The effects of different travel modes and travel destinations on COVID-19 transmission in global cities

Zhu, Rui; Anselin, Luc; Batty, M; Kwan, Mei‐Po; Chen, Min; Luo, Wei; Cheng, T.C.; Lim, Che Kang; Santi, Paolo; Cheng, Cheng; Gu, Qiushi; Wong, Man Sing; Zhang, Kai; Lü, Guonian; Ratti, Carlo

doi:10.1016/j.scib.2021.11.023

Cited by 26 publications

(17 citation statements)

References 15 publications

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“…When implementing the intervention, economic and social justification is one of the priorities that governments should consider [ 78 ]. Hence, it is a challenge for all countries to weigh the balance between epidemic development and socioeconomic loss [ 79 ].…”

Section: Discussionmentioning

confidence: 99%

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method

Luo¹,

Liu²,

Zhou³

et al. 2022

JMIR Public Health Surveill

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Background The COVID-19 Delta variant has presented an unprecedented challenge to countries in Southeast Asia (SEA). Its transmission has shown spatial heterogeneity in SEA after countries have adopted different public health interventions during the process. Hence, it is crucial for public health authorities to discover potential linkages between epidemic progression and corresponding interventions such that collective and coordinated control measurements can be designed to increase their effectiveness at reducing transmission in SEA. Objective The purpose of this study is to explore potential linkages between the spatiotemporal progression of the COVID-19 Delta variant and nonpharmaceutical intervention (NPI) measures in SEA. We detected the space-time clusters of outbreaks of COVID-19 and analyzed how the NPI measures relate to the propagation of COVID-19. Methods We collected district-level daily new cases of COVID-19 from June 1 to October 31, 2021, and district-level population data in SEA. We adopted prospective space-time scan statistics to identify the space-time clusters. Using cumulative prospective space-time scan statistics, we further identified variations of relative risk (RR) across each district at a half-month interval and their potential public health intervention linkages. Results We found 7 high-risk clusters (clusters 1-7) of COVID-19 transmission in Malaysia, the Philippines, Thailand, Vietnam, and Indonesia between June and August, 2021, with an RR of 5.45 (P<.001), 3.50 (P<.001), 2.30 (P<.001), 1.36 (P<.001), 5.62 (P<.001), 2.38 (P<.001), 3.45 (P<.001), respectively. There were 34 provinces in Indonesia that have successfully mitigated the risk of COVID-19, with a decreasing range between –0.05 and –1.46 due to the assistance of continuous restrictions. However, 58.6% of districts in Malaysia, Singapore, Thailand, and the Philippines saw an increase in the infection risk, which is aligned with their loosened restrictions. Continuous strict interventions were effective in mitigating COVID-19, while relaxing restrictions may exacerbate the propagation risk of this epidemic. Conclusions The analyses of space-time clusters and RRs of districts benefit public health authorities with continuous surveillance of COVID-19 dynamics using real-time data. International coordination with more synchronized interventions amidst all SEA countries may play a key role in mitigating the progression of COVID-19.

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Section: Discussionmentioning

confidence: 99%

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method

Luo¹,

Liu²,

Zhou³

et al. 2022

JMIR Public Health Surveill

Self Cite

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“…The travel mode is a factor influencing environmental and public health that cannot be ignored (58,59). Shared bicycles, as a healthy and environmentally sustainable travel mode, should be conveniently accessed by the public.…”

Section: Discussionmentioning

confidence: 99%

Prediction for Origin-Destination Distribution of Dockless Shared Bicycles: A Case Study in Nanjing City

Cao

Liang

Zhu

et al. 2022

Front. Public Health

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Shared bicycles are currently widely welcomed by the public due to their flexibility and convenience; they also help reduce chemical emissions and improve public health by encouraging people to engage in physical activities. However, during their development process, the imbalance between the supply and demand of shared bicycles has restricted the public's willingness to use them. Thus, it is necessary to forecast the demand for shared bicycles in different urban regions. This article presents a prediction model called QPSO-LSTM for the origin and destination (OD) distribution of shared bicycles by combining long short-term memory (LSTM) and quantum particle swarm optimization (QPSO). LSTM is a special type of recurrent neural network (RNN) that solves the long-term dependence problem existing in the general RNN, and is suitable for processing and predicting important events with very long intervals and delays in time series. QPSO is an important swarm intelligence algorithm that solves the optimization problem by simulating the process of birds searching for food. In the QPSO-LSTM model, LSTM is applied to predict the OD numbers. QPSO is used to optimize the LSTM for a problem involving a large number of hyperparameters, and the optimal combination of hyperparameters is quickly determined. Taking Nanjing as an example, the prediction model is applied to two typical areas, and the number of bicycles needed per hour in a future day is predicted. QPSO-LSTM can effectively learn the cycle regularity of the change in bicycle OD quantity. Finally, the QPSO-LSTM model is compared with the autoregressive integrated moving average model (ARIMA), back propagation (BP), and recurrent neural networks (RNNs). This shows that the QPSO-LSTM prediction result is more accurate.

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“…When making intervention regulations, economic and social justifications for public health policies are one of the priorities that governments would consider [41]. Hence, it is one of the challenges for all countries to live with COVID-19 and weigh the balance between epidemic development and social economic loss [42]. Given the social and economic status, most countries in SEA have decided to change their strategies from the elimination of cases to living with COVID-19 since August 2021 despite the new outbreak of Delta variant [8].…”

Section: Implications and Recommendationsmentioning

confidence: 99%

Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia

Luo

Liu

Zhou

et al. 2021

Preprint

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The global pandemic of COVID-19 presented an unprecedented challenge to all countries in the world, among which Southeast Asia (SEA) countries managed to maintain and mitigate the first wave of COVID-19 in 2020. However, these countries were caught in the crisis after the Delta variant was introduced to SEA, though many countries had immediately implemented non-pharmaceutical intervention (NPI) measures along with vaccination in order to contain the disease spread. To investigate the potential linkages between epidemic dynamics and public health interventions, we adopted a prospective space-time scan method to conduct spatiotemporal analysis at the district level in the seven selected countries in SEA from June 2021 to October 2021. Results reveal the spatial and temporal propagation and progression of COVID-19 risks relative to public health measures implemented by different countries. Our research benefits continuous improvements of public health strategies in preventing and containing this pandemic.

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The effects of different travel modes and travel destinations on COVID-19 transmission in global cities

Cited by 26 publications

References 15 publications

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method

Prediction for Origin-Destination Distribution of Dockless Shared Bicycles: A Case Study in Nanjing City

Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia

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