\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{Association between different screening strategies for SARS-CoV-2 and
deaths and severe disease in Italy.}



\author[1]{Edoardo Mannucci}%
\author[2]{Antonio Siilverii}%
\author[2]{Matteo Monami}%
\affil[1]{University of Florence}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 20, 2024}


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





\selectlanguage{english}
\begin{abstract}
Background The WHO recommends testing any suspected person with Severe
Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2), in order to limit
the spread of the epidemic. In Italy, some Regions opted for extensive
testing, whereas others limited tests to selected subjects. To assess
the influence of different strategies, we examined the incidence of
death and severe cases in Italy. Methods Data on new cases of
SARS-CoV-2, number of tests, deaths, and admissions to Intensive Care
Units (ICU) were retrieved in each Italian Region, from February 24th to
March 18th, 2020. As an index of different screening strategies, the
number of tests/positive test results (T/P) ratio as of March 7th, 2020,
was considered. The cumulative number of deaths and of new severe cases,
between March 23thand 25th was recorded. The association of those two
outcomes with the number of T/P ratio was assessed using linear
regression models. Results In the interval between March 23th-25th,
recorded deaths (*million inhabitants) were 14(3-54), whereas severe
cases were 31(10-112). Both the number of deaths and that of severe
cases showed a significant correlation (R2 .38 and .37, with
p\textless{}.01) with the T/P ratio. Deaths and severe cases were
associated with higher mean personal income and lower density of General
Practioners (GPs). The association of T/P with severe cases and deaths
retained statistical significance after adjusting for mean personal
income (R2 .20 and .21, respectively; both p=.04) and GPs density (R2.22
and .21, respectively; both p=.03). Conclusions A more aggressive
screening strategy for SARS-Cov-2, was associated with lower rates of
death and severe disease in Regions of Italy.%
\end{abstract}%



\sloppy


\textbf{Introduction}

The World Health Organization recommends to test any suspected person
with Severe Acute Respiratory Syndrome CoronaVirus-2
(SARS-CoV-2)\textsuperscript{1}, in order to isolate positive
individuals, limiting the spread of the epidemic. On the other hand,
extensive isolation of oligosymptomatic infected people and of their
close contacts, including many healthcare professionals, could reduce
the efficiency of healthcare systems in responding to the epidemic.
These different viewpoints are currently debated in Italy, where the
healthcare system has a Regional organization; different Regions have
adopted opposite strategies in this respect. Some Regions (e.g., Veneto)
opted for extensive testing, thus organizing laboratory facilities,
whereas others (e.g., Lombardia, Emilia-Romagna, and Piemonte) limited
diagnostic tests to selected subjects. Conversely, social distancing and
isolation measures (including lockdown) were decided at a National
level. To assess the potential influence of different testing
strategies, we examined the incidence of death and severe cases in 19
regions of Italy.

\textbf{Methods}

We retrieved daily data on new cases of SARS-CoV-2 (i.e., individuals
with positive test results), number of tests (reverse transcription
polymerase chain reaction; RT-PCR) performed, deaths, and admissions to
Intensive Care Units (ICU) in each Region, from February
24\textsuperscript{th} to March 18\textsuperscript{th}, 2020, obtained
from the Health Ministry website\textsuperscript{2}. Demographic,
socioeconomic and healthcare organization data were retrieved from the
National Institute of Statistics (ISTAT)\textsuperscript{3}.

As an index of different screening strategies, the number of
tests/positive test results (T/P) ratio as of March
7\textsuperscript{th}, 2020, was considered. The subsequent evolution of
the epidemic was assessed through the cumulative number of deaths and of
new severe cases, between March 23\textsuperscript{th} and
25\textsuperscript{th}, inclusive; the latter were defined as a
composite of death and admission to ICU. This work is based on publicly
available data, needing no ethical approval.

The association of those two outcomes with the number of T/Pratio at
March 7th was assessed using a linear regression model. For each
confounder significantly associated with outcomes, multivariate linear
regression models were applied to assess the independent contribution of
T/P, assuming two-sided p\textless{}.05 as significant. Analyses were
performed on SPSS (SPSS-Inc., Chicago, IL, USA) 25.0.

\textbf{Results}

The median number of tests per million inhabitants performed as of March
7\textsuperscript{th} in different Regions (with interquartile range)
was 240 (105-474), ranging from 58 to 2941. The median prevalence of
known SARS-CoV-2 infection was 27 (7-64) cases per million, ranging from
2 to 273. The number of tests and that of individuals with positive test
results showed a significant correlation (r=0.61, p=0.006). The T/Pratio
was 11.2 (5.0-19.8), with a range of 3.6-28.2. In the interval between
March 23\textsuperscript{th}and 25\textsuperscript{th}, recorded deaths
per million inhabitants were 14(3-54), with a range of 2-119, whereas
severe cases (ICU+death) were 31(10-112), ranging from 4to 271. Both the
number of deaths and that of severe cases on March
23\textsuperscript{th}-25\textsuperscript{th} showed a significant
correlation (R\textsuperscript{2} .38 and .37, with p=.004 and .006,
respectively) with the T/P ratio up to March
7\textsuperscript{th}(Figure 1). With the exclusion of apparent outlier
Lombardia, R\textsuperscript{2} for the correlation of deaths and severe
cases were .36 (p=.009) and .34 (p=.01), respectively.

Deaths and severe cases were associated with higher mean personal income
and lower density of General Practioners (GPs); deaths were also
associated with higher population density (Table 1). The association of
T/P with severe cases and deaths retained statistical significance after
adjusting for mean personal income (R\textsuperscript{2} .20 and .21,
respectively; both p=.04) and GPs density (R\textsuperscript{2}.22 and
.21, respectively; both p=.03).

\textbf{Discussion}

A higher number of tests/positive test results ratio, reflecting a more
aggressive screening strategy for SARS-Cov-2, was associated with lower
rates of death and severe disease in Regions of Italy. Although the
association was maintained after adjusting for some confounders, the
possibility of other unaccounted confounders cannot be excluded.
Moreover, results are specific for the time range considered. Despite
these limitations, this association should be considered by
policy-makers in other Countries faced by the threat of the epidemic.

\textbf{References}

\begin{enumerate}
\tightlist
\item
  \emph{https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen};
  Accessed April 1\textsuperscript{st}, 2020.
\item
  \emph{https://github.com/pcm-dpc/COVID-19/blob/master/dati-regioni/dpc-covid19-ita-regioni.csv};
  Accessed April 1\textsuperscript{st}, 2020.
\item
  \emph{http://dati.istat.it/}; Accessed April 1\textsuperscript{st},
  2020.
\end{enumerate}

\textbf{Acknowledgment section}

\textbf{Conflict of Interest Disclosures}

Dr Monami reports personal fees from Astra Zeneca,personal fees from
Boehringer-Ingelheim, personal fees from Eli-Lilly, personal fees from
Novo Nordisk, personal fees from Sanofi, and personal fees from
Takedaoutside the submitted work; Dr Mannucci reports grants and
personal fees from AstraZeneca, personal fees from Abbott, grants and
personal fees from Boehringer Ingelheim, grants and personal fees from
Eli Lilly, grants from Genentech, grants from Molteni, personal fees
from Merck, grants and personal fees from Novo Nordisk, and personal
fees from Sanofi outside the submitted work.

\textbf{Role of funding}

This research was performed as a part of the institutional activity of
the unit, with no specific funding. All expenses, including salaries of
the investigators, were covered by public research funds assigned to the
unit.

\textbf{Access to data and Data Analysis}

The corresponding author had full access to all the data in the study
and takes responsibility for the integrity of the data and the accuracy
of the data analysis.

\textbf{Legend to figure}

\textbf{Figure 1 --} Association of screening strategies with the
outcome of the SARS-CoV-2 infection. Linear regression models for the
association of severe cases (panel A) and deaths (panel B) on March
23\textsuperscript{rd}-25\textsuperscript{th} with the number of
tests/positive test results ratio up to March 7\textsuperscript{th}.

\textbf{Tables}

\textbf{Table 1 --} Unadjustedlinear regression models for the
association of deathsand severe caseswith different parameters.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& & & \textbf{23\textsuperscript{rd}--25\textsuperscript{th} March} &
\textbf{23\textsuperscript{rd}--25\textsuperscript{th} March} &
\textbf{23\textsuperscript{rd}--25\textsuperscript{th} March} &
\textbf{23\textsuperscript{rd}--25\textsuperscript{th}
March}\tabularnewline
\midrule
\endhead
\textbf{Parameters} & \textbf{Median {[}quartiles{]}} & \textbf{Range} &
\textbf{Deaths} & \textbf{Deaths} & \textbf{Severe cases} &
\textbf{Severe cases}\tabularnewline
& & & \emph{R\textsuperscript{2}} & \emph{p} &
\emph{R\textsuperscript{2}} & \emph{p}\tabularnewline
Age (years) & 45 {[}44-46{]} & 42-48 & .23 & .35 & .23 &
.35\tabularnewline
Age[?]65 years (\%) & 23 {[}21-25{]} & 20-30 & .27 & .28 & .27 &
.28\tabularnewline
Urbanization rate (\%) & 25 {[}17-36{]} & 0-60 & .20 & .41 & .20 &
.41\tabularnewline
Density (inh./Km\textsuperscript{2}) & 162 {[}104-267{]} & 39-424 & .31
& .21 & .31 & .21\tabularnewline
Personal income (1000\textbackslash{}euro/inh.) & 30 {[}25-32{]} & 22-35
& .62 & .006 & .62 & .006\tabularnewline
Public health expenditure
(\textbackslash{}euro/inh.)\textsuperscript{\#} & 1848 {[}1804-2022{]} &
1730-2113 & .18 & .47 & .18 & .47\tabularnewline
Intensive Care beds/mln*inh\textsuperscript{\#} & 81 {[}74-100{]} &
23-307 & .05 & .83 & .05 & .83\tabularnewline
General Practitioners/mln*inh.\textsuperscript{\#} & 735 {[}692-809{]} &
623-852 & .65 & .003 & .65 & .003\tabularnewline
\bottomrule
\end{longtable}

*2019; mln: million; inh.: inhabitants.

\textbf{Figure 1}

Panel A\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Panel B\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

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

