Objective To study the dynamic changes of soluble intracellular adhesion molecule-1 (sICAM-1), and to assess its role in the pathogenesis of hemorrhagic fever(HFRS) with renal syndrome. Methods A total of 30 patients with HFRS(case group) and 20 healthy subjects (control group) from Worker Hospital of Finance & Commerce of Qiqihar city were included in the study during 2006 - 2007. Double-antibody sandwich ELISA method was used to measure the level of sICAM-1 in serum samples. Results The serum levels of sICAM-1 in patients with HFRS in early stage, critical stage, convalescent stage were(47.56±6.51), (94.23±15.36), (54.19±8.42)ng/L,respectively. The serum level of sICAM-1 in control group was (22.63±3.40)ng/L. The above values were compared between any two groups, differences were statistically significant (all P < 0.01). The serum level of urea nitrogen in patients with HFRS in early stage, critical stage, convalescent stage were (5.16±0.12), (33.84±9.24),(8.20±1.30)mmol/L, respectively. The serum level of urea nitrogen in control group was (4.20±0.56)mmol/L.The above value were compared between any two groups, the differences were statistically significant (all P< 0.01). Conclusions sICAM-1 is involved in the pathogenesis of HFRS as protective factors. Cellular immune playes an important role in the pathogenesis of HFRS.

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
COVID-19 ; Cohort Studies ; Contact Tracing ; Humans ; Incidence ; Prospective Studies