Danielle Hawkins

coronavirus; covid-19

population health center

Environmental Chemicals

Environmental Health

Public Health

Center for Health Equity

No Evidence That People Alter Daily Travel After Having Symptoms That Could Be COVID-19

dhawkin — Fri, 19 Mar 2021 13:38:07 +0000

No Evidence That People Alter Daily Travel After Having Symptoms That Could Be COVID-19 dhawkin Fri, 03/19/2021 - 09:38

In This Story

Janusz Wojtusiak, PhD

New �鶹��Ƶ College of Health and Human Services study is one of first individual-level studies to track movements and symptoms during the COVID-19 pandemic

How can we better understand how people move during the pandemic and how they spread COVID-19? New �鶹��Ƶ’s College of Health and Human Services research is one of the first individual-level studies to explore this question.

Dr. Janusz Wojtusiak led the study published in the Journal of Healthcare Informatics Research. Wojtusiak and colleagues tracked symptoms and movements of 175 volunteer individuals on �鶹��Ƶ’s campus. They found that there is no evidence that participants altered their movements based on the symptoms they reported.

“We could not detect any significant change of movement when people should self-quarantine. On the other hand some people almost did not leave home since the beginning of the pandemic, while others move freely around,” said Wojtusiak.

Participants used the �鶹��Ƶ COVID HealthCheck^TM to record symptoms of possible COVID-19 infection and GPS and WiFi data to provide information on how they move during the pandemic. This allows the researchers to model and predict movements during the pandemic and in conjunction with any reported possible COVID-19 symptoms.

“By tracking individual movements and symptoms in our study, our findings could help inform effective public health interventions to reduce COVID-19 infections,” explains Wojtusiak.

In addition, Wojtusiak and colleagues analyzed de-identified �鶹��Ƶ COVID HealthCheck^TM responses and found that a headache was the most frequently reported symptom, and a headache was always listed as a symptom when any other symptoms were reported. Other commonly reported symptoms were coughs and sore throats.

Movement patterns varied among participants, with some only going out for essential trips while others moved about more. As a group, movement was consistent over the study period, which included a period when Virginia was under a stay-at-home order and when it was not. Participants traveled a total average of 139 miles per week, visiting an average of less than six locations per week. This low average mileage and number of sites visited does suggest that COVID-19-related restrictions affected their movement. However, they also found that even when participants reported symptoms of COVID-19 or contact with others with COVID-19, they did not change their movements as recommended by public health guidance.

�鶹��Ƶ has a very low COVID-19 infection rate, and during the period none of the study participants reported COVID-19 infection, so researchers weren’t able to link COVID-19 positive tests and movement. Future analysis will include data from the winter of 2020 so may provide more information on movement after COVID-19 infection. The researchers are also conducting surveys and interviews to provide richer data including reasons for complying or not complying with social distancing.

This research is possible thanks to the dedication of study participants at �鶹��Ƶ who share their data to allow for movement modeling.

The study is being funded by a pilot grant from �鶹��Ƶ’s College of Health and Human Services.

�鶹��Ƶ �鶹��Ƶ

�鶹��Ƶ is Virginia's largest and most diverse public research university. Located near Washington, D.C., �鶹��Ƶ enrolls 39,000 students from 130 countries and all 50 states. �鶹��Ƶ has grown rapidly over the past half-century and is recognized for its innovation and entrepreneurship, remarkable diversity and commitment to accessibility. For more information, visit https://www2.gmu.edu/.

�鶹��Ƶ the College of Health and Human Services

�鶹��Ƶ's College of Health and Human Services prepares students to become leaders and shape the public's health through academic excellence, research of consequence, community outreach, and interprofessional clinical practice. George �鶹��Ƶ is the fastest-growing Research I institution in the country. The College enrolls more than 1,900 undergraduate and 1,370 graduate students in its nationally-recognized offerings, including: 5 undergraduate degrees, 13 graduate degrees, and 7 certificate programs. The college is transitioning to a college of public health in the near future. For more information, visit https://chhs.gmu.edu/.

Topics

coronavirus; covid-19

Health Informatics

College of Health and Human Services Department of Health Administration and Policy

Michelle S. Williams, PhD, MSPH

faculty spotlight

African American Breast Cancer Survivor Cardiovascular Disease Risk High but Knowledge Low

dhawkin — Fri, 05 Mar 2021 14:45:20 +0000

African American Breast Cancer Survivor Cardiovascular Disease Risk High but Knowledge Low dhawkin Fri, 03/05/2021 - 09:45

In This Story

New research led by �鶹��Ƶ’s College of Health and Human Services faculty Dr. Michelle Williams found that although African American breast cancer survivors have a higher prevalence of CVD risk factors, their knowledge about CVD is low.

African American breast cancer survivors are four times more likely to die from breast cancer than women of all other races and ethnicities, and they have a disproportionately high rate of death from cardiovascular disease (CVD).

New research led by �鶹��Ƶ’s College of Health and Human Services faculty Dr. Michelle Williams assessed African American breast cancer survivors’ risk factors and knowledge about CVD in the Deep South, where health disparities between African American women and women of other races is even larger. They found that although African American breast cancer survivors have a higher prevalence of CVD risk factors, their knowledge about CVD is low.

The study was published in the Journal of Health Disparities Research and Practice in February.

Specifically, participants scored low on knowledge about heart attack symptoms and CVD-related medical information. Participants with healthier diets and higher levels of education had higher levels of CVD knowledge.

“We know that several CVD risk factors, such as hypertension and obesity, can be modified through lifestyle behavior changes,” adds Williams. “This is promising, but breast cancer survivors must be better informed about CVD risk by their health care providers.”

Their study included surveys of 70 breast cancer survivors who identified as African American or Black in Mississippi, Alabama, Tennessee, Louisiana, and Georgia.

“Our findings highlight the importance of informing African American breast cancer survivors about their increased risk for co-morbidities such as CVD and providing them with access to culturally appropriate CVD risk reduction interventions aimed at a variety of education levels,” explains Williams.

Williams and colleagues are currently conducting the next phase of the study, which will provide more in-depth information about CVD risk factors among African American breast cancer survivors.

This research was supported by a grant from the Mississippi Center for Clinical and Translational Research to the University of Mississippi Medical Center (Grant Number U54 GM115428).

�鶹��Ƶ �鶹��Ƶ

�鶹��Ƶ the College of Health and Human Services

Topics

Breast Cancer

cardiovascular disease

Health Disparities

College of Health and Human Services Department of Global and Community Health

Center for Health Equity

Symptoms and Movement Patterns During the COVID-19 Pandemic

dhawkin — Mon, 22 Feb 2021 21:55:42 +0000

Symptoms and Movement Patterns During the COVID-19 Pandemic dhawkin Mon, 02/22/2021 - 16:55

In This Story

Janusz Wojtusiak, PhD

How can we better understand how people move during the pandemic and how they spread COVID-19? Dr. Janusz Wojtusiak, associate professor of health informatics and director of the Machine Learning Inference Lab is leading one of the first individual-level studies on social distancing.

Participants use the �鶹��Ƶ COVID Health Check^TM to record symptoms of possible COVID-19 infection and GPS and WiFi data to provide information on how they move during the pandemic. This allows the researchers to model and predict movements during the pandemic and in conjunction with any reported possible COVID-19 symptoms. This could help inform effective public health interventions to reduce infection.

Initial findings from the first wave of the study, including data collected through September 2020, were published in the Journal of Healthcare Informatics Research. Wojtusiak and colleagues found that headache was the most frequently reported symptom and headache was always listed as a symptom when any other symptoms were reported. The next most commonly reported symptoms were cough and sore throat.

This research is possible thanks to the dedication of study participants who share their data to allow for movement modeling. Recruitment of �鶹��Ƶ faculty, staff, and students for the second wave of the study has begun. Learn more and sign up: https://www.mli.gmu.edu/sd/.

�鶹��Ƶ has a very low COVID-19 infection rate, and during the period none of the study participants reported COVID-19 infection, so researchers weren’t able to link COVID-19 positive tests and movement. Future analysis will include data from the 2020 winter so may provide more information on movement after COVID-19 infection. The researchers will also conduct surveys and interviews to provide richer data including reasons for complying or not complying with social distancing.

In a related study supported by the National Cancer Institute, Wojtusiak’s team analyzed individual movements of people on campus. Such micro-scale movements within buildings can be modeled using WiFi data collected each time a mobile phone or laptop is connected to the internet. In over 150 simulated scenarios they were able to reconstruct movements of volunteers within �鶹��Ƶ’s Peterson Hall. This technology is intended to support contact elicitation as part of contact tracing for COVID-19 or other infectious diseases.

Promising preliminary results show that the technology can change how public health officials think about contact tracing. Tests are now being conducted across other locations on Fairfax campus. You can learn more about the project at https://www.mli.gmu.edu/wifi.

Topics

Machine Learning in Health Care

Machine Learning

coronavirus; covid-19

College of Health and Human Services Department of Health Administration and Policy