Abstract
Mathematical modelling has played a pivotal role in understanding the epidemiology of and guiding public health responses to the ongoing coronavirus disease of 2019 (COVID-19) pandemic. Here, we review the role of epidemiological models in understanding evolving epidemic characteristics, including the effects of vaccination and Variants of Concern (VoC). We highlight ways in which models continue to provide important insights, including (1) calculating the herd immunity threshold and evaluating its limitations; (2) verifying that nascent vaccines can prevent severe disease, infection, and transmission but may be less efficacious against VoC; (3) determining optimal vaccine allocation strategies under efficacy and supply constraints; and (4) determining that VoC are more transmissible and lethal than previously circulating strains, and that immune escape may jeopardize vaccine-induced herd immunity. Finally, we explore how models can help us anticipate and prepare for future stages of COVID-19 epidemiology (and that of other diseases) through forecasts and scenario projections, given current uncertainties and data limitations.
Keywords: COVID-19; Educational aims; Future directions for research; Herd immunity threshold; Mathematical modelling; Vaccine allocation; Variants of Concern.
【저자키워드】 COVID-19, Mathematical modelling, variants of concern., Educational aims, Future directions for research, Herd immunity threshold, Vaccine allocation, 【초록키워드】 coronavirus disease, Efficacy, Vaccine, vaccination, pandemic, Immunity, Epidemiology, Infection, Transmission, variants, Epidemic, Characteristics, Immune escape, herd immunity, Mathematical modelling, Public health response, epidemiological, concern, Strains, 2019, severe disease, Herd immunity threshold, other diseases, Public health responses, help, Stage, circulating, Future, Effect, limitations, Prevent, highlight, less, 【제목키워드】 Epidemiology,