ABSTRACT
Background: In 2020, Brazil became the epicentre of the coronavirus disease (COVID-19) pandemic in Latin America, resulting in an unparalleled health catastrophe. Nevertheless, comprehensive clinical reports in Brazilian children are not available. Methods: This retrospective, hospital-based, active surveillance study was performed to identify paediatric patients with COVID-19 who presented at a private academic medical centre in a large urban area between March 2020 and March 2021. Clinical and demographic information was analysed for those requiring hospitalization, those with severe illness and those with clinical syndromes. Results: In total, 964 symptomatic cases were evaluated; of these, 17.7% required hospitalization, and 27.5% of hospitalized cases were classified as severe/critical. Acute bronchiolitis and pneumonia were the most common causes of hospitalization among the severe cases. Twenty-seven hospitalized children fulfilled the diagnostic criteria for multi-system inflammatory syndrome (median age 29 months; 85.2% cases were non-severe). A significant co-existing condition was present in 29% of hospitalized children. The risk of hospitalization was higher in children with at least one comorbidity, children aged <2 years and obese children. Increased risk of severe disease was described among those with leukopenia, leukocytosis or any significant comorbidity. No deaths occurred among the study population. Conclusion: Although most children with COVID-19 experienced mild disease, and no deaths occurred among the study population, a significant proportion of cases required hospitalization and developed severe illness. Obesity, young age, underlying comorbidity, leukopenia and leukocytosis were risk factors for hospitalization or severe disease.
ABSTRACT
The SARS-CoV-2 pandemic is a major concern all over the world and, as vaccines became available at the end of 2020, optimal vaccination strategies were subjected to intense investigation. Considering their critical role in reducing disease burden, the increasing demand outpacing production, and that most currently approved vaccines follow a two-dose regimen, the cost-effectiveness of delaying the second dose to increment the coverage of the population receiving the first dose is often debated. Finding the best solution is complex due to the trade-off between vaccinating more people with lower level of protection and guaranteeing higher protection to a fewer number of individuals. Here we present a novel extended age-structured SEIR mathematical model that includes a two-dose vaccination schedule with a between-doses delay modelled through delay differential equations and linear optimization of vaccination rates. By maintaining the minimum stock of vaccines under a given production rate, we evaluate the dose interval that minimizes the number of deaths. We found that the best strategy depends on an interplay between the vaccine production rate and the relative efficacy of the first dose. In the scenario of low first-dose efficacy, it is always better to vaccinate the second dose as soon as possible, while for high first-dose efficacy, the best strategy of time window depends on the production rate and also on second-dose efficacy provided by each type of vaccine. We also found that the rate of spread of the infection does not affect significantly the thresholds of the best window, but is an important factor in the absolute number of total deaths. These conclusions point to the need to carefully take into account both vaccine characteristics and roll-out speed to optimize the outcome of vaccination strategies.