The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach

Abstract

November 2020 received a string of encouraging results from leading vaccine developers raising hopes for the imminent availability of an effective and safe vaccine against the SARS-CoV-2. In the present work, we discuss the theoretical impact of introducing a vaccine across a range of scenarios. In particular, we investigate how vaccination coverage, efficacy, and delivery time affect the control of the transmission dynamics in comparison to mobility restrictions. The analysis is based on a metapopulation epidemic model structured by risk. We perform a global sensitivity analysis using the Sobol method. Our analysis suggest that the reduction of mobility among patches play a significant role in the mitigation of the disease close to the effect of immunization coverage of 30% achieved in 4 months. Moreover, for an immunization coverage between 20%-50% achieved in the first half of 2021 with a vaccine efficacy between 70%-95%, the percentage reduction in the total number of SARS-CoV-2 infections is between 30%-50% by the end of 2021 in comparison with the no vaccination scenario.

On mobility trends analysis of COVID–19 dissemination in Mexico City

“…The fraction of undocumented infections, ρ , was 0.027 within 95% CI [0.02, 0.04]. The estimated latency period, 1/ α , is 5.96 days within 95% CI [3.60, 8.93] days, which is in concordance with the value used of 5.99, 6.0, 5.1 and 5.0 in [ 50 , 52 , 68 , 69 ], and the estimated recovery period, 1/ γ , is 4.86 days within 95% CI [3.15, 9.33] days, which is lower in comparison with the ones used of 5.97 and 10.81 (asymptomatic and symptomatic class, respectively) in [ 69 ], 10.0 in [ 52 ], 7.0 in [ 50 ] and 5.0, 10.8 and 14.0 (reported infectious, symptomatic and asymptomatic class, respectively) in [ 68 ]. The inter-borough scale factor θ was 0.77 within 95% CI [0.61, 0.89], this value indicates that the mean number of trips made by a person is between three and four in one day, which makes sense with complete trips to get out of home, do some activities (e.g., work, shopping, or services), and return home.…”

“…In particular, we can observe that a different combination of the estimated parameters values obtained with the methods ADVI-Fullrank and ADVI-Meanfield give very similar fitted curves for diagnosed cases. We also observe that the recovery period time is more in accordance with the values used in [50,52,68,69] but the latency period is lower than the ones used there. We note that the parameters, β s , β a of the model (1) are considered as global; that is, they are assumed the same for all the boroughs of Mexico City and all the transportation modes.…”

How unequal vaccine distribution promotes the evolution of vaccine escape

“…The relaxation of these restrictions may have adverse effects if done too quickly [27][28][29], but our findings would indicate that the risk of vaccine escape may not be affected much as long as the distribution of vaccine continues to be equitable.…”

Modeling the COVID-19 pandemic: A primer and overview of mathematical epidemiology

“…The mean infectious periods in the asymptomatic and symptomatic infectious classes are 1/γ A , and 1/γ I , respectively. These individuals gain permanent immunity and move to the recovered class R. However, we remark that this assumption is only valid when studying the first outbreak because to date, it is still unknown how long natural immunity will last and there have been already confirmed cases of coronavirus reinfections [77,86,92,101].…”

“…However, the vaccine-induced immune response may not be as strong or long-lasting [82]. Apart from these problems, the initial and limited vaccine supply has raised some discussion on how to distribute COVID-19 vaccines [20,25,41,49,64,86]. Beyond prioritizing healthcare workers and the elderly, the optimal strategy for the general public remains complex.…”