Next Article in Journal
A Smart Tourism Recommendation Algorithm Based on Cellular Geospatial Clustering and Multivariate Weighted Collaborative Filtering
Previous Article in Journal
Assessing Place Type Similarities Based on Functional Signatures Extracted from Social Media Data
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies

College of Geospatial Information Science and Technology, Capital Normal University, North Road 105, Haidian District, Beijing 100048, China
*
Author to whom correspondence should be addressed.
Current address: Stuart Weitzman School of Design, University of Pennsylvania, 210 South 34th Street, Philadelphia, PA 19104, USA.
ISPRS Int. J. Geo-Inf. 2021, 10(9), 627; https://doi.org/10.3390/ijgi10090627
Submission received: 24 July 2021 / Revised: 13 September 2021 / Accepted: 16 September 2021 / Published: 18 September 2021

Abstract

The Coronavirus disease 2019 (COVID-19) has been spreading in New York State since March 2020, posing health and socioeconomic threats to many areas. Statistics of daily confirmed cases and deaths in New York State have been growing and declining amid changing policies and environmental factors. Based on the county-level COVID-19 cases and environmental factors in the state from March to December 2020, this study investigates spatiotemporal clustering patterns using spatial autocorrelation and space-time scan analysis. Environmental factors influencing the COVID-19 spread were analyzed based on the Geodetector model. Infection clusters first appeared in southern New York State and then moved to the central western parts as the epidemic developed. The statistical results of space-time scan analysis are consistent with those of spatial autocorrelation analysis. The analysis results of Geodetector showed that both temperature and population density were strong indications of the monthly incidence of COVID-19, especially in March and April 2020. There is a trend of increasing interactions between various risk factors. This study explores the spatiotemporal pattern of COVID-19 in New York State over ten months and explains the relationship between the disease transmission and influencing factors.
Keywords: COVID-19; Geodetector; New York State; spatial autocorrelation; space-time scan statistics COVID-19; Geodetector; New York State; spatial autocorrelation; space-time scan statistics

Share and Cite

MDPI and ACS Style

Zheng, A.; Wang, T.; Li, X. Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies. ISPRS Int. J. Geo-Inf. 2021, 10, 627. https://doi.org/10.3390/ijgi10090627

AMA Style

Zheng A, Wang T, Li X. Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies. ISPRS International Journal of Geo-Information. 2021; 10(9):627. https://doi.org/10.3390/ijgi10090627

Chicago/Turabian Style

Zheng, Anran, Tao Wang, and Xiaojuan Li. 2021. "Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies" ISPRS International Journal of Geo-Information 10, no. 9: 627. https://doi.org/10.3390/ijgi10090627

APA Style

Zheng, A., Wang, T., & Li, X. (2021). Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies. ISPRS International Journal of Geo-Information, 10(9), 627. https://doi.org/10.3390/ijgi10090627

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop