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Check out our new research proposing Autonomous GIS as the next-generation AI-powered GIS. Link the full preprint: https://www.researchgate.net/publication/370635187_Autonomous_GIS_the_next-generation_AI-powered_GIS Code for LLM-Geo: https://github.com/gladcolor/LLM-Geo  Autonomous GIS: the next-generation AI-powered GIS Abstract: Large Language Models (LLMs), such as ChatGPT, demonstrate a strong understanding of human natural language and have been explored and applied in various fields, including reasoning, creative writing, code generation, translation, and information retrieval. By adopting LLM as the reasoning core, we introduce Autonomous GIS (AutoGIS) as an AI-powered geographic information system (GIS) that leverages the LLM’s general abilities in natural language understanding, reasoning and coding for addressing spatial problems with...

Check out the full story here: https://www.sc.edu/study/colleges_schools/artsandsciences/about/news/2023/geography_grad_ermgent_tech.php

The 3rd International Lectures organized by International Society for Digital Earth where Dr. Zhenlong Li delivered an invited talk along with other two colleagues (Prof. Kathleen Stewart from University of Maryland and Prof. Song Gao from University of Wisconsin-Madison) attracted over 5,100 participants worldwide! "On March 21st, 2023, the 3rd ISDE International Lectures was successfully convened online, enlightening the attendees on the theme of “Human Mobility Analytics in the Big Data Era”. Thanks to the multi-channel exposure, this time’s lecture got more eyes on its discernment in the challenges of, approaches to and feasible techniques for the human mobility measurement,...

We are pleased to share that GIBD alumnus Daniel Newsome has taken on a new role as a Data Analytics Manager with Rise Interactive! Congratulations, Daniel!

Dr. Zhenlong Li (Institutional PI) and Dr. Grace Yan from Missouri S&T (PI) receive $190,000 funding from Taylor Geospatial Institute for a new project titled "Developing a SMART Geospatial Tool to Classify Building Archetype at Community Level towards Digital-Twins of Disaster Resilience (DTDR)". Project Goal: To achieve intergenerational, equitable resilience under the changing climate (society sustainability), considering the uncertainties in projecting future natural hazards, the overarching goal of this project is to develop powerful, evolving Digital-Twins for Disaster Resilience (DTDR), with cutting-edge GeoSpatial tools and engineering and social science breakthrough discoveries integrated. The DTDR will create future potential climate/hazard scenarios...

Special Issue Editors Dr. Xiao Li E-Mail Website Guest Editor Transport Studies Unit, University of Oxford, Oxford OX1 3QY, UK Interests: GIS; spatial data science; transport geography; mobility analytics Dr. Xiao Huang E-Mail Website Guest Editor Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, USA Interests: spatial analysis, remote sensing, human–environment interactions, social sensing, deep learning Special Issues, Collections and Topics in MDPI journals Dr. Zhenlong Li E-Mail Website Guest Editor Department of Geography, University of South Carolina, Columbia, SC 29208, USA Interests: GIScience; geospatial big data; spatial computing; GeoAI Special Issues, Collections and Topics in MDPI journals   Dear Colleagues, A sustainable transport system...

Our new article entitled "Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A case study of South Carolina" led by PhD Candidate Huan Ning is published in the International Journal of Applied Earth Observation and Geoinformation (IF: 7.672) by Elsevier.  The article is freely available at https://www.sciencedirect.com/science/article/pii/S1569843223000687 Abstract: Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has emerged as a valuable data source for revealing fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate...

Dr. Zhenlong Li is invited to give an online talk titled "Measuring Human Mobility with Big Geosocial Data: Challenges and Approaches" at the 3rd ISDE International Lectures on 21 March, 2023. "ISDE International Lectures, organized by the International Society for Digital Earth (ISDE) are a series of online events which feature invited lectures by well-known international experts in the field of Digital Earth. The event will invite speakers to give lectures every two months. The purpose of the events is to bring international scholars in the relevant research fields of Digital Earth together to exchange academic perspectives, share research results,...

South Carolina has a shortage of providers, and many children must be placed away from their original communities. This makes it difficult for birth parents, for children, for visitation and for providing health care. This project aims to produce statistics and maps on the distances from the children and youth original “home address” to their current foster care “provider” address and the distances from the child to the county office and from the provider to the county office for the South Carolina Department of Social Services (SCDSS). While SCDSS understands that many children and youth are placed outside of their...

GIBD members have organized a series of sessions and will deliver a number of presentations on geospatial big data and spatial computing at the Symposium on Harnessing the Geospatial Data Revolution for Sustainability Solutions, 2023 AAG Annual Meeting. All sessions are now accepting abstracts. We welcome your contributions. Big Data Computing for Geospatial Applications I https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/5738 Big Data Computing for Geospatial Applications II https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/6292 Human Mobility Analytics in Big Data Era https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/5741 Harnessing Geospatial Big Data for Infectious Diseases https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/5739 Social Sensing and Big Data Computing for Disaster Management https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/5742 Urban Sensing and Understanding via Big Data and GeoAI https://aag.secure-platform.com/aag2023/solicitations/39/sessiongallery/5740...

Huan Ning, our PhD candidate, is selected to receive one of the 14 Breakthrough Graduate Scholar awards across the entire USC system. Big congratulations, Huan! https://www.sc.edu/about/offices_and_divisions/research/news_and_pubs/news/2023/2023_Breakthrough_Awards_Announcement.php “Each year, the Office of the Vice President for Research receives a large number of nominations for each of the Breakthrough awards, and a committee of faculty reviewers selects award recipients from the many remarkable faculty and graduate student nominees representing the entire USC system. The close competition embodies the spirit of strong, high-level research conducted here at the university. This year, we are very pleased to present two Breakthrough Leadership in Research awards,...

GIBD members delivered presentations at the 4th Annual National Big Data Health Science Conference taken place at Columbia, South Carolina. Cuizhen Wang, Drones for 3D Monitoring of Coastal Ecosystem Healthiness with Sea Level Rise Zhenlong Li, Using Social Meda and Place Visitation Data for Public Health Research: Applications, Challenges, and Innovation Opportunities Fengrui Jing, Disparities in mental health service utilization among immigrants in the U.S. using geospatial big data Huan Ning, Using Smartphone-Based Place Visitation Big Data to Improve Health Measure Estimation

Dr. Fahui Wang, Cyril & Tutta Vetter Alumni Professor, Associate Dean, the Graduate School, Department of Geography and Anthropology, Louisiana State University, will deliver a keynote presentation titled “Four Methodological Themes in Spatial Health Science” at the 2023 National Big Data Health Science Conference on Feb. 11, 11:15 am – 12:00 pm. This talk outlines four methodological themes in spatial analytics with broad applications in public health, all grouped under the umbrella of “Spatial Health Science”. Spatial accessibility measures the relative ease by which the locations of health services can be reached, and serves as a major matric for location...

Dr. Zhenlong Li received a new grant from the Social, Behavioral, & Economic COVID Coordinating Center (SBE CCC) at the University of Michigan to investigate the geographic and racial disparities of COVID-19 impact on obesity-related behaviors using cellphone-based place visitation data. The project team also includes Drs. Andrew T Kaczynski, Shan Qiao, Bankole Olatosi, Jiajia Zhang, and Xiaoming Li from Arnold School of Public Health. Project overview: Obesity is a predictor of multiple negative health outcomes, including type 2 diabetes, coronary heart disease, hypertension, various cancers, and premature death. In addition, obesity significantly affects quality of life and is bidirectionally associated with many mental...

The two datasets (cellphone-based population flow data and Twitter data) are among the four research datasets released by the USC Big Data Health Science Center as part of the Research Data Repositories (RDR) initiative. Check out the Twitter data description at https://bigdata.sc.edu/twitter-data/ Check out the cellphone-based population flow (ODT flow) data description at https://bigdata.sc.edu/cell-phone-based-place-visitation-data/ News release: https://bigdata.sc.edu/bdhsc-rdr-announcement/

Registration for the 4th Annual National Big Data Health Science Conference is now open! Check out conference website for more information about the 2-day conference agenda, our fantastic lineup of keynote speakers, and other details at SC Big Data Health Science Center Conference 2023 | (sc-bdhs-conference.org).  The National Big Data Health Science Conference is a signature annual event of the Big Data Health Science Center (BDHSC). This 4th annual conference will include innovative plenary sessions, panels, and workshops that emphasize the role of interdisciplinary collaboration in Big Data applications and advancements in the health sciences. The USC BDHSC was funded by...

Alexander Fulham successfully defended his thesis proposal next Tuesday, Dec. 20 at 12:30 PM in Callcott 228. His proposal title is "Sentiment analysis of Swedish and Finnish Twitter users’ views toward NATO pre- and post- 2022 Russian reinvasion of Ukraine". His committee includes Drs. Zhenlong Li, Carl Dahlman, and Robert Kopack. Congratulations, Alex!

The article titled "Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time" is published in BMC Public Health. Jing F., Li Z., Qiao S., Zhang J., Olatosi B., Li X., (2022), Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time, BMC Public Health. https://doi.org/10.1186/s12889-022-14779-1 Another article " Using geospatial social media data for infectious disease studies: a systematic review" is accepted for publication in the International Journal of Digital Earth. Jing F., Li Z., Qiao S., Zhang J., Olatosi B., Li X., (2022), Using geospatial social...

The Big Data Health Science Center is seeking research and program-based abstracts for oral and poster presentations responsive to its 4th annual conference theme, “Unlocking the Power of Big Data in Health: Translating Data Science into Program Development and Implementation.” This conference will be held in-person at the Pastides Alumni Center in Columbia, SC on February 10-11, 2023. Accepted abstracts will be published in conference proceedings. Research and program-based abstracts in the areas of infectious diseases, other health conditions, artificial intelligence methods for sensing and diagnosis, electronic health records, social media research, genomics analysis, geospatial sciences, infrastructural and capacity development, professional development, community/industry engagement, academic...

We're still accepting papers for the Uncertainties in Big Data Analytics in Disaster Research session. Please consider being part of our awesome session that we have been organizing for 4 years now. In this session, we will bring together researchers, practitioners, and policy makers from different specialties, institutions, sectors, and continents to share ideas, findings, methodologies, and technologies that are needed to leverage geospatial big data in disaster research as well as address the uncertainties to increase usability and acceptability of these datasets. The session will also provide a platform to establish and strengthen personal connections, communication channels, and research collaborations. Significant...

Check out our new article titled “Exploring large-scale spatial distribution of fear of crime by integrating small sample surveys and massive street view images“, published in Environment and Planning B Urban Analytics and City Science. Abstract: A tremendous amount of research use questionnaires to obtain individuals’ fear of crime and aggregate it to the neighborhood level to measure the spatial distribution of fear of crime. However, the cost of using questionnaires to measure the large-scale spatial distribution of fear of crime is high. The built environment is known to influence people’s perceptions, including fear of crime. This study develops a machine...

The National Big Data Health Science Conference 2023, organized by UofSC Big Data Health Science Center (BDHSC),  will take place from February 10-11 at Pastides Alumni Center, Columbia, South Carolina. This year's theme is "Translating Data Science into Program Development and Implementation". Stay tuned with us! Read more at https://www.sc-bdhs-conference.org/

The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes immensely to the global economy. However, what remains incomplete is our quantitative understanding of how the restaurant industry was recovered from COVID-19 in terms of restaurant visitations and revenue, customers' origins as well as the relationship between restaurant visitations and travel distances. Existing studies in the context of COVID-19 mainly reply on survey data and cannot reveal the changing spectrum of the restaurant industry at a large spatial and temporal scale. Here we construct a spatially explicit evaluation of the effect of...

A new preprint article titled "Revealing geographic transmission pattern of COVID-19 using neighborhood- level simulation with human mobility data and SEIR model: A Case Study of South Carolina", led by our student Huan Ning is now available on medRxiv. Abstract: Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has been an emerging data source to reveal fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville,...

Check out the news release about our recent publication about the COVID-19 impact on the black-owned restaurants, led by Dr. Xiao Huang, our lab alumnus and now the Assistant Professor at the Department of Geosciences, University of Arkansas. https://www.eurekalert.org/news-releases/963549 Full article: https://www.researchgate.net/publication/361780077_Black_businesses_matter_A_longitudinal_study_of_black-owned_restaurants_in_the_COVID-19_pandemic_using_geospatial_big_data

Our new collaborative review article titled "Social media mining under the COVID-19 context: Progress, challenges, and opportunities" is published in the Special Issue "Harnessing Geospatial Big Data for Infectious Diseases" in the International Journal of Applied Earth Observation and Geoinformation. Abstract: Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media...

GIBD receives $30,000 from the USC BDHSC Pilot Project Program to conduct a pilot study of developing a novel network-based big data approach to measure healthcare utilization disparity. The project team include Drs. Zhenlong Li, Shan Qiao, Bankole Olatosi, and Jiajia Zhang. Project summary: Healthcare utilization is a critical factor that influences population health and wellbeing. To identify, explain, and address disparities and inequities in healthcare utilization, it is necessary to develop a valid measurement approach that can accurately capture the disparities and explore the factors that contribute to the disparities in a timely manner. Increasing attention is being paid...

Check out our new article titled "Black businesses matter: A longitudinal study of black-owned restaurants in the COVID-19 pandemic using geospatial big data " published in Annals of the American Association of Geographers . Abstract: Black communities in the U.S. have been disproportionately affected by the COVID-19 pandemic; however, few empirical studies have been conducted to examine the conditions of Black-owned businesses in the U.S. during this challenging time. In this paper, we assess the circumstances of Black-owned restaurants during the entire year of 2020 through a longitudinal quantitative analysis of restaurant patronage. Using multiple sources of geospatial big data,...

Check out the full article at https://www.researchgate.net/publication/362751541_An_optimal_sensors-based_simulation_method_for_spatiotemporal_event_detection  Abstract: Human movements in urban areas are essential for understanding the human-environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose an optimal sensors-based simulation method for spatiotemporal event detection using human activity signals derived from taxi trip data. A sensor here is an abstract concept such that only the true observation data at the sensor location will be treated as known data for the simulation. Specifically, we first identify the optimal number of sensors and their locations that have...

Access the full article here.  Abstract: Concentrated disadvantaged areas have been disproportionately affected by COVID-19 outbreak in the United States (US). Meanwhile, highly connected areas may contribute to higher human movement, leading to higher COVID-19 cases and deaths. This study examined whether place connectivity moderated the association between concentrated disadvantage and COVID-19 fatality. Using COVID-19 fatality over four time periods, we performed mixed-effect negative binomial regressions to examine the association between concentrated disadvantage, Twitter-based place connectivity, and county-level COVID-19 fatality, considering potential state-level variations. Results revealed that concentrated disadvantage was significantly associated with an increased COVID-19 fatality. More importantly, moderation...

GIBD lab member Yuqin Jiang successfully defended her dissertation titled "Quantifying Human Mobility Patterns During Disruptive Events with Big Data" on May 18, 2022.  Big thanks to her committee, Professors Susan Cutter, Michael Hodgson, and Qunying Huang (University of Wisconsin-Madison). Yuqin has accepted an offer to join Texas A&M University as a Postdoctoral Researcher in July 2022 to start her academic career! Congratulations, Yuqin!

Learning-Based Methods for Detection and Monitoring of Shallow Flood-Affected Areas: Impact of Shallow-Flood Spreading on Vegetation Density This study aims to investigate the impacts of shallow flood spreading on vegetation density using a time-series collection of Landsat images spanning 2012–2020. To do this, Support Vector Machine (SVM), Random Forest (RF), Classification and Regression tree (CART) and Deep Learning Convolutional Neural Network (DL-CNN) algorithms were employed for flood-affected areas mapping and monitoring. The models were trained by using 214, 235, 230, and 219 ground truth data for years 2012, 2014, 2017 and 2020 respectively. Our accuracy assessment via the area under...

GIBD lab member Huan Ning successfully defended his dissertation proposal "Neighborhood Mobility Assessment for Wheelchair Users Based on Street View Imagery and Deep Learning" on April 20, 2022.  Huan's dissertation committee consists of Professors Zhenlong Li (Chair),  Susan Wang, Michael Hodgson, Shan Qiao (Arnold School of Public Health). Congratulations, Huan!

Our new article titled "Converting street view images to land cover maps for metric mapping: a case study on sidewalk network extraction for the wheelchair users", led by GIBD member Huan Ning is accepted for publication by Computers, Environment and Urban Systems (acceptance rate: 12%, Impact Factor: 5.3). Abstract: Street view images are now widely used in web map services, providing on-site photos of street scenes for users to explore without physically being in the field. These photos record detailed visual information of the street environment with geospatial control; therefore, they can be used for metric mapping purposes. In this...

GIBD lab member Yuqin Jiang has accepted an academic job offer to join the Civil Engineering Department at the Texas A&M University as Postdoctoral Researcher in July 2022.  Yuqin will defend his dissertation proposal titled "Quantifying Human Mobility Patterns During Disruptive Events with Big Human Mobility Data" in May. Congratulations, Yuqin!

We are launching a new Special Issue "Harnessing Geospatial Big Data for Infectious Diseases" in the International Journal of Applied Earth Observation and Geoinformation (Elsevier) (Impact factor of 5.933). https://www.journals.elsevier.com/international-journal-of-applied-earth-observation-and-geoinformation/call-for-papers/call-for-papers-on-special-issue-harnessing-geospatial-big-data-for-infectious-diseases  Guest Editors: Dr. Zhenlong Li, University of South Carolina, USA Dr. Shengjie Lai, University of Southampton, UK Dr. Kathleen Stewart, University of Maryland, USA Dr. Bo Huang, Chinese University of Hong Kong, China Dr. Xiaoming Li, University of South Carolina, USA   Submission deadline: December 31, 2022 Planned publication date: Spring 2023 Aims and Scope: Public health is inextricably linked to geospatial context. Where, when, and how people interact with natural,...

GIBD members receive $34,993 in funding from South Carolina Sea Grant Consortium to develop a GIS-based siting tool for South Carolina mariculture site selection. The project team includes Dr. Zhenlong Li (PI), Dr. Cuizhen Wang (Co-PI), and Huan Ning. The shellfish industry in coastal South Carolina (SC) weighs heavily in culturing and harvesting eastern oyster (Crassostrea virginica) and hard clam (Mercenaria spp.) in tidal creeks and estuaries. Oyster farming in SC is relatively new and is in a smaller scale than those well-established mariculture industries in other Atlantic and Gulf coastal states. However, its economic and public benefits deserve to...

Congratulations, Yuqin!   More details about the Competition: https://aagcisg.wordpress.com/robert-raskin-student-competition-2022/

The article is open access available at: https://www.tandfonline.com/doi/full/10.1080/19475683.2022.2041725  Zhang, M., Wang, S., Hu, T., Fu, X., Wang, X., Hu, Y., Halloran B., Li Z. … & Bao, S. (2022). Human mobility and COVID-19 transmission: A systematic review and future directions. Annals of GIS, 1-14. Abstract: Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the...

GIBD lab members have co-organized 5 sessions and will deliver 6 presentations in 2022 AAG related to geospatial big data, human mobility, and public health. See more information below. Sessions organized Harnessing Geospatial Big Data for Infectious Diseases Type: Virtual Paper Day: 2/26/2022 Start Time: 9:40 AM End Time: 11:00 AM Organizer(s): Zhenlong Li , Shengjie Lai, Bo Huang, Kathleen Stewart Chairs(s): Zhenlong Li, University of South Carolina https://aag-annualmeeting.secure-platform.com/a/solicitations/19/sessiongallery/2952   Symposium on Human Dynamics Research: Human mobility in Big Data Era I Type: Virtual Paper Day: 2/27/2022 Start Time: 3:40 PM End Time: 5:00 PM Organizer(s): Yuqin Jiang, Zhenlong Li , Xiao Huang Chairs(s):...

The Big Data Health Science Center’s Geospatial Core is pleased to announce the second annual Geographic Information Science (GIS) Scholars Program. This program is being launched to recognize and support three outstanding undergraduate or graduate students who have demonstrated interest, potential, and/or experience in GIS and health research. GIS and health research is broadly defined, and includes, but is not limited to, using GIS to evaluate the social determinants of health, health behaviors, health outcomes, access to health care and social services, utilization of health services, environmental exposures, built environment, and other health-related factors through mapping and spatial analysis. Anyone...

GIBD lab member Grayson Morgan successfully defended his dissertation, “sUAS and Deep Learning for High-resolution Monitoring of Tidal Marshes in Coastal South Carolina”. His research committee includes Dr. Susan Wang (Chair), Dr. Michael Hodgson (co-Chair), Dr. Zhenlong Li, and Dr. Steve Schill from the Nature Conservancy. Big congratulations to the soon-to-be Dr. Morgan!  Excellent job, Grayson!

Our new collaborative review paper titled "Human mobility and COVID-19 transmission: a systematic review and future directions" has been accepted for publication by the Annals of GIS. Abstract:  Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and...

Welcome to join the 3rd annual National Big Data Health Science Conference on February 11-12, 2022 (virtual) organized by the UofSC Big Data Health Science Center. The theme of the conference this year is “Unlocking the Power of Big Data in Health: Developing an Interdisciplinary Response for Health Equity”. This conference will bring together leaders from academia, government, industry, and healthcare systems to focus on and forge new discussions about the role of interdisciplinary collaboration in Big Data applications and advancements in the health sciences. Register here: https://lnkd.in/eXC_JYJc The program agenda can be found here: https://www.sc-bdhs-conference.org/program-2022/  

Our new article titled “Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study“ is accepted for publication in the ISPRS International Journal of Geo-Information. Abstract: Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments in comparison with the popularly applied machine learning classifiers. This study seeks to explore the feasibility for using a U-Net deep learning architecture to classify bi-temporal high resolution county scale aerial images to determine the spatial extent and changes of land cover classes that...

Our new article titled "Population mobility and aging accelerate the outbreaks of COVID-19 in the Deep South: a county-level longitudinal analysis", authored by Chengbo Zeng, Jiajia Zhang, Zhenlong Li, Xiaowen Sun, Xueying Yang, Bankole Olatosi, Sharon B Weissman, and Xiaoming Li, has been accepted for publication by Clinical Infectious Diseases (Impact Factor: 9.1). We find that population mobility and aging at local areas contributed to the geospatial disparities in COVID-19 outbreaks among 418 counties in the Deep South. A significant interaction between mobility and proportion of older adults in predicting COVID-19 incidence was found. Effective disease control measures should be...

Dr. Zhenlong Li, collaborated with Dr. Shan Qiao from public health, has been awarded a project titled “A novel data-driven approach to empirically link structural racism and health access and utilization in South Carolina” by the UofSC OVPR Racial Justice and Equity Research Program. Other team members include Drs. Xiaoming Li, Bankole Olatosi, and Jiajia Zhang. Leveraging large place visitation records with high granularity sampled from mobile devices and census data, we propose an integrative big data approach to examine the association between structural racism and disparities in health care access in South Carolina. The proposed research will develop innovative...

Our new article titled "Studying patterns and predictors of HIV viral suppression using A Big Data approach: A research protocol", co-authored by Zhang J., Olatosi B., Yang X., Weissman S., Li Z., Hu J., Li X, is accepted for publication by BMC Infectious Diseases. This is a peer-reviewed protocol article where the study has received ~3.5 million funding from NIH. 2021-2026, Patterns and Predictors of Viral Suppression: A Big Data Approach, National Institutes of Health (NIH), R01AI164947, MPI: Bankole Olatosi and Jiajia Zhang; Co-Investigators:  Zhenlong Li, Sharon Weissman, Jianjun Hu, Xiaoming Li,  $3,500,000

Dr. Fengrui Jing received his PhD in GIScience from Sun Yat-sen University in 2021. He also holds a master’s degree in Physical Geography and two undergraduate degrees in Social Work and Psychology. His research focuses on using massive social media data to map neighborhood disorder and fear of crime, and to examine the causal relationship between micro built environment and fear of crime. Dr. Jing will work with Dr. Zhenlong Li and other team members in GIBD and USC Big Data Health Science Center (BDHSC, https://bigdata.sc.edu) to conduct cutting-edge and innovative interdisciplinary research on geospatial big data analytics (e.g., analyzing...

The novel SARS-CoV-2 variant of concern (VOC) Omicron (lineage B.1.1.529), together with four existing VOC variants, has raised serious concerns about the effectiveness of vaccines and the potential for a new wave of the pandemic (Figures 1 and 2) . This new strain was first detected in in November 2021 in South Africa and among international cases with a travel history from southern African countries. However, community transmission with associated clusters has now been reported in several countries. According to the COVID-19 Weekly Epidemiological Update published by the WHO, a total of 76 countries have reported confirmed cases of the...