Spatial-temporal differences of COVID-19 vaccinations in the U.S.

Although the disparities in COVID-19 outcomes have been proved, they have not been explicitly associated with COVID-19 full vaccinations. This paper examines the spatial and temporal patterns of the county-level COVID-19 case rates, fatality rates, and full vaccination rates in the United States from December 24, 2020 through September 30, 2021. Statistical and geospatial analyses show clear temporal and spatial patterns of the progression of COVID-19 outcomes and vaccinations. In the relationship between two time series, the fatality rates series was positively related to past lags of the case rates series. At the same time, case rates series and fatality rates series were negatively related to past lags of the full vaccination rates series. The lag level varies across urban and rural areas. The results of partial correlation, ordinary least squares (OLS) and Geographically Weighted Regression (GWR) also confirmed that the existing COVID-19 infections and different sets of socioeconomic, healthcare access, health conditions, and environmental characteristics were independently associated with COVID-19 vaccinations over time and space. These results empirically identify the geographic health disparities with COVID-19 vaccinations and outcomes and provide the evidentiary basis for targeting pandemic recovery and public health mitigation actions. Supplementary Information: The online version contains supplementary material available at 10.1007/s44212-022-00019-9.

Social distance integrated gravity model for evacuation destination choice

Evacuation is an effective and commonly taken strategy to minimize death and injuries from an incoming hurricane. For decades, interdisciplinary research has contributed to a better understanding of evacuation behavior. Evacuation destination choice modeling is an essential step for hurricane evacuation transportation planning. Multiple factors are identified associated with evacuation destination choices, in which long-term social factors have been found essential, yet neglected, in most studies due to difficulty in data collection. This study utilized long-term human movement records retrieved from Twitter to (1) reinforce the importance of social factors in evacuation destination choices, (2) quantify individual-level familiarity measurement and its relationship with an individual's destination choice, (3) develop a big data approach for aggregated county-level social distance measurement, and (4) demonstrate how gravity models can be improved by including both social distance and physical distance for evacuation destination choice modeling. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Digital Earth is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Spatial Disparities of COVID-19 Cases and Fatalities in United States Counties.

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 policies were significantly associated with higher fatalities, while existing community resilience had more influential spatial explanatory power. Using differences in percentage unemployment changes between 2019 and 2020 as a proxy for pre-emergent recovery revealed urban counties were hit harder in the early months of the pandemic, corresponding with imposed government mitigation policies. This longitudinal, place-based study confirms some early urban-rural patterns initially observed in the pandemic, as well as the disparate COVID-19 experiences among socially vulnerable populations. The results are critical in identifying geographic disparities in COVID-19 exposures and outcomes and providing the evidentiary basis for targeting pandemic recovery.