Multisystem Inflammatory Syndrome in Children and SARS-CoV-2 variants: a two-year ambispective multicentric cohort study in Catalonia, Spain. (preprint)

Purpose Multisystem inflammatory syndrome in children (MIS-C) is a rare but severe disease temporarily related to SARS-CoV-2. We aimed to describe the epidemiological, clinical and laboratory findings of all the MIS-C cases diagnosed in children < 18 years-old in Catalonia (Spain) to study their trend throughout the pandemic.Methods Multicenter ambispective observational cohort study (April 2020-April 2022). Data were obtained from the COVID-19 Catalan surveillance system and from all the hospitals in Catalonia. We analyzed MIS-C cases regarding SARS-CoV-2 variants for demographics, symptoms, severity, monthly MIS-C incidence, ratio between MIS-C and accumulated COVID-19 cases, and associated rate ratios (RR).Results Among 555,848 SARS-CoV-2 infections, 152 children were diagnosed with MIS-C. Monthly MIS-C incidence was 4.1 (95%CI: 3.4–4.8) per 1,000,000 people, and 273 (95%CI: 230–316) per 1,000,000 SARS-CoV-2 infections (i.e., one case per 3,700 SARS-CoV-2 infections). During the Omicron period, MIS-C RR was 8.2 (95%CI: 5.7–11.7) per 1,000,000 SARS-CoV-2 infections, significantly lower (p < 0.001) than for previous variant periods, in all age groups. Median [IQR] age of MIS-C was 8 [4–11] years, 62.5% male, and 80.2% without comorbidities. Common symptoms were gastrointestinal findings (88.2%) and fever > 39oC (81.6%), nearly 40% had an abnormal echocardiography and 7% coronary aneurysm. Clinical manifestations and laboratory data were not different throughout the variant periods (p > 0.05).Conclusions The rate ratio between MIS-C cases and SARS-CoV-2 infections was significantly lower in the Omicron period for all the age groups, including those not vaccinated, suggesting that the variant could be the main factor for this shift in the MISC trend. Regardless of variant type, the patients had similar phenotypes and severity throughout the pandemic.

The Spectrum of COVID-19 in Children in Spain (preprint)

Background: We aimed to identify the spectrum of disease in children with COVID-19, and the risk factors for admission in paediatric intensive care units (PICUs). Methods: : We conducted a multicentre, prospective study of children with SARS-CoV-2 infection in 76 Spanish hospitals. We included children with COVID-19 or multi-inflammatory syndrome (MIS-C) younger than 18 years old, attended during the first year of the pandemic. Results: We enrolled 1 200 children. A total of 666 (55.5%) were hospitalized, and 123 (18.4%) required admission to PICU. Most frequent major clinical syndromes in the cohort were: mild syndrome (including upper respiratory tract infection and flu-like syndrome, skin or mucosae problems and asymptomatic), 44.8%; bronchopulmonary syndrome (including pneumonia, bronchitis and asthma flare), 18.5%; fever without a source, 16.2%; MIS-C, 10.6%; and gastrointestinal syndrome, 10%. In hospitalized children, the proportions were: 28.5%, 25.7%, 16.5%, 19.1% and 10.2%, respectively. Risk factors associated with PICU admission were MIS-C (odds ratio [OR]: 37.5,95% CI 22.7 to 57.8), moderate or severe liver disease (OR: 9,95% CI 1.6 to 47.6), chronic cardiac disease (OR: 4.8,95% CI 1.8 to 13) and asthma or recurrent wheezing (OR: 2.8,95% CI 1.3 to 5.8). However, asthmatic children were admitted into the PICU due to MIS-C or pneumonia, not due to asthma flare. Conclusion: Hospitalized children with COVID-19 usually present as one of five major clinical phenotypes of decreasing severity. Risk factors for PICU include MIS-C, elevation of inflammation biomarkers, asthma, moderate or severe liver disease and cardiac disease.

Comparison of Growth Patterns of COVID-19 Cases through the ARIMA and Gompertz Models. Case Studies: Austria, Switzerland, and Israel.

On May 19, 2020, data confirmed that coronavirus 2019 disease (COVID-19) had spread worldwide, with more than 4.7 million infected people and more than 316,000 deaths. In this article, we carry out a comparison of the methods to calculate and forecast the growth of the pandemic using two statistical models: the autoregressive integrated moving average (ARIMA) and the Gompertz function growth model. The countries that have been chosen to verify the usefulness of these models are Austria, Switzerland, and Israel, which have a similar number of habitants. The investigation to check the accuracy of the models was carried out using data on confirmed, non-asymptomatic cases and confirmed deaths from the period February 21-May 19, 2020. We use the root mean squared error (RMSE), the mean absolute percentage error (MAPE), and the regression coefficient index R2 to check the accuracy of the models. The experimental results provide promising adjustment errors for both models (R2>0.99), with the ARIMA model being the best for infections and the Gompertz best for mortality. It has also been verified that countries are affected differently, which may be due to external factors that are difficult to measure quantitatively. These models provide a fast and effective system to check the growth of pandemics that can be useful for health systems and politicians so that appropriate measures are taken and countries' health care systems do not collapse.