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\makeglossaries
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\input{../data_mining_glossary.tex}

\begin{document}
\MyTitle{Bussiness Understanding Report}
\tableofcontents
\printglossary[type=bus]
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\section{Main papers that will be used in this work}

\Gls{latex} is not cool. It never works.

A \gls{model} is a model.

\begin{itemize}
    \item the fluprint database paper \cite{tomicFluPRINTDatasetMultidimensional2019}
    \item other papers
\end{itemize}

\section{background}

\cite{GuidanceIndustryClinical2007}
Influenza viruses are enveloped ribonucleic acid viruses belonging to the family of
Orthomyxoviridae and are divided into three distinct types on the basis of antigenic differences
of internal structural proteins (Ref. 2). Two influenza types, Type A and B, are responsible for
yearly epidemic outbreaks of respiratory illness in humans and are further classified based on the
structure of two major external glycoproteins, hemagglutinin (HA) and neuraminidase (NA).
Type B viruses, which are largely restricted to the human host, have a single HA and NA
subtype. In contrast, numerous HA and NA Type A influenza subtypes have been identified to
date. Type A strains infect a wide variety of avian and mammalian species.
Type A and B influenza variant strains emerge as a result of frequent antigenic change,
principally from mutations in the HA and NA glycoproteins. These variant strains may arise
through one of two mechanisms: selective point mutations in the viral genome (Refs. 3 and 4) or
from reassortment between two co-circulating strains (Refs. 5 and 6).
Since 1977, influenza A virus subtypes H1N1 and H3N2, and influenza B viruses have been in
global circulation in humans. The current U.S. licensed inactivated trivalent vaccines are
formulated to prevent influenza illness caused by these influenza viruses. Because of the
frequent emergence of new influenza variant strains, the antigenic composition of influenza
vaccines needs to be evaluated yearly, and the trivalent inactivated influenza vaccines are
reformulated almost every year. The immune response elicited by previous vaccination may not
be protective against new variants.
The Centers for Disease Control and Prevention’s (CDC’s) Advisory Committee on
Immunization Practices (ACIP) has expanded the recommendations for receipt of influenza
vaccination to include an increasing scope of at risk populations, currently including pregnant
women, persons 50 years of age and older, and children 6 to 59 months of age (Refs. 7, 8, and 9).

Increased demand for influenza vaccines, including that resulting from the broader
recommendations, the withdrawal from the U.S. market by several influenza vaccine
manufacturers, and intermittent decreases in vaccine production due to manufacturing problems
have led to shortages or delays in the availability of influenza vaccine over the past several
seasons. These shortages highlight both the complexity of the production process and the need
to increase the availability of influenza vaccines from multiple manufacturers. Currently, even
with full production, manufacturing capacity would not produce enough seasonal influenza
vaccine to vaccinate all those for whom the vaccine is now recommended. Finally, the
availability of adequate supplies of licensed seasonal inactivated influenza vaccines from
multiple manufacturers will be of value in responding to the emergence of a new pandemic
influenza strain.

\subsection{Influenza mortality papers}

\cite{thompsonMortalityAssociatedInfluenza2003}
Context  Influenza and respiratory syncytial virus (RSV) cause substantial
morbidity and mortality. Statistical methods used to estimate deaths in the
United States attributable to influenza have not accounted for RSV circulation.

Objective  To develop a statistical model using national mortality and viral
surveillance data to estimate annual influenza- and RSV-associated deaths in
the United States, by age group, virus, and influenza type and subtype.

Design, Setting, and Population  Age-specific Poisson regression models using
national viral surveillance data for the 1976-1977 through 1998-1999 seasons
were used to estimate influenza-associated deaths. Influenza- and
RSV-associated deaths were simultaneously estimated for the 1990-1991 through
1998-1999 seasons.

Main Outcome Measures  Attributable deaths for 3 categories: underlying
pneumonia and influenza, underlying respiratory and circulatory, and all
causes.

Results  Annual estimates of influenza-associated deaths increased
significantly beween the 1976-1977 and 1998-1999 seasons for all 3 death
categories (P<.001 for each category). For the 1990-1991 through 1998-1999
seasons, the greatest mean numbers of deaths were associated with influenza
A(H3N2) viruses, followed by RSV, influenza B, and influenza A(H1N1). Influenza
viruses and RSV, respectively, were associated with annual means (SD) of 8097
(3084) and 2707 (196) underlying pneumonia and influenza deaths, 36 155 (11
055) and 11 321 (668) underlying respiratory and circulatory deaths, and 51 203
(15 081) and 17 358 (1086) all-cause deaths. For underlying respiratory and
circulatory deaths, 90\% of influenza- and 78\% of RSV-associated deaths occurred
among persons aged 65 years or older. Influenza was associated with more deaths
than RSV in all age groups except for children younger than 1 year. On average,
influenza was associated with 3 times as many deaths as RSV.

Conclusions  Mortality associated with both influenza and RSV circulation
disproportionately affects elderly persons. Influenza deaths have increased
substantially in the last 2 decades, in part because of aging of the
population, underscoring the need for better prevention measures, including
more effective vaccines and vaccination programs for elderly persons.

Influenza infections result in substantial morbidity and mortality nearly every
year1,2 and estimates of this burden have played a pivotal role in formulating
influenza vaccination policy in the United States.3 However, numbers of deaths
attributable to influenza are difficult to estimate directly because influenza
infections typically are not confirmed virologically or specified on hospital
discharge forms or death certificates. In addition, many influenza-associated
deaths occur from secondary complications when influenza viruses are no longer
detectable.4,5 Nonetheless, wintertime influenza epidemics have been shown to
be associated with increased hospitalizations and mortality for many diagnoses,
including congestive heart failure, chronic obstructive pulmonary disease,
pneumonia, and bacterial superinfections.6-9

Respiratory syncytial virus (RSV) epidemics often overlap with influenza
epidemics,8,10 and RSV infections have been associated with substantial
morbidity and mortality in young children and more recently in older
adults.10-14 Like influenza, RSV infections can precipitate both cardiac and
pulmonary complications.15-17 Respiratory syncytial virus infections are rarely
diagnosed in adults, in part because available rapid antigen-detection tests
are insensitive in adults and few tests for RSV are requested for this age
group by medical practitioners.16,18 It is likely that some deaths previously
attributed to influenza are actually associated with RSV infection.13,14,19

In this study, we provide age-specific estimates of deaths attributable to
influenza, by virus type and subtype, and to RSV using Poisson regression
models that incorporates national respiratory viral surveillance data. Recent
deliberations of the Advisory Committee on Immunization Practices (ACIP)
regarding influenza vaccination recommendations3 guided our choice of age
groups for these analyses.

\cite{greenMortalityAttributableInfluenza2013}
Very different influenza seasons have been observed from 2008/09-2011/12 in
England and Wales, with the reported burden varying overall and by age group.
The objective of this study was to estimate the impact of influenza on
all-cause and cause-specific mortality during this period. Age-specific
generalised linear regression models fitted with an identity link were
developed, modelling weekly influenza activity through multiplying clinical
influenza-like illness consultation rates with proportion of samples positive
for influenza A or B. To adjust for confounding factors, a similar activity
indicator was calculated for Respiratory Syncytial Virus. Extreme temperature
and seasonal trend were controlled for. Following a severe influenza season in
2008/09 in 65+yr olds (estimated excess of 13,058 influenza A all-cause
deaths), attributed all-cause mortality was not significant during the 2009
pandemic in this age group and comparatively low levels of influenza A
mortality were seen in post-pandemic seasons. The age shift of the burden of
seasonal influenza from the elderly to young adults during the pandemic
continued into 2010/11; a comparatively larger impact was seen with the same
circulating A(H1N1)pdm09 strain, with the burden of influenza A all-cause
excess mortality in 15–64 yr olds the largest reported during 2008/09–2011/12
(436 deaths in 15–44 yr olds and 1,274 in 45–64 yr olds). On average, 76\% of
seasonal influenza A all-age attributable deaths had a cardiovascular or
respiratory cause recorded (average of 5,849 influenza A deaths per season),
with nearly a quarter reported for other causes (average of 1,770 influenza A
deaths per season), highlighting the importance of all-cause as well as
cause-specific estimates. No significant influenza B attributable mortality was
detected by season, cause or age group. This analysis forms part of the
preparatory work to establish a routine mortality monitoring system ahead of
introduction of the UK universal childhood seasonal influenza vaccination
programme in 2013/14.

\cite{iulianoEstimatesGlobalSeasonal2018}
Background
Estimates of influenza-associated mortality are important for national and
international decision making on public health priorities. Previous estimates
of 250.000 500.000 annual influenza deaths are outdated. We updated the
estimated number of global annual influenza-associated respiratory deaths using
country-specific influenza-associated excess respiratory mortality estimates
from 1999–2015.
Methods
We estimated country-specific influenza-associated respiratory excess mortality
rates (EMR) for 33 countries using time series log-linear regression models
with vital death records and influenza surveillance data. To extrapolate
estimates to countries without data, we divided countries into three analytic
divisions for three age groups (<65 years, 65-74 years, and >=75 years) using
WHO Global Health Estimate (GHE) respiratory infection mortality rates. We
calculated mortality rate ratios (MRR) to account for differences in risk of
influenza death across countries by comparing GHE respiratory infection
mortality rates from countries without EMR estimates with those with estimates.
To calculate death estimates for individual countries within each age-specific
analytic division, we multiplied randomly selected mean annual EMRs by the
country's MRR and population. Global 95\% credible interval (CrI) estimates were
obtained from the posterior distribution of the sum of country-specific
estimates to represent the range of possible influenza-associated deaths in a
season or year. We calculated influenza-associated deaths for children younger
than 5 years for 92 countries with high rates of mortality due to respiratory
infection using the same methods.
Findings
EMR-contributing countries represented 57\% of the global population. The
estimated mean annual influenza-associated respiratory EMR ranged from 0.1 to
6.4 per 100.000 individuals for people younger than 65 years, 2.9 to 44.0 per
100.000 individuals for people aged between 65 and 74 years, and 17.9 to 223.5
per 100.000 for people older than 75 years. We estimated that 291 243–645 832
seasonal influenza-associated respiratory deaths (4.0–8.8 per 100.000
individuals) occur annually. The highest mortality rates were estimated in
sub-Saharan Africa (2.8–16.5 per 100 000 individuals), southeast Asia (3.5-9.2
per 100.000 individuals), and among people aged 75 years or older (51.3-99.4
per 100.000 individuals). For 92 countries, we estimated that among children
younger than 5 years, 9243-105 690 influenza-associated respiratory deaths
occur annually.
Interpretation
These global influenza-associated respiratory mortality estimates are higher
than previously reported, suggesting that previous estimates might have
underestimated disease burden. The contribution of non-respiratory causes of
death to global influenza-associated mortality should be investigated.

\subsection{Vaccine success criteria}
\cite{zhouHospitalizationsAssociatedInfluenza2012}

Background. Age-specific comparisons of influenza and respiratory syncytial
virus (RSV) hospitalization rates can inform prevention efforts, including
vaccine development plans. Previous US studies have not estimated jointly the
burden of these viruses using similar data sources and over many seasons.

Methods. We estimated influenza and RSV hospitalizations in 5 age categories
(<1, 1–4, 5–49, 50–64, and >=65 years) with data for 13 states from 1993–1994
through 2007–2008. For each state and age group, we estimated the contribution
of influenza and RSV to hospitalizations for respiratory and circulatory
disease by using negative binomial regression models that incorporated weekly
influenza and RSV surveillance data as covariates.

Results. Mean rates of influenza and RSV hospitalizations were 63.5 (95\%
confidence interval [CI], 37.5–237) and 55.3 (95\% CI, 44.4–107) per 100000
person-years, respectively. The highest hospitalization rates for influenza
were among persons aged >=65 years (309/100000; 95\% CI, 186–1100) and those aged
<1 year (151/100000; 95\% CI, 151–660). For RSV, children aged <1 year had the
highest hospitalization rate (2350/100000; 95\% CI, 2220–2520) followed by those
aged 1–4 years (178/100000; 95\% CI, 155–230). Age-standardized annual rates per
100000 person-years varied substantially for influenza (33–100) but less for
RSV (42–77).

Conclusions. Overall US hospitalization rates for influenza and RSV are
similar; however, their age-specific burdens differ dramatically. Our estimates
are consistent with those from previous studies focusing either on influenza or
RSV. Our approach provides robust national comparisons of hospitalizations
associated with these 2 viral respiratory pathogens by age group and over time.

\cite{GuidanceIndustryClinical2007}
something about the effectiveness of vaccines.

\cite{dejongHaemagglutinationinhibitingAntibodyInfluenza2003}

The results of the haemagglutination-inhibiting (HI) antibody test for
influenza virus antibody in human sera closely match those produced by virus
neutralization assays and are predictive of protection. On the basis of the
data derived from 12 publications concerning healthy adults, we estimated the
median HI titre protecting 50\% of the vaccinees against the virus concerned at
28. This finding supports the current policy requiring vaccines to induce serum
HI titres of > or = 40 to the vaccine viruses in the majority of the vaccinees.
Unfortunately similar studies are scanty for the elderly, the group most at
risk of influenza. There still remain many unsolved technical problems with the
HI assay and we recommend that these problems be studied and the virus
neutralization test as a predictor of resistance to influenza be assessed.
Although the studies on this issue often give conflicting results, they
generally show that HI antibody responses to influenza vaccination tend to
diminish with increasing age, when health is often compromized. Advanced age in
itself seems not to be an independent factor in this process. However, even in
completely healthy elderly individuals the response to vaccination with an
antigenically new virus may be strongly reduced compared with younger
vaccinees.

\subsection{antibody response vaccine}
\cite{sridharCellularImmuneCorrelates2013}
The role of T cells in mediating heterosubtypic protection against natural
influenza illness in humans is uncertain.  The 2009 H1N1 pandemic (pH1N1)
provided a unique natural experiment to determine whether crossreactive
cellular immunity limits symptomatic illness in antibody-naive individuals. We
followed 342 healthy adults through the UK pandemic waves and correlated the
responses of pre-existing T cells to the pH1N1 virus and conserved core protein
epitopes with clinical outcomes after incident pH1N1 infection. Higher
frequencies of pre-existing T cells to conserved CD8 epitopes were found in
individuals who developed less severe illness, with total symptom score having
the strongest inverse correlation with the frequency of interferon-g (IFN-g)+
interleukin-2 (IL-2)− CD8+ T cells (r = −0.6, P = 0.004). Within this
functional CD8+IFN-g+IL-2− population, cells with the CD45RA+ chemokine (C-C)
receptor 7 (CCR7)− phenotype inversely correlated with symptom score and had
lung-homing and cytotoxic potential. In the absence of crossreactive
neutralizing antibodies, CD8+ T cells specific to conserved viral epitopes
correlated with crossprotection against symptomatic influenza. This protective
immune correlate could guide universal influenza vaccine development.

\cite{bentebibelInductionICOSCXCR3}
The role of T cells in mediating heterosubtypic protection against natural
influenza illness in humans is uncertain.  The 2009 H1N1 pandemic (pH1N1)
provided a unique natural experiment to determine whether crossreactive
cellular immunity limits symptomatic illness in antibody-naive individuals. We
followed 342 healthy adults through the UK pandemic waves and correlated the
responses of pre-existing T cells to the pH1N1 virus and conserved core protein
epitopes with clinical outcomes after incident pH1N1 infection. Higher
frequencies of pre-existing T cells to conserved CD8 epitopes were found in
individuals who developed less severe illness, with total symptom score having
the strongest inverse correlation with the frequency of interferon-g (IFN-g)+
interleukin-2 (IL-2)− CD8+ T cells (r = −0.6, P = 0.004). Within this
functional CD8+IFN-g+IL-2− population, cells with the CD45RA+ chemokine (C-C)
receptor 7 (CCR7)− phenotype inversely correlated with symptom score and had
lung-homing and cytotoxic potential. In the absence of crossreactive
neutralizing antibodies, CD8+ T cells specific to conserved viral epitopes
correlated with crossprotection against symptomatic influenza. This protective
immune correlate could guide universal influenza vaccine development.

\cite{trieuLongtermMaintenanceInfluenzaSpecific2017}
Background. Annual vaccination for healthcare workers and other high-risk
groups is the mainstay of the public health strategy to combat influenza.
Inactivated influenza vaccines confer protection by inducing neutralizing
antibodies efficiently against homologous and closely matched virus strains. In
the absence of neutralizing antibodies, cross-reactive T cells have been shown
to limit disease severity. However, animal studies and a study in
immunocompromised children suggested that repeated vaccination hampers CD8+ T
cells. Yet the impact of repeated annual influenza vaccination on both
cross-reactive CD4+ and CD8+ T cells has not been explored, particularly in
healthy adults.  Methods. We assembled a unique cohort of healthcare workers
who received a single AS03-adjuvanted H1N1pdm09 vaccine in 2009 and
subsequently either repeated annual vaccination or no further vaccination
during 2010–2013. Blood samples were collected before the influenza season or
vaccination to assess antibody and T-cell responses.  Results. Antibody titers
to H1N1pdm09 persisted above the protective level in both the repeated- and
single-vaccination groups.  The interferon γ+ (IFN-γ+) and multifunctional CD4+
T-cell responses were maintained in the repeated group but declined
significantly in the single-vaccination group. The IFN-γ+CD8+ T cells remained
stable in both groups.  Conclusions. This study provides the immunological
evidence base for continuing annual influenza vaccination in adults.

\subsection{Machine learning usage}

\cite{furmanApoptosisOtherImmune2013}
Despite the importance of the immune system in many diseases, there are
currently no objective benchmarks of immunological health. In an effort to
identifying such markers, we used influenza vaccination in 30 young (20–30
years) and 59 older subjects (60 to >89 years) as models for strong and weak
immune responses, respectively, and assayed their serological responses to
influenza strains as well as a wide variety of other parameters, including gene
expression, antibodies to hemagglutinin peptides, serum cytokines, cell subset
phenotypes and in vitro cytokine stimulation. Using machine learning, we
identified nine variables that predict the antibody response with 84\% accuracy.
Two of these variables are involved in apoptosis, which positively associated
with the response to vaccination and was confirmed to be a contributor to
vaccine responsiveness in mice. The identification of these biomarkers provides
new insights into what immune features may be most important for immune health.

\cite{sobolevAdjuvantedInfluenzaH1N1Vaccination2016}
Adjuvanted vaccines afford invaluable protection against disease, and the
molecular and cellular changes they induce offer direct insight into human
immunobiology. Here we show that within 24 h of receiving adjuvanted swine flu
vaccine, healthy individuals made expansive, complex molecular and cellular
responses that included overt lymphoid as well as myeloid contributions.
Unexpectedly, this early response was subtly but significantly different in
people older than ~35 years. Wide-ranging adverse clinical events can seriously
confound vaccine adoption, but whether there are immunological correlates of
these is unknown.  Here we identify a molecular signature of adverse events
that was commonly associated with an existing B cell phenotype. Thus
immunophenotypic variation among healthy humans may be manifest in complex
pathophysiological responses.

\cite{tsangGlobalAnalysesHuman2014}
A major goal of systems biology is the development of models that accurately
predict responses to perturbation. Constructing such models requires the
collection of dense measurements of system states, yet transformation of data
into predictive constructs remains a challenge. To begin to model human
immunity, we analyzed immune parameters in depth both at baseline and in
response to influenza vaccination. Peripheral blood mononuclear cell
transcriptomes, serum titers, cell subpopulation frequencies, and B cell
responses were assessed in 63 individuals before and after vaccination and were
used to develop a systematic framework to dissect inter- and intra-individual
variation and build predictive models of postvaccination antibody responses.
Strikingly, independent of age and pre-existing antibody titers, accurate
models could be constructed using pre-perturbation cell populations alone,
which were validated using independent baseline time points. Most of the
parameters contributing to prediction delineated temporally stable baseline
differences across individuals, raising the prospect of immune monitoring
before intervention.

\subsection{Problems of previous studies}
\cite{chattopadhyaySinglecellTechnologiesMonitoring2014}
The complex heterogeneity of cells, and their interconnectedness with each
other, are major challenges to identifying clinically relevant measurements
that reflect the state and capability of the immune system. Highly multiplexed,
single-cell technologies may be critical for identifying correlates of disease
or immunological interventions as well as for elucidating the underlying
mechanisms of immunity. Here we review limitations of bulk measurements and
explore advances in single-cell technologies that overcome these problems by
expanding the depth and breadth of functional and phenotypic analysis in space
and time. The geometric increases in complexity of data make formidable hurdles
for exploring, analyzing and presenting results. We summarize recent approaches
to making such computations tractable and discuss challenges for integrating
heterogeneous data obtained using these single-cell technologies.

\cite{galliEndOmicsHigh2019}
High-dimensional single-cell (HDcyto) technologies, such as mass cytometry
(CyTOF) and flow cytometry, are the key techniques that hold a great promise
for deciphering complex biological processes. During the last decade, we
witnessed an exponential increase of novel HDcyto technologies that are able to
deliver an in-depth profiling in different settings, such as various autoimmune
diseases and cancer. The concurrent advance of custom data-mining algorithms
has provided a rich substrate for the development of novel tools in
translational medicine research. HDcyto technologies have been successfully
used to investigate cellular cues driving pathophysiological conditions, and to
identify disease-specific signatures that may serve as diagnostic biomarkers or
therapeutic targets. These technologies now also offer the possibility to
describe a complete cellular environment, providing unanticipated insights into
human biology. In this review, we present an update on the current cutting-edge
HDcyto technologies and their applications, which are going to be fundamental
in providing further insights into human immunology and pathophysiology of
various diseases. Importantly, we further provide an overview of the main
algorithms currently available for data mining, together with the conceptual
workflow for high-dimensional cytometric data handling and analysis. Overall,
this review aims to be a handy overview for immunologists on how to design,
develop and read HDcyto data.

\cite{simoniMassCytometryPowerful2018}
Advancement in methodologies for single cell analysis has historically been a
major driver of progress in immunology. Currently, high dimensional flow
cytometry, mass cytometry and various forms of single cell sequencing-based
analysis methods are being widely adopted to expose the staggering
heterogeneity of immune cells in many contexts. Here, we focus on mass
cytometry, a form of flow cytometry that allows for simultaneous interrogation
of more than 40 different marker molecules, including cytokines and
transcription factors, without the need for spectral compensation. We argue
that mass cytometry occupies an important niche within the landscape of
single-cell analysis platforms that enables the efficient and in-depth study of
diverse immune cell subsets with an ability to zoom-in on myeloid and lymphoid
compartments in various tissues in health and disease. We further discuss the
unique features of mass cytometry that are favorable for combining multiplex
peptide-MHC multimer technology and phenotypic characterization of antigen
specific T cells. By referring to recent studies revealing the complexities of
tumor immune infiltrates, we highlight the particular importance of this
technology for studying cancer in the context of cancer immunotherapy. Finally,
we provide thoughts on current technical limitations and how we imagine these
being overcome.

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\bibliography{../references.bib}
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