Modeling and Research on an Immuno-Epidemiological Coupled System with Coinfection

Mathematical methods for scaling from within-host to population-scale in infectious disease systems

Mathematical modellers model infectious disease dynamics at different scales. Within-host models represent the spread of pathogens inside an individual, whilst between-host models track transmission between individuals. However, pathogen dynamics at one scale affect those at another. This has led to the development of multiscale models that connect within-host and between-host dynamics. In this article, we systematically review the literature on multiscale infectious disease modelling according to PRISMA guidelines, dividing previously published models into five categories governing their methodological approaches (Garira (2017)), explaining their benefits and limitations. We provide a primer on developing multiscale models of infectious diseases.

A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.

Modeling Syphilis and HIV Coinfection: A Case Study in the USA

Syphilis and HIV infections form a dangerous combination. In this paper, we propose an epidemic model of HIV-syphilis coinfection. The model always has a unique disease-free equilibrium, which is stable when both reproduction numbers of syphilis and HIV are less than 1. If the reproduction number of syphilis (HIV) is greater than 1, there exists a unique boundary equilibrium of syphilis (HIV), which is locally stable if the invasion number of HIV (syphilis) is less than 1. Coexistence equilibrium exists and is stable when all reproduction numbers and invasion numbers are greater than 1. Using data of syphilis cases and HIV cases from the US, we estimated that both reproduction numbers for syphilis and HIV are slightly greater than 1, and the boundary equilibrium of syphilis is stable. In addition, we observed competition between the two diseases. Treatment for primary syphilis is more important in mitigating the transmission of syphilis. However, it might lead to increase of HIV cases. The results derived here could be adapted to other multi-disease scenarios in other regions.

Effects of co-infection on vaccination behavior and disease propagation

Coinfection is the process of an infection of a single host with two or more pathogen variants or with two or more distinct pathogen species, which often threatens public health and the stability of economies. In this paper, we propose a novel two-strain epidemic model characterizing the co-evolution of coinfection and voluntary vaccination strategies. In the framework of evolutionary vaccination, we design two game rules, the individual-based risk assessment (IB-RA) updated rule, and the strategy-based risk assessment (SB-RA) updated rule, to update the vaccination policy. Through detailed numerical analysis, we find that increasing the vaccine effectiveness and decreasing the transmission rate effectively suppress the disease prevalence, and moreover, the outcome of the SB-RA updated rule is more encouraging than those results of the IB-RA rule for curbing the disease transmission. Coinfection complicates the effects of the transmission rate of each strain on the final epidemic sizes.

Serological reactivity of inactivated SARS-CoV-2 vaccine based on an S-RBD neutralizing antibody assay

Objectives

This study aimed to explore the regularity of S-RBD domain antibody reactivity after immunization with inactivated SARS-CoV-2 vaccine and evaluate the effect of this vaccine on the immune response.

Design or methods

Venous blood samples were collected from 1156 healthcare workers who participated in the phase III clinical trial of the SARS-CoV-2 inactivated vaccine. The S-RBD domain antibody levels in the serum were detected by ELISA 14 days after the first and second active immunization, respectively.

Results

The positive rates after inoculation of the first and second vaccination of S-RBD domain antibody against SARS-CoV-2 were 28.03% and 86.76%, respectively. The mean inhibition rate of S-RBD domain antibody against positive samples was 57.18 ± 18.87% after the second vaccination at 14 days. Sex and age had no effects on the positive rate. The positive rate was decreased in the high BMI group. Single-factor logistic analysis showed that there was no significant correlation between age and positive rate. BMI was negatively correlated with the positive rate.

Conclusions

After 2 immunizations, the positive rate of SARS-CoV-2 S-RBD domain antibody was high, and the vaccine had good immunogenicity. The improvement of the immune strategy should focus on the effects of BMI and other factors.