of risk, may break the chain of transmission and reduce the number of cases. Hence, this study has attempted to model the COVID-19 vulnerability using an integrated fuzzy multi-criteria decision-making (MCDM) approach, namely fuzzy-analytical hierarchy process (AHP) and fuzzy-technique for order preference by similarity to ideal solution (TOPSIS) for West Bengal, India, through geographic information system (GIS). A total of 15 parameters were utilised to model the COVID-19 vulnerability, which was further categorised into three criteria: social vulnerability, epidemiological vulnerability, and physical vulnerability. The final vulnerability mapping has been done using these three criteria through the GIS platform. This study reveals that COVID-19 infection highly threatens about 20% of the total area of West Bengal, 23.42% moderately vulnerable, and 57.03% of the area comes under low vulnerability. The highly vulnerable region includes the Kolkata, South 24 Paraganas, and North 24 Paraganas, which are considered highly populated districts of West Bengal. Therefore government agencies should be more focused and plan accordingly to safeguard the community, especially the region with very high COVID-19 vulnerability, from further spreading the infection.

Assessment of sanitation service gap in urban slums for tackling COVID-19

Coronavirus disease 2019 (COVID-19), caused by Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has been declared as a global pandemic by the World Health Organization (WHO). As the disease is highly infectious, the Global South countries are in a vulnerable situation with high urban population density and lack of Water, Sanitation, and Hygiene (WASH) services. The situation for the urban slum dwellers and low-income group clusters are becoming worse. Lack of health and sanitation service availability has already been an issue for them before the beginning of the pandemic. So, it is predictable that adopting this massive global pandemic is a critical challenge for them. This paper assesses the sanitation service gap in urban slums, which has become a severe challenge to tackle due to COVID-19. The study areas of this research are the Ranarmath slum and the Khema slum of Khulna city, Bangladesh. The SERVQUAL model has been used to identify the quality of sanitation service available in these informal residential settlements. The interpretation of questionnaire survey data from the two slums reveals that one slum lacks Assurance and Empathy, where the other slum lacks Tangibility and Responsiveness. However, the Tangibility, Reliability, and Responsiveness condition of both slums are flawed with the lack of latrine functionalities and services from concerned authorities. The incompatibility of the condition has been identified by evaluating the WHO's different sanitation management policy for COVID-19. The research concludes that sanitation services like handwashing facilities and water supply availability in the latrine directly related to COVID-19 prevention are indigent for these slums.

Community Preparedness and Practices for Prevention and Control of COVID-19 (COP-COVID): An Assessment from Rural Northern India

OBJECTIVES

The study assessed the community preparedness to manage the coronavirus disease 2019 (COVID-19) and access to health-care services during the lockdown of 2020 in a rural health block of northern India.

METHODS

A cross-sectional study was conducted during June-July, 2020, in 25 villages and 5 wards of a rural administrative block of Haryana. A pretested, semi-structured investigator-administered checklist was used to assess the community preparedness and practices for COVID-19 prevention/control and health-care access through direct observations and interviewing community health workers and beneficiaries.

RESULTS

Active surveillance for influenza-like illness was carried out in 86.7% of the study units, although the frequency was once a month. There was poor adherence (adherence: 0-3%) to COVID-19 infection prevention and control (IPC) measures such as physical distancing and use of face masks. Rural beneficiaries reported difficulty in accessing essential health-care services than their urban counterparts.

CONCLUSIONS

A qualitative study to understand the facilitators and barriers for the non-adherence to IPC measures by the study population and formulating behavior change communication strategies for improving the IPC measures is needed. Repeat, cross-sectional surveys at regular intervals may be planned to gauge the change and effect of the interventions on the community preparedness and practices.

Spatiotemporal Associations Between Social Vulnerability, Environmental Measurements, and COVID-19 in the Conterminous United States

This study summarizes the results from fitting a Bayesian hierarchical spatiotemporal model to coronavirus disease 2019 (COVID-19) cases and deaths at the county level in the United States for the year 2020. Two models were created, one for cases and one for deaths, utilizing a scaled Besag, York, Mollié model with Type I spatial-temporal interaction. Each model accounts for 16 social vulnerability and 7 environmental variables as fixed effects. The spatial pattern between COVID-19 cases and deaths is significantly different in many ways. The spatiotemporal trend of the pandemic in the United States illustrates a shift out of many of the major metropolitan areas into the United States Southeast and Southwest during the summer months and into the upper Midwest beginning in autumn. Analysis of the major social vulnerability predictors of COVID-19 infection and death found that counties with higher percentages of those not having a high school diploma, having non-White status and being Age 65 and over to be significant. Among the environmental variables, above ground level temperature had the strongest effect on relative risk to both cases and deaths. Hot and cold spots, areas of statistically significant high and low COVID-19 cases and deaths respectively, derived from the convolutional spatial effect show that areas with a high probability of above average relative risk have significantly higher Social Vulnerability Index composite scores. The same analysis utilizing the spatiotemporal interaction term exemplifies a more complex relationship between social vulnerability, environmental measurements, COVID-19 cases, and COVID-19 deaths.

A spatial interpretation of Australia's COVID-vulnerability

The school of social vulnerability in disaster sciences offers an alternative perspective on the current COVID-19 (coronavirus) pandemic crisis. Social vulnerability in general can be understood as a risk of exposure to hazard impacts, where vulnerability is embedded in the normal functioning of the society. The COVID-19 pandemic has exposed systemic (political and health care systems), demographic (aging, race) and,based on the results of our approach, spatial (spatial isolation and connectivity) yvulnerabilities as well. In this paper, we develop a risk prediction model based on two composite indicators of social vulnerability. These indicators reflect the two main contrasting risks associated with COVID-19, demographic vulnerability and, as consequences of the lockdowns, economic vulnerability. We conceptualise social vulnerability in the context of the extremely uneven spatial population distribution in Australia. Our approach helps extend understanding about the role of spatiality in the current pandemic disaster.

What determines city's resilience against epidemic outbreak: evidence from China's COVID-19 experience

By employing the city-level data from China during the spring of 2020, this study investigates the relationship between city-level resilience against the outbreak of COVID-19 pandemics and its affecting factors, including the inflow risk pressure of COVID-19 virus (population inflow from the epicenter), city agglomeration characteristics (urban population density and city size), healthcare resource adequacy, among others. The results reveal that, while managing COVID-19 inflow risk pressure plays a critical role in the city's pandemic disaster resilience, city agglomeration characteristics also matters. To be exact, we find that large and high-density cities with high inter and intra-city mobility flows have more difficulties in containing the epidemic spread, but improving healthcare infrastructure adequacy and urban governance capacity can increase time efficacy of pandemic control and then improve the city's resilience against pandemic. Although our analysis is based on the performance of Chinese cities in the case of COVID-19, the research framework can be applied in understanding COVID-19 control performance of cities in other countries and the findings can be useful for improving health-related urban resilience and sustainability.

Using machine learning to develop a novel COVID-19 Vulnerability Index (C19VI)

COVID-19 is now one of the most leading causes of death in the United States (US). Systemic health, social and economic disparities have put the minorities and economically poor communities at a higher risk than others. There is an immediate requirement to develop a reliable measure of county-level vulnerabilities that can capture the heterogeneity of vulnerable communities. This study reports a COVID-19 Vulnerability Index (C19VI) for identifying and mapping vulnerable counties. We proposed a Random Forest machine learning-based vulnerability model using CDC's sociodemographic and COVID-19-specific themes. An innovative 'COVID-19 Impact Assessment' algorithm was also developed for evaluating severity of the pandemic and to train the vulnerability model. Developed C19VI was statistically validated and compared with the CDC COVID-19 Community Vulnerability Index (CCVI). Finally, using C19VI and the census data, we explored racial inequalities and economic disparities in COVID-19 health outcomes. Our index indicates that 575 counties (45 million people) fall into the 'very high' vulnerability class, 765 counties (66 million people) in the 'high' vulnerability class, and 1435 counties (204 million people) in the 'moderate' or 'low' vulnerability class. Only 367 counties (20 million people) were found as 'very low' vulnerable areas. Furthermore, C19VI reveals that 524 counties with a racial minority population higher than 13% and 420 counties with poverty higher than 20% are in the 'very high' or 'high' vulnerability classes. The C19VI aims at helping public health officials and disaster management agencies to develop effective mitigation strategies especially for the disproportionately impacted communities.

Analyzing the Risk to COVID-19 Infection using Remote Sensing and GIS

Globally, the COVID-19 pandemic has become a threat to humans and to the socioeconomic systems they have developed since the industrial revolution. Hence, governments and stakeholders call for strategies to help restore normalcy while dealing with this pandemic effectively. Since till now, the disease is yet to have a cure; therefore, only risk-based decision making can help governments achieve a sustainable solution in the long term. To help the decisionmakers explore viable actions, we propose a risk-based assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water, and associated land use/land cover, are related with COVID-19 contagion and calculated them in a GIS-based multicriteria risk reduction method. The results showed disparateness in COVID-19 risk areas with a higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed prioritizing wards under higher risk zones for intelligent decision making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

Evaluating the plausible application of advanced machine learnings in exploring determinant factors of present pandemic: A case for continent specific COVID-19 analysis

Coronavirus disease, a novel severe acute respiratory syndrome (SARS COVID-19), has become a global health concern due to its unpredictable nature and lack of adequate medicines. Machine Learning (ML) models could be effective in identifying the most critical factors which are responsible for the overall fatalities caused by COVID-19. The functional capabilities of ML models in epidemiological research, especially for COVID-19, are not substantially explored. To bridge this gap, this study has adopted two advanced ML models, viz. Random Forest (RF) and Gradient Boosted Machine (GBM), to perform the regression modelling and provide subsequent interpretation. Five successive steps were followed to carry out the analysis: (1) identification of relevant key explanatory variables; (2) application of data dimensionality reduction for eliminating redundant information; (3) utilizing ML models for measuring relative influence (RI) of the explanatory variables; (4) evaluating interconnections between and among the key explanatory variables and COVID-19 case and death counts; (5) time series analysis for examining the rate of incidences of COVID-19 cases and deaths. Among the explanatory variables considered in this study, air pollution, migration, economy, and demographic factor were found to be the most significant controlling factors. Since a very limited research is available to discuss the superiority of ML models for identifying the key determinants of COVID-19, this study could be a reference for future public health research. Additionally, all the models and data used in this study are open source and freely available, thereby, reproducibility and scientific replication will be achievable easily.