Measures to prevent nosocomial transmissions of COVID-19 based on interpersonal contact data.

BACKGROUND: With the global spreading of Coronavirus disease (COVID-19), many primary care medical workers have been infected, particularly in the early stages of this pandemic. Although extensive studies have explored the COVID-19 transmission patterns and (non-) pharmaceutical intervention to protect the general public, limited research has analysed the measures to prevent nosocomial transmission based upon detailed interpersonal contacts between medical staff and patients. AIM: This paper aims to develop and evaluate proactive prevention measures to contain the nosocomial transmission of COVID-19. The specific objectives are (1) to understand the virus transmission via interpersonal contacts among medical staff and patients; (2) to define proactive measures to reduce the risk of infection of medical staff and (3) evaluate the effectiveness of these measures to control the COVID-19 epidemic in hospitals. METHODS: We observed the operation of a typical primary hospital in China to understand the interpersonal contacts among medical staff and patients. We defined effective distance as the indicator for risk of transmission. Then three proactive measures were proposed based upon the observations, including a medical staff rotation system, the establishment of a separate fever clinic and medical staff working alone. Finally, the impacts of these measures are evaluated with a modified Susceptible-Exposure-Infected-Removed model accommodating the situation of hospitals and asymptomatic and latent infection of COVID-19. The case study was conducted with the hospital observed in December 2019 and February 2020. FINDINGS: The implementation of the medical staff rotation system has the most significant impact on containing the epidemic. The establishment of a separate fever clinic and medical staff working alone also benefits from inhibiting the epidemic outbreak. The simulation finds that if effective prevention and control measures are not taken in time, it will lead to a surge of infection cases in all asymptomatic probabilities and incubation periods.

Revealing spatiotemporal transmission patterns and stages of COVID-19 in China using individual patients' trajectory data.

Gauging viral transmission through human mobility in order to contain the COVID-19 pandemic has been a hot topic in academic studies and evidence-based policy-making. Although it is widely accepted that there is a strong positive correlation between the transmission of the coronavirus and the mobility of the general public, there are limitations to existing studies on this topic. For example, using digital proxies of mobile devices/apps may only partially reflect the movement of individuals; using the mobility of the general public and not COVID-19 patients in particular, or only using places where patients were diagnosed to study the spread of the virus may not be accurate; existing studies have focused on either the regional or national spread of COVID-19, and not the spread at the city level; and there are no systematic approaches for understanding the stages of transmission to facilitate the policy-making to contain the spread. To address these issues, we have developed a new methodological framework for COVID-19 transmission analysis based upon individual patients' trajectory data. By using innovative space-time analytics, this framework reveals the spatiotemporal patterns of patients' mobility and the transmission stages of COVID-19 from Wuhan to the rest of China at finer spatial and temporal scales. It can improve our understanding of the interaction of mobility and transmission, identifying the risk of spreading in small and medium-sized cities that have been neglected in existing studies. This demonstrates the effectiveness of the proposed framework and its policy implications to contain the COVID-19 pandemic.

Dynamic anti-spike protein antibody profiles in COVID-19 patients.

OBJECTIVES: This study intended to investigate the dynamics of anti-spike (S) IgG and IgM antibodies in COVID-19 patients. METHODS: Anti-S IgG/IgM was determined by a semi-quantitative fluorescence immunoassay in the plasma of COVID-19 patients at the manifestation and rehabilitation stages. The immunoreactivity to full-length S proteins, C-terminal domain (CTD), and N-terminal domain (NTD) of S1 fragments were determined by an ELISA assay. Clinical properties at admission and discharge were collected simultaneously. RESULTS: The positive rates of anti-S IgG/IgM in COVID-19 patients were elevated after rehabilitation compared to the in-patients. Anti-S IgG and IgM were not apparent until day 14 and day ten, respectively, according to Simple Moving Average analysis with five days' slide window deduction. More than 90% of the rehabilitation patients exhibited IgG and IgM responses targeting CTD-S1 fragments. Decreased total peripheral lymphocytes, CD4+ and CD8+ T cell counts were seen in COVID-19 patients at admission and recovered after the rehabilitation. CONCLUSIONS: Anti-S IgG and IgM do not appear at the onset with the decrease in T cells, making early serological screening less significant. However, the presence of high IgG and IgM to S1-CTD in the recovered patients highlights humoral responses after SARS-CoV-2 infection, which might be associated with efficient immune protection in COVID-19 patients.