Dynamic analysis and evaluation of asymptomatic infection in the spread of COVID-19 (preprint)

COVID-19 has spread worldwide for nearly two years. Many countries have experienced repeated epidemics, that is, after the epidemic has been controlled for a period of time, the number of new cases per day is low, and the outbreak will occur again a few months later. In order to study the relationship between this low level of infection and the number of asymptomatic infections, and to evaluate the role of asymptomatic infections in the development of the epidemic, we have established an improved infectious disease dynamics model that can be used to evaluate the spread of the COVID-19 epidemic, and fitted the epidemic data in the three flat periods in England. According to the obtained parameters, according to the calculation of the model, the proportion of asymptomatic infections in these three flat periods are 41%, 53% and 58% respectively. After the first flat period, the number of daily newly confirmed cases predicted by the model began to increase around July 1, 2020. After more than four months of epidemic spread, it reached a peak on November 12, which is consistent with the actual case situation. Unanimous. After the second flat period, the model predicts that the number of new confirmed cases per day will increase from about May 7, 2021, and after about 73 days of epidemic development, it will reach a peak on July 20, showing the overall trend of the epidemic. In the above, the predicted results of the model are consistent with the actual cases. After the third flat period, the number of daily newly diagnosed cases predicted by the model began to increase around December 1, 2021, and reached a peak in December, and the number of cases will drop to a very low level after May 2022. According to our research results, due to the large number of asymptomatic infections, the spread of the epidemic is not easy to stop completely in a short time. However, when the epidemic enters a period of flat time, nucleic acid testing is performed, and asymptomatic infections are isolated at home for 14 days (the recovery period of symptomatic infection is about 10 days) may be an option that can be considered to interrupt the transmission of the case.

A kinetic model considering the decline of antibody level and vaccination of COVID-19 (preprint)

In order to evaluate the decline in antibody levels and the impact of vaccination on the spread of the epidemic, we establish COVID-19 dynamic models that consider the decline in antibody levels and the effects of vaccination, and retrospectively evaluate the epidemic situation in England. Based on the epidemic data in England from September 1 to October 31, 2020, considering the continuous decline in the antibody level of COVID-19 recovers, an improved SEIR infectious disease dynamics model that considers the reinfection of recovers due to the decline in antibody levels is established. The kinetic parameters of the SEIR model are obtained by fitting. On this basis, a SEIRV infectious disease dynamic model with vaccination is established to study the impact of different vaccination rates and vaccine failure rates on the development of the epidemic in England. We obtain the lower the vaccine failure rate, the fewer new cases. When the vaccination rate is fixed at 0.005 (equivalent to 250000 people vaccinated every day), the peak of the epidemic will decrease with the decrease of vaccine failure rate. The peak value when the failure rate is 0.001 is 81.4% lower than the peak value when the failure rate is 0.01, and the peak value when the failure rate is 0.01 is 89.5% lower than the peak value when the failure rate is 0.02. When the failure rate is less than 0.01, the peak time will advance with the decrease of failure rate; when the failure rate is greater than 0.01, the peak time will be delayed with the decrease of failure rate; when the failure rate is 0.01, the peak time is 528 days later than that when the failure rate is 0.001 and 295 days later than that when the failure rate is 0.05. On the 60th day of vaccination, the vaccine failure rate of 0.002 decreases the number of cases by 5.8% compared with the vaccine failure rate of 0.01; on the 70th day of vaccination, the vaccine failure rate of 0.002 reduces the number of cases by 9.1% compared with the vaccine failure rate of 0.01. Therefore, with the extension of time, the vaccine with low failure rate has a more obvious effect on reducing the number of cases than the vaccine with high failure rate. When the vaccine failure rate is fixed at 0.005, we study the impact of different vaccination rates on the spread of the epidemic in England, the result shows that the peak of epidemic situation decreases with the increase of vaccination rate, and the peak time advance with the increase of vaccination rate, when the vaccination rate is 0.025, the peak decreases by 74.8% and the peak time was 114 days earlier than that when the vaccination rate is 0.005.Therefore, the higher the vaccine efficiency and vaccination rate, the lower the peak of the epidemic. On the basis of improving the effectiveness of vaccines, increasing the vaccination rate is of practical significance for controlling the spread of the epidemic.

An autocrine Vitamin D-driven Th1 shutdown program can be exploited for COVID-19 (preprint)

Pro-inflammatory immune responses are necessary for effective pathogen clearance, but cause severe tissue damage if not shut down in a timely manner1,2. Excessive complement and IFN-{gamma}-associated responses are known drivers of immunopathogenesis3 and are among the most highly induced immune programs in hyper-inflammatory SARS-CoV2 lung infection4. The molecular mechanisms that govern orderly shutdown and retraction of these responses remain poorly understood. Here, we show that complement triggers contraction of IFN-{gamma} producing CD4+ T helper (Th) 1 cell responses by inducing expression of the vitamin D (VitD) receptor (VDR) and CYP27B1, the enzyme that activates VitD, permitting T cells to both activate and respond to VitD. VitD then initiates the transition from pro-inflammatory IFN-{gamma}+ Th1 cells to suppressive IL-10+ Th1 cells. This process is primed by dynamic changes in the epigenetic landscape of CD4+ T cells, generating superenhancers and recruiting c-JUN and BACH2, a key immunoregulatory transcription factor5-7. Accordingly, cells in psoriatic skin treated with VitD increased BACH2 expression, and BACH2 haplo-insufficient CD4+ T cells were defective in IL-10 production. As proof-of-concept, we show that CD4+ T cells in the bronchoalveolar lavage fluid (BALF) of patients with COVID-19 are Th1-skewed and that VDR is among the top regulators of genes induced by SARS-CoV2. Importantly, genes normally down-regulated by VitD were de-repressed in CD4+ BALF T cells of COVID-19, indicating that the VitD-driven shutdown program is impaired in this setting. The active metabolite of VitD, alfacalcidol, and cortico-steroids were among the top predicted pharmaceuticals that could normalize SARS-CoV2 induced genes. These data indicate that adjunct therapy with VitD in the context of other immunomodulatory drugs may be a beneficial strategy to dampen hyperinflammation in severe COVID-19.