\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[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Understanding and managing uncertainty and variability for wastewater
monitoring beyond the pandemic: Lessons learned from the United Kingdom
National COVID-19 Surveillance Programmes}



\author[1,1]{Matthew Wade}%
\author[1,1]{Anna Lo Jacomo}%
\author[2,2]{Elena Armenise}%
\author[1,1]{Mathew Brown}%
\author[1,1]{Joshua Bunce}%
\author[3,3]{Graeme Cameron}%
\author[4,4]{Zhou Fang}%
\author[5,5]{Kata Farkas}%
\author[6,6]{Deidre Gilpin}%
\author[7,7]{David Graham}%
\author[1,1]{Jasmine Grimsley}%
\author[2,2]{Alwyn Hart}%
\author[8,8]{Till Hoffmann}%
\author[2,2]{Katherine Jackson}%
\author[5,9]{David Jones}%
\author[1,1]{Chris Lilley}%
\author[10,10]{John McGrath}%
\author[11,11]{Jennifer McKinley}%
\author[11,11]{Cormac McSparron}%
\author[11,11]{Behnam Firoozi Nejad}%
\author[12,12]{Mario Morvan}%
\author[7,7]{Marcos Quintela-Baluja}%
\author[4,4]{Adrian Roberts}%
\author[13,13]{Andrew Singer}%
\author[1,1]{Célia Souque}%
\author[14,14]{Vanessa Speight}%
\author[1,1]{Chris Sweetapple}%
\author[2,2]{Glenn Watts}%
\author[15,15]{Andrew Weightman}%
\author[16,16]{Barbara Kasprzyk-Hordern}%
\affil[1]{Joint Biosecurity Centre, Department of Health and Social Care}%
\affil[2]{Environment Agency}%
\affil[3]{Scottish EnvironmentProtection Agency}%
\affil[4]{Biomathematics and Statistics Scotland}%
\affil[5]{School of Natural Sciences, Bangor University}%
\affil[6]{School of Pharmacy, Queen's University Belfast}%
\affil[7]{School of Engineering, Newcastle University}%
\affil[8]{Department of Mathematics, Imperial College London}%
\affil[9]{School of Natural Sciences}%
\affil[10]{School of Biological Sciences, Queen's University Belfast}%
\affil[11]{School of Natural and Built Environment, Queen's University Belfast}%
\affil[12]{Department of Physics and Astronomy, University College London}%
\affil[13]{UK Centre for Ecology \& Hydrology}%
\affil[14]{Department of Civil and Structural Engineering, Sheffield University}%
\affil[15]{Cardiff School of Biosciences, Cardiff University}%
\affil[16]{Department of Chemistry, University of Bath}%


\vspace{-1em}



  
  \date{May 24, 2024}


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





\selectlanguage{english}
\begin{abstract}
The COVID-19 pandemic has put unprecedented pressure on public health
resources around the world. From adversity opportunities have arisen to
measure the state and dynamics of human disease at a scale not seen
before. Early in the COVID-19 epidemic scientists and engineers
demonstrated the use of wastewater as a medium by which the virus could
be monitored both temporally and spatially. In the United Kingdom this
evidence prompted the development of National wastewater surveillance
programmes involving UK Government agencies academics and private
companies. In terms of speed and scale the programmes have proven to be
unique in its efforts to deliver measures of virus dynamics across a
large proportion of the populations in all four regions of the country.
This success has demonstrated that wastewater-based epidemiology (WBE)
can be a critical component in public health protection at regional and
national levels and looking beyond COVID-19 is likely to be a core tool
in monitoring and informing on a range of biological and chemical
markers of human health; some established (e.g. pharmaceutical usage)
and some emerging (e.g. metabolites of stress). We present here a
discussion of uncertainty and variation associated with surveillance of
wastewater focusing on lessons-learned from the UK programmes monitoring
COVID-19 but addressing the areas that can broadly be applied to WBE
more generally. Through discussion and the use of case studies we
highlight that sources of uncertainty and variability that can impact
measurement quality and importantly interpretation of data for public
health decision-making are varied and complex. While some factors remain
poorly understood and require dedicated research we present approaches
taken by the UK programmes to manage and mitigate the more tractable
components. This work provides a platform to integrate uncertainty
management through data analysis quality assurance and modelling into
the inevitable expansion of WBE activities as part of One Health
initiatives.%
\end{abstract}%



\sloppy




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

