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George Mason doctoral candidate study on COVID-19 and family ties earns 'Best Poster Presentation' at International Pandemic Sciences Conference
George Mason University computational and data sciences doctoral candidate, Jericho McLeod, attended the International Pandemic Sciences Conference at Oxford University in July, presenting his research on the spread of COVID-19 through extended family connections. The conference, which hosted some of the top minds in the field, selected McLeod’s work as the “best poster presentation” in the Epidemiology, Data and Analytics category.
![Jericho McLeod smiles with his award certificate for best poster.](/sites/default/files/styles/small/public/2024-07/Jericho%20Award_2.jpg?itok=tmGecB-a)
Scientists have long studied the spread of diseases, but the emergence of COVID-19 and its profound impact on society have underscored the critical need to understand where and how diseases spread. As McLeod reviewed literature on disease transmission as part of his PhD in Computational Science and Informatics, he and George Mason associate professor of computational data sciences Eduardo López noticed a gap in the models and now seek to correct it.
In trying to understand why disease transmissions were worse in some areas over others, McLeod and López dove into COVID-19 data looking specifically at extended family ties—meaning family members beyond the nuclear family of parents and children—think cousins, aunts, uncles, or grandparents.
“According to research on social networks in the United States, individuals during crises like COVID-19, contract their social circles yet become more active with them,” said McLeod. “During lockdown, you saw your friends less, but may have still delivered groceries to your grandmother regularly,” said McLeod
McLeod and López wanted to know if these ties played a role in the spread of COVID-19—which would mean current data and models may be missing an essential component in understanding the way disease spreads.
Their study’s goal, with the help of doctoral students Bryan Adams, Unchitta Kan, Valentin Vergara Hidd, and Mailun (Alan) Zhang, was to confirm that these networks mattered enough to warrant future research and updates to disease modeling. Studies by McLeod, López, and Kan previously confirmed that people migrated closer to family more frequently after the pandemic began and that availability of extended family plays a primary factor in influencing face-to-face interaction, laying the groundwork for this research. So, should these relationships be considered in models demonstrating the spread of disease? McLeod says yes.
The team gathered obituaries in the Unites States between 2020 to 2022 to examine familial relationships with CDC data on deaths by geography, age, and gender. They found that during COVID-19, there were more instances of multiple family members dying within short periods (e.g. 60 days) compared to 2018 and 2019, where such cases were less common. This rise in deaths aligns with CDC data on excess deaths but is more noticeable between different waves of the pandemic.
![McLeod stands with López in front of their research poster at the conference.](/sites/default/files/styles/small/public/2024-07/Jericho%20Award%203.jpg?itok=mdGIAaPw)
“I am very proud of our work, and it has been collaborative in every way,” said López. “Jericho has a strong ability to work through the data engineering portion of a problem, but also has the intuition necessary to make this research happen. We were optimistic that we would see the effects that we did and now we have this great opportunity to study something that people have just completely overlooked.”
McLeod earned a degree in accounting from the University of South Alabama before attending George Mason University to earn his MBA. One of his business courses with George Mason professor of information systems and operations management, Pallab Sanyal, introduced students to data analytics and machine learning, which McLeod said he found fascinating. To make his resume stand out among other business graduates, he elected to pursue a PhD and to obtain the knowledge and tools to solve complex social problems using data. That led him to the computational science and informatics program and his work with López.
“I wanted to earn my PhD and here I am now attending international conferences learning about the most cutting-edge research,” said McLeod. “Attending the [Oxford] conference was so energizing. It brought together a collection of top minds, and Dr. López, who’s an expert in this space, knew the right people to introduce me to which led to additional conversations, ideation, and thoughts on future directions for this research.”
George Mason’s Graduate Student Travel Fund, offered by the Office of the Provost, supported McLeod’s trip to the Oxford based conference.