Predicting COVID-19 fatality rate based on age group using LSTM

Zahra Ramezani; Jamshid Charati; Seyed Mousavi; Ghasem Oveis; Mohammad Parsai; Fatemeh Abdollahi

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Predicting COVID-19 fatality rate based on age group using LSTM

Author: Zahra RAMEZANI ¹ ; Jamshid CHARATI ¹ ; Seyed MOUSAVI ² ; Ghasem OVEIS ³ ; Mohammad PARSAI ⁴ ; Fatemeh ABDOLLAHI ⁵
Author Information

1. Department of Epidemiology and Biostatistics, School of Health, Mazandaran University of Medical Sciences
2. Department of Psychiatry, Psychiatry and Behavioral Sciences Research Center, Addiction Institute, Mazandaran, University of Medical Sciences
3. Health Vice-chancellor of Mazandaran University of Medical Sciences
4. Control Disease Center, Mazandaran University of Medical Sciences
5. Department of Public Health, Psychiatry and Behavioral Sciences Research Center, Mazandaran University of Medical Sciences
Publication Type:Journal Article
Keywords: Age classification; COVID-19; Fatality rate; Incidence rate; Long short-term memory model; Prediction
From: Asian Pacific Journal of Tropical Medicine 2021;14(12):564-574
CountryChina
Language:Chinese
Abstract: Objective: To predict the daily incidence and fatality rates based on long short-term memory (LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran. Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other. Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females (49.7%), and 25 586 were males (50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively; for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.