Investigating COVID-19 transmission in a tertiary hospital in Hanoi, Vietnam using social network analysis.

OBJECTIVES: In March 2020, a COVID-19 outbreak in a major referral hospital in Hanoi, Vietnam led to 7664 patients and staff being sent into lockdown for 2 weeks, and more than 52,200 persons across 49 provinces being quarantined. We assessed SARS-CoV-2 transmission patterns during this to-date largest hospital outbreak in Vietnam using social network analysis (SNA). METHODS: We constructed a directed relational network and calculated network metrics for 'degree', 'betweenness', 'closeness' and 'eigenvector' centrality to understand individual-level transmission patterns. We analysed network components and modularity to identify sub-network structures with disproportionately big effects. RESULTS: We detected 68 connections between 46 confirmed cases, of whom 27 (58.7%) were ancillary support staff, 7 (15.2%) caregivers, 6 (13%) patients and 2 (4.4%) nurses. Among the 10 most important cases selected by each SNA network metric, transmission dynamics clustered in 17 cases, of whom 12 (70.6%) cases were ancillary support staff. Ancillary support staff also constituted 71.1% of cases in the dominant sub-network and 68.8% of cases in the three largest sub-communities. CONCLUSIONS: We identified non-clinical ancillary support staff, who are responsible for room service and food distribution in hospital wards in Vietnam, as a group with disproportionally big impacts on transmission dynamics during this outbreak. Our findings call for a holistic approach to nosocomial outbreak prevention and response that includes both clinical and non-clinical hospital staff. Our work also shows the potential of SNA as a complementary outbreak investigation method to better understand infection patterns in hospitals and similar settings.

The network of psychosocial health in middle-aged and older adults during the first COVID-19 lockdown.

PURPOSE: Psychosocial health problems, such as social isolation, loneliness, depression and anxiety, have gained attention during the COVID-19 pandemic and are commonly co-occurring. We investigated the network of psychosocial health constructs during the COVID-19 pandemic. METHODS: This study included 4553 participants (mean age: 68.6 ± 11.2 years, 56% women) from the prospective Rotterdam Study, who filled out a questionnaire between April and July 2020, the time of the first COVID-19 wave in the Netherlands. Psychosocial health constructs included were depressive symptoms (Center for Epidemiological Studies Depression scale), anxiety symptoms (Hospital Anxiety and Depression scale), loneliness (University of California, Los Angeles loneliness scale), social connectedness (five items) and pandemic-related worry (five items). We estimated mixed graphical models to assess the network of items of these constructs and whether age and sex affected the network structure. RESULTS: Within the network of psychosocial constructs, a higher depressive symptoms score was particularly associated with items of loneliness and social connectedness, whereas overall anxiety was particularly associated with items of pandemic-related worry. Between people from different sex and age, the network structure significantly altered. CONCLUSION: This study demonstrates that within the same network of psychosocial health constructs, depressive symptom score is particularly associated with loneliness and social connectedness, whereas anxiety symptom score is associated with pandemic-related worry during the first COVID-19 lockdown. Our results support that psychosocial constructs should be considered in conjunction with one another in prevention and treatment efforts in clinical care, and that these efforts need to be tailored to specific demographic groups.

Exploring online social networks of school leaders in times of COVID-19.

The COVID-19 pandemic has raised a wide range of challenges for school leaders that they now (rapidly) have to address. Consequently, they also turn to informal learning networks, in order to share and collect information and reach out to their communities. In this context, the current study investigates the underlying networks structures among school leaders, what type of information is being shared, and what differences can be identified when comparing a nation-wide and a localized sample. We collected data from a US nation-wide sample of 15 relevant Twitter conversations, as well as Tweets from an US urban mid-sized public school district. Using a mixed-methods approach, we discovered several key structural dimensions and a host of highly influential actors. Moreover, we found semantic evidence for users sharing information on topics such as status reports. Finally, we discovered that the urban sample did not overly use the nation-wide, very specific approach of including COVID-19 related hashtags. Instead, they used more localized terminologies. These findings are valuable for policy makers, as they map the underlying communication patterns and provide valuable insights into who is moving what types of resources as part of the emerging governance approach on social media.

Virus systems biology: Proteomics profiling of dynamic protein networks during infection.

The host cell proteome undergoes a variety of dynamic changes during viral infection, elicited by the virus itself or host cell defense mechanisms. Studying these changes on a global scale by integrating functional and physical interactions within protein networks during infection is an important tool to understand pathology. Indeed, proteomics studies dissecting protein signaling cascades and interaction networks upon infection showed how global information can significantly improve understanding of disease mechanisms of diverse viral infections. Here, we summarize and give examples of different experimental designs, proteomics approaches and bioinformatics analyses that allow profiling proteome changes and host-pathogen interactions to gain a molecular systems view of viral infection.

Intestinal Inflammation Modulates the Expression of ACE2 and TMPRSS2 and Potentially Overlaps With the Pathogenesis of SARS-CoV-2-related Disease.

BACKGROUND AND AIMS: The presence of gastrointestinal symptoms and high levels of viral RNA in the stool suggest active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication within enterocytes. METHODS: Here, in multiple, large cohorts of patients with inflammatory bowel disease (IBD), we have studied the intersections between Coronavirus Disease 2019 (COVID-19), intestinal inflammation, and IBD treatment. RESULTS: A striking expression of ACE2 on the small bowel enterocyte brush border supports intestinal infectivity by SARS-CoV-2. Commonly used IBD medications, both biologic and nonbiologic, do not significantly impact ACE2 and TMPRSS2 receptor expression in the uninflamed intestines. In addition, we have defined molecular responses to COVID-19 infection that are also enriched in IBD, pointing to shared molecular networks between COVID-19 and IBD. CONCLUSIONS: These data generate a novel appreciation of the confluence of COVID-19- and IBD-associated inflammation and provide mechanistic insights supporting further investigation of specific IBD drugs in the treatment of COVID-19. Preprint doi: https://doi.org/10.1101/2020.05.21.109124.