A new transport-based approach for simulating impact of urban mobility on COVID-19 propagation

El-alaouy, El-arbi; Abdelali, Hamd Ait; Zennayi, Yahya; Bourzeix, François; Amine, Mohamed; Malka, G.

doi:10.1109/icds53782.2021.9626768

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“…The prediction based on the mobility was proposed [22]. To address the impact of urban mobility on COVID-19 propagation, the traffic systems have been developed [23].…”

Section: Introductionmentioning

confidence: 99%

The Effects of Time Window-Averaged Mobility on Effective Reproduction Number of COVID-19 Viral Variants in Urban Cities

et al. 2022

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During epidemics, the estimation of the effective reproduction number (ERN) associated with infectious disease is a challenging topic for policy development and medical resource management. The emergence of new viral variants is common in widespread pandemics including the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A simple approach is required toward an appropriate and timely policy decision for understanding the potential ERN of new variants is required for policy revision. We investigated time-averaged mobility at transit stations as a surrogate to correlate with the ERN using the data from three urban prefectures in Japan. The optimal time windows, i.e., latency and duration, for the mobility to relate with the ERN were investigated. The optimal latency and duration were 5–6 and 8 days, respectively (the Spearman’s ρ was 0.109–0.512 in Tokyo, 0.365–0.607 in Osaka, and 0.317–0.631 in Aichi). The same linear correlation was confirmed in Singapore and London. The mobility-adjusted ERN of the Alpha variant was 15–30%, which was 20–40% higher than the original Wuhan strain in Osaka, Aichi, and London. Similarly, the mobility-adjusted ERN of the Delta variant was 20%–40% higher than that of the Wuhan strain in Osaka and Aichi. The proposed metric would be useful for the proper evaluation of the infectivity of different SARS-CoV-2 variants in terms of ERN as well as the design of the forecasting system.

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“…The prediction based on the mobility was proposed [22]. To address the impact of urban mobility on COVID-19 propagation, the traffic systems have been developed [23].…”

Section: Introductionmentioning

confidence: 99%