Research Projects Directory

Research Projects Directory

10,053 active projects

This information was updated 3/28/2024

The Research Projects Directory includes information about all projects that currently exist in the Researcher Workbench to help provide transparency about how the Workbench is being used. Each project specifies whether Registered Tier or Controlled Tier data are used.

Note: Researcher Workbench users provide information about their research projects independently. Views expressed in the Research Projects Directory belong to the relevant users and do not necessarily represent those of the All of Us Research Program. Information in the Research Projects Directory is also cross-posted on AllofUs.nih.gov in compliance with the 21st Century Cures Act.

342 projects have 'COVID' in the scientific questions being studied description
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Homeless project(Data- V7)-Final

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Scientific Questions Being Studied

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Project Purpose(s)

  • Educational

Scientific Approaches

I want to apply various machine learning ,data analysis and statistical technique so That I can find out correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Anticipated Findings

I have found that COPD, smoking history and certain diseases play a pivotal role in Covid-19 hospitalizations.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • J M Imtinan Uddin - Graduate Trainee, University of Tennessee, Chattanooga
  • Hong Qin - Mid-career Tenured Researcher, University of Tennessee, Chattanooga

Collaborators:

  • Mohammad Aman Ullah Al Amin - Graduate Trainee, University of Tennessee, Chattanooga

Duplicate of "Official State" Language Equity

With a growing diverse, immigrant-based population in the US we need to ensure that everyone has the healthy literacy and knowledge to protect us all. In the US with many speaking another primary language or language other than English at…

Scientific Questions Being Studied

With a growing diverse, immigrant-based population in the US we need to ensure that everyone has the healthy literacy and knowledge to protect us all. In the US with many speaking another primary language or language other than English at home, states that have put forward "English-only" legislation require government information (health, voting information, personal rights) are limiting the scope and reach of this information that these institutions themselves consider vital.

My current project looks to see how the communities in these different states are impacted in their education, workplace safety, COVID understanding, and neighborhood based on "English-only" verse other language requirements or no requirements.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

1) Three-digit zipcode related data to show comparisons between Illinois and Conneticut which have a similar Limited English Proficiency population and Immigrant population, but differ for state language (Illinois is English Only)
2) Consider socio-demographic variables, but also adjust the analysis for health and healthcare access variables including insurance, chronic conditions, primary care. etc.
3) Outcomes of COVID-19 understanding, protection access, and self-reported health

Anticipated Findings

Current research highlights how trust in the source of information influences following guidance and was especially the case related to the government during the COVID-19 pandemic and initial rollout of protective behavior advice and vaccination. Studies have also highlighted how Limited English Proficiency is an additional barriers to immigrants and those who speak another language than English at home. The combination of the government only being required to share information in English may further have immigrants feel isolated and unable to receive necessary healthcare.

Demographic Categories of Interest

  • Race / Ethnicity
  • Access to Care
  • Others

Data Set Used

Controlled Tier

Research Team

Owner:

PASC Data Exploration

The purpose of this study is to evaluate the effect of data shifts on prediction of Long COVID. Data shifts occur when models trained on source environments perform worse in target environments. This question is important because examining the impact…

Scientific Questions Being Studied

The purpose of this study is to evaluate the effect of data shifts on prediction of Long COVID. Data shifts occur when models trained on source environments perform worse in target environments. This question is important because examining the impact of data shifts on Long COVID can help assess how models will perform in different environments and with different populations.

Project Purpose(s)

  • Disease Focused Research (Long COVID)

Scientific Approaches

I plan to use the All of Us data to identify a cohort of Long COVID patients and relevant controls. A temporal machine learning model will be used to determine source accuracy and further experiments will be used to assess accuracy in different environments.

Anticipated Findings

We anticipate that model performance will decrease in target environments when compared to the source environments. These results would contribute to the body of scientific knowledge by providing visibility to the impact of developing Long COVID prediction models without extensive testing in target environments.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Covid/Appendicitis

The purpose of this investigation is to learn whether having COVID predisposes individuals to have an episode of acute appendicitis.

Scientific Questions Being Studied

The purpose of this investigation is to learn whether having COVID predisposes individuals to have an episode of acute appendicitis.

Project Purpose(s)

  • Disease Focused Research (Covid 19)

Scientific Approaches

The All Of Us dataset will be queried for patients with appendicitis and COVID, and the R software package will be used to ascertain any statistical significance between the two conditions.

Anticipated Findings

If an association is found, this would open a new avenue of research that would allow scientists to better understand the pathogenesis of both of these conditions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Scott Taber - Graduate Trainee, Baylor College of Medicine

Built_environment_covid_V4

Study the COVID-19 spread and mental health associated with built environment using COPE COVID-19 survey data. COPE data provides unique opportunity to study the medical and social impacts of built environment, such as the household types. The study will conduct…

Scientific Questions Being Studied

Study the COVID-19 spread and mental health associated with built environment using COPE COVID-19 survey data. COPE data provides unique opportunity to study the medical and social impacts of built environment, such as the household types. The study will conduct secondary use of the survey to study the association, providing evidence for policy makers.

Project Purpose(s)

  • Disease Focused Research (COVID-19)
  • Social / Behavioral
  • Ethical, Legal, and Social Implications (ELSI)

Scientific Approaches

We will use the COPE survey data and conduct logistic regression analyses to study the associations.

Anticipated Findings

We expect built environment types will be associated with the spread of COVID-19 and potentially impose stress to the residents. We also expect indoor behaviors (e.g., shopping) will be related to COVID-19 spread.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Haiquan Li - Early Career Tenure-track Researcher, University of Arizona

Collaborators:

  • Wenting luo - Graduate Trainee, University of Arizona
  • Anna Jiang - Undergraduate Student, University of Arizona
  • Edwin Baldwin - Graduate Trainee, University of Arizona

COVID and Health Literacy

Although there are vaccinations and treatments for COVID-19, negative health outcomes persist for various groups of individuals. Previous studies show how housing status (Ahmad et al.), income (Clouston et al.), and speaking a non-English language (Rozenfeld et al.) were significant…

Scientific Questions Being Studied

Although there are vaccinations and treatments for COVID-19, negative health outcomes persist for various groups of individuals. Previous studies show how housing status (Ahmad et al.), income (Clouston et al.), and speaking a non-English language (Rozenfeld et al.) were significant risk factors for one’s health outcomes during the pandemic. Health literacy is thought to be one way to promote disease prevention (Hange et al.). We hope to explore the data to better understand the impact and the nuances of using health literacy as a disease prevention tool. We are specifically interested in understanding how health literacy relates to resilience against COVID-19 among diverse populations. We aim to see what interventions are necessary and could be implemented before major public health crises to make populations more resilient and overcome barriers to accessing healthcare. We hypothesize that health literacy is a powerful tool that can be used to overcome health disparities.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

We intend to first use exploratory data analysis to find basic trends. We will use statistical methods to find correlations and relationships among the data. The datasets we will use will be specific for health literacy, other social determinants of health (i.e., food insecurity, income, etc.), and we will algin those data sets with de-identified demographic information and health outcomes. We are especially interested in the COVID-19 data and the surveys collected. The tools we will use include the All of Us datasets and any relevant statistical software that can be used when studying this data set. Again, we hope to find predictive variables that can shed insight into how health literacy – or, perhaps, other social determinants of health – can be used to make communities more prepared for when public health emergencies arise.

Anticipated Findings

We anticipate corroborating with previous research and finding that the social determinants of health are a major factor in promoting resilience and well-being during COVID-19. If this is the case, this will support our understanding of how to enable academic and other institutions to better collaborate with diverse populations and enable them to be more self-sufficient. We intend to bring a strengths-based and culture-based approach to studying the information and to, again, better support populations in future public health emergencies.

Demographic Categories of Interest

  • Age
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

GMS6805_v2

for a class research project we want to investigate relationship between obesity, measures of perceived stress and covid. we are interested in additional relationship for obese patients in underserved and rural areas.

Scientific Questions Being Studied

for a class research project we want to investigate relationship between obesity, measures of perceived stress and covid. we are interested in additional relationship for obese patients in underserved and rural areas.

Project Purpose(s)

  • Educational

Scientific Approaches

we are hoping to use EHR domains and physical measurement domains to identify obese patients. we also plan to use survey questions to identify factors related to SDOH, health care access and how they relate to obesity and have changed during covid.

Anticipated Findings

We expect to find that patients with obesityhave worse outcomes. Additionally, we expect those outcomes to be mitigated by location, health care access and SDOH factors

Demographic Categories of Interest

  • Geography
  • Others

Data Set Used

Controlled Tier

Research Team

Owner:

Mental Health After COVID

In this study I intend to answer: 1. How COVID-19 affected the mental health of adults starting from 2020-present? 2. How many of these individuals turned to substance abuse to deal with their declining mental health? The reason for exploring…

Scientific Questions Being Studied

In this study I intend to answer:
1. How COVID-19 affected the mental health of adults starting from 2020-present?
2. How many of these individuals turned to substance abuse to deal with their declining mental health?

The reason for exploring this data is because many people within my community are still suffering from the affects of COVID today and many of them self-cope in an unhealthy way.

Project Purpose(s)

  • Educational

Scientific Approaches

I plan to look at and compare electronic health records, health and lifestyle surveys, patients overall health and lifestyle for this study. I will also be looking at COVD-19 participant experience, and social determinants of health further progress in this study.

Anticipated Findings

I expect to find that the mental health of many adults and adolescents did in fact decline through the COVID-19 years. When this occurred, many drove to substance abuse to further cope with the issues they were facing whether it may be financial, socially, or just within themselves. I believe that this information can give the science community a better look into how pandemics can leave an impact even after vaccines and cures were brought out.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

Smell loss and Social Determinants of Health

Smell loss has been an increasing issue since the COVID pandemic. The goal of this study is to determine if there are sociodemographic barriers to healthcare access for patients who suffer from smell loss.

Scientific Questions Being Studied

Smell loss has been an increasing issue since the COVID pandemic. The goal of this study is to determine if there are sociodemographic barriers to healthcare access for patients who suffer from smell loss.

Project Purpose(s)

  • Disease Focused Research (Smell Loss)

Scientific Approaches

The database will be searched for all participants with a diagnosis of smell loss. Responses to the health care access and utilization survey will be obtained. The data will undergo a de-identification process before becoming available for analysis. We will seek to answer the question: What components undermine the patient-physician relationship in patients with smell loss and how do these factors negatively influence the access and utilization of health care services in patients?

Anticipated Findings

I would expect those with lower socioeconomic factors have worse access for care for their smell loss. I would expect being unable to afford specialists or followup care to also be a high barrier. Difficult to understand health information may also impact their access.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Dennis Tang - Senior Researcher, Cedars-Sinai Medical Center

Test for manuscript preparation

Exploring the data to see the number of individuals with diabetes and COVID-19 within the database. Future research will focus on new-onset diabetes in individuals diagnosed with COVID-19.

Scientific Questions Being Studied

Exploring the data to see the number of individuals with diabetes and COVID-19 within the database. Future research will focus on new-onset diabetes in individuals diagnosed with COVID-19.

Project Purpose(s)

  • Disease Focused Research (Diabetes Mellitus and COVID-19)

Scientific Approaches

Datasets will include individuals with new-onset diabetes and COVID-19 . GWAS studies will be utilized to assess genetic risk scores and the social determinants of health survey will be used to analyze social determinants of health in this population.

Anticipated Findings

The findings from the study will provide foundational information about individuals diagnosed with new-onset diabetes after COVID-19 infection.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Theresa Koleck - Early Career Tenure-track Researcher, University of Pittsburgh

Impact of long COVID on surgical outcomes

Long Covid is a significant health care burden. During COVID a meaningful pause was placed on elective surgery. We have emerged from the pandemic with a number of a patients being impacted by longCOVID. Understanding the impacts on recovery are…

Scientific Questions Being Studied

Long Covid is a significant health care burden. During COVID a meaningful pause was placed on elective surgery. We have emerged from the pandemic with a number of a patients being impacted by longCOVID. Understanding the impacts on recovery are important for planning. First we will identify the clinical (seeking care) and societal burden (impacted with long COVID but did not seek care for this) of long COVID and the number of surgical procedures being performed. We will determine in peri-operative outcomes are impacted. Examples of outcomes include length of stay, complications post operatively and readmission rate.

Project Purpose(s)

  • Disease Focused Research (Long Covid impacts on surgical recovery)
  • Control Set
  • Ancestry

Scientific Approaches

We will use questionnaires, demographic data, and ICD10 cm codes to determine the extent of Long Covid across a number of domains. We wish to understand if there is a difference in health care utilization in participants in All of US compared to clinical cohorts from local EHR data. This is an initial exploration of the data set to better understand the fields available and better understand the prevalence of the condition in this population. As understanding of the dataset grows we will seek to better understand risk factors for the development of the condition including potential genomic predictors. We will need a control cohort of patients which match baseline characteristics.

Anticipated Findings

We hypothesize that patients with longCOVID experience worse perioperative outcomes compared to those who do not have long COVID.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Access to Care

Data Set Used

Controlled Tier

Research Team

Owner:

Re-purposing Computable Phenotypes for Public Health Disease Surveillance

This study proposes a novel application for a well-established method of cohort identification in biomedical research, known as computable phenotyping, for EHR-based public health surveillance of chronic diseases. At the core of the proposed research study is the repurposing of…

Scientific Questions Being Studied

This study proposes a novel application for a well-established method of cohort identification in biomedical research, known as computable phenotyping, for EHR-based public health surveillance of chronic diseases. At the core of the proposed research study is the repurposing of already developed and validated EHR-based computable phenotyping algorithms for disease surveillance while assessing those algorithms’ transferability or portability to two national data repositories, All of Us Research Program and National COVID Cohort Collaborative (N3C), and establishing the concordance between repurposed computable phenotypes within and across two distinct data networks. The outcome measure for evaluating computable phenotype performance will be disease prevalence estimates.

Project Purpose(s)

  • Disease Focused Research (type 2 diabetes, depression, dementia, asthma, breast cancer, lung cancer)
  • Population Health
  • Educational
  • Methods Development
  • Control Set

Scientific Approaches

EHR data will be used to apply algorithms designed for patient cohort identification from a number of large research networks (eMERGE/PheKB, PCORnet, OHDSI and MDPHnet ) to ascertain disease prevalence estimates for a number of chronic diseases and conditions. Performance of re-purposed algorithms will be compared within All of Us and between All of Us and N3C. Prevalence estimates will be validated against those from the most recent traditional national surveillance surveys (i.e. American Community Survey, NHANES, BRFSS).

Anticipated Findings

Using computable phenotyping algorithms for disease surveillance is a novel application. Re-using already developed and validated algorithms for disease surveillance is also a novel approach which would maximize the utility of resources spent in developing and validating each algorithm.

Demographic Categories of Interest

  • Age
  • Geography

Data Set Used

Controlled Tier

Research Team

Owner:

Duplicate of Covid-19 vaccine uptake among cancer survivors V

The purpose of the study is to evaluate the modifiable, multilevel factors associated with COVID-19 vaccine uptake among cancer survivors from the All of Us dataset.

Scientific Questions Being Studied

The purpose of the study is to evaluate the modifiable, multilevel factors associated with COVID-19 vaccine uptake among cancer survivors from the All of Us dataset.

Project Purpose(s)

  • Disease Focused Research (cancer)
  • Population Health
  • Social / Behavioral

Scientific Approaches

A cohort of cancer survivors will be from using the database. Various survey questions will aid in answering our research aims. In addition, the covid-19 survey questionnaires will also be used to determine our outcome of interest.

Anticipated Findings

Multilevel factors are anticipated to be associated with vaccine uptake and hesitance. These results can help to identify specific characteristics of cancer survivors that make them more or less likely to experience vaccine hesitancy and inform efforts to target, adapt and tailor interventions to their needs.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Angel Arizpe - Graduate Trainee, University of Southern California
  • Albert Farias - Early Career Tenure-track Researcher, University of Southern California

Collaborators:

  • Katelyn Queen - Graduate Trainee, University of Southern California
  • Alberto Carvajal Jr - Graduate Trainee, University of Southern California

COVID-19 and risk of hidradenitis suppurativa

In people who were diagnosed with hidradenitis suppurativa between 2020 and 2024, how many were exposed to COVID-19 prior to diagnosis, compared to the people affected with COVID-19 without hidradenitis suppurativa? Hidradenitis suppurativa is a chronic inflammatory disease characterized by…

Scientific Questions Being Studied

In people who were diagnosed with hidradenitis suppurativa between 2020 and 2024, how many were exposed to COVID-19 prior to diagnosis, compared to the people affected with COVID-19 without hidradenitis suppurativa?

Hidradenitis suppurativa is a chronic inflammatory disease characterized by painful and inflamed nodules accompanied by draining sinus tracts. Inflammatory overactivation occurs in COVID-19 infection, and prior COVID-19 may be a risk factor for subsequent hidradenitis suppurativa diagnosis. Understanding risk factors for hidradenitis suppurativa will both further elucidate its pathogenesis and aid in diagnosis and prevention.

Project Purpose(s)

  • Disease Focused Research (hidradenitis suppurativa)

Scientific Approaches

This case control study will aim to use the All of Us Registered Tier Dataset v7. R will be used for statistical analyses.

Anticipated Findings

It is anticipated that COVID-19 will increase risk of hidradenitis occurrence. These findings will advance the risk factor management for hidradenitis suppurativa, as well as advance understanding of its pathogenesis.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Han Li - Graduate Trainee, University of Florida

JAK/STAT SNPs

We will identify human SNPs on JAK and STAT genes that are related to immune response. We have 500 data set from COVID-19 vaccination and identified their SNPs. However, we don't know those SNPs are related to disease or different…

Scientific Questions Being Studied

We will identify human SNPs on JAK and STAT genes that are related to immune response. We have 500 data set from COVID-19 vaccination and identified their SNPs. However, we don't know those SNPs are related to disease or different extent of immunity. Therefore, we want to know how much each SNP has been identified in human sample using all of US data base.

Project Purpose(s)

  • Methods Development
  • Control Set
  • Ancestry

Scientific Approaches

I have a SNP list from our COVID-19 vaccination study and want to check how many people carry certain SNPs on JAK and STAT genes from the list. Finally, I want to determine which SNPs are pathogenic and which one can regulate immunity even though it is not related to any disease.

Anticipated Findings

Many groups are interested in identifying human SNPs using GWAS study. However, only a few are validated their function, and not all SNPs cause disease. Therefore, I want to classify pathogenic ones and nonpathogenic ones and investigate what nonpathogenic ones play role in immunity, especially in the manner of vaccination. If I find answer for this question, we can understand about vaccination effect in certain population carrying those SNPs.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Hye Kyung Lee - Senior Researcher, National Institute of Diabetes and Digestive and Kidney Diseases (NIH - NIDDK)

Perinatal Health Controlled

Do the Latino health patterns in All of Us data replicate well-established Latino paradox patterns in pregnancy outcomes? Has COVID-19 disrupted this pattern?

Scientific Questions Being Studied

Do the Latino health patterns in All of Us data replicate well-established Latino paradox patterns in pregnancy outcomes? Has COVID-19 disrupted this pattern?

Project Purpose(s)

  • Population Health

Scientific Approaches

All variables necessary for carrying out this research project are available in the All of Us data. Descriptive analyses will first focus on breaking down and stratifying pregnancy outcomes into cross-tabulations rates in the following ways:
• Hispanic/Latino versus non-Hispanic Latino White, non-Hispanic Latino Black, and non-Hispanic Latino Asian groups;
• Then, to explore whether these patterns vary by US-born versus foreign-born status (using country of birth or preferred language as a proxy, depending on what’s available in the dataset)

Anticipated Findings

We expect patterns between non-Hispanic Whites and Hispanic/Latinos to be similar, but when splitting by nativity status, for us to see differences, with US born Hispanic/Latinos having worse patterns compared to foreign born Hispanic/Latinos.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Vida Pourmand - Graduate Trainee, University of California, Irvine

Perinatal paper

Do the Latino health patterns in All of Us data replicate well-established Latino paradox patterns in pregnancy outcomes? Has COVID-19 disrupted this pattern?

Scientific Questions Being Studied

Do the Latino health patterns in All of Us data replicate well-established Latino paradox patterns in pregnancy outcomes? Has COVID-19 disrupted this pattern?

Project Purpose(s)

  • Population Health

Scientific Approaches

All variables necessary for carrying out this research project are available in the All of Us data. Descriptive analyses will first focus on breaking down and stratifying pregnancy outcomes into cross-tabulations rates in the following ways:
• Hispanic/Latino versus non-Hispanic Latino White, non-Hispanic Latino Black, and non-Hispanic Latino Asian groups;
• Then, to explore whether these patterns vary by US-born versus foreign-born status (using country of birth or preferred language as a proxy, depending on what’s available in the dataset)

Anticipated Findings

We expect patterns between non-Hispanic Whites and Hispanic/Latinos to be similar, but when splitting by nativity status, for us to see differences, with US born Hispanic/Latinos having worse patterns compared to foreign born Hispanic/Latinos.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Registered Tier

Research Team

Owner:

  • Vida Pourmand - Graduate Trainee, University of California, Irvine

Vaccine Utilization

Research question: What factors affect vaccine utilization rates in Latino/Hispanic, Black, and African-American groups across the United States? This question is important because addressing vaccine hesitancy is crucial for achieving widespread vaccination and controlling the COVID-19 pandemic. Those communities have…

Scientific Questions Being Studied

Research question: What factors affect vaccine utilization rates in Latino/Hispanic, Black, and African-American groups across the United States?

This question is important because addressing vaccine hesitancy is crucial for achieving widespread vaccination and controlling the COVID-19 pandemic. Those communities have been disproportionately affected by the pandemic, experiencing higher infection rates and worse health outcomes. Identifying the factors that contribute to vaccine hesitancy in these communities will help public health officials and policymakers develop targeted interventions to increase vaccination rates and reduce disparities in COVID-19 outcomes. This research will provide valuable insights that can inform public health strategies and improve health equity for all communities.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational

Scientific Approaches

For our study on vaccine hesitancy among racialized communities in COVID-19 using quantitative analysis of survey datasets to identify trends. We will use R for analysis. This approach will provide a comprehensive understanding of vaccine hesitancy in these communities, aiding targeted interventions for public health improvement.

Anticipated Findings

The study anticipates identifying key factors influencing vaccine hesitancy including access to healthcare, historical mistrust, and cultural beliefs. Understanding these factors and how they interact will be critical for developing targeted interventions to improve vaccination rates and reduce disparities in COVID-19 outcomes.

The findings will contribute to the scientific knowledge by providing insights into the impact of vaccine hesitancy on vaccination rates and COVID-19 outcomes among racialized communities, informing public health interventions, and highlighting the importance of addressing social determinants of health in promoting vaccine uptake.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Data Set Used

Controlled Tier

Research Team

Owner:

SUD

Evaluating Substance Use Disorder as it relates to Covid-19 Outcomes

Scientific Questions Being Studied

Evaluating Substance Use Disorder as it relates to Covid-19 Outcomes

Project Purpose(s)

  • Disease Focused Research (substance-related disorder)
  • Educational
  • Methods Development
  • Control Set

Scientific Approaches

Fill in later

Anticipated Findings

Fill in later

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Uma Sarder - Graduate Trainee, Meharry Medical College
  • Wajehah Sanders - Graduate Trainee, Meharry Medical College
  • Saul Ashley - Graduate Trainee, Meharry Medical College
  • Aize Cao - Early Career Tenure-track Researcher, Meharry Medical College
  • Jeffrey Goodwin - Early Career Tenure-track Researcher, Meharry Medical College
  • Christopher Brown - Graduate Trainee, Meharry Medical College

DB7 of CRS study

What are some of the significant characteristics of Covid 19 patients who lost sense of smell. Why important: to understand the potential cause of the loss of smell for Covid 19 Patients.

Scientific Questions Being Studied

What are some of the significant characteristics of Covid 19 patients who lost sense of smell.
Why important: to understand the potential cause of the loss of smell for Covid 19 Patients.

Project Purpose(s)

  • Disease Focused Research (covid 19)
  • Methods Development

Scientific Approaches

Build ML models to discover the potentail patterns for the Covid 19 patients who had smell lose

Anticipated Findings

Find significant features that can predict the smell lose for Covid 19 patients and potentially guide the recovery process of the patients

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Renjie Hu - Early Career Tenure-track Researcher, University of Houston

Collaborators:

  • Thamer Alnazzal - Graduate Trainee, University of Houston
  • Roshan Dongre - Graduate Trainee, Houston Methodist Research Institute
  • Najm Khan - Graduate Trainee, Rutgers, The State University of New Jersey
  • Meher Gajula - Graduate Trainee, University of Houston
  • lichang zhu - Graduate Trainee, University of Houston
  • Faizaan Khan - Graduate Trainee, Houston Methodist Research Institute
  • Ying Lin - Early Career Tenure-track Researcher, University of Houston
  • Aatin Dhanda - Graduate Trainee, Rutgers, The State University of New Jersey
  • Sai Phani Ram Popuri - Graduate Trainee, University of Houston
  • Muyun Lu - Graduate Trainee, University of Houston

Discrimination, Depression, Suicide

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Scientific Questions Being Studied

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational

Scientific Approaches

We will use the COVID-19 Participant Experience (COPE) survey and the Patient Health Questionnaire (PHQ-9). We will conduct mixed effects modeling and lagged analyses. We may also conduct mediation analyses.

Anticipated Findings

We anticipate that people who experience higher levels of discrimination will be more likely to have increased symptoms of depression and suicidality.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Registered Tier

Research Team

Owner:

  • Sarah Lee - Graduate Trainee, University of Massachusetts Medical School

Collaborators:

  • Alexander Wilkins - Other, University of Massachusetts Medical School

covid

We are evaluating the impact of socioeconomic risk factors and particulate matter exposure on severity of COVID-19 outcomes.

Scientific Questions Being Studied

We are evaluating the impact of socioeconomic risk factors and particulate matter exposure on severity of COVID-19 outcomes.

Project Purpose(s)

  • Disease Focused Research (covid)

Scientific Approaches

Dataset will have all patients with COVID > 18 years of age. We will perform descriptives and logistic regression.

Anticipated Findings

We anticipate that higher particulate matter exposure contributes to more severe disease and contributes to mortality.

Demographic Categories of Interest

  • Age
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Sophia Kwon - Early Career Tenure-track Researcher, New York University, Grossman School of Medicine

Duplicate of AOU_Recover_Long_Covid_v6

The purpose of this workspace was to implement the published XGBoost machine learning (ML) model, which was developed using the National COVID Cohort Collaborative’s (N3C) EHR repository to identify potential patients with PASC/Long COVID in All of Us Research Program.

Scientific Questions Being Studied

The purpose of this workspace was to implement the published XGBoost machine learning (ML) model, which was developed using the National COVID Cohort Collaborative’s (N3C) EHR repository to identify potential patients with PASC/Long COVID in All of Us Research Program.

Project Purpose(s)

  • Disease Focused Research (Long COVID)
  • Population Health
  • Methods Development
  • Control Set
  • Ancestry

Scientific Approaches

To achieve this objective, data science workflows were used to apply ML algorithms on the Researcher Workbench. This effort allowed an expansion in the number of participants used to evaluate the ML models used to identify risk of PASC/Long COVID and also serve to validate the efforts of one team and providing insight to other teams. These models were implemented within the All of Us Controlled Tier data (C2022Q2R2), which was last refreshed on June 22, 2022. We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset.

Anticipated Findings

We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset.

Demographic Categories of Interest

  • Age
  • Geography
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Sophia Kwon - Early Career Tenure-track Researcher, New York University, Grossman School of Medicine

Chronic respiratory diseases after TB and need for rehabilitation

The incidence of reported tuberculosis (TB) in the United States is about 2.7 cases per 100,000 persons every year except in 2020, a year that coincides with COVID-19. In 2022 8,331 TB cases were reported in the United States. Studies…

Scientific Questions Being Studied

The incidence of reported tuberculosis (TB) in the United States is about 2.7 cases per 100,000 persons every year except in 2020, a year that coincides with COVID-19. In 2022 8,331 TB cases were reported in the United States. Studies report higher chronic respiratory diseases among survivors of TB infection. A substantial proportion of tuberculosis patients remain with pulmonary symptoms and reduced physical capacity despite successful treatment. The objective of this research is to 1) assess the distribution of chronic respiratory disease development among diverse TB infection survivors in the United States, 2) evaluate disparity post-TB follow-up (and respiratory rehabilitation effort, if any) disparity by birthplace (foreign-born vs domestic-born), Race/ethnicity, and insurance status, and 3) develop a prediction model on who would develop chronic respiratory disease among TB-infection survivors.

Project Purpose(s)

  • Disease Focused Research (tuberculosis)
  • Population Health

Scientific Approaches

The data set for this research will be a cohort of TB infection survivors. we will use descriptive and regression methods to analyze this data. We will use Python code in Jupyter Notebook to analyze this data.

Anticipated Findings

The anticipated finding of this study is a description of the distribution of chronic respiratory diseases among diverse TB infection survivors in the United States and the disparity in follow-up. Prediction model on who would develop chronic respiratory disease among TB-infection survivors.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Kedir Turi - Early Career Tenure-track Researcher, Indiana University

Smoking and Mental Health Exploration

Have explored relationships between stress and smoking in a number of studies. Would like to look at relationships between smokers and non-smokers using diagnostic and survey data, particularly in the area of mental health. Also interested in exploring Covid survey…

Scientific Questions Being Studied

Have explored relationships between stress and smoking in a number of studies. Would like to look at relationships between smokers and non-smokers using diagnostic and survey data, particularly in the area of mental health. Also interested in exploring Covid survey data.

Project Purpose(s)

  • Other Purpose (To explore differences in demographics including mental health diagnoses and indicators in smokers versus non-smokers.)

Scientific Approaches

Initial exploration with basic comparisons (t-test, Chi-square, etc.) using both self-reported smoking and electronic medical record reporting of smoking status to look at differences in mental health diagnoses and questionnaire responses assessing mental health self-reports. Will use r script to run these comparisons. Will adjust (covary) for basic demographics (age, gender). This is intended for hypothesis generation.

Anticipated Findings

At this point this is strictly exploratory and for the purpose of research question/hypothesis generation.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • PAUL THURAS - Project Personnel, University of Minnesota

Collaborators:

  • David Sosnowski - Project Personnel, Johns Hopkins University
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