Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses

Abstract

This study aims to inform SARS-CoV-2 vaccine development/licensure/decision-making/implementation, using mathematical modeling, by determining key preferred vaccine product characteristics and associated population-level impacts of a vaccine eliciting long-term protection. A prophylactic vaccine with efficacy against acquisition (VES) ≥70% can eliminate the infection. A vaccine with VES <70% may still control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, if it is supplemented with <20% reduction in contact rate, or if it is complemented with herd-immunity. At VES of 50%, the number of vaccinated persons needed to avert one infection is 2.4, and the number is 25.5 to avert one severe disease case, 33.2 to avert one critical disease case, and 65.1 to avert one death. The probability of a major outbreak is zero at VES ≥70% regardless of the number of virus introductions. However, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact. In addition to the reduction in infection acquisition, developers should assess the natural history and disease progression outcomes when evaluating vaccine impact.

Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19

“…Mathematical modeling played an influential role in guiding the national public-health response by characterizing and understanding the epidemic, forecasting health care needs, predicting the impact of social and physical distancing restrictions, and rationalizing and justifying the easing of restrictions. While this article illustrates a successful case study, the modeling tools employed here can be adapted and applied in other countries to guide SARS-CoV-2 epidemic control, preparedness for the current or future waves of infection, or enforcement and easing of restrictions or other interventions, such as vaccination [ 21 ].…”

“…Building on our previously developed models [ 8 , 18 - 21 ], an age-structured, meta-population, deterministic mathematical model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression (Figure S1 in the Online Supplementary Document ). The model stratified the Qatari population into groups (“compartments”) according to the major nationality groups (Indians, Bangladeshis, Nepalese, Qataris, Egyptians, Filipinos, and all other nationalities), age group by decile, infection status (infected, uninfected), severity of illness (asymptomatic/mild, severe, critical), and disease/hospitalization stage (severe, critical), using sets of coupled, nonlinear, differential equations.…”

Quality-Adjusted Life-Year Losses Averted With Every COVID-19 Infection Prevented in the United States

“…These estimates are in line with current modeling efforts with large SEIR models. 17 Therefore, after a vaccine becomes available, we allow R(t) to decrease linearly over 1 year to reach levels of herd immunity or R(t)~0. 8 In total, we account for the growth in infections from the index infection date over the next 15 months, with each new infection experiencing the probabilistically similar QALY loss for the patient and their family members as our index case.…”

Epidemiological Differences in the Impact of COVID-19 Vaccination in the United States and China

“…Since the primary endpoint of the vaccine’s randomized clinical trials was efficacy of the vaccine against laboratory-confirmed COVID-19 cases [ 6 , 7 , 8 ], and not just any infection, documented or undocumented, it is unknown whether the vaccine prophylactically reduces susceptibility to the infection (that is, efficacy defined as the proportional reduction in the susceptibility to infection among those vaccinated compared to those unvaccinated [ 5 ]) or whether it just reduced serious symptomatic COVID-19 cases with no effect on infection (that is, efficacy against disease progression, defined as the proportional reduction in the fraction of individuals with severe or critical infection among those vaccinated but who still acquired the infection compared to those unvaccinated [ 5 ]). These two mechanisms of action bracket the two extremes for the vaccine’s biological effect, with the former mechanism being the most optimistic (reducing both infection and disease) and the latter being the most pessimistic (reducing only disease).…”

“…We previously developed a mathematical model to investigate the generic population-level impact of SARS-CoV-2 vaccination [ 5 ]. In light of recently produced vaccines with ~95% efficacy against Coronavirus Disease 2019 (COVID-19) symptomatic disease [ 6 , 7 ], the model was extended to assess the impact of these novel vaccines on COVID-19 morbidity and mortality in two major countries at different epidemic phases, the United States (US) and China.…”