Spike-specific CXCR3+ TFH cells play a dominant functional role in supporting antibody responses in SARS-CoV-2 infection and vaccination (preprint)

CD4+ T follicular helper (TFH) cells are required for high-quality antibody generation and maintenance. However, the longevity and functional role of these cells are poorly defined in COVID-19 convalescents and vaccine recipients. Here, we longitudinally investigated the dynamics and functional roles of spike-specific circulating TFH cells and their subsets in convalescents at the 2nd, 5th, 8th, 12th and 24th months after COVID-19 symptom onset and in vaccinees after two and three doses of inactivated vaccine. SARS-CoV-2 infection elicited robust spike-specific TFH cell and antibody responses, of which spike-specific CXCR3+ TFH cells but not spike-specific CXCR3- TFH cells and neutralizing antibodies were persistent for at least two years in more than 80% of convalescents who experienced symptomatic COVID-19, which was well coordinated between spike-specific TFH cell and antibody responses at the 5th month after infection. Inactivated vaccine immunization also induced spike-specific TFH cell and antibody responses; however, these responses rapidly declined after six months with a two-dose standard administration, and a third dose significantly promoted antibody maturation and potency. Functionally, spike-specific CXCR3+ TFH cells exhibited better responsiveness than spike-specific CXCR3- TFH cells upon spike protein stimulation in vitro and showed superior capacity in supporting spike-specific antibody secreting cell (ASC) differentiation and antibody production than spike-specific CXCR3- TFH cells cocultured with autologous memory B cells. In conclusion, spike-specific CXCR3+ TFH cells played a dominant functional role in antibody elicitation and maintenance in SARS-CoV-2 infection and vaccination, suggesting that induction of CXCR3-biased spike-specific TFH cell differentiation will benefit SARS-CoV-2 vaccine development aiming to induce long-term protective immune memory.

A sampling scheme for estimating the prevalence of a pandemic (preprint)

The spread of COVID-19 makes it essential to investigate its prevalence. In such investigation research, as far as we know, the widely-used sampling methods didn't use the information sufficiently about the numbers of the previously diagnosed cases, which provides a priori information about the true numbers of infections. This motivates us to develop a new, two-stage sampling method in this paper, which utilises the information about the distributions of both population and diagnosed cases, to investigate the prevalence more efficiently. The global likelihood sampling, a robust and efficient sampler to draw samples from any probability density function, is used in our sampling strategy, and thus, our new method can automatically adapt to the complicated distributions of population and cases. Moreover, the corresponding estimating method is simple, which facilitates the practical implementation. Some recommendations for practical implementation are given. Finally, several simulations and a practical example verified its efficiency.