本研究藉由迴歸及ARMA模型探討兩個不同性質的院區對於A醫院個人防護裝備 (PPE) 需求之影響。實證結果發現，E院區的篩檢人數對於PPE使用量有顯著的正向影響，可能因為E院區位於台北市區，篩檢人數以及門診人數都較多，為防止院內擴散的情況發生對於PPE有正向影響。陽性人數及疫苗接種人數對PPE有顯著負向影響，表示可能隨著疫苗的普及，民眾對於疫情的抵抗力上升，醫院對於PPE的需求反而跟著降低。入境隔離政策鬆綁對於PPE的使用情況有顯著的正向影響，另外，確診及接觸者處理方式進入較為寬鬆的第二與第三階段，醫院對於PPE的需求量有顯著的負向影響。

This study aims to investigate the impacts of two distinct hospital campuses on the demand for Personal Protective Equipment (PPE) at Hospital A using a multiple regression model and Auto-regression and Moving Average (ARMA) model.
The empirical results indicate that the number of screenings at E district has a significantly positive impact on the demand of PPE. We guess that E district is located in the urban area of Taipei metropolis in which the number of screenings and outpatient visits are higher than the other district and resulting in a greater need for PPE.
On the other hand, the higher, the number of positive cases and vaccinated individuals, the lower the PPE demand. This suggests that the government public's regulations were stringent to contain virus increases as vaccination becomes more widespread at first, and could lead to a decreased demand for PPE.
The relaxation of inbound isolation policies also has a significantly positive impact on the demand for PPE. Finally, a series of more flexible regulatory policies significantly decrease the demand for PPE in both districts.

參考文獻
一、英文文獻
Abdelrhim, M., & Elsayed, A. (2020). The Effect of COVID-19 Spread on the e-commerce market: The case of the 5 largest e-commerce companies in the world. Available at SSRN 3621166.

Adams, J. G., & Walls, R. M. (2020). Supporting the health care workforce during the COVID-19 global epidemic. Jama, 323(15), 1439-1440.

Ahmed, J., Malik, F., Arif, T. B., Majid, Z., Chaudhary, M. A., Ahmad, J., ... & Khalid, M. (2020). Availability of personal protective equipment (PPE) among US and Pakistani doctors in COVID-19 pandemic. Cureus, 12(6).

Alabdulrazzaq, H., Alenezi, M. N., Rawajfih, Y., Alghannam, B. A., Al-Hassan, A. A., & Al-Anzi, F. S. (2021). On the accuracy of ARIMA based prediction of COVID-19 spread. Results in Physics, 27, 104509.

Bell, D., Nicoll, A., Fukuda, K., Horby, P., Monto, A., Hayden, F., ... & Van Tam, J. (2006). Non-pharmaceutical interventions for pandemic influenza, national and community measures. Emerging infectious diseases, 12(1), 88-94.
Sepkowitz, K. A., & Eisenberg, L. (2005). Occupational deaths among healthcare workers. Emerging infectious diseases, 11(7), 1003.

Box, G. E., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time series analysis: forecasting and control. John Wiley & Sons.

Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: understanding AIC and BIC in model selection. Sociological methods & research, 33(2), 261-304.

Chiang, C. H., Chiang, C. H., & Chiang, C. H. (2021). Maintaining mask stockpiles in the COVID-19 pandemic: Taiwan as a learning model. Infection Control & Hospital Epidemiology, 42(2), 244-245.

Ceylan, Z. (2020). Estimation of COVID-19 prevalence in Italy, Spain, and France. Science of The Total Environment, 729, 138817.

Chaurasia, V., & Pal, S. (2020). COVID-19 pandemic: ARIMA and regression model-based worldwide death cases predictions. SN Computer Science, 1(5), 288.
Chyon, F. A., Suman, M. N. H., Fahim, M. R. I., & Ahmmed, M. S. (2022). Time series analysis and predicting COVID-19 affected patients by ARIMA model using machine learning. Journal of Virological Methods, 301, 114433.

Chujai, P., Kerdprasop, N., & Kerdprasop, K. (2013, March). Time series analysis of household electric consumption with ARIMA and ARMA models. In Proceedings of the international multiconference of engineers and computer scientists (Vol. 1, pp. 295-300). Hong Kong: IAENG.

Debata, B., Patnaik, P., & Mishra, A. (2020). COVID‐19 pandemic! It's impact on people, economy, and environment. Journal of Public Affairs, 20(4), e2372.

Del Rio, C., & Malani, P. N. (2020). COVID-19—new insights on a rapidly changing epidemic. Jama, 323(14), 1339-1340.

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.

E.J. Emanuel, G. Persad, R. Upshur, B. Thome, M. Parker, A. Glickman, ..., J.P. Phillips
Fair Allocation of Scarce Medical Resources in the Time of Covid-19
New England Journal of Medicine, 382 (21) (2020), pp. 2049-2055

Forrester, J. D., Hunter, J. C., Pillai, S. K., Arwady, M. A., Ayscue, P., Matanock, A., ... & De Cock, K. M. (2014). Cluster of Ebola cases among Liberian and US health care workers in an Ebola treatment unit and adjacent hospital—Liberia, 2014. Morbidity and Mortality Weekly Report, 63(41), 925.

Furman, E., Cressman, A., Shin, S., Kuznetsov, A., Razak, F., Verma, A., & Diamant, A. (2021). Prediction of personal protective equipment use in hospitals during COVID-19. Health Care Management Science, 24, 439-453.

Gautam, S., & Hens, L. (2020). COVID-19: Impact by and on the environment, health and economy. Environment, Development and Sustainability, 22, 4953-4954.

Ghosal, S., Sengupta, S., Majumder, M., & Sinha, B. (2020). Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases-March 14th 2020). Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), 311-315.

Granger, C. W., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of econometrics, 2(2), 111-120.

Huang, I. Y. F. (2020). Fighting COVID‐19 through government initiatives and collaborative governance: the Taiwan experience. Public Administration Review, 80(4), 665-670.

Holland, M., Zaloga, D. J., & Friderici, C. S. (2020). COVID-19 Personal Protective Equipment (PPE) for the emergency physician. Visual journal of emergency medicine, 19, 100740.

Hoernke, K., Djellouli, N., Andrews, L., Lewis-Jackson, S., Manby, L., Martin, S., ... & Vindrola-Padros, C. (2021). Frontline healthcare workers’ experiences with personal protective equipment during the COVID-19 pandemic in the UK: a rapid qualitative appraisal. BMJ open, 11(1), e046199.

Hersi, M., Stevens, A., Quach, P., Hamel, C., Thavorn, K., Garritty, C., ... & Moher, D. (2015). Effectiveness of personal protective equipment for healthcare workers caring for patients with filovirus disease: a rapid review. PloS one, 10(10), e0140290.
Mathieu, E., Ritchie, H., Ortiz-Ospina, E., Roser, M., Hasell, J., Appel, C., ... & Rodés-Guirao, L. (2021). A global database of COVID-19 vaccinations. Nature human behaviour, 5(7), 947-953.

Kutralam-Muniasamy, G., Pérez-Guevara, F., & Shruti, V. C. (2022). A critical synthesis of current peer-reviewed literature on the environmental and human health impacts of COVID-19 PPE litter: new findings and next steps. Journal of Hazardous Materials, 422, 126945.

Kirubarajan, A., Khan, S., Got, T., Yau, M., Bryan, J. M., & Friedman, S. M. (2020). Mask shortage during epidemics and pandemics: a scoping review of interventions to overcome limited supply. BMJ open, 10(11), e040547.

Kwan, W. M., Mok, C. K., Kwok, Y. T., Lam, H. W., Chan, K. H., Law, T. H. S., ... & Tang, Y. H. (2020). Bundled interventions for consumption management and monitoring of personal protective equipment in COVID-19 pandemic in Hong Kong local hospitals. BMJ Open Quality, 9(4), e000990.

Kumar, M., & Anand, M. (2014). An application of time series ARIMA forecasting model for predicting sugarcane production in India. Studies in Business and Economics, 9(1), 81-94.

Livingston, E., Desai, A., & Berkwits, M. (2020). Sourcing personal protective equipment during the COVID-19 pandemic. Jama, 323(19), 1912-1914.

Mondal, P., Shit, L., & Goswami, S. (2014). Study of effectiveness of time series modeling (ARIMA) in forecasting stock prices. International Journal of Computer Science, Engineering and Applications, 4(2), 13.

Ozili, P. K., & Arun, T. (2023). Spillover of COVID-19: impact on the Global Economy. In Managing Inflation and Supply Chain Disruptions in the Global Economy (pp. 41-61). IGI Global.

Perone, G. (2020). An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy. MedRxiv, 2020-04.

Ranney, M. L., Griffeth, V., & Jha, A. K. (2020). Critical supply shortages—the need for ventilators and personal protective equipment during the Covid-19 pandemic. New England Journal of Medicine, 382(18), e41.

Rational use of personal protective equipment for coronavirus disease 2019 (COVID-19) (n.d.): Interim guidance 27 February 2020. https://apps.who.int/iris/bitstream/handle/10665/331215/WHO-2019-nCov-IPCPPE_use-2020.1-eng.pdf. Accessed 27 Feb 2020.

Rath, S., Tripathy, A., & Tripathy, A. R. (2020). Prediction of new active cases of coronavirus disease (COVID-19) pandemic using multiple linear regression model. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 1467-1474.

Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.

Sahai, A. K., Rath, N., Sood, V., & Singh, M. P. (2020). ARIMA modelling & forecasting of COVID-19 in top five affected countries. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 1419-1427.

Segal, P. (2016). The role of personal protective equipment in infection prevention history. Infection Control Today (October 17).

Sharma, S. K., Bhardwaj, S., Bhardwaj, R., & Alowaidi, M. (2021). Nonlinear time series analysis of pathogenesis of COVID-19 pandemic spread in Saudi Arabia. CMC-Comput Mater Continua, 66(1), 805-825.

Shrestha, N., Shad, M. Y., Ulvi, O., Khan, M. H., Karamehic-Muratovic, A., Nguyen, U. S. D., ... & Haque, U. (2020). The impact of COVID-19 on globalization. One Health, 11, 100180.

Singh, J., & Singh, J. (2020). COVID-19 and its impact on society. Electronic Research Journal of Social Sciences and Humanities, 2.

Siegel, J. D., Rhinehart, E., Jackson, M., & Chiarello, L. (2007). 2007 guideline for isolation precautions: preventing transmission of infectious agents in health care settings. American journal of infection control, 35(10), S65-S164.

Singh, R. K., Rani, M., Bhagavathula, A. S., Sah, R., Rodriguez-Morales, A. J., Kalita, H., ... & Kumar, P. (2020). Prediction of the COVID-19 pandemic for the top 15 affected countries: Advanced autoregressive integrated moving average (ARIMA) model. JMIR public health and surveillance, 6(2), e19115.

Summers, J., Cheng, H. Y., Lin, H. H., Barnard, L. T., Kvalsvig, A., Wilson, N., & Baker, M. G. (2020). Potential lessons from the Taiwan and New Zealand health responses to the COVID-19 pandemic. The Lancet Regional Health-Western Pacific, 4, 100044.

Sureka, B., Sinha, A., Tak, V., Garg, M. K., Bhatia, P. K., Bhardwaj, P., ... & Misra, S. (2020). Customized personal protective equipment (PPE): Solution to conservation and management of supplies during the coronavirus disease 2019 (COVID-19) pandemic. Journal of Family Medicine and Primary Care, 9(5), 2180.

Swaminathan, A., Martin, R., Gamon, S., Aboltins, C., Athan, E., Braitberg, G., ... & Grayson, M. L. (2007). Personal protective equipment and antiviral drug use during hospitalization for suspected avian or pandemic influenza1. Emerging infectious diseases, 13(10), 1541.

Verma, A. K., & Prakash, S. (2020). Impact of covid-19 on environment and society. Journal of Global Biosciences, 9(5), 7352-7363.

Verbeek, J. H., Rajamaki, B., Ijaz, S., Sauni, R., Toomey, E., Blackwood, B., ... & Balci, F. S. K. (2020). Personal protective equipment for preventing highly infectious diseases due to exposure to contaminated body fluids in healthcare staff. Cochrane database of systematic reviews, (4).

Wang, C. J., Ng, C. Y., & Brook, R. H. (2020). Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing. Jama, 323(14), 1341-1342.

Weisberg, S. (2005). Applied linear regression (Vol. 528). John Wiley & Sons.

WHO. Shortage of PPE endangering health workers worldwide,
3 March 2020. Available: https://www.who.int/news-room/detail/03-03-2020-shortage-of-personal-protective-equipment-endangeringhealth-workers-worldwide

World Health Organization. (2015). Health worker Ebola infections in Guinea, Liberia and Sierra Leone: a preliminary report 21 May 2015 (No. WHO/EVD/SDS/REPORT/2015.1). World Health Organization. https://www.who.int/publications/i/item/WHO-EVD-SDS-REPORT-2015.1

World Health Organization. (2003). Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003. http://www. who. int/csr/sars/country/table2004_04_21/en/index. html.

Zhang, G. P. (2003). Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing, 50, 159-175.

Zheng, C., Shao, W., Chen, X., Zhang, B., Wang, G., & Zhang, W. (2022). Real-world effectiveness of COVID-19 vaccines: a literature review and meta-analysis. International Journal of Infectious Diseases, 114, 252-260.

二、中文文獻
台灣衛生福利部疾病管制署。因應本土疫情持續嚴峻，指揮中心自即日起至5月28日止提升全國疫情警戒至第三級，各地同步加嚴、加大防疫限制，嚴守社區防線。台灣衛生福利部疾病管制署官網。
民110年5月19日，取自:
https://www.cdc.gov.tw/Bulletin/Detail/abDtRS-xzztQeAchjX9fqw?typeId=9

台灣衛生福利部疾病管制署。因應全球COVID-19疫情回升且Delta變異株持續傳播持續執行「邊境嚴管」措施。台灣衛生福利部疾病管制署官網。
民110年7月26日，取自:
https://www.cdc.gov.tw/Category/ListContent/EmXemht4IT-IRAPrAnyG9A?uaid=B-q5olcKuBQQnVdUhEJyng

台灣衛生福利部疾病管制署。自3月1日至3月31日適度放寬防疫措施，並調整相關規定，請民眾自主落實防疫措施，共同維護國內社區安全。台灣衛生福利部疾病管制署官網。
民111年2月24日，取自:
https://www.cdc.gov.tw/Bulletin/Detail/gccjvyS5_y3GjQkJ98eAHg?typeid=9

台灣衛生福利部疾病管制署。COVID-19疫苗統計資料。台灣衛生福利部疾病管制署官網。
取自:
https://www.cdc.gov.tw/Category/Page/9jFXNbCe-sFK9EImRRi2Og