Developing a Video Game as an Awareness and Research Tool Based on SARS-CoV-2 Epidemiological Dynamics and Motivational Perspectives

In mid-2020, the University of Liège (ULiège, Belgium) commissioned the ULiège Video Game Research Laboratory (Liège Game Lab) and the AR/VR Lab of the HEC-Management School of ULiège to create a serious game to raise awareness of preventive measures for its university community. This project has its origins in two objectives of the institutional policy of ULiège in response to the crisis caused by SARS-CoV-2 to raise awareness among community members of various preventive actions that can reduce the spread of the virus and to inform about the emergence and progression of a pandemic. After almost two years of design, the project resulted in the creation of SARS Wars, a decision-making management game for browsers and smartphones. This article presents the creative process of the game, specifically the integration of an adapted SEIR (susceptible-exposed-infectious-recovered) model, as well as the modeling of intercompartmental circulation dynamics in the game's algorithm, and the various limitations observed regarding the game's original missions and possibilities for future work. The SARS-CoV-2 video game project may be considered an innovative way to translate epidemiology into a language that can be used in the scope of citizen sciences. On the one hand, it provides an engaging tool and encourages active participation of the audience. On the other hand, it allows us to have a better understanding of the dynamic changes of a pandemic or an epidemic (crisis preparedness, monitoring, and control) and to anticipate potential consequences in the given parameters at set time (emerging risk identification), while offering insights for impact on some parameters on motivation (social science aspect).

Impact of COVID-19 Vaccination on Short-Term Perceived Change in Physical Performance among Elite Athletes: An International Survey.

COVID-19 vaccination raised concerns about its potential effects on physical performance. To assess the impact of COVID-19 vaccination on the perceived change in physical performance, we conducted an online survey among elite athletes from Belgium, Canada, France and Luxembourg, with questions about socio-demographics, COVID-19 vaccination, perceived impact on physical performance and perceived pressure to get vaccinated. Full vaccination was defined as two doses of mRNA or vector vaccine or a heterologous vaccine scheme. Among 1106 eligible athletes contacted, 306 athletes answered the survey and were included in this study. Of these, 72% perceived no change in their physical performance, 4% an improvement and 24% a negative impact following full COVID-19 vaccination. For 82% of the included athletes, the duration of the negative vaccine reactions was ≤3 days. After adjustment for potential confounding variables, practicing an individual sport, a duration of vaccine reactions longer than 3 days, a high level of vaccine reaction and the perceived pressure to get vaccinated were independently associated with a perceived negative impact on physical performance of more than 3 days after the vaccination. The perceived pressure to get vaccinated appears to be a parameter associated with the negative perceived change in the physical performance and deserves further consideration.

Systematic Review of the Key Factors Influencing the Indoor Airborne Spread of SARS-CoV-2.

The COVID-19 pandemic due to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been plaguing the world since late 2019/early 2020 and has changed the way we function as a society, halting both economic and social activities worldwide. Classrooms, offices, restaurants, public transport, and other enclosed spaces that typically gather large groups of people indoors, and are considered focal points for the spread of the virus. For society to be able to go "back to normal", it is crucial to keep these places open and functioning. An understanding of the transmission modes occurring in these contexts is essential to set up effective infection control strategies. This understanding was made using a systematic review, according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA) 2020 guidelines. We analyze the different parameters influencing airborne transmission indoors, the mathematical models proposed to understand it, and discuss how we can act on these parameters. Methods to judge infection risks through the analysis of the indoor air quality are described. Various mitigation measures are listed, and their efficiency, feasibility, and acceptability are ranked by a panel of experts in the field. Thus, effective ventilation procedures controlled by CO2-monitoring, continued mask wearing, and a strategic control of room occupancy, among other measures, are put forth to enable a safe return to these essential places.

Incidence of long COVID-19 in people with previous SARS-Cov2 infection: a systematic review and meta-analysis of 120,970 patients

The long-term consequences of the coronavirus disease 19 (COVID-19) are likely to be frequent but results hitherto are inconclusive. Therefore, we aimed to define the incidence of long-term COVID signs and symptoms as defined by the World Health Organization, using a systematic review and meta-analysis of observational studies. A systematic search in several databases was carried out up to 12 January 2022 for observational studies reporting the cumulative incidence of long COVID signs and symptoms divided according to body systems affected. Data are reported as incidence and 95% confidence intervals (CIs). Several sensitivity and meta-regression analyses were performed. Among 11,162 papers initially screened, 196 were included, consisting of 120,970 participants (mean age: 52.3 years;48.8% females) who were followed-up for a median of six months. The incidence of any long COVID symptomatology was 56.9% (95% CI 52.2–61.6). General long COVID signs and symptoms were the most frequent (incidence of 31%) and digestive issues the least frequent (7.7%). The presence of any neurological, general and cardiovascular long COVID symptomatology was most frequent in females. Higher mean age was associated with higher incidence of psychiatric, respiratory, general, digestive and skin conditions. The incidence of long COVID symptomatology was different according to continent and follow-up length. Long COVID is a common condition in patients who have been infected with SARS-CoV-2, regardless of the severity of the acute illness, indicating the need for more cohort studies on this topic.

Incidence of long COVID-19 in people with previous SARS-Cov2 infection: a systematic review and meta-analysis of 120,970 patients.

The long-term consequences of the coronavirus disease 19 (COVID-19) are likely to be frequent but results hitherto are inconclusive. Therefore, we aimed to define the incidence of long-term COVID signs and symptoms as defined by the World Health Organization, using a systematic review and meta-analysis of observational studies. A systematic search in several databases was carried out up to 12 January 2022 for observational studies reporting the cumulative incidence of long COVID signs and symptoms divided according to body systems affected. Data are reported as incidence and 95% confidence intervals (CIs). Several sensitivity and meta-regression analyses were performed. Among 11,162 papers initially screened, 196 were included, consisting of 120,970 participants (mean age: 52.3 years; 48.8% females) who were followed-up for a median of six months. The incidence of any long COVID symptomatology was 56.9% (95% CI 52.2-61.6). General long COVID signs and symptoms were the most frequent (incidence of 31%) and digestive issues the least frequent (7.7%). The presence of any neurological, general and cardiovascular long COVID symptomatology was most frequent in females. Higher mean age was associated with higher incidence of psychiatric, respiratory, general, digestive and skin conditions. The incidence of long COVID symptomatology was different according to continent and follow-up length. Long COVID is a common condition in patients who have been infected with SARS-CoV-2, regardless of the severity of the acute illness, indicating the need for more cohort studies on this topic.

Interventions for Improving Long COVID-19 Symptomatology: A Systematic Review.

INTRODUCTION: Although the understanding of several aspects of long COVID-19 syndrome is increasing, there is limited literature regarding the treatment of these signs and symptoms. The aim of our systematic review was to understand which therapies have proved effective against the symptoms of long COVID-19. METHODS: A systematic search for randomized controlled or clinical trials in several databases was conducted through 15 May 2022. Specific inclusion criteria included: (1) intervention studies, either randomized controlled (RCTs) or clinical trials; (2) diagnosis of long COVID-19, according to the World Health Organization criteria; (3) presence of long COVID-19 for at least 12 weeks after SARS-CoV-2 infection. RESULTS: We initially found 1638 articles to screen. After removing 1602 works based on their title/abstract, we considered 35 full texts, and among them, two intervention studies were finally included. The first RCT focused on the greater improvement of treatment combining olfactory rehabilitation with oral supplementation with Palmitoylethanolamide and Luteolin in patients with olfactory dysfunction after COVID-19. The second study evaluated the positive impact of aromatherapy vs. standard care in adult females affected by fatigue. CONCLUSION: Our systematic review found only two intervention studies focused on patients affected by long COVID-19. More intervention studies are needed to investigate potentially positive interventions for long COVID-19 symptoms.

Influenza Vaccination and COVID-19 Outcomes in People Older than 50 Years: Data from the Observational Longitudinal SHARE Study.

Existing literature on the association between influenza vaccination and COVID-19 infection/outcomes is conflicting. Therefore, we aimed to investigate the association between influenza vaccination and COVID-19 outcomes in a large cohort of adults who participated in the SHARE (Survey of Health, Ageing, and Retirement in Europe). Information regarding influenza vaccination in the previous year, and medical and demographic characteristics, were self-reported. Positivity for COVID-19, symptomatology, and hospitalization were also ascertained using self-reported information. An adjusted logistic regression analysis (including 15 baseline factors or propensity score) was used to assess the association between influenza vaccination and COVID-19 outcomes. A total of 48,408 participants (mean age 67 years; 54.1% females) were included. The prevalence of influenza vaccination was 38.3%. After adjusting for 15 potential confounders, influenza vaccination was significantly associated with a lower risk of positivity for COVID-19 (OR = 0.95; p < 0.0001), symptomatic forms (OR = 0.87; p < 0.0001), and hospitalization for COVID-19 (OR = 0.95; p < 0.0001). The results were similar when using a propensity score approach. In conclusion, influenza vaccination may be beneficial for the prevention of COVID-19, as the present study found that influenza vaccination was associated with a small/moderate lower risk of COVID-19 infection and adverse outcomes.

Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study.

BACKGROUND: Since the beginning of the pandemic, hospitals have been constantly overcrowded, with several observed waves of infected cases and hospitalisations. To avoid as much as possible this situation, efficient tools to facilitate the diagnosis of COVID-19 are needed. OBJECTIVE: To evaluate and compare prediction models to diagnose COVID-19 identified in a systematic review published recently using performance indicators such as discrimination and calibration measures. METHODS: A total of 1618 adult patients present at two Emergency Department triage centers and for whom qRT-PCR tests had been performed were included in this study. Six previously published models were reconstructed and assessed using diagnostic tests as sensitivity (Se) and negative predictive value (NPV), discrimination (Area Under the Roc Curve (AUROC)) and calibration measures. Agreement was also measured between them using Kappa's coefficient and IntraClass Correlation Coefficient (ICC). A sensitivity analysis has been conducted by waves of patients. RESULTS: Among the 6 selected models, those based only on symptoms and/or risk exposure were found to be less efficient than those based on biological parameters and/or radiological examination with smallest AUROC values (< 0.80). However, all models showed good calibration and values above > 0.75 for Se and NPV but poor agreement (Kappa and ICC < 0.5) between them. The results of the first wave were similar to those of the second wave. CONCLUSION: Although quite acceptable and similar results were found between all models, the importance of radiological examination was also emphasized, making it difficult to find an appropriate triage system to classify patients at risk for COVID-19.

Decision-based interactive model to determine re-opening conditions of a large university campus in Belgium during the first COVID-19 wave.

BACKGROUND: The role played by large-scale repetitive SARS-CoV-2 screening programs within university populations interacting continuously with an urban environment, is unknown. Our objective was to develop a model capable of predicting the dispersion of viral contamination among university populations dividing their time between social and academic environments. METHODS: Data was collected through real, large-scale testing developed at the University of Liège, Belgium, during the period Sept. 28th-Oct. 29th 2020. The screening, offered to students and staff (n = 30,000), began 2 weeks after the re-opening of the campus but had to be halted after 5 weeks due to an imposed general lockdown. The data was then used to feed a two-population model (University + surrounding environment) implementing a generalized susceptible-exposed-infected-removed compartmental modeling framework. RESULTS: The considered two-population model was sufficiently versatile to capture the known dynamics of the pandemic. The reproduction number was estimated to be significantly larger on campus than in the urban population, with a net difference of 0.5 in the most severe conditions. The low adhesion rate for screening (22.6% on average) and the large reproduction number meant the pandemic could not be contained. However, the weekly screening could have prevented 1393 cases (i.e. 4.6% of the university population; 95% CI: 4.4-4.8%) compared to a modeled situation without testing. CONCLUSION: In a real life setting in a University campus, periodic screening could contribute to limiting the SARS-CoV-2 pandemic cycle but is highly dependent on its environment.

Frailty but not sarcopenia nor malnutrition increases the risk of developing COVID-19 in older community-dwelling adults.

BACKGROUND: The identification of coronavirus disease 2019 (COVID-19) risk factors is requested to implement prevention strategies. AIM: To explore the associations between the COVID-19 incidence and malnutrition, sarcopenia, and frailty, identified as potential risk factors in previous cross-sectional studies. METHODS: Malnutrition, sarcopenia, and frailty were assessed at the last available follow-up from the Sarcopenia and Physical Impairments with Advancing Age (SarcoPhAge) cohort (i.e., the fifth year that ended in 2019) according to the Mini-Nutritional Assessment short-form, the European Working Group on Sarcopenia in Older People (EWGSOP2), and the Fried criteria, respectively. Information regarding the COVID-19 was gathered by phone calls interviews in April 2021 to measure its self-declared incidence. Adjusted Cox regressions and Kaplan-Meier curves were performed. RESULTS: The present study included 241 participants [median age 75.6 (73.0-80.6) years, 63.1% women]. Among them, 27 participants (11.2%) developed the non-fatal Covid-19. No significant increased risks of COVID-19 were observed in patients with malnutrition [adjusted HR 1.14 (0.26-5.07)] and sarcopenia [adjusted HR 1.25 (0.35-4.42)]. Nevertheless, the incidence of COVID-19 was significantly higher in frail (44.4%) than in robust participants (8.5%) [Adjusted HR 7.01 (2.69-18.25)], which was confirmed by the Kaplan-Meier curves (p < 0.001). Among the frailty syndrome components, a low physical activity level was the only one significantly associated with an increased risk of COVID-19 [adjusted HR 5.18 (1.37-19.54)]. CONCLUSION: Despite some limitations in the methodology of this study (i.e., limited sample size, COVID-19 incidence self-reported and not assessed systematically using objective measurements) requiring careful  consideration, an increased risk to develop COVID-19 was observed in the presence of the frailty syndrome. Further investigations are needed to elaborate on our findings.

Transmission of SARS-CoV-2 After COVID-19 Screening and Mitigation Measures for Primary School Children Attending School in Liège, Belgium.

Importance: Recent data suggest a relatively low incidence of COVID-19 among children. The possible role that children attending primary school may play in the transmission of SARS-CoV-2 remains poorly understood. Objective: To gain a better understanding of the possible role of children in the transmission of SARS-CoV-2. Design, Setting, and Participants: This prospective cohort study was conducted from September 21 to December 31, 2020, in a primary school in Liège, Belgium, among a volunteer sample of 181 children, parents, and school employees. Exposures: Participants were tested for SARS-CoV-2 infection once a week for 15 weeks through throat washing, performed with 5 mL of saline and collected in a sterile tube after approximately 30 seconds of gargling. Quantitative reverse transcription-polymerase chain reaction was performed to detect SARS-CoV-2 infection. Main Outcomes and Measures: In case of test positivity, participants were asked to complete a questionnaire aimed at determining the timing of symptom onset and symptom duration. SARS-CoV-2 genetic sequencing was also performed. Confirmed cases were linked based on available information on known contacts and viral sequences. Results: A total of 181 individuals participated in this study, including 63 children (34 girls [54.0%]; mean [SD] age, 8.6 [1.9] years [range, 5-13 years]) and 118 adults (75 women [63.6%]; mean [SD] age, 42.5 [5.7] years [range, 30-59 years]). Forty-five individuals (24.9%) tested positive: 13 children (20.6%; 95% CI, 10.6%-30.6%) and 32 adults (27.1%; 95% CI, 19.1%-35.7%) (P = .34). Children were more often asymptomatic compared with adults (6 [46.2%; 95% CI, 19.1%-73.3%] vs 4 of 31 [12.9%; 95% CI, 1.3%-24.5%]; P = .04). The median duration of symptoms was shorter in children than in adults (0.00 days [IQR, 0.00-1.00 days] vs 15.00 days [IQR, 7.00-22.00 days]). A reconstruction of the outbreak revealed that most transmission events occurred between teachers and between children within the school. Of the observed household transmission events, most seemed to have originated from a child or teacher who acquired the infection at school. Conclusions and Relevance: Despite the implementation of several mitigation measures, the incidence of COVID-19 among children attending primary school in this study was comparable to that observed among teachers and parents. Transmission tree reconstruction suggests that most transmission events originated from within the school. Additional measures should be considered to reduce the transmission of SARS-CoV-2 at school, including intensified testing.

A systematic review of prediction models to diagnose COVID-19 in adults admitted to healthcare centers.

BACKGROUND: The COVID-19 pandemic is putting significant pressure on the hospital system. To help clinicians in the rapid triage of patients at high risk of COVID-19 while waiting for RT-PCR results, different diagnostic prediction models have been developed. Our objective is to identify, compare, and evaluate performances of prediction models for the diagnosis of COVID-19 in adult patients in a health care setting. METHODS: A search for relevant references has been conducted on the MEDLINE and Scopus databases. Rigorous eligibility criteria have been established (e.g., adult participants, suspicion of COVID-19, medical setting) and applied by two independent investigators to identify suitable studies at 2 different stages: (1) titles and abstracts screening and (2) full-texts screening. Risk of bias (RoB) has been assessed using the Prediction model study Risk of Bias Assessment Tool (PROBAST). Data synthesis has been presented according to a narrative report of findings. RESULTS: Out of the 2334 references identified by the literature search, 13 articles have been included in our systematic review. The studies, carried out all over the world, were performed in 2020. The included articles proposed a model developed using different methods, namely, logistic regression, score, machine learning, XGBoost. All the included models performed well to discriminate adults at high risks of presenting COVID-19 (all area under the ROC curve (AUROC) > 0.500). The best AUROC was observed for the model of Kurstjens et al (AUROC = 0.940 (0.910-0.960), which was also the model that achieved the highest sensitivity (98%). RoB was evaluated as low in general. CONCLUSION: Thirteen models have been developed since the start of the pandemic in order to diagnose COVID-19 in suspected patients from health care centers. All these models are effective, to varying degrees, in identifying whether patients were at high risk of having COVID-19.