From Immunogen to COVID-19 vaccines: Prospects for the post-pandemic era.

The COVID-19 pandemic has affected millions of people and posed an unprecedented burden on healthcare systems and economies worldwide since the outbreak of the COVID-19. A considerable number of nations have investigated COVID-19 and proposed a series of prevention and treatment strategies thus far. The pandemic prevention strategies implemented in China have suggested that the spread of COVID-19 can be effectively reduced by restricting large-scale gathering, developing community-scale nucleic acid testing, and conducting epidemiological investigations, whereas sporadic cases have always been identified in numerous places. Currently, there is still no decisive therapy for COVID-19 or related complications. The development of COVID-19 vaccines has raised the hope for mitigating this pandemic based on the intercross immunity induced by COVID-19. Thus far, several types of COVID-19 vaccines have been developed and released to into financial markets. From the perspective of vaccine use in globe, COVID-19 vaccines are beneficial to mitigate the pandemic, whereas the relative adverse events have been reported progressively. This is a review about the development, challenges and prospects of COVID-19 vaccines, and it can provide more insights into all aspects of the vaccines.

A Review of Multi-Compartment Infectious Disease Models.

Multi-compartment models have been playing a central role in modelling infectious disease dynamics since the early 20th century. They are a class of mathematical models widely used for describing the mechanism of an evolving epidemic. Integrated with certain sampling schemes, such mechanistic models can be applied to analyse public health surveillance data, such as assessing the effectiveness of preventive measures (e.g. social distancing and quarantine) and forecasting disease spread patterns. This review begins with a nationwide macromechanistic model and related statistical analyses, including model specification, estimation, inference and prediction. Then, it presents a community-level micromodel that enables high-resolution analyses of regional surveillance data to provide current and future risk information useful for local government and residents to make decisions on reopenings of local business and personal travels. r software and scripts are provided whenever appropriate to illustrate the numerical detail of algorithms and calculations. The coronavirus disease 2019 pandemic surveillance data from the state of Michigan are used for the illustration throughout this paper.