ACADSTAFF UGM
| Title | : | Two years antibody responses following SARS-CoV-2 infection in humans: a study protocol |
| Author | : |
Prof. dr. Eggi Arguni, M.Sc., Ph.D., Sp.A(K). (1) |
| Date | : | 0 2021 |
| Keyword | : | covid-19,SARS-CoV-2,kinetics of immune response antibody,risk factor covid-19,SARS-CoV-2,kinetics of immune response antibody,risk factor |
| Abstract | : | Background As a newly emerging virus, the longitudinal antibody response to the novel SARS-CoV- 2 in infected patients remains extensively unknown. As a newly emerging virus, the long term antibody response to the novel SARS-CoV-2 in infected patients and their residential neighbourhood remain extensively unknown. This information will provide insights into the virus antibody kinetics over a relatively long period of time as well as transmission risk factors in the community, which will eventually guide control policies. By understanding this will determine how long the anti-SARS-Cov-2 antibody may persist and wane. During an outbreak the risk factors of infection that potentially engender in the community may warrant us to guide control policies. We aim to prospectively observe the kinetics anti SARS-CoV-2 antibody for 2 years after infection in relation to disease severity and to determine the risk and protective factors of SARS CoV-2 infections. Methods and analysis A cohort of RT-PCR confirmed SARS-CoV-2 patients (case) will be prospectively followed for 2 years and will be compared to a control population. Control group comprises SARS-CoV-2 non-infected people who live in one kilometer radius from their matched case subject’s residence (location matching). This study will recruit at least 165 patients and 660 controls within the cases’ respective neighbourhood. Demographic, community variables, behavioural, as well as relevant clinical data will be collected. Serum samples that will be taken at various times will be tested for IgG/IgM anti SARS-Cov2 Spike 1 RBD antibody by ELISA. Kaplan-Meier method will be used to calculate cumulative seroconversion rates, and their association with disease severity will be estimated by logistic regression. The risk and protective factors associated with the SARS-CoV-2 infection will be determined using conditional (matched) logistic regression and presented as odds ratio (OR) and its 95% confidence interval. |
| Group of Knowledge | : | Ilmu Kedokteran Klinik |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Submitted
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