Taiwan has been successful in controlling the COVID-19 epidemic with a soft lockdown policy and extensive community screening. This study aims to evaluate the effectiveness of these measures in Taiwan. We used a mathematical model to simulate the spread of COVID-19 in Taiwan, considering the impact of the soft lockdown policy and community screening. The results showed that the soft lockdown policy significantly reduced the transmission rate of COVID-19, while extensive community screening helped identify and isolate infected individuals. The combination of these measures effectively controlled the epidemic in Taiwan.
@article{chan2022effectiveness,title={Effectiveness of controlling COVID-19 epidemic by implementing soft lockdown policy and extensive community screening in Taiwan},author={Chan, Ta-Chien and Chou, Ching-Chi and Chu, Yi-Chi and Tang, Jia-Hong and Chen, Li-Chi and Lin, Hsien-Ho and Chen, Kevin J and Chen, Ran-Chou},journal={Scientific Reports},volume={12},number={1},pages={12053},year={2022},publisher={Nature Publishing Group UK London},doi={10.1038/s41598-022-16011-x},dimensions={true},}
TJPH
Comparing performance between static and dynamic populations applied to COVID-19 hotspot prediction
Ching-Chi Chou, Hsien-Ho Lin, Kevin J Chen, and 2 more authors
Objectives: This study aimed to set up the prediction model of COVID-19 hotspot areas by using the census data and human mobility from telecommunication data in Taipei and New Taipei City. The comparison between their accuracy and limitations can provide the relevant insights for future epidemic control. Methods: The spatio-temporal resolution is fixed at the village level in two cities in May 2021. The static and dynamic data are used to construct the mobility network. The former applies gravity model to mimic human flow, and the latter uses telecommunication data as the measure of mobility. We propose the footprints similarity by structural equivalence of spatial networks and integrate it with the number of confirmed cases for computing the risk level of the villages. The performance of the models is evaluated using ROC curves and logistic regression under different thresholds for the confirmed cases. Results: The mobility derived from the telecommunication data provided better prediction performance than that from the census data; they have an average AUC of 0.75 and 0.69, respectively. Besides, the telecommunication data had a tendency to identify a further village as high-risk zone compared to the gravity model. According to the results of logistic regression, the odds ratio (OR) of exceeding the cases’ threshold estimated from the telecommunication data is 1.45 on average, while the one estimated from the census data is 1.10. Conclusions: Telecommunication data can be beneficial in identifying the potential high-risk areas and enhancing situational awareness in advance.
@article{chou2022比較靜態與動態人口資料應用於新冠肺炎,title={Comparing performance between static and dynamic populations applied to COVID-19 hotspot prediction},author={Chou, Ching-Chi and Lin, Hsien-Ho and Chen, Kevin J and Chen, Ran-Chou and Chan, Ta-Chien},journal={Taiwan Journal of Public Health},volume={41},number={6},pages={611--626},year={2022},publisher={Taiwan Public Health Association},url={https://doi.org/10.6288/TJPH.202212_41(6).111074},doi={10.6288/TJPH.202212_41(6).111074},}
TGIS
Predicting the hotspots of COVID-19 outbreak by Telecom data - Take Taipei City and New Taipei City as an example.
Ching-Chi Chou, Kevin J, Ran-Chou Chen, and 1 more author
Ching-Chi Chou received the Best Paper Award in 2022 Taiwan Geographical Information Conference
@article{周敬棋2022應用電信數據於新冠肺炎疫情熱區預測,title={Predicting the hotspots of COVID-19 outbreak by Telecom data - Take Taipei City and New Taipei City as an example.},author={Chou, Ching-Chi and J, Kevin and Chen, Ran-Chou and Chan, Ta-Chien},year={2022},journal={Taiwan Geographical Information Conference},}
2018
BGSC
Living or Leaving? The Alteration and Perception of Place Names of Kavalan in Yilan, Taiwan
T. L. Shih, Ching-Chi Chou, and Y. C. Chen
Bulletin of The Geographical Society of China, 2018
@article{石宗霖2018留留,title={Living or Leaving? The Alteration and Perception of Place Names of Kavalan in Yilan, Taiwan},author={Shih, T. L. and Chou, Ching-Chi and Chen, Y. C.},journal={Bulletin of The Geographical Society of China},number={61},pages={51--66},year={2018},publisher={中華民國地理學會},doi={10.29972/BGSC.201809_(61).0005},}