Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

Importance: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies. Objective: To develop a haplotype-based artificial intelligence (HAI) model for identifying novel variants, including mixture variants (MVs) of known variants and new variants with novel mutations. Design, Setting, and Participants: This cross-sectional study used serially observed viral genomic sequences globally (prior to March 14, 2022) to train and validate the HAI model and used it to identify variants arising from a prospective set of viruses from March 15 to May 18, 2022. Main Outcomes and Measures: Viral sequences, collection dates, and locations were subjected to statistical learning analysis to estimate variant-specific core mutations and haplotype frequencies, which were then used to construct an HAI model to identify novel variants. Results: Through training on more than 5 million viral sequences, an HAI model was built, and its identification performance was validated on an independent validation set of more than 5 million viruses. Its identification performance was assessed on a prospective set of 344 901 viruses. In addition to achieving an accuracy of 92.8% (95% CI within 0.1%), the HAI model identified 4 Omicron MVs (Omicron-Alpha, Omicron-Delta, Omicron-Epsilon, and Omicron-Zeta), 2 Delta MVs (Delta-Kappa and Delta-Zeta), and 1 Alpha-Epsilon MV, among which Omicron-Epsilon MVs were most frequent (609/657 MVs [92.7%]). Furthermore, the HAI model found that 1699 Omicron viruses had unidentifiable variants given that these variants acquired novel mutations. Lastly, 524 variant-unassigned and variant-unidentifiable viruses carried 16 novel mutations, 8 of which were increasing in prevalence percentages as of May 2022. Conclusions and Relevance: In this cross-sectional study, an HAI model found SARS-COV-2 viruses with MV or novel mutations in the global population, which may require closer examination and monitoring. These results suggest that HAI may complement phylogenic variant assignment, providing additional insights into emerging novel variants in the population.

Effectiveness of tailored COVID-19 messages for vulnerable Australians: A study protocol.

Multiple approaches can be used to communicate public health messages through mass media. It is unclear which approaches are superior for meeting the needs of the general community along with vulnerable population subgroups. To compare different public health strategy communication approaches for influencing the COVID-safe behavioural intentions of both community and vulnerable population subgroups. This study will conduct three concurrent 'helix' randomised controlled trials with Latin square sequencing and factorial intervention allocation to assess the effectiveness of different communication strategies amongst the Australian general community and six subgroups that are considered vulnerable to contracting, transmitting or experiencing severe consequences of COVID-19 infection. Communication approaches being compared include: the format of communication (written versus video), who is providing information (general practitioner, politician, community-representative), what is said and how it is delivered (direct information provision versus conversational approach) and the visual content of video messaging (animation versus 'talking head'). Recruited participants will be randomly allocated to receive a specific combination of health messaging strategies using six different COVID-19 context areas. Outcomes will be assessed in a survey using behaviour intention questions, and questions surrounding level of agreement with feeling represented in the health messaging strategy. These trials will use a unique research approach to provide an experimental evidence base to help guide development of impactful and inclusive COVID-19 and related public health messaging. All three trials are registered with the Australian New Zealand Clinical Trials Registry (ANZCTR). Trial 1: Update and impact of Government recommendations about COVID-19 (coronavirus)-Stage 3, Trial 1, vulnerable subgroup populations (ACTRN12622000606785). Trial 2: Update and impact of Government recommendations about COVID-19 (coronavirus)-Stage 3, Trial 2, community group (ACTRN12622000605796). Trial 3: Update and impact of Government recommendations about COVID-19 (coronavirus)-Stage 3, Trial 3, What communication strategy is most effective for both vulnerable and community group populations? (ACTRN12622000617763).

Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy.

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.37*10-4, 1.0*10-15, 4.76*10-7 and 1.56*10-4, respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p values < 1.0*10-15). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact remdesivir binding.

Australian public health COVID-19 messaging is missing its mark in some vulnerable communities and people who reject COVID-19 safety advice.

Background: There are groups in our community who may be more vulnerable to contracting, transmitting, or experiencing negative health impacts of COVID-19 than the general community. They may also have greater difficulty accessing, accepting, and acting upon COVID-19 public health information. Our aim was to understand if vulnerable communities and those who express "COVID-risk" behavioural intentions seek and respond differently to COVID-19 public health information. Methods: This observational, cross-sectional study recruited adults aged over 18 years from the Australian general community and six community groups (people with disabilities and their caregivers, Aboriginal and Torres Strait Islanders, aged care workers, street-based sex workers, refugees and asylum seekers, and the deaf and hard of hearing). We investigated attitudes and beliefs about COVID-19 public health messages. We identified factors associated with the respondent's perception of the ease of finding information and understanding it, and its relevance to them. We also examined latent classes that were developed based on attitudes to public health measures and vulnerable group categories, along with demographic variables. Results: We received 1444 responses (n = 1121 general community; n ≥50 for each vulnerable group). The vulnerable groups examined found COVID-19 public health messages as easy, if not easier, to find and understand than the general community. Four latent classes were identified: COVID-safe mask wearers (10% of sample), COVID-safe test takers (56%), COVID-risk isolators (19%) and COVID-risk visitors (15%). The COVID-risk classes (34% of sample) were less likely to consider COVID-19 information easy to find, understandable, and relevant. Conclusions: Additional public health messaging strategies may be needed for targeting people with "COVID-risk" beliefs and attitudes who appear across the community (general and vulnerable groups) rather than just targeting specific cultural or other groupings that we think may be vulnerable. COVID-risk classes identified through this study were not defined by demographic characteristics or cultural groupings, but were spread across vulnerable communities and the general community. Different approaches for tailoring and delivery of specific public health information for these groups are needed.

Application of Statistical Learning to Identify Omicron Mutations in SARS-CoV-2 Viral Genome Sequence Data From Populations in Africa and the United States.

Importance: With timely collection of SARS-CoV-2 viral genome sequences, it is important to apply efficient data analytics to detect emerging variants at the earliest time. Objective: To evaluate the application of a statistical learning strategy (SLS) to improve early detection of novel SARS-CoV-2 variants using viral sequence data from global surveillance. Design, Setting, and Participants: This case series applied an SLS to viral genomic sequence data collected from 63 686 individuals in Africa and 531 827 individuals in the United States with SARS-CoV-2. Data were collected from January 1, 2020, to December 28, 2021. Main Outcomes and Measures: The outcome was an indicator of Omicron variant derived from viral sequences. Centering on a temporally collected outcome, the SLS used the generalized additive model to estimate locally averaged Omicron caseload percentages (OCPs) over time to characterize Omicron expansion and to estimate when OCP exceeded 10%, 25%, 50%, and 75% of the caseload. Additionally, an unsupervised learning technique was applied to visualize Omicron expansions, and temporal and spatial distributions of Omicron cases were investigated. Results: In total, there were 2698 cases of Omicron in Africa and 12 141 in the United States. The SLS found that Omicron was detectable in South Africa as early as December 31, 2020. With 10% OCP as a threshold, it may have been possible to declare Omicron a variant of concern as early as November 4, 2021, in South Africa. In the United States, the application of SLS suggested that the first case was detectable on November 21, 2021. Conclusions and Relevance: The application of SLS demonstrates how the Omicron variant may have emerged and expanded in Africa and the United States. Earlier detection could help the global effort in disease prevention and control. To optimize early detection, efficient data analytics, such as SLS, could assist in the rapid identification of new variants as soon as they emerge, with or without lineages designated, using viral sequence data from global surveillance.

Post-COVID-19 Conditions Among Children 90 Days After SARS-CoV-2 Infection.

Importance: Little is known about the risk factors for, and the risk of, developing post-COVID-19 conditions (PCCs) among children. Objectives: To estimate the proportion of SARS-CoV-2-positive children with PCCs 90 days after a positive test result, to compare this proportion with SARS-CoV-2-negative children, and to assess factors associated with PCCs. Design, Setting, and Participants: This prospective cohort study, conducted in 36 emergency departments (EDs) in 8 countries between March 7, 2020, and January 20, 2021, included 1884 SARS-CoV-2-positive children who completed 90-day follow-up; 1686 of these children were frequency matched by hospitalization status, country, and recruitment date with 1701 SARS-CoV-2-negative controls. Exposure: SARS-CoV-2 detected via nucleic acid testing. Main Outcomes and Measures: Post-COVID-19 conditions, defined as any persistent, new, or recurrent health problems reported in the 90-day follow-up survey. Results: Of 8642 enrolled children, 2368 (27.4%) were SARS-CoV-2 positive, among whom 2365 (99.9%) had index ED visit disposition data available; among the 1884 children (79.7%) who completed follow-up, the median age was 3 years (IQR, 0-10 years) and 994 (52.8%) were boys. A total of 110 SARS-CoV-2-positive children (5.8%; 95% CI, 4.8%-7.0%) reported PCCs, including 44 of 447 children (9.8%; 95% CI, 7.4%-13.0%) hospitalized during the acute illness and 66 of 1437 children (4.6%; 95% CI, 3.6%-5.8%) not hospitalized during the acute illness (difference, 5.3%; 95% CI, 2.5%-8.5%). Among SARS-CoV-2-positive children, the most common symptom was fatigue or weakness (21 [1.1%]). Characteristics associated with reporting at least 1 PCC at 90 days included being hospitalized 48 hours or more compared with no hospitalization (adjusted odds ratio [aOR], 2.67 [95% CI, 1.63-4.38]); having 4 or more symptoms reported at the index ED visit compared with 1 to 3 symptoms (4-6 symptoms: aOR, 2.35 [95% CI, 1.28-4.31]; ≥7 symptoms: aOR, 4.59 [95% CI, 2.50-8.44]); and being 14 years of age or older compared with younger than 1 year (aOR, 2.67 [95% CI, 1.43-4.99]). SARS-CoV-2-positive children were more likely to report PCCs at 90 days compared with those who tested negative, both among those who were not hospitalized (55 of 1295 [4.2%; 95% CI, 3.2%-5.5%] vs 35 of 1321 [2.7%; 95% CI, 1.9%-3.7%]; difference, 1.6% [95% CI, 0.2%-3.0%]) and those who were hospitalized (40 of 391 [10.2%; 95% CI, 7.4%-13.7%] vs 19 of 380 [5.0%; 95% CI, 3.0%-7.7%]; difference, 5.2% [95% CI, 1.5%-9.1%]). In addition, SARS-CoV-2 positivity was associated with reporting PCCs 90 days after the index ED visit (aOR, 1.63 [95% CI, 1.14-2.35]), specifically systemic health problems (eg, fatigue, weakness, fever; aOR, 2.44 [95% CI, 1.19-5.00]). Conclusions and Relevance: In this cohort study, SARS-CoV-2 infection was associated with reporting PCCs at 90 days in children. Guidance and follow-up are particularly necessary for hospitalized children who have numerous acute symptoms and are older.

Corticosteroids and Other Treatments Administered to Children Tested for SARS-CoV-2 Infection in Emergency Departments.

OBJECTIVE: We sought to determine if corticosteroid administration is associated with a SARS-CoV-2 nucleic acid test-positive result and to describe therapies administered to SARS-CoV-2 infected children. METHODS: We collected cross-sectional data from participants recruited in 41 pediatric emergency departments (ED) in 10 countries between March 2020 and June 2021. Participants were <18 years old, had signs or symptoms of, or risk factors for acute SARS-CoV-2 infection, and had nucleic acid testing performed. To determine if SARS-CoV-2 test status was independently associated with corticosteroid administration, we used a multivariable conditional logistic regression model matched by study site to compare treatments administered based on SARS-CoV-2 test and disposition status. This analysis was repeated for the subgroup of study participants who were hospitalized. RESULTS: 30.3% (3,121/10,315) of participants were SARS-CoV-2-positive. Although remdesivir was more commonly administered to SARS-CoV-2-positive children, use was infrequent (25/3120 [0.8%] vs 1/7188 [0.01%]; P = .001). Corticosteroid use was less common among SARS-CoV-2-positive children (219/3120 [7.0%] vs 759/7190 [10.6%]; P < .001). Among hospitalized children, there were no differences in provision of inotropes, respiratory support, chest drainage or extracorporeal membrane oxygenation between groups. Corticosteroid administration was associated with age, history of asthma, wheezing, study month, hospitalization and intensive care unit admission; it was not associated with a positive SARS-CoV-2 test result overall (aOR: 0.91; 95%CI: 0.74, 1.12) or among the subgroup of those hospitalized (aOR: 1.04; 95%CI: 0.75, 1.44). CONCLUSIONS: Few disease-specific treatments are provided to SARS-CoV-2-positive children; clinical trials evaluating therapies in children are urgently needed.

Mutations in viral nucleocapsid protein and endoRNase are discovered to associate with COVID19 hospitalization risk

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients;388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytical power, we accessed 7137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values < 0.01). Using temporal synchrony, we identified a four SNV-haplotype (t19839-g28881-g28882-g28883) that was significantly associated with case/control status (Fisher’s exact p = 2.84 × 10–11). This haplotype appeared in April 2020, peaked in June, and persisted into January 2021. The association was replicated (OR = 5.46, p-value = 4.71 × 10−12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering “cytokine storms” and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status.

Outcomes of SARS-CoV-2-Positive Youths Tested in Emergency Departments: The Global PERN-COVID-19 Study.

Importance: Severe outcomes among youths with SARS-CoV-2 infections are poorly characterized. Objective: To estimate the proportion of children with severe outcomes within 14 days of testing positive for SARS-CoV-2 in an emergency department (ED). Design, Setting, and Participants: This prospective cohort study with 14-day follow-up enrolled participants between March 2020 and June 2021. Participants were youths aged younger than 18 years who were tested for SARS-CoV-2 infection at one of 41 EDs across 10 countries including Argentina, Australia, Canada, Costa Rica, Italy, New Zealand, Paraguay, Singapore, Spain, and the United States. Statistical analysis was performed from September to October 2021. Exposures: Acute SARS-CoV-2 infection was determined by nucleic acid (eg, polymerase chain reaction) testing. Main Outcomes and Measures: Severe outcomes, a composite measure defined as intensive interventions during hospitalization (eg, inotropic support, positive pressure ventilation), diagnoses indicating severe organ impairment, or death. Results: Among 3222 enrolled youths who tested positive for SARS-CoV-2 infection, 3221 (>99.9%) had index visit outcome data available, 2007 (62.3%) were from the United States, 1694 (52.6%) were male, and 484 (15.0%) had a self-reported chronic illness; the median (IQR) age was 3 (0-10) years. After 14 days of follow-up, 735 children (22.8% [95% CI, 21.4%-24.3%]) were hospitalized, 107 (3.3% [95% CI, 2.7%-4.0%]) had severe outcomes, and 4 children (0.12% [95% CI, 0.03%-0.32%]) died. Characteristics associated with severe outcomes included being aged 5 to 18 years (age 5 to <10 years vs <1 year: odds ratio [OR], 1.60 [95% CI, 1.09-2.34]; age 10 to <18 years vs <1 year: OR, 2.39 [95% CI 1.38-4.14]), having a self-reported chronic illness (OR, 2.34 [95% CI, 1.59-3.44]), prior episode of pneumonia (OR, 3.15 [95% CI, 1.83-5.42]), symptoms starting 4 to 7 days prior to seeking ED care (vs starting 0-3 days before seeking care: OR, 2.22 [95% CI, 1.29-3.82]), and country (eg, Canada vs US: OR, 0.11 [95% CI, 0.05-0.23]; Costa Rica vs US: OR, 1.76 [95% CI, 1.05-2.96]; Spain vs US: OR, 0.51 [95% CI, 0.27-0.98]). Among a subgroup of 2510 participants discharged home from the ED after initial testing and who had complete follow-up, 50 (2.0%; 95% CI, 1.5%-2.6%) were eventually hospitalized and 12 (0.5%; 95% CI, 0.3%-0.8%) had severe outcomes. Compared with hospitalized SARS-CoV-2-negative youths, the risk of severe outcomes was higher among hospitalized SARS-CoV-2-positive youths (risk difference, 3.9%; 95% CI, 1.1%-6.9%). Conclusions and Relevance: In this study, approximately 3% of SARS-CoV-2-positive youths tested in EDs experienced severe outcomes within 2 weeks of their ED visit. Among children discharged home from the ED, the risk was much lower. Risk factors such as age, underlying chronic illness, and symptom duration may be useful to consider when making clinical care decisions.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020-March 2021) Using a Statistical Learning Strategy.

The emergence and establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest (VOIs) and variants of concern (VOCs) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from coronavirus disease 2019 (COVID-19) cases in the United States (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from 19 January 2020 to 15 March 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics and to identify VRVs with significant and substantial dynamics (false discovery rate q-value < 0.01; maximum VRV proportion >10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modeling was performed to gain insight into the potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which had not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identified 17 VRVs ~91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of four VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported a potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

Work-Home System Analysis and Musculoskeletal Discomfort of Workers in Covid-19 Pandemic Context

The study aimed to analyse work-home system factors and their connection with workers’ comfort, musculoskeletal discomfort (MSD) and perceived quality of work. Methods: A virtual survey was given to 196 administrative workers of a bank in Lima Peru. The survey consisted of four sections: consent form, sociodemographic data, risk factors of the work system and questions about comfort and MSD. Descriptive data was presented in percentages and associations were established with the chi-square statistic test. The significance level was 0.05. Results: The rate of musculoskeletal discomfort reached 96%, the most frequent body regions being the neck (91%), upper back (89%) and lower back region (89%). Regarding the work-home system, 49% of the study subjects worked in the bedroom and/or the living room, 32% had a desk, 18% used an adjustable chair, 37% worked at a dining table and 34% indicated that domestic activities overlapped with their work activities. The workers’ greatest perceived benefit was spending time with their families (59%). MSD was associated mainly with organisational factors (p <0.01). Comfort was associated with the backrest and type of seat, along with factors related to the environment and work tasks (p <0.05). Conclusion: Work-home systems are not prepared for performing office work. They raise MSD rates and reduce the quality of work, as perceived by workers. Spending time with family acted as a protective and negative factor. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Pediatric Emergency Research Network (PERN): A decade of global research cooperation in paediatric emergency care.

OBJECTIVES: The Pediatric Emergency Research Network (PERN) was launched in 2009 with the intent for existing national and regional research networks in paediatric emergency care to organise globally for the conduct of collaborative research across networks. METHODS: PERN has grown from five to eight member networks over the past decade. With an executive committee comprising representatives from all member networks, PERN plays a supportive and collaborative rather than governing role. The full impact of PERN's facilitation of international collaborative research, although somewhat difficult to quantify empirically, can be measured indirectly by the observed growth of the field, the nature of the increasingly challenging research questions now being addressed and the collective capacity to generate and implement new knowledge in treating acutely ill and injured children. RESULTS: Beginning as a pandemic response studying H1N1 influenza risk factors in children, PERN research has progressed to multiple observational studies and ongoing global randomised controlled trials (RCTs). As a recent example, PERN has developed sufficient network infrastructure to enable the rapid initiation of a prospective observational study in response to the current COVID-19 pandemic. CONCLUSIONS: Following its success with developing global research, the PERN goal now is to promote the implementation of scientific advances into everyday clinical practice by: (i) expanding the capacity for global RCTs; (ii) deepening the focus on implementation science; (iii) increasing attention to healthcare disparities; and (iv) expanding PERN's reach into resource-restricted regions. Through these actions, PERN aims to meet the needs of acutely ill and injured children throughout the world.

Prevalence and risk of severe asthma in adult patients with COVID-19

Rationale: As of December 7, 2020, there have been over 66 million confirmed cases of COVID-19 worldwide and over 1.5 million deaths attributed to the pandemic. Health outcomes of people with COVID-19 range from no symptoms to severe illness and death. Asthma is a highly prevalent chronic inflammatory disease of the airways that afflicts over 330 million people worldwide. Because SARS-CoV-2 is primarily a respiratory virus, people with asthma are apprehensive that they may be at increased risk of acquiring COVID-19 and suffer poorer outcomes. However, data addressing this hypothesis have been scarce until very recently. Methods: We reviewed the epidemiologic literature related to asthma's potential role in COVID-19 severity. Studies were identified through the PubMed and medRxiv databases, and by cross-referencing citations in identified studies, available in print or online before October 8, 2020. Asthma prevalence data were obtained from studies of people with confirmed COVID-19. Meta-analyses were conducted to produce weighted pooled prevalence ratios (PR) of asthma for hospitalized versus non-hospitalized participants, those with severe COVID-19 versus non-severe COVID-19, and those who died vs. survived. Results: Eleven studies provided data on the prevalence of asthma in people who were hospitalized with COVID-19 and those who were deemed well enough to be sent home with the disease (Table 1). The prevalence of asthma in these two groups was 8.5% (95% CI=6.4-10.9) and 8.2% (95% CI=6.8-9.8), respectively. The pooled PR for hospitalized individuals vs. those not hospitalized was 0.94 (0.78-1.12), p=0.49. Likewise, twenty-four studies provided data on asthma prevalence among patients hospitalized with COVID-19 according to disease severity (Table 1). The prevalence of asthma in patients with “severe” and “not severe” COVID-19 was 8.2% (95% CI=6.2-10.5) and 7.0% (95% CI=5.8-8.3), respectively. The pooled PR for asthma according to COVID-19 severity was 1.10 (95% CI=0.90-1.35, p=0.35). Twelve studies provided data from those who either died of COVID-19 or survived (Table 1). The prevalence of asthma in these two groups was 6.1% (95% CI=3.8-8.9) and 7.5% (95% CI=5.3-10.0), respectively. The pooled PR for asthma among patients who died from COVID-19 vs. those who survived was 0.76 (0.52-1.10, p=0.15). Conclusions: The results of our analyses do not provide clear evidence of increased risk of COVID-19 diagnosis, hospitalization or severity, due to asthma. These findings should provide some reassurance to people with asthma regarding the novel coronavirus and its potential to increase their risk of severe morbidity from COVID.

Mood Profiling for Sustainable Mental Health among Athletes

Mood responses are a well-established mental health indicator. Gauging mental health status over time often involves periodic mood assessment using a standardized measure, a process referred to as mood profiling. Comparison of observed mood scores against relevant normative data is central to effective mood profiling. The primary purpose of our study was to improve existing norms for the Brunel Mood Scale (BRUMS) using a large internet sample. The secondary purpose was to discuss how mood profiling can be used to promote sustainable mental health primarily among athletes but also with relevance to non-athletes. The BRUMS was completed via the In The Mood website by 15,692 participants. Significant differences between observed mean scores and existing normative data were evident for all six mood dimensions, prompting norm refinement. Specific group norms were generated to address sex differences in mood responses and differences by athlete/nonathlete status. The revised tables of normative data for the BRUMS should be used by researchers in future investigations of mood responses and by applied practitioners seeking to monitor mood responses as an indicator of mental health status. Applications of mood profiling with elite athletes are exemplified, along with recommendations for using mood profiling in the pursuit of sustainable mental health.

Prospective cohort study of children with suspected SARS-CoV-2 infection presenting to paediatric emergency departments: a Paediatric Emergency Research Networks (PERN) Study Protocol.

INTRODUCTION: Relatively limited data are available regarding paediatric COVID-19. Although most children appear to have mild or asymptomatic infections, infants and those with comorbidities are at increased risk of experiencing more severe illness and requiring hospitalisation due to COVID-19. The recent but uncommon association of SARS-CoV-2 infection with development of a multisystem inflammatory syndrome has heightened the importance of understanding paediatric SARS-CoV-2 infection. METHODS AND ANALYSIS: The Paediatric Emergency Research Network-COVID-19 cohort study is a rapid, global, prospective cohort study enrolling 12 500 children who are tested for acute SARS-CoV-2 infection. 47 emergency departments across 12 countries on four continents will participate. At enrolment, regardless of SARS-CoV-2 test results, all children will have the same information collected, including clinical, epidemiological, laboratory, imaging and outcome data. Interventions and outcome data will be collected for hospitalised children. For all children, follow-up at 14 and 90 days will collect information on further medical care received, and long-term sequelae, respectively. Statistical models will be designed to identify risk factors for infection and severe outcomes. ETHICS AND DISSEMINATION: Sites will seek ethical approval locally, and informed consent will be obtained. There is no direct risk or benefit of study participation. Weekly interim analysis will allow for real-time data sharing with regional, national, and international policy makers. Harmonisation and sharing of investigation materials with WHO, will contribute to synergising global efforts for the clinical characterisation of paediatric COVID-19. Our findings will enable the implementation of countermeasures to reduce viral transmission and severe COVID-19 outcomes in children. TRIAL REGISTRATION NUMBER: NCT04330261.

Human-animal interactions and bat coronavirus spillover potential among rural residents in Southern China

available from the publisher. FAU - Li, Hongying