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Article: Counties with Lower Insurance Coverage and Housing Problems Are Associated with Both Slower Vaccine Rollout and Higher COVID-19 Incidence.

Donadio, Gregory / Choudhary, Mayank / Lindemer, Emily / Pawlowski, Colin / Soundararajan, Venky

2021 Volume 9, Issue 9

Abstract: Equitable vaccination distribution is a priority for outcompeting the transmission of COVID-19. Here, the impact of demographic, socioeconomic, and environmental factors on county-level vaccination rates and COVID-19 incidence changes is assessed. In ... ...

Abstract	Equitable vaccination distribution is a priority for outcompeting the transmission of COVID-19. Here, the impact of demographic, socioeconomic, and environmental factors on county-level vaccination rates and COVID-19 incidence changes is assessed. In particular, using data from 3142 US counties with over 328 million individuals, correlations were computed between cumulative vaccination rate and change in COVID-19 incidence from 1 December 2020 to 6 June 2021, with 44 different demographic, environmental, and socioeconomic factors. This correlation analysis was also performed using multivariate linear regression to adjust for age as a potential confounding variable. These correlation analyses demonstrated that counties with high levels of uninsured individuals have significantly lower COVID-19 vaccination rates (Spearman correlation: -0.460,
Language	English
Publishing date	2021-08-31
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2703319-3
ISSN	2076-393X
ISSN	2076-393X
DOI	10.3390/vaccines9090973
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Article ; Online: Counties with lower insurance coverage are associated with both slower vaccine rollout and higher COVID-19 incidence across the United States

Lindemer, Emily / Choudhary, Mayank / Donadio, Gregory / Pawlowski, Colin / Soundararajan, Venky

medRxiv

Abstract: Efficient and equitable vaccination distribution is a priority for effectively outcompeting the transmission of COVID-19 globally. A recent study from the Centers for Disease Control and Prevention (CDC) identified that US counties with high social ... ...

Abstract	Efficient and equitable vaccination distribution is a priority for effectively outcompeting the transmission of COVID-19 globally. A recent study from the Centers for Disease Control and Prevention (CDC) identified that US counties with high social vulnerability according to metrics such as poverty, unemployment, low income, and no high school diploma, have significantly lower rates of vaccination compared to the national average1. Here, we build upon this analysis to consider associations between county-level vaccination rates and 68 different demographic, socioeconomic, and environmental factors for 1,510 American counties with over 228 million individuals for which vaccination data was also available. Our analysis reveals that counties with high levels of uninsured individuals have significantly lower COVID-19 vaccination rates (Spearman correlation: -0.264), despite the fact that the CDC has mandated that all COVID-19 vaccines are free and cannot be denied to anyone based upon health insurance coverage or immigration status. Furthermore, we find that the counties with high levels of uninsured individuals tend to have the highest COVID-19 incidence rates in March 2021 relative to December 2020 (Spearman correlation: 0.388). Among the 68 factors analyzed, insurance coverage is the only factor which is highly correlated with both vaccination rate and change in COVID-19 incidence during the vaccination period (\|Spearman correlation\| > 0.25). We also find that counties with higher percentages of Black and Hispanic individuals have significantly lower vaccination rates (Spearman correlations: -0.128, -0.136) and lesser declines of COVID-incidence rates (Spearman correlations: 0.334, 0.330) during the vaccination period. Surprisingly however, after controlling for race, we find that the association between lack of insurance coverage and vaccination rate as well as COVID-19 incidence rates is largely driven by counties with a majority white population. Among the counties with high proportions of white residents (top 10% decile), the association between insurance coverage and vaccination rate is significant (Spearman correlation: -0.210, p-value: 0.002), but among counties with low proportions of white residents (bottom 10% decile) this association is not significant (Spearman correlation: 0.072, p-value: 0.088). Taken together, this study highlights the fact that intricate socioeconomic factors are correlated not just to COVID-19 vaccination rates, but also to COVID-19 incidence fluctuations, underscoring the need to improve COVID-19 vaccination campaigns in marginalized communities. The strong positive correlation between low levels of health insurance coverage and low vaccination rates is particularly concerning, and calls for improved public health messaging to emphasize the fact that health insurance is not required to be eligible for any of the FDA-authorized COVID-19 vaccines in the United States.
Keywords	covid19
Language	English
Publishing date	2021-03-26
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2021.03.24.21254270
Database	COVID19

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Article ; Online: "Yes, but will it work for

Panch, Trishan / Pollard, Tom J / Mattie, Heather / Lindemer, Emily / Keane, Pearse A / Celi, Leo Anthony

NPJ digital medicine

2020 Volume 3, Page(s) 87

Abstract: Benchmark datasets have a powerful normative influence: by determining how the real world is represented in data, they define which problems will first be solved by algorithms built using the datasets and, by extension, who these algorithms will ... ...

Abstract	Benchmark datasets have a powerful normative influence: by determining how the real world is represented in data, they define which problems will first be solved by algorithms built using the datasets and, by extension, who these algorithms will work
Keywords	covid19
Language	English
Publishing date	2020-06-19
Publishing country	England
Document type	Journal Article ; Review
ISSN	2398-6352
ISSN (online)	2398-6352
DOI	10.1038/s41746-020-0295-6
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Article ; Online: Two distinct classes of degenerative change are independently linked to clinical progression in mild cognitive impairment.

Coutu, Jean-Philippe / Lindemer, Emily R / Konukoglu, Ender / Salat, David H

Neurobiology of aging

2017 Volume 54, Page(s) 1–9

Abstract: We previously demonstrated 2 statistically distinct factors of degeneration in Alzheimer's disease: one strongly related to white matter damage and age interpreted as "age- and vascular-related", and the other related to cortical atrophy thought to ... ...

Abstract	We previously demonstrated 2 statistically distinct factors of degeneration in Alzheimer's disease: one strongly related to white matter damage and age interpreted as "age- and vascular-related", and the other related to cortical atrophy thought to represent "neurodegenerative changes associated with Alzheimer's disease". Those factors are now replicated in a distinct cross-sectional data set of 364 participants from the Alzheimer's Disease Neuroimaging Initiative and their interpretation is improved using correlations with CSF biomarkers. Furthermore, we now show that changes in both factors over 2 years are independently associated with decline in Mini-Mental State Examination score in a longitudinal subset of 116 individuals with mild cognitive impairment. Progression in the "age- and vascular-related" factor was greater for individuals with 2 APOE ε4 alleles and linked to a greater attributable change in Mini-Mental State Examination than the "neurodegenerative" factor. These results suggest benefits of targeting white matter and vascular health to complement interventions focused on the neurodegenerative aspect of the disease, even in individuals with little discernable vascular comorbidity.
MeSH term(s)	Aged ; Cerebral Cortex/diagnostic imaging ; Cerebral Cortex/pathology ; Cognitive Dysfunction/diagnostic imaging ; Cognitive Dysfunction/pathology ; Cross-Sectional Studies ; Datasets as Topic ; Disease Progression ; Female ; Humans ; Male ; Nerve Degeneration ; Neuroimaging ; White Matter/diagnostic imaging ; White Matter/pathology
Language	English
Publishing date	2017-02-16
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	604505-4
ISSN	1558-1497 ; 0197-4580
ISSN (online)	1558-1497
ISSN	0197-4580
DOI	10.1016/j.neurobiolaging.2017.02.005
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Article ; Online: White matter abnormalities and cognition in patients with conflicting diagnoses and CSF profiles.

Lindemer, Emily R / Greve, Douglas N / Fischl, Bruce / Salat, David H / Gomez-Isla, Teresa

Neurology

2018 Volume 90, Issue 17, Page(s) e1461–e1469

Abstract: Objective: To determine whether white matter changes influence progression of cognitive decline in individuals with clinically diagnosed Alzheimer disease (AD) and differing biomarker profiles.: Methods: Two hundred thirty-six individuals from the ... ...

Abstract	Objective: To determine whether white matter changes influence progression of cognitive decline in individuals with clinically diagnosed Alzheimer disease (AD) and differing biomarker profiles. Methods: Two hundred thirty-six individuals from the Alzheimer's Disease Neuroimaging Initiative database with clinical diagnoses of cognitively normal older adult (older controls [OCs]), mild cognitive impairment, and AD were studied. Support vector machine experiments were first performed to determine the utility of various biomarkers for classifying individuals by clinical diagnosis. General linear models were implemented to assess the relationships between CSF measures of β-amyloid 1-42, phosphorylated tau Results: CSF biomarkers alone classified individuals with AD vs OCs with 82% accuracy, and the addition of WMSA did not enhance this. Both CSF biomarkers as well as WMSA volume significantly contributed to predicting cognitive decline in executive and memory domains when assessed across all 236 individuals. In individuals with pathologic levels of both CSF biomarkers, WMSA only significantly contributed to models of future executive function decline. In individuals with subpathologic CSF biomarker levels (levels similar to those in OC individuals), WMSA significantly contributed to prediction of memory decline and were the sole significant predictor of executive function decline. Conclusions: WMSA hold additional predictive power regarding cognitive progression in older individuals and are most effective as biomarkers in individuals who are cognitively impaired but do not fit the expected CSF biomarker profile of AD.
MeSH term(s)	Alzheimer Disease/cerebrospinal fluid ; Alzheimer Disease/complications ; Alzheimer Disease/diagnostic imaging ; Amyloid beta-Peptides/cerebrospinal fluid ; Apolipoprotein E4/genetics ; Case-Control Studies ; Cognition Disorders/cerebrospinal fluid ; Cognition Disorders/complications ; Cognition Disorders/diagnostic imaging ; Female ; Humans ; Leukoaraiosis/complications ; Leukoaraiosis/diagnostic imaging ; Leukoaraiosis/pathology ; Linear Models ; Longitudinal Studies ; Magnetic Resonance Imaging ; Male ; Neuropsychological Tests ; Peptide Fragments/cerebrospinal fluid ; Sex Characteristics ; Support Vector Machine ; tau Proteins/cerebrospinal fluid
Chemical Substances	Amyloid beta-Peptides ; Apolipoprotein E4 ; Peptide Fragments ; amyloid beta-protein (1-42) ; tau Proteins
Language	English
Publishing date	2018-03-23
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000005353
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Article ; Online: Turning the crank for machine learning: ease, at what expense?

Pollard, Tom J / Chen, Irene / Wiens, Jenna / Horng, Steven / Wong, Danny / Ghassemi, Marzyeh / Mattie, Heather / Lindemer, Emily / Panch, Trishan

The Lancet. Digital health

2019 Volume 1, Issue 5, Page(s) e198–e199

MeSH term(s)	Arm ; Deep Learning ; Exercise Test ; Feasibility Studies ; Humans
Language	English
Publishing date	2019-09-05
Publishing country	England
Document type	Journal Article ; Comment
ISSN	2589-7500
ISSN (online)	2589-7500
DOI	10.1016/S2589-7500(19)30112-8
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Article ; Online: A Framework for Predicting Impactability of Digital Care Management Using Machine Learning Methods.

Mattie, Heather / Reidy, Patrick / Bachtiger, Patrik / Lindemer, Emily / Nikolaev, Nikolay / Jouni, Mohammad / Schaefer, Joann / Sherman, Michael / Panch, Trishan

Population health management

2019 Volume 23, Issue 4, Page(s) 319–325

Abstract: Digital care management programs can reduce health care costs and improve quality of care. However, it is unclear how to target patients who are most likely to benefit from these programs ex ante, a shortcoming of current "risk score"-based approaches ... ...

Abstract	Digital care management programs can reduce health care costs and improve quality of care. However, it is unclear how to target patients who are most likely to benefit from these programs ex ante, a shortcoming of current "risk score"-based approaches across many interventions. This study explores a framework to define impactability by using machine learning (ML) models to identify those patients most likely to benefit from a digital health intervention for care management. Anonymized insurance claims data were used from a commercially insured population across several US states and combined with inferred sociodemographic data. The approach involves creating 2 models and the comparative analysis of the methodologies and performances therein. The authors first train a cost prediction model to calculate the differences in predicted (without intervention) versus actual (with onboarding onto digital health platform) health care expenditures for patients (N
MeSH term(s)	Adult ; Costs and Cost Analysis ; Digital Technology/methods ; Female ; Humans ; Machine Learning ; Male ; Middle Aged ; Models, Statistical ; Telemedicine/methods
Language	English
Publishing date	2019-11-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2454546-6
ISSN	1942-7905 ; 1942-7891
ISSN (online)	1942-7905
ISSN	1942-7891
DOI	10.1089/pop.2019.0132
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Article ; Online: Regional staging of white matter signal abnormalities in aging and Alzheimer's disease.

Lindemer, Emily R / Greve, Douglas N / Fischl, Bruce R / Augustinack, Jean C / Salat, David H

NeuroImage. Clinical

2017 Volume 14, Page(s) 156–165

Abstract: White matter lesions, quantified as 'white matter signal abnormalities' (WMSA) on neuroimaging, are common incidental findings on brain images of older adults. This tissue damage is linked to cerebrovascular dysfunction and is associated with cognitive ... ...

Abstract	White matter lesions, quantified as 'white matter signal abnormalities' (WMSA) on neuroimaging, are common incidental findings on brain images of older adults. This tissue damage is linked to cerebrovascular dysfunction and is associated with cognitive decline. The regional distribution of WMSA throughout the cerebral white matter has been described at a gross scale; however, to date no prior study has described regional patterns relative to cortical gyral landmarks which may be important for understanding functional impact. Additionally, no prior study has described how regional WMSA volume scales with total global WMSA. Such information could be used in the creation of a pathologic 'staging' of WMSA through a detailed regional characterization at the individual level. Magnetic resonance imaging data from 97 cognitively-healthy older individuals (OC) aged 52-90 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were processed using a novel WMSA labeling procedure described in our prior work. WMSA were quantified regionally using a procedure that segments the cerebral white matter into 35 bilateral units based on proximity to landmarks in the cerebral cortex. An initial staging was performed by quantifying the regional WMSA volume in four groups based on quartiles of total WMSA volume (quartiles I-IV). A consistent spatial pattern of WMSA accumulation was observed with increasing quartile. A clustering procedure was then used to distinguish regions based on patterns of scaling of regional WMSA to global WMSA. Three patterns were extracted that showed high, medium, and non-scaling with global WMSA. Regions in the high-scaling cluster included periventricular, caudal and rostral middle frontal, inferior and superior parietal, supramarginal, and precuneus white matter. A data-driven staging procedure was then created based on patterns of WMSA scaling and specific regional cut-off values from the quartile analyses. Individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were then additionally staged, and significant differences in the percent of each diagnostic group in Stages I and IV were observed, with more AD individuals residing in Stage IV and more OC and MCI individuals residing in Stage I. These data demonstrate a consistent regional scaling relationship between global and regional WMSA that can be used to classify individuals into one of four stages of white matter disease. White matter staging could play an important role in a better understanding and the treatment of cerebrovascular contributions to brain aging and dementia.
MeSH term(s)	Aged ; Aged, 80 and over ; Aging/pathology ; Alzheimer Disease/complications ; Alzheimer Disease/diagnostic imaging ; Analysis of Variance ; Brain Mapping ; Diffusion Tensor Imaging ; Female ; Humans ; Image Processing, Computer-Assisted ; Leukoencephalopathies/diagnostic imaging ; Leukoencephalopathies/etiology ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Psychiatric Status Rating Scales
Language	English
Publishing date	2017-01-23
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2701571-3
ISSN	2213-1582 ; 2213-1582
ISSN (online)	2213-1582
ISSN	2213-1582
DOI	10.1016/j.nicl.2017.01.022
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Article ; Online: Differential Regional Distribution of Juxtacortical White Matter Signal Abnormalities in Aging and Alzheimer's Disease.

Lindemer, Emily R / Greve, Douglas N / Fischl, Bruce / Augustinack, Jean C / Salat, David H

Journal of Alzheimer's disease : JAD

2017 Volume 57, Issue 1, Page(s) 293–303

Abstract: Background: White matter signal abnormalities (WMSA) (also known as 'hyperintensities') on MRI are commonly seen in normal aging and increases have been noted in Alzheimer's disease (AD), but whether there is a spatial specificity to these increases is ... ...

Abstract	Background: White matter signal abnormalities (WMSA) (also known as 'hyperintensities') on MRI are commonly seen in normal aging and increases have been noted in Alzheimer's disease (AD), but whether there is a spatial specificity to these increases is unknown. Objective: To discern whether or not there is a spatial pattern of WMSA in the brains of individuals with AD that differs from those who exhibit cognitively healthy aging. Method: Structural MRI data from the Alzheimer's Disease Neuroimaging Initiative public database were used to quantify WMSA in 35 regions of interest (ROIs). Regional measures were compared between cognitively healthy older controls (OC; n = 107) and individuals with a clinical diagnosis of AD (n = 127). Regional WMSA volume was also assessed in individuals with mild cognitive impairment (MCI; n = 74) who were 6, 12, and 24 months away from AD conversion. Results: WMSA volume was significantly greater in AD compared to OC in 24 out of 35 ROIs after controlling for age, and nine were significantly higher after normalizing for total WMSA. Regions with greater WMSA volume in AD included rostral frontal, inferior temporal, and inferior parietal WM. In MCI, frontal and temporal regions demonstrated significantly greater WMSA volume with decreasing time-to-AD-conversion. Discussion: Individuals with AD have greater regional volume of WMSA compared to OC regardless of age or total WMSA volume. Accumulation of regional WMSA is linked to time to AD conversion in individuals with MCI. These findings indicate WMSA is an important pathological component of AD development.
MeSH term(s)	Aged ; Alzheimer Disease/diagnostic imaging ; Brain/diagnostic imaging ; Female ; Healthy Aging/pathology ; Humans ; Magnetic Resonance Imaging ; Male ; Organ Size ; White Matter/diagnostic imaging
Language	English
Publishing date	2017-01-12
Publishing country	Netherlands
Document type	Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1440127-7
ISSN	1875-8908 ; 1387-2877
ISSN (online)	1875-8908
ISSN	1387-2877
DOI	10.3233/JAD-161057
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Article ; Online: Case fatality rates for COVID-19 are higher than case fatality rates for motor vehicle accidents for individuals over 40 years of age

Puranik, Arjun / Niesen, Michiel J.M. / Lindemer, Emily / Lenehan, Patrick / Cristea-Platon, Tudor / Pawlowski, Colin / Soundararajan, Venky

medRxiv

Abstract: The death toll of the COVID-19 pandemic has been unprecedented, due to both the high number of SARS-CoV-2 infections and the seriousness of the disease resulting from these infections. Here, we present mortality rates and case fatality rates for COVID-19 ...

Abstract	The death toll of the COVID-19 pandemic has been unprecedented, due to both the high number of SARS-CoV-2 infections and the seriousness of the disease resulting from these infections. Here, we present mortality rates and case fatality rates for COVID-19 over the past year compared with other historic leading causes of death in the United States. Among the risk categories considered, COVID-19 is the third leading cause of death for individuals 40 years old and over, with an overall annual mortality rate of 325 deaths per 100K individuals, behind only cancer (385 deaths per 100K individuals) and heart disease (412 deaths per 100K individuals). In addition, for individuals 40 years old and over, the case fatality rate for COVID-19 is greater than the case fatality rate for motor vehicle accidents. In particular, for the age group 40-49, the relative case fatality rate of COVID-19 is 1.5 fold (95% CI: [1.3, 1.7]) that of a motor vehicle accident, demonstrating that SARS-CoV-2 infection may be significantly more dangerous than a car crash for this age group. For older adults, COVID-19 is even more dangerous, and the relative case fatality rate of COVID-19 is 29.4 fold (95% CI: [23.2, 35.7]) that of a motor vehicle accident for individuals over 80 years old. On the other hand, motor vehicle accidents have a 4.5 fold (95% CI: [3.9, 5.1]) greater relative case fatality rate compared to COVID-19 for the age group of 20-29 years. These results highlight the severity of the COVID-19 pandemic especially for adults above 40 years of age and underscore the need for large-scale preventative measures to mitigate risks for these populations. Given that FDA-authorized COVID-19 vaccines have now been validated by multiple studies for their outstanding real-world effectiveness and safety, vaccination of all individuals who are over 40 years of age is one of the most pressing public health priorities of our time.
Keywords	covid19
Language	English
Publishing date	2021-04-13
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2021.04.09.21255193
Database	COVID19

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