# Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis

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## Abstract

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## 1. Introduction

## 2. Materials and Methods

#### 2.1. Twitter Surveys

- No surgical restrictions
- Partial restrictions (more than half of the usual)
- Extensive restrictions (less than half of the usual)
- No scheduled surgery

#### 2.2. Transition of Responses to the Survey

#### 2.3. The Number of General Anesthesia under Restriction

#### 2.4. Nationwide Report of the Estimation of the Number of General Anesthesia from the Japanese Society of Anesthesiologists (JSA)

#### 2.5. Ethics

## 3. Results

^{4}cases of general anesthesia were performed per week in Japan. The number of general anesthesia (10

^{4}cases per week unit) was estimated to be 4.24 [95% CI: 4.18, 4.29] in the first-week survey (13 March 2020), 2.99 [2.91, 3.07] in the seventh-week survey (27 April 2020) and 4.23 [4.18, 4.28] in the last week survey (14 August 2020).

^{4}cases/week (96.3% compared to 2015), while the pessimistic scenario had a median of 4.17 × 10

^{4}cases/week (93.7%). From the seventh week of the survey (27 April 2020), the optimistic scenario median was 3.32 × 10

^{4}cases/week (74.5%), while that of the pessimistic scenario was 2.52 × 10

^{4}cases/week (56.5%), respectively. From the last week of the survey (14 August 2020), the optimistic scenario median was 4.30 × 10

^{4}cases/week (96.5%), while that of the pessimistic scenario was 4.13 × 10

^{4}cases/week (92.9%). The maximum difference between optimistic and pessimistic scenarios was 1.32-fold on 2 May 2020.

## 4. Discussion

## 5. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- Zhu, N.; Zhang, D.; Wang, W.; Li, X.; Yang, B.; Song, J.; Zhao, X.; Huang, B.; Shi, W.; Lu, R.; et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med.
**2020**, 382, 727–733. [Google Scholar] [CrossRef] [PubMed] - Normile, D. Japan ends its COVID-19 state of emergency. Science
**2020**. [Google Scholar] [CrossRef] - Guan, W.J.; Ni, Z.Y.; Hu, Y.; Liang, W.H.; Ou, C.Q.; He, J.X.; Liu, L.; Shan, H.; Lei, C.L.; Hui, D.S.C.; et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med.
**2020**, 382, 1708–1720. [Google Scholar] [CrossRef] [PubMed] - Meselson, M. Droplets and Aerosols in the Transmission of SARS-CoV-2. N. Engl. J. Med.
**2020**, 382, 2063. [Google Scholar] [CrossRef] [PubMed] - Zarzaur, B.L.; Stahl, C.C.; Greenberg, J.A.; Savage, S.A.; Minter, R.M. Blueprint for Restructuring a Department of Surgery in Concert With the Health Care System During a Pandemic: The University of Wisconsin Experience. JAMA Surg.
**2020**, 155, 628–635. [Google Scholar] [CrossRef] [PubMed] [Green Version] - American College of Surgeons. COVID-19: Elective Case Triage Guidelines for Surgical Care. 2020. Available online: https://www.facs.org/covid-19/clinical-guidance/elective-case (accessed on 8 February 2021).
- The Centers for Medicare & Medicaid Services. Non-Emergent, Elective Medical Services, and Treatment Recommendations 2020. Available online: https://www.cms.gov/files/document/cms-non-emergent-elective-medical-recommendations.pdf (accessed on 8 February 2021).
- Spinelli, A.; Pellino, G. COVID-19 pandemic: Perspectives on an unfolding crisis. Br. J. Surg.
**2020**, 107, 785–787. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Tuech, J.J.; Gangloff, A.; Schwarz, L. Our challenge is to adapt the organization of our system to the six stages of the epidemic to go beyond the COVID-19 crisis. Br. J. Surg.
**2020**, 107, e189. [Google Scholar] [CrossRef] - Aramaki, E.; Maskawa, S.; Morita, M. Twitter Catches The Flu: Detecting Influenza Epidemics using Twitter. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Edinburgh, Scotland, UK, 27–31 July 2011; pp. 1568–1576. [Google Scholar]
- Sang, E.; Bos, J. Predicting the 2011 dutch senate election results with twitter. In Proceedings of the Workshop on Semantic Analysis in Social Media, Avignon, France, 23–27 April 2012; pp. 53–60. [Google Scholar]
- Jones, M.T. Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk; International Monetary Fund: Washington, DC, USA, 2005; No. 5-219. [Google Scholar]
- Aksu, C.; Cesur, S.; Kuş, A.; Toker, K. General Anesthesia Practices during the COVID-19 Pandemic in Turkey: A Cohort Study with a National Survey. Cureus
**2020**, 12, e10910. [Google Scholar] [CrossRef] - Bhatia, K.; Columb, M.; Bewlay, A.; Eccles, J.; Hulgur, M.; Jayan, N.; Lie, J.; Verma, D.; Parikh, R. The effect of COVID-19 on general anaesthesia rates for caesarean section. A cross-sectional analysis of six hospitals in the north-west of England. Anaesthesia
**2020**. [Google Scholar] [CrossRef] - COVIDSurg Collaborative. Elective surgery cancellations due to the COVID-19 pandemic: Global predictive modelling to inform surgical recovery plans. Br. J. Surg.
**2020**, 107, 1440–1449. [Google Scholar] [CrossRef] - Holmer, H.; Bekele, A.; Hagander, L.; Harrison, E.M.; Kamali, P.; Ng-Kamstra, J.S.; Khan, M.A.; Knowlton, L.; Leather, A.J.M.; Marks, I.H.; et al. Evaluating the collection, comparability and findings of six global surgery indicators. Br. J. Surg.
**2019**, 106, e138–e150. [Google Scholar] [CrossRef] [PubMed] [Green Version]

**Figure 1.**Transition scheme of the proportion of surveys. (1: Green) No surgical restrictions, (2: Yellow) partial restrictions, (3: Orange) extensive restrictions, and (4: Red) no scheduled surgery. ${p}_{ij}$ is the transition probability from response $i$ to response $j$.

**Figure 2.**Distribution of the degree of restriction for each response group. The mean percentages of the restrictions were generated from the gamma distribution. No surgical restrictions (green), partial restrictions (yellow), extensive restrictions (orange), and no scheduled surgery (red) were generated from the gamma distribution

**Gamma**(α, β). The set of parameters for the gamma distribution, (α, β), were defined so that the respective median of the gamma distribution was 1.0 for “No surgical restrictions,” 0.7 for “Partial restrictions,” 0.4 for “Extensive restrictions,” and 0.1 for “No scheduled surgery.” The variance of the gamma distribution was 0.005.

**Figure 3.**The transition of the proportion of responses to the survey. A solid line was an estimated transition and dots were actual data.

**Figure 4.**Estimation of the number of general anesthesia in Japan from the survey results. The violin plots show the distribution of the estimated number of general anesthesia performed at 1989 hospitals in Japan.

**Figure 5.**Estimation of the number of general anesthesia in Japan from the results of the surveys for the three scenarios as a sensitivity analysis and comparison between the estimation of the number of the general anesthesia and the report from the Japanese Society Anesthesiologists (JSA). The JSA reported the results of the estimated number of general anesthesia from 1415 authorized institutes from 23 April 2020.

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**MDPI and ACS Style**

Fujii, Y.; Daijo, H.; Hirota, K.
Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis. *Medicina* **2021**, *57*, 153.
https://doi.org/10.3390/medicina57020153

**AMA Style**

Fujii Y, Daijo H, Hirota K.
Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis. *Medicina*. 2021; 57(2):153.
https://doi.org/10.3390/medicina57020153

**Chicago/Turabian Style**

Fujii, Yosuke, Hiroki Daijo, and Kiichi Hirota.
2021. "Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis" *Medicina* 57, no. 2: 153.
https://doi.org/10.3390/medicina57020153