Removing negative impacts from inevitable non-reproducible and non-specific antibody-probe interactions in viral serology (preprint)

Serological assays are indispensable tools in public health. Presently deployed serological assays, however, largely overlook research progress made in the last two decades that jeopardize the conceptual foundation of these assays, i.e., antibody (Ab) specificity. Challenges to traditional understanding of Ab specificity include Ab poly-specificity, and most recently non-reproducible Ab-probe interactions (NRIs). Here, using SARS-CoV-2 and 4 common livestock viruses as a test bed, we developed a new serological platform that integrates recent understanding about Ab specificity. We first demonstrate that the response rate (RR) from a large sized serum pool (~100) is not affected by NRIs or by non-specific Ab-probe interactions (NSIs), so RR can be incorporated into the diagnostic probe selection process. We subsequently used multiple probes (configured as a “protein peptide hybrid microarray”, PPHM) to generate a digital microarray index (DMI), and finally demonstrate that DMI-based analysis yields an extremely robust probabilistic trend that enables accurate diagnosis of viral infection that overcomes multiple negative impacts exerted by NSI/NRI. Thus, our study with SARS-CoV-2 confirms that the PPHM-RR-DMI platform enables very rapid development of serological assays that outperform traditional assays (for both sensitivity and specificity) and supports that the platform is extendable to other viruses.

Previously unrecognized non-reproducible antibody-antigen interactions and their implications for diagnosis of viral infections including COVID-19 (preprint)

Antibody-antigen (Ab-Ag) interactions are canonically described by a model which exclusively accommodates non-interaction (0) or reproducible-interaction (RI) states, yet this model is inadequate to explain often-encountered non-reproducible signals. Here, by monitoring diverse experimental systems and confirmed COVID-19 clinical sera using a peptide microarray, we observed that non-specific interactions (NSI) comprise a substantial proportion of non-reproducible antibody-based results. This enabled our discovery and capacity to reliably identify non-reproducible Ab-Ag interactions (NRI), as well as our development of a powerful explanatory model ("0-RI-NRI-Hook four-state model") that is [mAb]-dependent, regardless of specificity, which ultimately shows that both NSI and NRI are not predictable yet certain-to-happen. In experiments using seven FDA-approved mAb drugs, we demonstrated the use of NSI counts in predicting epitope type. Beyond challenging the centrality of Ab-Ag interaction specificity data in serology and immunology, our discoveries also facilitated the rapid development of a serological test with uniquely informative COVID-19 diagnosis performance.

Modeling the Control of COVID-19: Impact of Policy Interventions and Meteorological Factors (preprint)

In this paper, we propose a dynamical model to describe the transmission of COVID-19, which is spreading in China and many other countries. To avoid a larger outbreak in the worldwide, Chinese government carried out a series of strong strategies to prevent the situation from deteriorating. Home quarantine is the most important one to prevent the spread of COVID-19. In order to estimate the effect of population quarantine, we divide the population into seven categories for simulation. Based on a Least-Squares procedure and officially published data, the estimation of parameters for the proposed model is given. Numerical simulations show that the proposed model can describe the transmission of COVID-19 accurately, the corresponding prediction of the trend of the disease is given. The home quarantine strategy plays an important role in controlling the disease spread and speeding up the decline of COVID-19. The control reproduction number of most provinces in China are analyzed and discussed adequately. We should pay attention to that, though the epidemic is in decline in China, the disease still has high risk of human-to-human transmission continuously. Once the control strategy is removed, COVID-19 may become a normal epidemic disease just like flu. Further control for the disease is still necessary, we focus on the relationship between the spread rate of the virus and the meteorological conditions. A comprehensive meteorological index is introduced to represent the impact of meteorological factors on both high and low migration groups. As the progress on the new vaccine, we design detail vaccination strategies for COVID-19 in different control phases and show the effectiveness of efficient vaccination. Once the vaccine comes into use, the numerical simulation provide a promptly prospective research.