The spatial clustering analysis of COVID-19 and its associated factors in mainland China at the prefecture level

Abstract

Coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Many associated factors including population movement, meteorological parameters, air quality and socioeconomic conditions can affect COVID-19 transmission. However, no study has combined these various factors in a comprehensive analysis. We collected data on COVID-19 cases and the factors of interest in 340 prefectures of mainland China from 1 December 2019 to 30 April 2020. Moran's I statistic, Getis-Ord Gi ⁎ statistic and Kulldorff's space-time scan statistics were used to identify spatial clusters of COVID-19, and the geographically weighted regression (GWR) model was applied to investigate the effects of the associated factors on COVID-19 incidence. A total of 67,449 laboratory-confirmed cases were reported during the study period. Wuhan city as well as its surrounding areas were the cluster areas, and January 25 to February 21, 2020, was the clustering time of COVID-19. The population outflow from Wuhan played a significant role in COVID-19 transmission, with the local coefficients varying from 14.87 to 15.02 in the 340 prefectures. Among the meteorological parameters, relative humidity and precipitation were positively associated with COVID-19 incidence, while the average wind speed showed a negative correlation, but the relationship of average temperature with COVID-19 incidence inconsistent between northern and southern China. NO 2 was positively associated, and O 3 was negatively associated, with COVID-19 incidence. Environment with high levels of inbound migration or travel, poor ventilation, high humidity or heavy rainfall, low temperature, and high air pollution may be favorable for the growth, reproduction and spread of SARS-CoV-2. Therefore, applying appropriate lockdown measures and travel restrictions, strengthening the ventilation of living and working environments, controlling air pollution and making sufficient preparations for a possible second wave in the relatively cold autumn and winter months may be helpful for the control and prevention of COVID-19.

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

“…2 . Two provinces, Hubei and Hunan, were identified as the high-risk provinces ( Liu et al, 2021 ), seven were medium-risk provinces, such as Jiangsu, Anhui and Sichuan, and the Xinjiang Uygur Autonomous Region was selected as a low-risk province. Because about two thirds of total meat consumption in China is pork, pork was selected as the livestock product to assess the provincial agricultural product price differences, ( Xie et al, 2020 ), crucian carp, carp, and silver carp were selected as the aquatic products, based on the agricultural product types in the China Agricultural Price Survey Yearbook, celery cabbage, cucumber, beans and green pepper were selected as the representative vegetables, and Fuji apples, watermelons and bananas were selected as the representative fruit.…”

Spatial priority for COVID-19 vaccine rollout against limited supply

“…The analysis presented in this study is at the district level due to a lack of data availability at a smaller scale. Several studies have highlighted the potential of cluster analysis for identifying the spatial distribution of COVID-19 cases at a small scale (see for example, 53 , 54 , 55 ). Additionally, technological advancements like contract tracing applications have created new opportunities for identifying COVID-19 cases at a granular scale (see for example, 56 , 57 , 58 ).…”

Environmental impact of increased soap consumption during COVID-19 pandemic: Biodegradable soap production and sustainable packaging

“…The coronavirus disease 2019 (COVID-19), as a zoonotic disease, is a strain of severe acute respiratory syndrome that has posed severe global health challenges and affected human life quality. This pandemic has already resulted in extreme societal, economic, and political disruption worldwide ( Zambrano-Monserrate et al, 2020 ; Liu et al, 2021 ; Akrofi and Antwi, 2020 ; Teymourian et al, 2021 ). In a systematic review of physical measures to reduce respiratory virus transmission, handwashing was demonstrated to reduce transmission by 45–55% ( Jefferson et al, 2009 ; Brauer et al, 2020 ).…”