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Nowcasting and Forecasting the Spread of COVID-19 and Healthcare Demand in Turkey, a Modeling Study.
Arslan, Seyma; Ozdemir, Muhammed Yusuf; Ucar, Abdullah.
  • Arslan S; Public Health Department, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey.
  • Ozdemir MY; Center for Primary Care and Public Health, Queen Mary University of London, London, United Kingdom.
  • Ucar A; Public Health Department, Institute of Health Sciences, Istanbul University, Istanbul, Turkey.
Front Public Health ; 8: 575145, 2020.
Article in English | MEDLINE | ID: covidwho-1069762
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ABSTRACT

Background:

This study aims to estimate the total number of infected people, evaluate the effects of NPIs on the healthcare system, and predict the expected number of cases, deaths, hospitalizations due to COVID-19 in Turkey.

Methods:

This study was carried out according to three dimensions. In the first, the actual number of infected people was estimated. In the second, the expected total numbers of infected people, deaths, hospitalizations have been predicted in the case of no intervention. In the third, the distribution of the expected number of infected people and deaths, and ICU and non-ICU bed needs over time has been predicted via a SEIR-based simulator (TURKSAS) in four scenarios.

Results:

According to the number of deaths, the estimated number of infected people in Turkey on March 21 was 123,030. In the case of no intervention the expected number of infected people is 72,091,595 and deaths is 445,956, the attack rate is 88.1%, and the mortality ratio is 0.54%. The ICU bed capacity in Turkey is expected to be exceeded by 4.4-fold and non-ICU bed capacity by 3.21-fold. In the second and third scenarios compliance with NPIs makes a difference of 94,303 expected deaths. In both scenarios, the predicted peak value of occupied ICU and non-ICU beds remains below Turkey's capacity.

Discussion:

Predictions show that around 16 million people can be prevented from being infected and 94,000 deaths can be prevented by full compliance with the measures taken. Modeling epidemics and establishing decision support systems is an important requirement.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Forecasting / COVID-19 / Health Services Needs and Demand / Hospitalization / Models, Theoretical Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Front Public Health Year: 2020 Document Type: Article Affiliation country: Fpubh.2020.575145

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Forecasting / COVID-19 / Health Services Needs and Demand / Hospitalization / Models, Theoretical Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Front Public Health Year: 2020 Document Type: Article Affiliation country: Fpubh.2020.575145