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Time Series Modelling and Simulating the Lockdown Scenarios of COVID-19 in Kurdistan Region of Iraq
Milad Abdullah1, Kamal Kolo2, Peyman Aspoukeh2
1Scientific Research Centre, Soran University, Soran, Iraq. milad.abdullah@soran.edu.iq.
Insights
Mathematical models and simulations were used to analyze Coronavirus disease (COVID-19) spread in Iraq's Kurdistan Region. Findings indicate a high risk of future infection waves, necessitating public health interventions.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- The Coronavirus disease (COVID-19) pandemic has caused over 30 million global infections by September 2020.
- Iraq reported over 300,000 COVID-19 cases by March 2020.
Purpose of the Study:
- To analyze COVID-19 data using mathematical models and simulations.
- To forecast potential future infection rates in the Kurdistan Region of Iraq.
Main Methods:
- Utilized time series models: Simple Exponential Model, Holt's Method, and Brown's Models.
- Conducted particle-based artificial simulations in a virtual environment representing a portion of Erbil.
Main Results:
- The study illustrates COVID-19's spread patterns within Kurdistan.
- Modeling indicates a significant risk of second and third infection waves due to sporadic cases.
Conclusions:
- Urgent need for the regional government to minimize large gatherings.
- Establishment of a continuously updated scientific disease statistics registry is crucial.
- Implementation of a public nationwide database to track infected individuals is recommended to curb transmission.
Introduction:
Since the first published cases of the Coronavirus disease known as COVID-19 in the city of Wuhan Hubei Province in China, up until to the time of preparation of this report in mid-September 2020, more than 30 million people have been infected all over the world. In March 2020, more than 300,000 cases have been reported all over Iraq. This study aims to represent data analysis, modelling and forecasting approaches to the presented data in the Kurdistan Region of Iraq.
Methodology:
The project involves mathematical models for forecasting and artificial simulations using particles. In the study, time series models including Simple Exponential Model, Holt's Method and Brown's Models have been used for the forecasting of the future potential rates in the area. A series of simulations have been conducted to observe the possibilities of virus spread rates in a virtual world which represents a quarter of Erbil.
Results:
The outcome of the study shows how the disease have spread in Kurdistan, and what are the current rates to compare with neighbour regions. The modelling clearly shows that with cases still sporadically appearing, the risk of second and third waves of infections is high.
Conclusions:
Therefore, the regional government must reduce unnecessary gatherings to the lowest possible level. A scientific registry system of disease statistics must be put in place and rigorously updated all the times. We recommend the officials use a nationwide database provided to the public to monitor movement of every infected individual, to prevent further spread.
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