Social and Behavioral Sciences Commons^™

The Times, They Are A-Changin’: Tracking Shifts In Mental Health Signals From Early Phase To Later Phase Of The Covid-19 Pandemic In Australia, Siqin Wang, Xiao Huang, Tao Hu, Mengxi Zhang, Zhenlong Li, Huan Ning, Jonathan Corcoran, Asaduzzaman Khan, Yan Liu, Jiajia Zhang Ph.D., Xiaoming Li Ph.D.

Faculty Publications

Introduction Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts.

Methods Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public’s mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities.

Results Australians’ …

Revealing Public Opinion Towards Covid-19 Vaccines With Twitter Data In The United States: Spatiotemporal Perspective, Tao Hu, Siqin Wang, Wei Luo, Mengxi Zhang, Xiao Huang, Yingwei Yan, Regina Liu, Kelly Ly, Viraj Kacker, Bing She, Zhenlong Li

Faculty Publications

Background: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance.

Objective:The aim of this study was to investigate public opinion and perception on COVID-19 vaccines in the United …

Using Mobile Device Data To Track The Effects Of The Covid-19 Pandemic On Spatiotemporal Patterns Of National Park Visitation, John A. Kupfer, Zhenlong Li, Huan Ning, Xiao Huang

Faculty Publications

Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices and released by SafeGraph as part of their Social Distancing Metric dataset. Based on comparisons with visitation statistics released by the U.S. National Park Service, our results confirmed that mobility records from digital devices can effectively capture park visitation patterns but with much finer spatiotemporal granularity. In general, triggers …

Spatial Disparities Of Covid-19 Cases And Fatalities In United States Counties, Sarah L. Jackson, Sahar Derakhshan, Leah Blackwood, Logan Lee, Qian Huang, Margot Habets, Susan L. Cutter

Faculty Publications

This paper examines the spatial and temporal trends in county-level COVID-19 cases and fatalities in the United States during the first year of the pandemic (January 2020–January 2021). Statistical and geospatial analyses highlight greater impacts in the Great Plains, Southwestern and Southern regions based on cases and fatalities per 100,000 population. Significant case and fatality spatial clusters were most prevalent between November 2020 and January 2021. Distinct urban–rural differences in COVID-19 experiences uncovered higher rural cases and fatalities per 100,000 population and fewer government mitigation actions enacted in rural counties. High levels of social vulnerability and the absence of mitigation …

Using Mobile Device Data To Track The Effects Of The Covid-19 Pandemic On Spatiotemporal Patterns Of National Park Visitation, John A. Kupfer, Zhenlong Li, Huan Ning, Xiao Huang

Faculty Publications

Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices and released by SafeGraph as part of their Social Distancing Metric dataset. Based on comparisons with visitation statistics released by the U.S. National Park Service, our results confirmed that mobility records from digital devices can effectively capture park visitation patterns but with much finer spatiotemporal granularity. In general, triggers …

Spatiotemporal Patterns Of Human Mobility And Its Association With Land Use Types During Covid-19 In New York City, Yuqin Jiang, Xiao Huang, Zhenlong Li

Faculty Publications

The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in New York City. With New York City open data, human mobility pattern changes were detected by different categories of land use, including residential, parks, transportation facilities, and workplaces. This study further compares human mobility patterns by …