Estimating Infection-Related Human Mobility Networks Based on Time Series Data of COVID-19 Infection in Japan
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Abstract
Background: Comprehensive and evidence-based countermeasures against emerging infectious diseases have become increasingly important in recent years. COVID-19 and many other infectious diseases are spread by human movement and contact, but complex transportation networks in the 21st century make it difficult to predict disease spread in rapidly changing situations. It is especially challenging to estimate the network of infection transmission in countries where traffic and human movement data infrastructure is not yet developed. Methods: In this study, we devised a method utilizing an ordinary and partial differential equations-based mathematical model and a modified mathematical optimization method to estimate the network of transmission of COVID-19 from the time series data of its infection and applied it to determine its spread across areas in Japan. Furthermore, utilizing the estimated human mobility network, we predicted the spread of infection using the Tokyo Olympics as a model. Findings: We incorporated the effects of soft lockdowns, such as the declaration of a state of emergency, and changes in the infection network due to government-sponsored travel promotion, and revealed that the estimated effective distance captured human mobility changing dynamically in the different stages of the pandemic. The model predicted that the Tokyo Olympic and Paralympic Games would increase the number of infected cases in the host prefectures by up to 80%. Interpretation: The models used in this study are available online, and our data-driven infection network models are scalable, whether it be at the level of a city, town, country, or continent, and applicable anywhere in the world, as long as the time-series data of infections per region is available. These estimations of effective distance and the depiction of infectious disease networks based on actual infection data are expected to be useful in devising data-driven countermeasures against emerging infectious diseases worldwide.
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SciScore for 10.1101/2021.08.02.21261486: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The PDE was replaced by a series of ordinary differential equations (ODEs) by finite difference approximations, which were solved using the SciPy software. SciPysuggested: (SciPy, RRID:SCR_008058)Transformation of a map of Japan based on the effective distance from Tokyo and local connectivity: We created a transformed map of Japan according to the Mercator projection (i.e., the longitude and latitude corresponding to the x and y coordinates in the Euclidean plane, respectively) depending on the effective dis-tance from Tokyo, which was estimated from the diffusion equation and local … SciScore for 10.1101/2021.08.02.21261486: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The PDE was replaced by a series of ordinary differential equations (ODEs) by finite difference approximations, which were solved using the SciPy software. SciPysuggested: (SciPy, RRID:SCR_008058)Transformation of a map of Japan based on the effective distance from Tokyo and local connectivity: We created a transformed map of Japan according to the Mercator projection (i.e., the longitude and latitude corresponding to the x and y coordinates in the Euclidean plane, respectively) depending on the effective dis-tance from Tokyo, which was estimated from the diffusion equation and local interactions between prefectures (Supplementary Figure 7). Mercatorsuggested: (Mercator, RRID:SCR_014493)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:However, the proposed method has some limitations. Importantly, the assumption of the diffusion process from Tokyo is qualitatively different between periods before and after peaks of infection and does not allow to quantitatively compare effective distances between these periods. Thus, improvements in methodology to the estimate effective distance based on the uniform assumption remain to be addressed in future studies.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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