Serological follow-up study indicates high seasonal coronavirus infection and reinfection rates in early childhood
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PROVIDER: PRJEB52369 | ENA |
REPOSITORIES: ENA
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Project description:Seasonal human coronaviruses (HCoVs) cause respiratory infections, especially in children. Currently, the knowledge on early childhood seasonal coronavirus infections and the duration of antibody levels following the first infections is limited. Here we analyzed serological follow-up samples to estimate the rate of primary infection and reinfection(s) caused by seasonal coronaviruses in early childhood. Serum specimens were collected from 140 children at ages of 13, 24, and 36 months (1, 2, and 3 years), and IgG antibody levels against recombinant HCoV nucleoproteins (N) were measured by enzyme immunoassay (EIA). Altogether, 84% (118/140) of the children were seropositive for at least one seasonal coronavirus N by the age of 3 years. Cumulative seroprevalences for HCoVs 229E, HKU1, NL63, and OC43 increased by age, and they were 45%, 27%, 70%, and 44%, respectively, at the age of 3 years. Increased antibody levels between yearly samples indicated reinfections by 229E, NL63, and OC43 viruses in 20-48% of previously seropositive children by the age of 3 years. Antibody levels declined 54-73% or 31-77% during the year after seropositivity in children initially seropositive at 1 or 2 years of age, respectively, in case there was no reinfection. The correlation of 229E and NL63, and OC43 and HKU1 EIA results, suggested potential cross-reactivity between the N specific antibodies inside the coronavirus genera. The data shows that seasonal coronavirus infections and reinfections are common in early childhood and the antibody levels decline relatively rapidly. IMPORTANCE The rapid spread of COVID-19 requires better knowledge on the rate of coronavirus infections and coronavirus specific antibody responses in different population groups. In this work we analyzed changes in seasonal human coronavirus specific antibodies in young children participating in a prospective 3-year serological follow-up study. We show that based on seropositivity and changes in serum coronavirus antibody levels, coronavirus infections and reinfections are common in early childhood and the antibodies elicited by the infection decline relatively rapidly. These observations provide further information on the characteristics of humoral immune responses of coronavirus infections in children.
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Project description:In individuals highly exposed to hepatitis C virus (HCV), reinfection is common, suggesting that natural development of sterilising immunity is difficult. In those that are reinfected, some will develop a persistent infection, while a small proportion repeatedly clear the virus, suggesting natural protection is possible. The aim of this study was to characterise immune responses associated with rapid natural clearance of HCV reinfection. Broad neutralising antibodies (BnAbs) and Envelope 2 (E2)-specific memory B cell (MBCs) responses were examined longitudinally in 15 subjects with varied reinfection outcomes. BnAb responses were associated with MBC recall, but not with reinfection clearance. Strong evidence of antigen imprinting was found, and the B cell receptor repertoire showed a high level of clonality with ongoing somatic hypermutation of many clones over subsequent reinfection events. Single cell transcriptomic analyses showed that cleared reinfections featured an activated transcriptomic profile in HCV-specific B cells that rapidly expanded upon reinfection. MBC quality, but not necessarily breadth of nAb responses, is important for protection against antigenically diverse variants, which is encouraging for HCV vaccine development.
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Project description:Epidemiological models of COVID-19 transmission assume that recovered individuals have a fully protected immunity. To date, there is no definite answer about whether people who recover from COVID-19 can be reinfected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the absence of a clear answer about the risk of reinfection, it is instructive to consider the possible scenarios. To study the epidemiological dynamics with the possibility of reinfection, I use a Susceptible-Exposed-Infectious-Resistant-Susceptible model with the time-varying transmission rate. I consider three different ways of modeling reinfection. The crucial feature of this study is that I explore both the difference between the reinfection and no-reinfection scenarios and how the mitigation measures affect this difference. The principal results are the following. First, the dynamics of the reinfection and no-reinfection scenarios are indistinguishable before the infection peak. Second, the mitigation measures delay not only the infection peak, but also the moment when the difference between the reinfection and no-reinfection scenarios becomes prominent. These results are robust to various modeling assumptions.
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Project description:Epidemiological models of COVID-19 transmission assume that recovered individuals have a fully pro- tected immunity. To date, there is no definite answer about whether people who recover from COVID-19 can be reinfected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the absence of a clear answer about the risk of reinfection, it is instructive to consider the possible scenarios. To study the epidemiological dynamics with the possibility of reinfection, I use a Susceptible-Exposed-Infectious- Resistant-Susceptible model with the time-varying transmission rate. I consider three different ways of modeling reinfection. The crucial feature of this study is that I explore both the difference between the reinfection and no-reinfection scenarios and how the mitigation measures affect this difference. The principal results are the following. First, the dynamics of the reinfection and no-reinfection scenarios are in- distinguishable before the infection peak. Second, the mitigation measures delay not only the infection peak, but also the moment when the difference between the reinfection and no-reinfection scenarios becomes prominent. These results are robust to various modeling assumptions.
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