This toolbox includes codes and an example to compute and visualize spatial tessellation of infectious disease spread for epidemic decision support. Infectious diseases have severe impacts on both economy and public health in the US and the world. Due to the heterogeneity of disease spread, there are spatial variations in the demand for medical resources such as PPE, testing kits, and vaccines. Thus, how to effectively estimate the location and coverage of resource centers based on spatial analysis of heterogeneous infection distribution is paramount.
Author: Runsang Liu and Hui Yang
Affiliation:
The Pennsylvania State University
310 Leohard Building, University Park, PA
Email: yanghui@gmail.com
If you find this toolbox useful, please cite the following papers:
[1] Liu, R., & Yang, H. (2021). Spatial Tessellation of Infectious Disease Spread for Epidemic Decision Support. IEEE robotics and automation letters, 7(1), pp. 626-633. DOI: 10.1109/LRA.2021.3131699
[2] H. Yang, S. Zhang, R. Liu, A. Krall, Y. Wang, M. Ventura, and C. Deflitch (2021). Epidemic Informatics and Control: A Review from System Informatics to Epidemic Response and Risk Management in Public Health. AI and Analytics for Public Health“ Proceedings of 2020 INFORMS International Conference on Service Science, pp. 1-46. Berlin: Springer. DOI: 10.1007/978-3-030-75166-1_1
[3] R. Zhu, F. Aqlan, and H. Yang, “Optimal Resource Allocation for Coverage Control of City Crimes.” AI and Analytics for Public Health, Springer International Publishing, 2022, pp. 149–61, doi:10.1007/978-3-030-75166-1_9
Hui Yang (2025). Optimizing spatial tessellation for coverage control (https://in.mathworks.com/matlabcentral/fileexchange/178774-optimizing-spatial-tessellation-for-coverage-control), MATLAB Central File Exchange.
Retrieved .
Liu, Runsang, and Hui Yang. “Spatial Tessellation of Infectious Disease Spread for Epidemic Decision Support.” IEEE Robotics and Automation Letters, vol. 7, no. 1, Institute of Electrical and Electronics Engineers (IEEE), Jan. 2022, pp. 626–33, doi:10.1109/lra.2021.3131699.
Liu, Runsang, and Hui Yang. “Spatial Tessellation of Infectious Disease Spread for Epidemic Decision Support.” IEEE Robotics and Automation Letters, vol. 7, no. 1, Institute of Electrical and Electronics Engineers (IEEE), Jan. 2022, pp. 626–33, doi:10.1109/lra.2021.3131699.
APA
Liu, R., & Yang, H. (2022). Spatial Tessellation of Infectious Disease Spread for Epidemic Decision Support. IEEE Robotics and Automation Letters, 7(1), 626–633. Institute of Electrical and Electronics Engineers (IEEE). Retrieved from http://dx.doi.org/10.1109/LRA.2021.3131699
BibTeX
@article{Liu_2022, title={Spatial Tessellation of Infectious Disease Spread for Epidemic Decision Support}, volume={7}, ISSN={2377-3774}, url={http://dx.doi.org/10.1109/LRA.2021.3131699}, DOI={10.1109/lra.2021.3131699}, number={1}, journal={IEEE Robotics and Automation Letters}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Liu, Runsang and Yang, Hui}, year={2022}, month=jan, pages={626–633} }
Yang, Hui, et al. “Epidemic Informatics and Control: A Review from System Informatics to Epidemic Response and Risk Management in Public Health.” AI and Analytics for Public Health, Springer International Publishing, 2022, pp. 1–58, doi:10.1007/978-3-030-75166-1_1.
Yang, Hui, et al. “Epidemic Informatics and Control: A Review from System Informatics to Epidemic Response and Risk Management in Public Health.” AI and Analytics for Public Health, Springer International Publishing, 2022, pp. 1–58, doi:10.1007/978-3-030-75166-1_1.
APA
Yang, H., Zhang, S., Liu, R., Krall, A., Wang, Y., Ventura, M., & Deflitch, C. (2022). Epidemic Informatics and Control: A Review from System Informatics to Epidemic Response and Risk Management in Public Health. In AI and Analytics for Public Health (pp. 1–58). Springer International Publishing. Retrieved from http://dx.doi.org/10.1007/978-3-030-75166-1_1
BibTeX
@inbook{Yang_2022, title={Epidemic Informatics and Control: A Review from System Informatics to Epidemic Response and Risk Management in Public Health}, ISBN={9783030751661}, ISSN={2198-7254}, url={http://dx.doi.org/10.1007/978-3-030-75166-1_1}, DOI={10.1007/978-3-030-75166-1_1}, booktitle={AI and Analytics for Public Health}, publisher={Springer International Publishing}, author={Yang, Hui and Zhang, Siqi and Liu, Runsang and Krall, Alexander and Wang, Yidan and Ventura, Marta and Deflitch, Chris}, year={2022}, pages={1–58} }
Zhu, Rui, et al. “Optimal Resource Allocation for Coverage Control of City Crimes.” AI and Analytics for Public Health, Springer International Publishing, 2022, pp. 149–61, doi:10.1007/978-3-030-75166-1_9.
Zhu, Rui, et al. “Optimal Resource Allocation for Coverage Control of City Crimes.” AI and Analytics for Public Health, Springer International Publishing, 2022, pp. 149–61, doi:10.1007/978-3-030-75166-1_9.
APA
Zhu, R., Aqlan, F., & Yang, H. (2022). Optimal Resource Allocation for Coverage Control of City Crimes. In AI and Analytics for Public Health (pp. 149–161). Springer International Publishing. Retrieved from http://dx.doi.org/10.1007/978-3-030-75166-1_9
BibTeX
@inbook{Zhu_2022, title={Optimal Resource Allocation for Coverage Control of City Crimes}, ISBN={9783030751661}, ISSN={2198-7254}, url={http://dx.doi.org/10.1007/978-3-030-75166-1_9}, DOI={10.1007/978-3-030-75166-1_9}, booktitle={AI and Analytics for Public Health}, publisher={Springer International Publishing}, author={Zhu, Rui and Aqlan, Faisal and Yang, Hui}, year={2022}, pages={149–161} }
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