An Introduction to Biopolitics and Shock Economy of COVID-19: Medical Perspectives and Socioeconomic Dynamics

This edited volume on the biopolitics and shock economy of COVID-19 crisis embraces a wide spectrum of topics such as shock economy, medical perspectives on COVID-19, application of geospatial technology, infectivity, immunity, and severity of the disease, as well as ontology of the disease emergence as important factors for adoption of relevant biopolitical measures, sociocultural obstacles, COVID-19-induced transaction costs, social support and resilience of inhabitants of marginalized areas, as well as business resilience factors, entrepreneurship, and digital transformation. Through each chapter of this book, the authors, with their expertise in the theme they picked, have attempted to unfold some emerging aspects in the COVID-19 crisis which could benefit not only the academics but also the institutional, social, economic, developmental, and health policy-makers as well as the health practitioners on the ground. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Oral microbial taxa associated with risk for SARS-CoV-2 infection.

Hypothesis and objective: The oral and digestive tract microbial ecosystem has sparked interest because of its impact on various systemic diseases and conditions. The oral cavity serves not only as a reservoir for many potentially virulent microbiota but also as an important entry point and portal to the human body system. This is especially significant in the transmissibility of the virulent current pandemic virus SARS-CoV-2. The oral and digestive microbiome influences the inflammatory burden and effectiveness of the immune system and serves as a marker of activity of these host processes. The host immune response plays a role in infection susceptibility, including SARS-CoV-2. The purpose of this study is to investigate the role of specific salivary oral microbiome in susceptibility to SARS-CoV-2 infection. Methods and results: One hundred six subjects of known medical and dental history who consented to provide saliva samples between January 2017 and December 2019 were included in this study. Sixteen had become COVID-19 positive based on the PCR test by 3/01/2021. A comparison of oral microbiome bacteria taxa profiles based on 16S rRNA sequencing revealed differences between the two groups in this pilot study. Conclusions: These bacteria taxa may be markers of increased susceptibility to SARS-CoV-2 infection in the unvaccinated population.

Unraveling complex relationships between COVID-19 risk factors using machine learning based models for predicting mortality of hospitalized patients and identification of high-risk group: a large retrospective study.

Background: At the end of 2019, the coronavirus disease 2019 (COVID-19) pandemic increased the hospital burden of COVID-19 caused by the SARS-Cov-2 and became the most significant health challenge for nations worldwide. The severity and high mortality of COVID-19 have been correlated with various demographic characteristics and clinical manifestations. Prediction of mortality rate, identification of risk factors, and classification of patients played a crucial role in managing COVID-19 patients. Our purpose was to develop machine learning (ML)-based models for the prediction of mortality and severity among patients with COVID-19. Identifying the most important predictors and unraveling their relationships by classification of patients to the low-, moderate- and high-risk groups might guide prioritizing treatment decisions and a better understanding of interactions between factors. A detailed evaluation of patient data is believed to be important since COVID-19 resurgence is underway in many countries. Results: The findings of this study revealed that the ML-based statistically inspired modification of the partial least square (SIMPLS) method could predict the in-hospital mortality among COVID-19 patients. The prediction model was developed using 19 predictors including clinical variables, comorbidities, and blood markers with moderate predictability (Q2 = 0.24) to separate survivors and non-survivors. Oxygen saturation level, loss of consciousness, and chronic kidney disease (CKD) were the top mortality predictors. Correlation analysis showed different correlation patterns among predictors for each non-survivor and survivor cohort separately. The main prediction model was verified using other ML-based analyses with a high area under the curve (AUC) (0.81-0.93) and specificity (0.94-0.99). The obtained data revealed that the mortality prediction model can be different for males and females with diverse predictors. Patients were classified into four clusters of mortality risk and identified the patients at the highest risk of mortality, which accentuated the most significant predictors correlating with mortality. Conclusion: An ML model for predicting mortality among hospitalized COVID-19 patients was developed considering the interactions between factors that may reduce the complexity of clinical decision-making processes. The most predictive factors related to patient mortality were identified by assessing and classifying patients into different groups based on their sex and mortality risk (low-, moderate-, and high-risk groups).

Covid-19 and Diabetes Risk Prediction for Diabetic Patient using Advance Machine Learning Techniques and Fuzzy Inference System

Diabetes has become a common and critical disease which generally occurs due to the presence of high sugar in blood for long time. A diabetic patient has to follow different rules and restrictions where he/she has to be under proper attention by measuring diabetes level frequently to avoid unexpected risk. The risk become more when patient even doesn't know that he/she is already having diabetes and doesn't follow those restrictions. To prevent this risk, everyone should check the diabetes status to be sure. With the same target different system using machine learning techniques have been introduced which can predict the diabetes status of a patient. But the challenging fact is that the performances and accuracy of those models are questionable where there may be a huge risk of patient's life. The conventional systems are not able to show that which level of diabetes a patient can have using the previous records. To solve this issue, through this paper an efficient system has been proposed with which the diabetes status can be predicted correctly. The proposed system can also show the complexity of diabetes as well as the Covid-19 risk percentage that can also be possible to measure. After comparing several machine learning techniques, the suitable model has been selected where high level of accuracy has been ensured in term of predicting the disease. © 2022 IEEE.

'How shall we handle this situation?' Social workers' discussions about risks during the COVID-19 pandemic in Swedish elder care

Within a context where New Public Management [NPM] has become increasingly influential in shaping everyday working practices, social workers often handle risks in their everyday work using formalised bureaucratic procedures, among other strategies. As the COVID-19 pandemic progressed, rapid changes occurred in Swedish elder care that social workers were required to address in their everyday work. Intra-professional case conferences amongst social workers provide one opportunity to discuss individual viewpoints and obtain suggestions from colleagues on how to proceed with a case. These discussions have so far received little scholarly attention. In this study we used a data set consisting of 39 audio-recorded case conferences to analyse social workers' intra-professional discussions about risks during the COVID-19 pandemic. In the case conferences, social workers discussed the risks that were accentuated by the pandemic, such as the risk of spreading COVID-19 to clients, the risk of unmet care needs amongst clients, risks related to accountability, and the risks pertaining to blurred boundaries between different organisations. The collegial discussions in case conferences included opportunities for social workers to use their collective professional experience and competency to establish creative solutions 'on the go' and to discuss various ways of handling and balancing different risks while continuing to carry out their work in the changing and unknown situation. Our findings highlight the importance of collegial support in social work in dealing with accentuated risks during the pandemic.Copyright © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

An investigation of methods for protecting human research subjects at medical schools during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic was a unique time in history to study the protection of human research subjects at medical schools. The COVID-19 pandemic resulted in an unprecedented disruption on the conduct of human subjects research in the United States. Medical schools around the country had to rapidly pivot and adopt new risk mitigation practices to protect research participants. The purpose of this study was to investigate the influence of the COVID-19 pandemic on the protection of human research subjects at medical schools. Five research medical institutions that are geographically spread across the United States were selected for this two-phase study. All five were among the top 25 NIH research funded institutions in 2021. Phase one included a deductive content analysis of publicly available research guidance documents using the Hierarchy of Controls as the conceptual framework. Based on the findings, a semi-structured interview protocol was developed and a research manager from each study site was interviewed. Guidelines and practices for the protection of human research subjects have changed as a result of the COVID-19 pandemic;however, IRB policies have not. Despite universal protective measures that should be taken, for example masking, there are nuances to research study modifications that were left at the study team level for the sites involved in this study. A practical implication from this study was that COVID-19 risk reduction plans are not a one size fits all approach. The medical schools in this study provided study teams with the flexibility to tailor risk mitigation procedures to the study population. A significant implication was the discovery that IRBs were not approving ramp up plans and it was typically done at the department level. The pandemic exposed weaknesses in medical schools' preparedness for the continuation of human subjects research during a public health emergency. It is recommended that their Institutional Review Boards (IRBs) develop an emergency plan to ensure the continuation of research during future pandemic or other public health emergencies. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Daily routine and habits during COVID-19 lockdown in Italy: An observational survey

Introduction: Between March–May 2020, the Italian Government applied restrictive measures to reduce the risk of contagion, fostering a potential condition of occupational deprivation. Methods: A digital survey was administered in June 2020 including closed and open questions. The goal was to report how the first Italian lockdown affected daily routine. Results: 648 surveys were valid. Most respondents were workers and spent lockdown at home. Before quarantine, the most representative occupations were working and housekeeping;the significant ones were working and meeting friends/relatives. Wellbeing meant meeting friends/relatives and hobbies/interests. During lockdown, respondents dedicated themselves to housekeeping and working;meaningful occupations were working and cooking. All data was stratified according to age and perceived wellbeing;open questions were categorized by the researchers. Discussion: A daily routine in compliance with lockdown restrictions required a change in habits. Time was used for occupations not strictly contentful;finance and work gained significance. It is to hypothesize that the idea of wellbeing was deeply altered. Conclusions: The study focuses on a slice of everyday life in times of emergency, it highlights people adaptability and their experiences according to age and future plans. Occupational justice emerges as a strong topic: the environment influences wellbeing, habits, and self-perception. AD -, Mendrisio, Canton Ticino, Switzerland;, Milano, Italy;DEASS, Manno, Switzerland ;, Milano, Italy;, Milan, Italy ;, Magenta - Milan, Italy ;, Milano, Italy;, Rome, Italy ;, Mendrisio, Canton Ticino, Switzerland;, Milano, Italy;DEASS, Manno, Switzerland

Community, Communication, and Capacity Building: Integrated Risks of COVID-19 Response in India

While COVID-19 is classified as a pandemic caused by a foreign virus, it turned out to be a human-induced disaster in India where various aspects of the disaster response exposed the social construction of risk. Infodemic, mass migration of labourers and accidental deaths other than COVID 19 not just indicate poor response but also endorse severe impacts of gaps in risk communication and capacity building. Risk communication plays a vital role in generating effective disaster response, however, it can also have grave consequences if not managed well. This paper highlights various aspects of COVID-19 risk communications in India, which emerged as an important gap in both planning and practices of disaster management in the country. The paper is based on the secondary data and literature published on COVID-19 impacts and response in general and risk communication in particular. The paper argues for a need to incorporate risk communication as an important component of disaster management planning, process, and capacity building for effective community participation and response. © 2023 DMICS.

Acute stroke associated with novel coronavirus infection COVID-19

Background. COVID-19 is a widespread, important, and frequently fatal disease, considered a risk factor for the development and progression of other pathologies. One of the most common associated conditions is stroke. Objective: to identify the patterns of occurrence and mechanisms of ischemic stroke (IS) development under novel coronavirus infection COVID-19. Patients/Methods. The prospective study included 80 individuals: 20 COVID-19 patients with subsequent IS development (main group);40 COVID-19 patients without cerebrovascular accident (comparison group);20 healthy volunteers (control group). Concen-trations of fibrinogen, antithrombin III, D-dimer, von Willebrand factor (vWF), C-reactive protein (CRP), matrix metalloproteinase-2 (MMP-2), cytokines (interleukin, IL) — IL-6, IL-8, IL-10, tumor necrosis factor-alpha (tumor necrosis factor-alpha, TNF-α) were accessed in peripheral blood. The study was carried out from November 2020 to February 2021. The primary endpoint of the study was IS development in COVID-19 patients. Results. In 70% patients of the main group a stroke developed by the end of the second week from the infection onset. The main risk factor in 12 (57%) COVID-19 patients with an unfavorable stroke course and subsequent development of multiple organ failure syndrome (MOFS) was a high comorbidity with various forms of circulatory system pathology. All 12 patients with IS and MOFS (100%) showed a statistically significant changes in many clinical and laboratory parameters by the end of the first day after admission to the hospital: they had arterial hypertension (100%), tachycardia (80%), significant increased blood levels of D-dimer (83%), vWF (75%), IL-10 (92%), TNF-α (92%), CRP (100%), MMP-2 (100%). Conclusions. COVID-19 and high comorbidity with various forms of circulatory system pathology are 2 significant risk factors for both the occurrence and adverse course of stroke and its outcomes. Arterial hypertension, increased blood levels of D-dimer, vWF, IL-10, TNF-α, CRP and MMP-2 are the early predictors of acute MOFS development in more than 75% of COVID-19 patients with stroke. © Kabaeva E.N., Litvitskiy P.F., Artyukov O.P., Tushova K.A., Nozdryukhina N.V., Ershov A.V., 2022

Case Study: Impact of Regulatory Restrictions and Tax Policy on Breakeven Analysis and Risk Management

The objective of this case study is to enable students to analyze the financial impact of an unexpected catastrophic event on a retail business and how the strategic operational decisions made in response to regulatory restrictions and changes in tax policy impact the business's risk tolerance and breakeven analysis. To provide students with a context for comparison, this case study provides students with the opportunity to analyze the financial statements of a retail business prior to the occurrence of an unexpected catastrophic event, how the catastrophic event impacted revenue and profitability, and how the risk reduction strategies the business employed contained the adverse impact of the factors brought on by that catastrophic event on breakeven. This case study addresses a core gap in the body of knowledge by analyzing a business in three distinct stages of the business life cycle: (1) in the start-up phase;(2) in pre-crisis operations mode;and (3) in crisis mode confronted with an unexpected catastrophic event amidst governmental shutdowns, state and federal regulatory restrictions, and emergency changes to the tax policy. Examining a fictitious restaurant (a composite of the sales statistics of three actual restaurants located in Long Island, New York from 2019 to 2021) in operation for one year prior to the COVID-19 pandemic, students are given the opportunity to think critically about how strategic operational decisions made to generate sales, to minimize risk, to comply with mandated state government policy, and to take advantage of federal tax relief policy, collectively changed the financial projections and impacted the breakeven analysis of that business. Students are able to evaluate business start-up costs, first year (pre-pandemic) sales and costs, and second year (during pandemic) sales and costs of a retail business. Students then evaluate how the United States' federal PPP relief loan program, along with other pandemic relief programs for businesses and individuals, impacted profitability and business strategy. Students also assess risk, risk tolerance, and how the strategies employed to minimize risk impact a business. The motivation for this case study is to provide students with an illustrative example of an entity at various stages of the business life cycle, to explore the surrounding context of the impact of external environmental events, and to identify the effects of strategic operational responses to the various regulatory changes that were brought on by a catastrophic event. This case study is designed for use in courses that study revenue projection, tax, internal controls, breakeven analysis, and risk management. Teaching Note: While this case study uses a restaurant as a model, prior understanding of the restaurant industry is not necessary. Any student or instructor can use their practical knowledge and experience as a consumer to adequately analyze the issues presented. © 2023 by the authors.

COVID-19 and supply chain risk mitigation: a case study from India

PurposeThis study prioritizes the supply chain risks (SCRs) and determines risk mitigation strategies (RMSs) for the Indian apparel industry to mitigate the shock of the COVID-19 pandemic disruption.Design/methodology/approachInitially, 23 SCRs within the apparel industry are identified through an extant literature review. Further, a fuzzy analytical hierarchy process (FAHP) is utilized to prioritize the SCRs considering the epidemic situations to understand the criticality of SCRs and determine appropriate RMSs to mitigate the shock of SCRs during COVID-19.FindingsThis study prioritized and ranked the SCRs within the Indian apparel industry based on their severity during the COVID-19 disruption. Results indicate that the demand uncertainty and pandemic disruption risks are the most critical. Based on the SCRs, the present work evaluated and suggested the flexibility and postponement mitigation strategies for the case under study.Research limitations/implicationsThis study has novel implications to the existing literature on supply chain risk management in the form of the FAHP framework. Supply chain practitioners from the other industrial sectors can extend the proposed FAHP framework to assess the SCRs and identify suitable mitigation strategies. The results aid the practitioners working in an apparel industry to benchmark and deploy the proposed RMSs in their firm.Originality/valueThe present study is a unique and earlier attempt to develop a quantitative framework using FAHP to evaluate and determine the risk mitigation strategy for managing the SCRs during the coronavirus epidemic.

COVID-19 and implications for automation

COVID-19 may accelerate the automation of jobs as employers invest in technology to safeguard against pandemics. We identify occupations that have high automation potential and also exhibit a high risk of viral infection. We examine regional variation in terms of which U.S. local labour markets are most at risk. Next, we outline the differential impacts COVID-19 may have on different demographic groups. We find that the highest-risk occupations in the U.S. are those held by females with mid- to low-wage and education levels. Using comparable data for 25 other countries, we also find that women in this demographic are at the highest risk internationally.

The effect of COVID-19 on tourists' attitudes and travel intentions: an empirical study on camping/glamping tourism in Turkey during COVID-19

PurposeIn this study, visitors' attitudes and behavioural intentions towards camping/glamping tourism in Turkey during the pandemic were investigated using the extended theory of planned behaviour (TPB). The model has been extended to include constructs such as risk perception and risk aversion attitudes that stem from COVID-19 to predict visitors' attitudes and behavioural intentions.Design/methodology/approachThe data were collected through an online questionnaire from 432 participants who have experience and interest in camping/glamping tourism in Turkey. The responses were analysed using the structural equation modelling (SEM).FindingsThe findings show that besides the basic TPB structures, other added variables also significantly affect visitors' attitudes and intentions. Moreover, it has been observed that the risk perception and risk aversion attitude derived from COVID-19 increase negative emotions in visitors and decreased behavioural intentions.Research limitations/implicationsThe results of the study are discussed for future research as well as its academic and practical implications.Originality/valueThis theoretical expansion is thought to increase the theory's predictive power in predicting visitors' behaviour during the pandemic.

Risk of SARS-CoV-2 infection in a large cohort of Ontario workers

IntroductionWork is a key determinant of COVID-19 outcomes, however occupational surveillance is a critical information gap in many countries, including Canada. Understanding the risk of SARS-CoV-2 by occupation can identify high risk groups that can be targeted for prevention strategies.Materials and MethodsThe cohort includes 1,205,847 former workers compensation (non-COVID-19) claimants (aged 15–65) linked to health databases in Ontario, Canada. Incident cases were defined as either having a confirmed positive polymerase chain reaction (PCR) test in the Ontario Laboratory Information System (OLIS), or an International Classification of Diseases (ICD-10-CA) diagnostic code of U07.1 in hospitalization or emergency department records (February 2020-December 2021). Workers were followed until diagnosis, death, emigration, age 65 or end of follow-up. Sex- and age-adjusted Cox proportional hazards models were used to estimate hazards ratios (HR) and 95% confidence intervals (CI) by occupation, compared to all other cohort members. Analyses were also conducted to examine occupational trends in testing and diagnosis during waves of infection.ResultsOverall, 80,740 COVID-19 cases were diagnosed among workers during follow-up, of those, 80% were diagnosed with a positive PCR test. Associations were identified between COVID-19 diagnosis and employment in nursing (HR=1.44, CI95%=1.40–1.49), air transport operating (HR=1.61, CI95%=1.47–1.77), textile/fur/leather products fabricating, assembling, and repairing (HR=1.38, CI95%=1.25–1.54), apparel and furnishing services (HR=1.38, CI95%=1.19–1.60), and janitor and cleaning services (HR=1.11, CI95%=1.06–1.16). Restricted analyses where health care workers were omitted from the comparison group strengthened some associations for other high-risk workers. Test positivity ranged between 4–16% across major occupation groups. Risks varied over time and with changes in protective measures in workplaces and in broader communities.ConclusionsElevated risk of SARS-CoV-2 infection in health care, manufacturing, transportation, and service workers were identified, underscoring the importance of including occupational data in COVID-19 surveillance. Occupational trends in severe outcomes and vaccination are also being explored.

IMPACT OF COVID 19 ON RISK MANAGEMENT AND SUSTAINABLE DEVELOPMENT GOALS

This article describes and analyses the state of the art and potential areas of research in relation to the impact of COVID-19 on risk management and the Sustainable Development Goals (SDGs). In total, 28 research publications published between 2020 and 2021 related to COVID-19, risk management and the Sustainable Development Goals are analysed in the Web of Science (WOS) core collection database. The publications cover 54 authors, 25 countries and 21 institutions including 17 universities worldwide. Among other techniques, content analysis of the identified articles is used. © 2022 by the authors. Licensee AEIPRO, Spain.

What drives university students to practice social distancing? Evidence from South Korea and Vietnam

As COVID‐19 has caused unprecedented social change, governments are implementing several social measures to control transmission. Among them, social distancing is being enforced in almost all countries and is effective in preventing infection. Based on the importance of social distancing, this study identifies factors influencing the intention towards social distancing. The research model was developed by introducing risk perception in the theory of planned behaviour. To examine the proposed model, a survey was conducted with 339 university students from two countries, South Korea and Vietnam. The data were analysed using the partial least squares method. The results show that social distancing attitude and perceived behavioural control significantly influence social distancing intention. The findings indicate that both affective risk perception and cognitive risk perception serve as imperative factors in the formation of social distancing attitudes, subjective norms and perceived behavioural control. However, subjective norms and nationality do not affect social distancing intention. Based on the results, suggestions are made for policymakers to establish effective social measures.

How Do COVID-19 Risk, Life-Safety Risk, Job Insecurity, and Work-Family Conflict Affect Miner Performance? Health-Anxiety and Job-Anxiety Perspectives.

The coronavirus pandemic (COVID-19) has created challenging working conditions in coal-production activities. In addition to the massive loss of resources for miners, it has had a devastating impact on these individuals' mental health. Based on the conservation of resources (COR) theory and a resource-loss perspective, this study examined the impact of COVID-19 risk, life-safety risk, perceived job insecurity, and work-family conflict on miners' job performance. Moreover, this study investigated the mediating role of job anxiety (JA) and health anxiety (HA). The study data were collected through online structured questionnaires disseminated to 629 employees working in a coal mine in China. The data analysis and hypothesis generation were conducted using the structural equation modeling (partial least squares) method. The results demonstrated that the perception of COVID-19 risk, life-safety risk, job insecurity, and work-family conflict negatively and significantly impacted miners' job performance. In addition, JA and HA negatively mediated the relationships between the perception of COVID-19 risk, life-safety risk, perceived job insecurity, work-family conflict, and job performance. The findings of this study can give coal-mining companies and their staff useful insights into how to minimize the pandemic's effects on their operations.

COVID-19 related risk perception and altruistic response amongst undergraduates on reopening of educational institutes.

OBJECTIVE: To determine the coronavirus disease-2019-related risk perception and altruistic response among undergraduate medical students post-lockdown. Methods: The analytical cross-sectional study was conducted from October 1, 2020, to March 31, 2021, at the Baqai Medical University, Karachi, and comprised undergraduates aged 16 and above, studying in medical, dental, physiotherapy, pharmacy and Information technology departments. Data was collected using a structured and standardised online questionnaire. Positive responses led to a perceived risk score ranging 0-9, with a higher score indicating a greater perception of risk. The score was corelated with demographic variables. Data was analysed using SPSS 21. RESULTS: Of the 743 subjects, 472(63.5%) were females. The overall mean age of the sample was 21.34±1.8 years. The mean risk perception score was 3.8±2.5, and it was significantly associated with disease exposure (p<0.001). Altruism had a strong association with the perceived risk score (p<0.001), indicating lower risk perception. Conclusion: The risk perception among the students was low, pointing towards a need of psychological assistance programme for the students.

The effect of COVID-19 risk perception on pro-environmental behavior of Chinese consumers: Perspectives from affective event theory.

Introduction: COVID-19 has altered human cognition and changed the cultural values of society. However, there has not been much debate among scholars about whether these above changes have led to an increase in pro-environmental behavior (PEB) of Chinese consumers. Methods: A comprehensive model was developed based on affective event theory. An online questionnaire was distributed, and 501 usable questionnaires were collected. In addition, two complementary approaches were employed: partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA). Results: The PLS-SEM results showed that COVID-19 risk perception, nostalgia, the awe of nature, and attitude were found to have a positive effect on PEB; and the moderating effect of power distance belief (PD) between nostalgia (NO), attitude (AT) and PEB was confirmed. According to the NCA results, AT and NO are necessary conditions for the PEB of consumers. Discussion: This study provides deeper insight into the understanding of consumers' pro-environmental behavior in the context of COVID-19 through the combined use of PLS-SEM and NCA.

Associations between COVID-19 risk, multiple environmental exposures, and housing conditions: A study using individual-level GPS-based real-time sensing data.

Few studies have used individual-level data to explore the association between COVID-19 risk with multiple environmental exposures and housing conditions. Using individual-level data collected with GPS-tracking smartphones, mobile air-pollutant and noise sensors, an activity-travel diary, and a questionnaire from two typical neighborhoods in a dense and well-developed city (i.e., Hong Kong), this study seeks to examine 1) the associations between multiple environmental exposures (i.e., different types of greenspace, PM2.5, and noise) and housing conditions (i.e., housing types, ownership, and overcrowding) with individuals' COVID-19 risk both in residential neighborhoods and along daily mobility trajectories; 2) which social groups are disadvantaged in COVID-19 risk through the perspective of the neighborhood effect averaging problem (NEAP). Using separate multiple linear regression and logistical regression models, we found a significant negative association between COVID-19 risk with greenspace (i.e., NDVI) both in residential areas and along people's daily mobility trajectories. Meanwhile, we also found that high open space and recreational land exposure and poor housing conditions were positively associated with COVID-19 risk in high-risk neighborhoods, and noise exposure was positively associated with COVID-19 risk in low-risk neighborhoods. Further, people with work places in high-risk areas and poor housing conditions were disadvantaged in COVID-19 risk.