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Projecting the Short-Term Trend of COVID-19 in Iraq

Published: 03 December 2020 Publication History

Abstract

The novel coronavirus that causes the now well-known COVID-19 illness has affected the whole world as the number of daily reported cases has exceeded 250,000. The spread trend of the virus across the globe has varied from one country to another, mainly because of each government’s response. In this article, we discuss the statistics of the cases in Iraq and provide a projection model based on the current situation and government interventions. Using daily reported cases data from February 24, 2020--July 31, 2020, we report 6-week-ahead projections of daily cases, critical cases, and deaths. Specifically, we propose a simple machine learning-based model based on Gaussian Process regression to project the future trend of COVID-19 in Iraq. This work aims to aid the Iraqi government by providing a statistical tool to provide future estimates of the suspected and death cases resulting from COVID-19 and make strategic decisions.

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Cited By

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  • (2023)Performance Assessment of DL Model in Iraq for Covid-19 Patient Severity Prediction from X-Ray Scan ImagesJournal of Image Processing and Intelligent Remote Sensing10.55529/jipirs.36.1.11(1-11)Online publication date: 23-Sep-2023
  • (2023)Exploring epigenetic drugs as potential inhibitors of SARS-CoV-2 main protease: a docking and MD simulation studyJournal of Biomolecular Structure and Dynamics10.1080/07391102.2023.223671442:13(6892-6903)Online publication date: 17-Jul-2023
  • (2022)Community mapping of COVID-19 cases admitted from April to June 2020 at a tertiary health care hospital in Raigad district in Maharashtra, IndiaMGM Journal of Medical Sciences10.4103/mgmj.mgmj_22_229:2(177)Online publication date: 2022
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Published In

cover image Digital Government: Research and Practice
Digital Government: Research and Practice  Volume 2, Issue 1
COVID-19 Commentaries
January 2021
116 pages
EISSN:2639-0175
DOI:10.1145/3434277
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 December 2020
Online AM: 30 October 2020
Accepted: 01 October 2020
Revised: 01 August 2020
Received: 01 August 2020
Published in DGOV Volume 2, Issue 1

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  1. COVID-19
  2. Iraq
  3. machine learning

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Cited By

View all
  • (2023)Performance Assessment of DL Model in Iraq for Covid-19 Patient Severity Prediction from X-Ray Scan ImagesJournal of Image Processing and Intelligent Remote Sensing10.55529/jipirs.36.1.11(1-11)Online publication date: 23-Sep-2023
  • (2023)Exploring epigenetic drugs as potential inhibitors of SARS-CoV-2 main protease: a docking and MD simulation studyJournal of Biomolecular Structure and Dynamics10.1080/07391102.2023.223671442:13(6892-6903)Online publication date: 17-Jul-2023
  • (2022)Community mapping of COVID-19 cases admitted from April to June 2020 at a tertiary health care hospital in Raigad district in Maharashtra, IndiaMGM Journal of Medical Sciences10.4103/mgmj.mgmj_22_229:2(177)Online publication date: 2022
  • (2021)Worldwide Prediction on COVID-19 Spreading Future Trends using Gaussian ModelInternational Journal of Scientific Research in Science and Technology10.32628/IJSRST218546(291-298)Online publication date: 7-Oct-2021

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