Spatial access to public hospitals during COVID-19 in Nottinghamshire, UK.

We intend to tackle two under-addressed issues in access to healthcare services during the COVID-19 pandemic: first, the spatiotemporal dynamic of access during the pandemic of acute communicable disease; second, the demographic and socioeconomic access disparities. We used the two-step floating catchment area (2SFCA) method to measure the spatial access to public hospitals during the second COVID-19 wave (September 28th-February 28th, 2021) in Nottinghamshire, UK. To investigate the temporal variation in access along with the development of the pandemic, we divided our study period into 11 sections and applied the 2SFCA to each of them. The results indicate that western Nottinghamshire is better than the eastern part from a spatial perspective and the north-western urban area represents the highest spatial access; temporally, the accessibility of the public hospitals generally decreased when the number of cases increased. Particular low accessibility was observed at the beginning of the pandemic when the outbreak hit the university region and its vicinities during the back-to-school season. Our disparity analysis found that i) the access of the senior population to public hospitals deviated from that of the general population, ii) the access was positively associated with socioeconomic status, and iii) all disparities were related to the urban-rural discrepancy. These findings can help to plan temporary clinics or hospitals during epidemic emergencies. More generally, they provide scientific support to pandemic-related healthcare resource allocation and policy- making, particularly for people in vulnerable areas.

Assisting scalable diagnosis automatically via CT images in the combat against COVID-19.

The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

Are Emotion Regulation Strategies Different among 3-6-Year-Old Aggressive Children? Evidence from China.

BACKGROUND: During the long-time home quarantine due to COVID-19, preschool-age children can be easily stricken by negative emotions, which give rise to aggressive behaviors. Aggressive behaviors are of different types at the preschool stage. We aimed to investigate the differences of emotion regulation strategies among children age 3-6 yr old with different aggression types and explore the relationship between emotion regulation strategies and aggressive behaviors. METHODS: The aggressive behaviors of 1,187 children sampled (event sampling method) from 5 kindergartens in five cities in Henan Province of China were observed on the spot in 2020. Three aggression types (i.e., physical, verbal, and indirect) were selected to conduct a questionnaire survey on emotion regulation strategies and discuss the differences among aggressive children in emotion regulation strategies. RESULTS: Children of different genders are significantly different in aggressive behaviors and problem solving, as well as children at different age levels in self-comfort, passive reaction, and negative regulation strategies. Significant interaction exists between gender and aggression but not in negative regulation strategy; significant interaction also exists between age and aggression but not in cognitive reconstruction, substitutive activity, and aggressive behavior. Significant differences exist among children of different aggression types in positive and negative regulation strategies. The discrimination accuracy of emotion regulation strategies for aggression types is 66.5%. CONCLUSION: Significant differences exist among 3-6-yr-old aggressive children in emotion regulation strategies, and emotion regulation strategies can effectively distinguish aggressive children of different types.