Precision Mapping of COVID-19 Vulnerable Locales by Epidemiological and Socioeconomic Risk Factors, Developed Using South Korean Data

Weinstein, Bayarmagnai; Silva, Alan Ricardo da; Kouzoukas, Dimitrios E.; Bose, Tanima; Kim, Gwang Jin; Correa, Paola; Pondugula, Santhi; Lee, Yoon-Jung; Kim, Jihoo; Carpenter, David O.

doi:10.3390/ijerph18020604

Cited by 16 publications

(25 citation statements)

References 45 publications

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“…In a study using data gathered in Korea, the risk of COVID-19 increased in line with immutable factors, such as higher area morbidity, crowding, and population mobility. Lower rates of social distancing, as well as poorer access to healthcare and education, also increased the risk of infection [ 37 ]. These variables can only be challenged using a broad, population based approach to systematic change.…”

Section: The Effect Of Covid-19 On People Who Do Not Use Psychiatric Servicesmentioning

confidence: 99%

The Collateral Damage of the COVID-19 Outbreak on Mental Health and Psychiatry

Simon

Schenk

Palm

et al. 2021

IJERPH

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The potential consequences of the COVID-19 outbreak are multifarious and remain largely unknown. Deaths as a direct result of the condition are already in the millions, and the number of indirect deaths is likely to be even higher. Pre-existing historical inequalities are compounded by the virus, driving increased rates of infection and deaths amongst people who use drugs and alcohol, those belonging to racial-ethnic minority groups, poorer communities, LBGTQ+ populations, healthcare workers, and other members of the care economy; all of whom are already at increased risk of adverse mental health effects. In this paper we suggest that a central role of mental health practitioners is advocacy: both for people who use psychiatric services and for those who, due to the effects of the pandemic, are at an increased risk of needing to do so.

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Section: The Effect Of Covid-19 On People Who Do Not Use Psychiatric Servicesmentioning

confidence: 99%

The Collateral Damage of the COVID-19 Outbreak on Mental Health and Psychiatry

Simon

Schenk

Palm

et al. 2021

IJERPH

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“…For instance, in South Korea, the complete location information and demographics information is also released. Furthermore, temporal information and mask status is also published for the people's awareness [35]. Many studies reported that people with individualistic orientation are less likely to consider the control measures acceptable because they have higher privacy concerns and lower perceptions of the social benefits.…”

Section: Disclosing Information Of Confirmed Cases Of Covid-19mentioning

confidence: 99%

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

Majeed

Lee

2021

Inventions

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With the advent of the pandemic (e.g., novel corona virus disease 2019 (COVID-19)), a tremendous amount of data about individuals are collected by the health authorities on daily basis for curbing the disease’s spread. The individuals’ data collection/processing at a massive scale for community well-being with the help of digital solutions (e.g., mobile apps for mobility and proximity analysis, contact tracing through credit card usage history, facial recognition through cameras, and crowd analysis using cellular networks data etc.) raise several privacy concerns. Furthermore, the privacy concerns that are arising mainly due to the fine-grained data collection has hindered the response to tackle this pandemic in many countries. Hence, acquiring/handling individuals data with privacy protection has become a vibrant area of research in these pandemic times. This paper explains the shift in privacy paradigm due to the pandemic (e.g., COVID-19) which involves more and detailed data collection about individuals including locations and demographics. We explain technical factors due to which the people’s privacy is at higher risk in the COVID-19 time. In addition, we discuss privacy concerns in different epidemic control measures (ECMs) (e.g., contact tracing, quarantine monitoring, and symptoms reporting etc.) employed by the health authorities to tackle this disease. Further, we provide an insight on the data management in the ECMs with privacy protection. Finally, the future prospects of the research in this area tacking into account the emerging technologies are discussed. Through this brief article, we aim to provide insights about the vulnerability to user’s privacy in pandemic times, likely privacy issues in different ECMs adopted by most countries around the world, how to preserve user’s privacy effectively in all phases of the ECMs considering relevant data in loop, and conceptual foundations of ECMs to fight with future pandemics in a privacy preserving manner.

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“…The built environment risk indicator is meant to identify areas at a higher risk of COVID-19 infection due to lack of adequate space available to adhere to shelter-in-place mandates and other precautions that aim to limit the spread of COVID-19 [ 16 , 27 , 28 , 29 , 30 , 31 ]. The indicator is composed of four variables: Population density, operationally defined as the total number of persons divided by the ZCTA’s land area in square miles.…”

Section: Methodsmentioning

confidence: 99%

“…The social vulnerability indicator is a close replica of the 2018 social vulnerability index (SVI), which was created by the Center for Disease Control and Prevention (CDC) to identify vulnerable areas in need of preparation and response to hazardous events or natural disasters. The SVI indicator addresses the level to which community experiences different social conditions, such as unemployment and that might affect its ability to prepare and respond to hazardous events, such as the COVID-19 pandemic [ 29 , 30 , 31 ]. The CDC’s SVI is only available at the census tract level.…”

Section: Methodsmentioning

confidence: 99%

“…Previous research has found that existing spatial inequality is reproduced over time, specifically that urban spatial structures produce and reproduce socioeconomic inequalities [ 27 , 28 ]. The racial discrepancies among COVID-19 outcomes in the U.S. have not only been attributed to COVID-19 comorbidities, but also to the social, economic, and physical factors that provide communities with the capacity to safely practice physical distancing in order to reduce COVID-19 community spread [ 16 , 29 , 30 , 31 , 32 , 33 , 34 ]. While much has been made of herd immunity [ 17 , 18 ] in the absence of a vaccine that can attempt to accomplish that status, far more important at this point is focusing on how to employ data to identify communities whose medical vulnerabilities occur in the context of social and environmental risks and make them highly likely to be exposed, become infected and potentially suffer significant and costly morbidity and mortality outcomes [ 6 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 Medical Vulnerability Indicators: A Predictive, Local Data Model for Equity in Public Health Decision Making

Ong¹,

Pech²,

Gutierrez³

et al. 2021

IJERPH

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This article reports the outcome of a project to develop and assess a predictive model of vulnerability indicators for COVID-19 infection in Los Angeles County. Multiple data sources were used to construct four indicators for zip code tabulation areas: (1) pre-existing health condition, (2) barriers to accessing health care, (3) built environment risk, and (4) the CDC’s social vulnerability. The assessment of the indicators finds that the most vulnerable neighborhoods are characterized by significant clustering of racial minorities. An overwhelming 73% of Blacks reside in the neighborhoods with the two highest levels of pre-existing health conditions. For the barriers to accessing health care indicator, 40% of Latinx reside in the highest vulnerability places. The built environment indicator finds that selected Asian ethnic groups (63%), Latinx (55%), and Blacks (53%) reside in the neighborhoods designated as high or the highest vulnerability. The social vulnerability indicator finds 42% of Blacks and Latinx and 38% of selected Asian ethnic group residing in neighborhoods of high vulnerability. The vulnerability indicators can be adopted nationally to respond to COVID-19. The metrics can be utilized in data-driven decision making of re-openings or resource distribution such as testing, vaccine distribution and other pandemic-related resources to ensure equity for the most vulnerable.

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Precision Mapping of COVID-19 Vulnerable Locales by Epidemiological and Socioeconomic Risk Factors, Developed Using South Korean Data

Cited by 16 publications

References 45 publications

The Collateral Damage of the COVID-19 Outbreak on Mental Health and Psychiatry

The Collateral Damage of the COVID-19 Outbreak on Mental Health and Psychiatry

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

COVID-19 Medical Vulnerability Indicators: A Predictive, Local Data Model for Equity in Public Health Decision Making

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