ABSTRACT
Background Early diagnostic indicators and the identification of possible progression to severe or critical COVID-19 in children are unknown. To investigate the immune characteristics of early SARS-CoV-2 infection in children and possible key prognostic factors for early identification of critical COVID-19, a retrospective study including 121 children with COVID-19 was conducted. Peripheral blood lymphocyte subset counts, T cell-derived cytokine concentrations, inflammatory factor concentrations, and routine blood counts were analyzed statistically at the initial presentation. Results The T lymphocyte subset and natural killer cell counts decreased with increasing disease severity. Group III (critical cases) had a higher Th/Tc ratio than groups I and II (common and severe cases); group I had a higher B cell count than groups II and III. IL-6, IL-10, IFN-γ, SAA, and procalcitonin levels increased with disease severity. Hemoglobin concentration, and RBC and eosinophil counts decreased with disease severity. Groups II and III had significantly lower lymphocyte counts than group I. T, Th, Tc, IL-6, IL-10, RBC, and hemoglobin had relatively high contribution and area under the curve values. Conclusions Decreased T, Th, Tc, RBC, hemoglobin and increased IL-6 and IL-10 in early SARS-CoV-2 infection in children are valuable indices for early diagnosis of disease severity. The significantly reduced Th and Tc cells and significantly increased IL-6, IL-10, ferritin, procalcitonin, and SAA at this stage in children with critical COVID-19 may be closely associated with the systemic cytokine storm caused by immune dysregulation.
Subject(s)
COVID-19 , Reflex, AbnormalABSTRACT
Chinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. There have been reports external icon of spread from an infected patient with no symptoms to a close contact, which means the incubation individuals may has the possibility of infectiousness. However, the traditional transmission model, Susceptible-Exposed-Infectious-Recovered (SEIR) model, assumes that the exposed individual is being infected but without infectiousness. Thus, the estimating infected populations based on SEIR model from the existing literatures seems too far more than the official reported data. Here, we inferred that the epidemic could be spread by exposed (incubation) individuals. Then, we provide a new Exposed-identified-Recovered (EIR) model, and simulated the epidemic spreading processes from free propagation phase to extremely control phase. Then, we estimate of the size of the epidemic and forecast the future development of the epidemics under strong prevention interventions. According to the spread characters of 2019-nCov, we construct a novel EIR compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported official data, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the spreading trend of 2019-nCov under different prevention policy scenarios are estimated. The epidemic spreading trends under different quarantine rate and action starting date of prevention policy are simulated and compared.