Risk of COVID-19 Transmission Aboard Aircraft: An Epidemiological Analysis Based on the National Health Information Platform (preprint)

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the type of coronavirus that causes the Coronavirus Disease 2019 (COVID-19), is mainly spread by respiratory droplets and aerosols. This study aims to investigate the risk of COVID-19 transmission on aircraft. This in turn provides the scientific basis for the return of air travel from pandemic to normal conditions.Methods: We obtained data on all international flights to Lanzhou, China, from June 1 to August 1, 2020, through the Gansu Province National Health Information Platform and the official website of the Gansu Provincial Center for Disease Control and Prevention. We calculated the period prevalence rate of COVID-19 among the passengers of all flights during the 14-day period following the flight, and stratified the prevalence by the seat positions (aisle, middle, window), and the relationship to other confirmed cases (1-2 rows ahead, same row, 1-2 rows behind). Results: Three international flights arrived in Lanzhou, China, during the study period, from Riyadh (MU7792), Jeddah (MU7790), and Moscow (CA608) each. The flights had a total of 700 passengers, of whom 405 (57.9%) were male and 80 (11.4%) were children below age fourteen. Twenty-seven (3.9%) passengers were confirmed to have COVID-19. There were no fatalities and all patients were cured. We identified three family clusters of cases. Confirmed patients were primarily male (n=17, 65.4%) with a median age of 27.0 years. The majority of confirmed cases were seated in the middle rows of the economy class, or near public facility areas such as restrooms and galleys. The prevalence of COVID-19 did not differ between passengers sitting on window, aisle or middle seats. Compared with passengers sitting on the same row up to two rows behind a confirmed case, passengers seated in the two rows ahead a confirmed case were at a slightly higher risk of being infected. Conclusions: COVID-19 may possibly be transmitted during a passenger flight, although there is still no direct evidence.

Associations Between the Use of Non-Steroidal Anti-Inflammatory Drugs and Adverse Outcomes Among Patients with COVID-19: A Systematic Review and Meta-Analysis (preprint)

Background: There are concerns that the use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase the risk of adverse outcomes in COVID-19 patients. Therefore, this study aimed to synthesize the existing evidence on associations between the use of NSAIDs and adverse outcomes among patients with COVID-19.Methods: Systematic search of WHO COVID-19 Database, Medline, The Cochrane Library, Web of Science, Embase, China Biology Medicine disc, China National Knowledge Infrastructure, and Wanfang Database for all articles published from January 1, 2020, to August 10, 2021, as well as a supplementary search of Google Scholar. We included comparative observational studies and randomized controlled trials that enrolled patients with COVID-19 who took NSAIDs before or after diagnosis of COVID-19. Data extraction and quality assessment of methodology of included studies were completed by two reviewers independently. We conducted a meta-anlysis on the main outcomes, as well as selected subgroup analyses stratified by the type of NSAID.Fingings: Fifteen non-randomized studies evaluating 24700 adult COVID-19 patients were identified. The use of NSAIDs in patients with COVID-19, compared with no use of NSAIDs, was not significantly associated with an elevated mortality (odds ratio [OR]=0.94, 95% confidence interval [CI]: 0.87 to 1.02), or an increased probability of ICU admission (OR=1.35, 95% CI: 0.73 to 2.49), requiring mechanical ventilation (OR=1.23, 95% CI: 0.71 to 2.13), or administration of supplemental oxygen (OR=0.99, 95% CI: 0.91 to 1.08). The subgroup analyses revealed that the use of ibuprofen (OR=1.22, 95% CI: 0.32 to 4.60), etoricoxib (OR=0.36, 95% CI: 0.02 to 6.49) or celecoxib (zero deaths in both groups) were not associated with an increased risk of death in COVID-19 patients, compared with not using any NSAID.Interpretation: Fever is one of the main clinical symptoms of COVID-19. According to our findings, NSAIDs such as ibuprofen can be used to treat fever in COVID-19 patients safely.Funding: None to declare. Declaration of Interest: None to declare.

Geospatial Model of COVID-19 Spreading and Vaccination With Event Gillespie Algorithm (preprint)

We developed a model and a software package for stochastic simulations of transmission of COVID-19 and other similar infectious diseases, that takes into account contact network structures and geographical distribution of population density, detailed up to a level of location of individuals. Our analysis framework includes a surrogate model optimization process for quick fitting of the model’s parameters to the observed epidemic curves for cases, hospitalizations and deaths. This set of instruments (the model, the simulation code, and the optimizer) is a useful tool for policymakers and epidemic response teams who can use it to forecast epidemic development scenarios in local environments (on the scale from towns to large countries) and design optimal response strategies. The simulation code also includes a geospatial visualization subsystem, presenting detailed views of epidemic scenarios directly on population density maps. We used the developed framework to draw predictions for COVID-19 spreading in the canton of Geneva, Switzerland.

Novel application of capture-recapture methods to estimate the completeness of contact tracing during a large outbreak of Ebola Virus Disease, Democratic Republic of Congo, 2018-2020 (preprint)

Despite its critical role in containing outbreaks, the efficacy of contact tracing (CT), measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of CT by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of Congo. We applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved cases with a) any contacts and b) infected contacts, to compute CT sensitivity. Geometric distributions were the best fitting models. Our results indicate that CT efforts identified almost all (n=792, 99%) of the cases with any contacts, but only half (n=207, 48%) of the cases with infected contacts, suggesting that CT efforts performed well at identifying contacts during the listing stage, but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the current COVID-19 pandemic.

Consistency of recommendations and methodological quality of guidelines for the diagnosis and treatment of COVID-19.

OBJECTIVE: Since the beginning of the COVID-19 epidemic, a large number of guidelines on diagnosis and treatment of COVID-19 have been developed, but the quality of those guidelines and the consistency of recommendations are unclear. The objective of this study is to evaluate the quality of the diagnosis and treatment guidelines on COVID-19 and analyze the consistency of the recommendations of these guidelines. METHODS: We searched for guidelines on diagnosis and/or treatment of COVID-19 through PubMed, CBM, CNKI, and WanFang Data, from January 1, 2020 to August 31, 2020. In addition, we also searched official websites of the US CDC, European CDC and WHO, and some guideline collection databases. We included diagnosis and/or treatment guidelines for COVID-19, including rapid advice guidelines and interim guidelines. Two trained researchers independently extracted data and four trained researchers evaluated the quality of the guidelines using the AGREE II instruments. We extracted information on the basic characteristics of the guidelines, guideline development process, and the recommendations. We described the consistency of the direction of recommendations for treatment and diagnosis of COVID-19 across the included guidelines. RESULTS: A total of 37 guidelines were included. Most included guidelines were assessed as low quality, with only one of the six domains of AGREE II (clarity of presentation) having a mean score above 50%. The mean scores of three domains (stakeholder involvement, the rigor of development and applicability) were all below 30%. The recommendations on diagnosis and treatment were to some extent consistent between the included guidelines. Computed tomography (CT), X-rays, lung ultrasound, RT-PCR, and routine blood tests were the most commonly recommended methods for COVID-19 diagnosis. Thirty guidelines were on the treatment of COVID-19. The recommended forms of treatment included supportive care, antiviral therapy, glucocorticoid therapy, antibiotics, immunoglobulin, extracorporeal membrane oxygenation (ECMO), convalescent plasma, and psychotherapy. CONCLUSIONS: The methodological quality of currently available diagnosis and treatment guidelines for COVID-19 is low. The diagnosis and treatment recommendations between the included guidelines are highly consistent. The main diagnostic methods for COVID-19 are RT-PCR and CT, with ultrasound as a potential diagnostic tool. As there is no effective treatment against COVID-19 yet, supportive therapy is at the moment the most important treatment option.

A stochastic geospatial epidemic model and simulation using an event modulated Gillespie algorithm (preprint)

We developed a model and a software package for stochastic simulations of transmission of COVID-19 and other similar infectious diseases, that takes into account contact network structures and geographical distribution of population density, detailed up to a level of location of individuals. Our analysis framework includes a surrogate model optimization process for quick fitting of the model's parameters to the observed epidemic curves for cases, hospitalizations and deaths. This set of instruments (the model, the simulation code, and the optimizer) is a useful tool for policymakers and epidemic response teams who can use it to forecast epidemic development scenarios in local environments (on the scale from towns to large countries) and design optimal response strategies. The simulation code also includes a geospatial visualization subsystem, presenting detailed views of epidemic scenarios directly on population density maps. We used the developed framework to draw predictions for COVID-19 spreading in the canton of Geneva, Switzerland.

Future scenarios for the SARS-CoV-2 epidemic in Switzerland: an age-structured model (preprint)

The recent lifting of COVID-19 related restrictions in Switzerland causes uncertainty about the future of the epidemic. We developed a compartmental model for SARS-CoV-2 transmission in Switzerland and projected the course of the epidemic until the end of year 2020 under various scenarios. The model was age-structured with three categories, children (0-17), adults (18-64) and seniors (65- years). Lifting all restrictions according to the plans disclosed by the Swiss federal authorities by mid-May resulted in a rapid rebound in the epidemic, with the peak expected in July. Measures equivalent to at least 90% reduction in all contacts were able to eradicate the epidemic; 56% reduction in contacts could keep the intensive care unit occupancy under the critical level, and delay the next wave until October. Scenarios where strong contact reductions were only applied in selected age groups could not suppress the epidemic, increasing the risk of a next wave in July, and another stronger wave in September. Future interventions need to cover all age groups to keep the SARS-CoV-2 epidemic under control.

A follow-up study of children infected with SARS-CoV-2 from Western China (preprint)

Background: To clarify the characteristic and the duration of positive nucleic acid in children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including asymptomatic children. Methods: A total of 32 children confirmed with SARS-CoV-2 infection between January 24 and February 12, 2020 from four provinces in Western China were enrolled in this study and followed up until discharge and quarantine 14 days later. Results: Eleven children (34%) were asymptomatic, among whom six children had normal computed tomographic (CT) scan images. Age and gender were not associated with clinical symptoms or the results of CT scan in children infected with SARS-CoV-2. The concentrations of white blood cells and neutrophils were higher in children with asymptomatic infection than in children with clinical symptoms or CT abnormalities. Patients who presented with CT abnormalities had lower D-dimer or lower total bilirubin than those who had normal CT scan but clinical symptoms. All children recovered and no one died or was admitted to the pediatric intensive care unit (PICU). The mean duration of positive SARS-CoV-2 nucleic acid was 15.4 (SD=7.2) days and similar for both asymptomatic children and children with symptoms or CT abnormalities. We found a significant negative correlation between the lymphocyte count and the duration of positive nucleic acid test. Conclusions: Children with asymptomatic infection should be quarantined for the same duration as symptomatic patients infected with SARS-CoV-2. The clinical significance and mechanism behind the negative correlation between the number of lymphocytes and the duration of positive SARS-CoV-2 needs further study.

The epidemic situation of COVID-19 in Gansu Province, China — a Big Data analysis of the National Health Information Platform (preprint)

Objective This study is to explore the patient characteristics and transmission chains of COVID-19 in the population of Gansu province, and support decision-making. Methods We collected data from Gansu National Health Information Platform. We conducted a case-control study, including patients with COVID-19 confirmed between January 23 and February 6, 2020 as cases, and all inpatients, outpatients and emergency patients except those with COVID-19 during the same period as the control group. We compared the gender and age between two groups. We also described the incubation period, consultation time and sources of infection in the cases, and calculated the secondary cases that occurred within Gansu for each imported case. Results We found no differences in gender (P=0.107). COVID-19 cases were more likely to occur among the middle-aged people (P=0.038). Twenty-eight (41.8%) of the 67 cases had a history of direct exposure in Wuhan. Twenty-five (52.2%) cases came from ten families, and we found no clear reports of modes of transmission other than family clusters. The largest number of secondary cases linked to a single source was nine. Conclusion There is no difference in gender between the cases and controls. However, COVID-19 patients were slightly younger than those attending for other reasons. The most common suspected mode of transmission was through family cluster. Gansu and other settings worldwide should continue to strengthen the utilization of big data in epidemic control.