\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[english]{babel}



\usepackage{float}








\begin{document}

\title{Prediction of Global Spread of Covid-19 Pandemic: A Review and Research
Challenges}



\author[1]{Saloni Shah }%
\author[1]{Aos Mulahuwaish }%
\author[2]{Kayhan Ghafoor }%
\author[1]{Halgurd S. Maghdid }%
\affil[1]{Affiliation not available}%
\affil[2]{Salahaddin University-Erbil}%


\vspace{-1em}



  
  \date{June 13, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Since the initial reports of the Coronavirus surfacing in Wuhan, China;
the novel virus currently without a cure has spread like a wildfire
across the globe. The virus spread exponentially across all inhabited
continent; catching local governments by surprise in many cases and
bringing the world economy to a standstill. As local authorities work on
a response to deal with the virus, the scientific community has stepped
in to help analyse and predict the pattern and conditions that would
influence the spread of this unforgiving virus. Using existing
statistical modelling tools to latest AI technology; the scientific
community has used public and privately available data to help with
predictions. A lot of this data research has enabled local authorities
to plan their response -- whether that is to deploy tightly available
medical resources like ventilators or how and when to enforce policies
to social distance including lockdowns. On one hand, this paper shows
what accuracy of research brings to enable fighting this disease; while
on the other hand it also shows what lack of response from local
authorities can do in spreading this virus. This is our attempt in
compiling different research methods and comparing their accuracy in
predicting the spread of COVID-19.%
\end{abstract}%



\sloppy




\selectlanguage{english}
\FloatBarrier
\end{document}

