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Indirect Forecasting of the Number of Intensive Care Beds and Hospital Capacity for the COVID-19 Outbreak in Turkey Until the End of April
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Original Research
VOLUME: 18 ISSUE: 1
P: 22-30
March 2020

Indirect Forecasting of the Number of Intensive Care Beds and Hospital Capacity for the COVID-19 Outbreak in Turkey Until the End of April

J Turk Soc Intens Care 2020;18(1):22-30
DOI: 10.4274/tybd.galenos.2020.68077
Handan Ankaralı 1
Seyit Ankaralı 2
1. İstanbul Medeniyet Üniversitesi Tıp Fakültesi, Biyoistatistik ve Tıp Bilişimi Anabilim Dalı, İstanbul, Türkiye
2. İstanbul Medeniyet Üniversitesi Tıp Fakültesi, Biyoistatistik ve Tıp Bilişimi Anabilim Dalı, İstanbul, Türkiye
3. İstanbul Medeniyet Üniversitesi Tıp Fakültesi, Fizyoloji Anabilim Dalı, İstanbul, Türkiye
4. İstanbul Medeniyet Üniversitesi Tıp Fakültesi, Fizyoloji Anabilim Dalı, İstanbul, Türkiye
No information available.
No information available
Received Date: 05.04.2020
Accepted Date: 10.04.2020
Publish Date: 14.10.2020
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ABSTRACT

Objective:

The COVID-19 outbreak has been threatening the entire world for approximately 4 months. Healthcare management is one of the most important precautions to be taken for the successful management of this epidemic. Evidence-based estimates are of great importance in solving these problems. In this study, as of the first week of April, we provide a description of Turkey according to the indicators of the COVID-19 outbreak in each city and an evaluation of the relationship between the population density of each province and the number of cases. Additionally, we calculate the change in the new case rate and aim to estimate the number of intensive care beds and the number of intubations needed on a day-to-day basis.

Materials and Methods:

The outbreak indicators and number of tests announced by the Ministry of Health of the Turkish Republic day-by-day were used. A Poisson regression model was used for data analysis. In addition, a new algorithm was proposed to estimate healthcare needs.

Results:

The relationship between urban density and the total number of cases was found to be statistically significant (r=0.464, p<0.001). When the density increased by one person, the total number of cases was estimated to increase by one. Minor changes were observed in the rate of new cases within the daily tests between March 29 and April 5. The total numbers of intensive care patients, intubated patients, patients quarantined at home or hospitalized in the normal service, and recovered patients, as well as the total case numbers were used in the calculations. By using the total forecasted cases, the service infrastructure requirements to be provided in hospitals, such as the number of beds and the number of intubations, were estimated and given in tables.

Conclusion:

When priorities are questioned in the coming days, it should not be forgotten that these types of studies will be helpful to solve important health problems.

Keywords: Intensive care, intubation, COVID-19, time series, poisson regression

References

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WHO. Coronavirus disease 2019 (COVID-19) Situation Report – 62. March 2020.Available from: URL: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200322-sitrep-62-covid-19.pdf?sfvrsn=755c76cd_2 (Accessed April 4, 2020)
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TC Sağlık Bakanlığı Web Sitesi https://www.saglik.gov.tr/
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IHME COVID-19 health service utilization forecasting team, Murray CJL. Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months. medRxiv doi: 10.1101/2020.03.27.20043752
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