The spatiotemporal evolution of COVID-19 in China and its impact on urban economic resilience.

The spread of the novel coronavirus (COVID-19) has had a major political, economic, social, and cultural impact on various countries worldwide. Based on economic operation, public opinion, public health, government policies and population inflow in the affected areas, this study measures daily economic resilience during the COVID-19 outbreak in 286 prefecture-level cities in China (from 1st January to 8th February, 2020). Specifically, this study further investigates the economic resilience and the number of COVID-19 cases by analysing the evolutionary trend of their spatial distribution pattern using the standard deviation ellipse (SDE). The impact of COVID-19 on economic resilience is examined using a panel vector autoregressive model. The following are the findings. (1) The economic resilience value decreased throughout the study period, but the cities with high economic resilience showed a trend of spatial diffusion in the late study period. Wuhan's lockdown strategy was benefit to control the spread of COVID-19, and promptly stopped the decline of China's economic resilience. (2) Economic resilience and the number of COVID-19 cases influenced their future trends positively, but this effect gradually decreased over time. During the COVID-19, although the number of confirmed cases significantly influenced China's economic resilience, and the disease's spread was evident, China maintained a high level of economic development resilience. (3) The rise in economic resilience during the pandemic's early stages promoted the number of confirmed cases, but the strength of this relationship gradually declined as the pandemic progressed. Returning to work and other activities may increase the risk of infection. Numerous policies implemented at the outbreak' inception aided in laying the groundwork for economic resilience. Although the outbreak had a detrimental effect on economic resilience in the later stages of the pandemic, a convergent trend was observed at the end of the research period. (4) Using variance decomposition, we discovered that future economic resilience was significantly influenced by itself and by relatively few changes. However, the impact of confirmed cases on economic resilience becomes apparent after the fourth period. This indicates that the number of confirmed cases must be limited during the initial stages. The early support of various sectors in China facilitated the spatial expansion of economically resilient cities. The pandemic has a non-negligible negative impact on economic resilience, but this has been mitigated by Wuhan's timely closure.

Enterovirus D68-Associated Acute Respiratory Illness ─ New Vaccine Surveillance Network, United States, July-November 2018-2020.

Enterovirus D68 (EV-D68) is associated with a broad spectrum of illnesses, including mild to severe acute respiratory illness (ARI) and acute flaccid myelitis (AFM). Enteroviruses, including EV-D68, are typically detected in the United States during late summer through fall, with year-to-year fluctuations. Before 2014, EV-D68 was infrequently reported to CDC (1). However, numbers of EV-D68 detection have increased in recent years, with a biennial pattern observed during 2014-2018 in the United States, after the expansion of surveillance and wider availability of molecular testing. In 2014, a national outbreak of EV-D68 was detected (2). EV-D68 was also reported in 2016 via local (3) and passive national (4) surveillance. EV-D68 detections were limited in 2017, but substantial circulation was observed in 2018 (5). To assess recent levels of circulation, EV-D68 detections in respiratory specimens collected from patients aged <18 years* with ARI evaluated in emergency departments (EDs) or admitted to one of seven U.S. medical centers† within the New Vaccine Surveillance Network (NVSN) were summarized. This report provides a provisional description of EV-D68 detections during July-November in 2018, 2019 and 2020, and describes the demographic and clinical characteristics of these patients. In 2018, a total of 382 EV-D68 detections in respiratory specimens obtained from patients aged <18 years with ARI were reported by NVSN; the number decreased to six detections in 2019 and 30 in 2020. Among patients aged <18 years with EV-D68 in 2020, 22 (73%) were non-Hispanic Black (Black) persons. EV-D68 detections in 2020 were lower than anticipated based on the biennial circulation pattern observed since 2014. The circulation of EV-D68 in 2020 might have been limited by widespread COVID-19 mitigation measures; how these changes in behavior might influence the timing and levels of circulation in future years is unknown. Ongoing monitoring of EV-D68 detections is warranted for preparedness for EV-D68-associated ARI and AFM.

SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study.

Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions. We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. The use of high-efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% credible interval (CrI): 73.1-85.7%) and 87% (CrI: 80.0-92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

Risk factors of SARS-CoV-2 infection in healthcare workers: a retrospective study of a nosocomial outbreak.

BACKGROUND: Healthcare workers (HCWs) are at the forefront of fighting against the COVID-19 pandemic. However, they are at high risk of acquiring the pathogen from infected patients and transmitting to other HCWs. We aimed to investigate risk factors for nosocomial COVID-19 infection among HCWs in a non-COVID-19 hospital yard. METHODS: Retrospective data collection on demographics, lifestyles, contact status with infected subjects for 118 HCWs (including 12 COVID-19 HCWs) at Union Hospital of Wuhan, China. Sleep quality and working pressure were evaluated by the Pittsburgh Sleep Quality Index (PSQI) and The Nurse Stress Index (NSI), respectively. The follow-up duration was from Dec 25, 2019, to Feb 15, 2020. RESULTS: A high proportion of COVID-19 HCWs had engaged in night shift-work (75.0% vs. 40.6%) and felt working under pressure (66.7% vs. 32.1%) than uninfected HCWs. SARS-CoV-2 infected HCWs had significantly higher scores of PSQI and NSI than uninfected HCWs (P < 0.001). Specifically, scores of 5 factors (sleep quality, sleep time, sleep efficiency, sleep disorder, and daytime dysfunction) in PSQI were higher among infected HCWs. For NSI, its 5 subscales (nursing profession and work, workload and time allocation, working environment and resources, patient care, management and interpersonal relations) were all higher in infected than uninfected nurse. Furthermore, total scores of PSQI (HR = 2.97, 95%CI = 1.86-4.76; P <0.001) and NSI (HR = 4.67, 95%CI = 1.42-15.45; P = 0.011) were both positively associated with the risk of SARS-CoV-2 infection. CONCLUSION: Our analysis shows that poor sleep quality and higher working pressure may increase the risk of nosocomial SARS-CoV-2 infection among HCWs.