Development of a vulnerability index for diagnosis with the novel coronavirus, COVID-19, in Washington State, USA

Amram, Ofer; Amiri, Solmaz; Lutz, Robert; Rajan, Bhardwaj; Monsivais, Pablo

doi:10.1016/j.healthplace.2020.102377

Cited by 49 publications

(61 citation statements)

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“…Further, researchers have been concerned with socioeconomic inequalities related to the risk of COVID-19 transmission ( Bambra et al, 2020 , Khalatbari-Soltani et al, 2020 ). For example, studies from the United States, where the highest number of cases and deaths have been observed, have shown that COVID-19 incidence and mortality were associated with poverty level at the zip code ( Amram et al, 2020 ) and county levels ( Zhang and Schwartz, 2020 ). Similar socioeconomic disparities were confirmed in Spain ( Baena-Díez et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…These studies indicate that income, education, and occupation may be key factors in the exposure risk of COVID-19. In addition, population density has been found to be associated with COVID-19 infections and deaths ( Amram et al, 2020 , Zhang and Schwartz, 2020 ). Japan has also seen an increased number of cases in metropolitan areas, including Tokyo and Osaka ( Japanese Ministry of Health, Labour and Welfare, 2020b ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Who is staying home and who is not? Demographic, socioeconomic, and geographic differences in time spent outside the home during the COVID-19 outbreak in Japan

Hanibuchi¹,

Yabe²,

Nakaya³

2021

Preventive Medicine Reports

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Who is staying home and who is not? Demographic, socioeconomic, and geographic differences in time spent outside the home during the COVID-19 outbreak in Japan

Hanibuchi¹,

Yabe²,

Nakaya³

2021

Preventive Medicine Reports

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“…26 Elevated COVID-19 infection risk was found among essential service occupations in a study of Washington State. 27 We found that service occupation type was not independently associated with risk of infection. It is possible the measure of essential employment excluded pertinent occupations, or was skewed toward a lower-risk essential workplace that was able to ensure social distancing practices and provide PPE.…”

Section: Relation To Previous Studiesmentioning

confidence: 61%

“…A dynamic evidence base indicates disproportionate risk of COVID-19 infection among some socio-demographic populations. 2,7,14,15,24,25,27 Our study helps to validate and expand understanding of these inequities, integrating several risk factors into an index reflecting composite vulnerability to infection. Our findings reinforce the urgent need for increased testing accessibility for vulnerable communities at higher risk of infection.…”

Section: Discussionmentioning

confidence: 96%

Data-Driven Development of a Small-Area COVID-19 Vulnerability Index for the United States

Amram

Amiri

et al. 2020

Preprint

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As the COVID-19 pandemic continues to surge in the United States, it has become clear that infection risk is higher in certain populations, particularly socially and economically marginalized groups. Social risk factors, together with other demographic and community characteristics, may reveal local variations and inequities in COVID risk that could be useful for targeting testing and interventions. Yet to date, rates of infection and estimations of COVID risk are typically reported at the county and state level. In this study we develop a small area vulnerability index based on publicly-available sociodemographic data and 668,428 COVID diagnoses reported in 4,803 ZIP codes in the United States (15% of all ZIP codes). The outcome was COVID-19 diagnosis rates per 100,000 people by ZIP code. Explanatory variables included sociodemographic characteristics obtained from the 2018 American Community Survey 5-year estimates. Bayesian multivariable techniques were used to capture complexities of spatial data and spatial autocorrelation and identify individual risk factors and derive their respective weights in the index. COVID-19 diagnosis rates varied from zero to 29,508 per 100,000 people. The final vulnerability index showed that higher population density, higher percentage of noninsured, nonwhite race and Hispanic ethnicity were positively associated with COVID-19 diagnosis rates. Our findings indicate disproportionate risk of COVID-19 infection among some populations and validate and expand understanding of these inequities, integrating several risk factors into a summary index reflecting composite vulnerability to infection. This index can provide local public health and other agencies with evidence-based metrics of COVID risk at a geographical scale that has not been previously available to most US communities.

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“…While it is an important study to help quantify the impacts of COVID-19 for AIAN Peoples, it is likely a gross under-estimation. Considering the serious data challenges, public health researchers and policy makers utilized the CDC's SVI to implement place-based COVID-19 mitigation efforts (Amram et al, 2020;Gaynor and Wilson, 2020;Kim and Bostwick, 2020); yet we identified that whether and how SVI can help mitigation efforts for Indigenous Peoples and communities is unclear. There were several key findings of the study.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 in New Mexico Tribal Lands: Understanding the Role of Social Vulnerabilities and Historical Racisms

2020

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The Coronavirus 2019 (COVID-19) pandemic has disproportionally affected Indigenous Peoples. Unfortunately, there is no accurate understanding of COVID-19's impacts on Indigenous Peoples and communities due to systematic erasure of Indigenous representation in data. Early evidence suggests that COVID-19 has been able to spread through pre-pandemic mechanisms ranging from disproportionate chronic health conditions, inadequate access to healthcare, and poor living conditions stemming from structural inequalities. Using innovative data, we comprehensively investigate the impacts of COVID-19 on Indigenous Peoples in New Mexico at the zip code level. Specifically, we expand the U.S. Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to include the measures of structural vulnerabilities from historical racisms against Indigenous Peoples. We found that historically-embedded structural vulnerabilities (e.g., Tribal land status and higher percentages of house units without telephone and complete plumbing) are critical in understanding the disproportionate burden of COVID-19 that American Indian and Alaska Native populations are experiencing. We found that historically-embedded vulnerability variables that emerged epistemologically from Indigenous knowledge had the largest explanatory power compared to other social vulnerability factors from SVI and COVID-19, especially Tribal land status. The findings demonstrate the critical need in public health to center Indigenous knowledge and methodologies in mitigating the deleterious impacts of COVID-19 on Indigenous Peoples and communities, specifically designing place-based mitigating strategies.

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Development of a vulnerability index for diagnosis with the novel coronavirus, COVID-19, in Washington State, USA

Cited by 49 publications

References 1 publication

Who is staying home and who is not? Demographic, socioeconomic, and geographic differences in time spent outside the home during the COVID-19 outbreak in Japan

Who is staying home and who is not? Demographic, socioeconomic, and geographic differences in time spent outside the home during the COVID-19 outbreak in Japan

Data-Driven Development of a Small-Area COVID-19 Vulnerability Index for the United States

COVID-19 in New Mexico Tribal Lands: Understanding the Role of Social Vulnerabilities and Historical Racisms

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