The resurgence risk of COVID-19 in China in the presence of immunity waning and ADE: A mathematical modelling study

Abstract

The mass vaccination program has been actively promoted since the end of 2020. However, waning immunity, antibody-dependent enhancement (ADE), and increased transmissibility of variants make the herd immunity untenable and the implementation of dynamic zero-COVID policy challenging in China. To explore how long the vaccination program can prevent China at low resurgence risk, and how these factors affect the long-term trajectory of the COVID-19 epidemics, we developed a dynamic transmission model of COVID-19 incorporating vaccination and waning immunity, calibrated using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and two doses reach 77.92% on 31 August 2021. However, despite the mass vaccination, randomly introducing infected cases in the post-vaccination period causes large outbreaks quickly with waning immunity, particularly for SARS-CoV-2 variants with higher transmissibility. The results showed that with the current vaccination program and 50% of the population wearing masks, mainland China can be protected at low resurgence risk until 8 January 2023. However, ADE and higher transmissibility for variants would significantly shorten the low-risk period by over 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequent outbreaks decrease, indicating that subsequent outbreaks boosted immunity in the population level, further indicating that follow-up vaccination programs can help mitigate or avoid the possible outbreaks. The findings revealed that the integrated effects of multiple factors: waning immunity, ADE, relaxed interventions, and higher variant transmissibility, make controlling COVID-19 challenging. We should prepare for a long struggle with COVID-19, and not entirely rely on the COVID-19 vaccine.

Keywords: Antibody-dependent enhancement; COVID-19; Immunity waning; Mathematical model; Resurgence risk; Vaccination.

Fig. 1

Schematic diagram illustrating the COVID-19 transmission incorporated with the vaccination program and immunity waning.

Fig. 2

Impact of ADE and normalized interventions on the number of newly confirmed cases and effective reproduction number during the transmission period when 10 infected cases are introduced on 1 September 2021.

Fig. 3

Schematic diagram illustrating (a) the different introduction times and the simulation period, (b) the critical introduction time $T_1$ and $T_2$ separating the low-risk, medium-risk, and high-risk periods.

Fig. 4

Impact of the ADE and different introduction time on the number of newly confirmed cases and the effective reproduction number by setting the introduction time as the initial transmission time. Introduction times are assumed to be 1 September 2021, 1 November 2021, and 1 January 2022, respectively.

Fig. 5

(a)-(b) Effect of $\beta ,\kappa$, and $\omega$ on $R_s$, respectively. (c)-(d) Values of $R(t,s)$ with different introduction time s (taking 1 September 2021 as the initial time) and transmission period t (taking the introduction time as initial time of the transmission process).

Fig. 6

Time required for the newly confirmed cases to increase to $I_0$ and $5I_0$, respectively, when introducing infected cases at different times for different $\beta$ and $\kappa$.

Fig. 7

Contour plots of $T_1$ and $T_2$ with respect to $\beta$ and $\kappa ,\beta$ and $\omega$, by taking 1 September 2021 as the initial time.