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\begin{document}

\title{Influenza A virus transmission in swine farms and during transport in
the swine supply chain}



\author[1]{Jonathan Tin Lai Cheung}%
\author[1]{Eric Lau}%
\author[1]{Ziying Jin}%
\author[1]{Huachen Zhu}%
\author[1]{Yi Guan}%
\author[1]{Malik Piere}%
\affil[1]{The University of Hong Kong School of Public Health}%


\vspace{-1em}



  
  \date{May 05, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The last influenza pandemic in 2009 emerged from swine and surveillance
of swine influenza is important for pandemic preparedness. Movement of
swine during husbandry, trade or marketing for slaughter provide
opportunities for transfer and possible genetic reassortment of swine
influenza viruses. Over 90\% of the swine slaughtered at the central
swine abattoir in Hong Kong are imported from farms located in multiple
provinces in mainland China. There is opportunity for virus
cross-infection during this transport and slaughter process. Of the
26,980 swabs collected in the slaughterhouse in Hong Kong from 5
\textsuperscript{th} January 2012 to 15 \textsuperscript{th} December
2016, we analyzed sequence data on influenza A (H3N2) virus isolates (n
= 174) in conjunction with date of sampling and originating farm.
Molecular epidemiology provided evidence of virus cross-infection
between swine originating from different farms during transport and also
evidence of a virus lineage persisting in a swine farm for over 2 years.
We used virus serology and isolation data from 4,226 paired pig serum
and nasal swabs collected from swine originating from Guangdong Province
to compare the force of infection (FOI) during transport and within
farms. The mean weekly FOI during transport was \selectlanguage{greek}λ \selectlanguage{english}\textsubscript{t} =
0.0286 (95\% CI = 0.0211-0.0391) while the weekly FOI in farms was \selectlanguage{greek}λ
\selectlanguage{english}\textsubscript{f} = 0.0089 (95\% CI = 0.0084-0.0095), assuming a
duration of stay in farm of 28 weeks, suggesting increased force of
infection during the transport process. Potential risk factors for
infection including the duration in transport, length of stay at
slaughterhouse and farm-level seroprevalence were also assessed by
multivariable logistic regression analysis. Transport may increase virus
cross-infection rates and provide opportunities for virus reassortment
potentially increasing zoonotic risk to those involved in the
transportation and slaughtering processes.%
\end{abstract}%



\sloppy


\textbf{Influenza A virus transmission in swine farms and during
transport in the swine supply chain}

Jonathan Tin Lai Cheung\textsuperscript{1}, Eric HY
Lau\textsuperscript{1}, Ziying Jin\textsuperscript{1,2,3}, Huachen
Zhu\textsuperscript{1,2,3}, Yi Guan\textsuperscript{1,2,3}, Malik
Peiris\textsuperscript{1}

\textsuperscript{1} School of Public Health, The University of Hong Kong

\textsuperscript{2} State Key Laboratory of Emerging Infectious
Diseases, School of Public Health, The University of Hong Kong, Hong
Kong, P. R. China.

\textsuperscript{3} Guangdong-Hong Kong Joint Laboratory of Emerging
Infectious Diseases/Joint Laboratory for International Collaboration in
Virology and Emerging Infectious Diseases, Joint Institute of Virology
(Shantou University and The University of Hong Kong), Shantou
University, Shantou, P. R. China.

Address correspondence to:

Malik Peiris, School of Public Health, The University of Hong Kong, Hong
Kong SAR, P.R. China Email: malik@hku.hk

Yi Guan, State Key Laboratory of Emerging Infectious Diseases, School of
Public Health, The University of Hong Kong, Hong Kong SAR, P. R. China.
Email: yguan@hku.hk





\textbf{Summary:}

The last influenza pandemic in 2009 emerged from swine and surveillance
of swine influenza is important for pandemic preparedness. Movement of
swine during husbandry, trade or marketing for slaughter provide
opportunities for transfer and possible genetic reassortment of swine
influenza viruses. Over 90\% of the swine slaughtered at the central
swine abattoir in Hong Kong are imported from farms located in multiple
provinces in mainland China. There is opportunity for virus
cross-infection during this transport and slaughter process. Of the
26,980 swabs collected in the slaughterhouse in Hong Kong from
5\textsuperscript{th} January 2012 to 15\textsuperscript{th} December
2016, we analyzed sequence data on influenza A (H3N2) virus isolates (n
= 174) in conjunction with date of sampling and originating farm.
Molecular epidemiology provided evidence of virus cross-infection
between swine originating from different farms during transport and also
evidence of a virus lineage persisting in a swine farm for over 2 years.
We used virus serology and isolation data from 4,226 paired pig serum
and nasal swabs collected from swine originating from Guangdong Province
to compare the force of infection (FOI) during transport and within
farms. The mean weekly FOI during transport was \selectlanguage{greek}λ\selectlanguage{english}\textsubscript{t} =
0.0286 (95\% CI = 0.0211-0.0391) while the weekly FOI in farms was
\selectlanguage{greek}λ\selectlanguage{english}\textsubscript{f} = 0.0089 (95\% CI = 0.0084-0.0095), assuming a
duration of stay in farm of 28 weeks, suggesting increased force of
infection during the transport process. Potential risk factors for
infection including the duration in transport, length of stay at
slaughterhouse and farm-level seroprevalence were also assessed by
multivariable logistic regression analysis. Transport may increase virus
cross-infection rates and provide opportunities for virus reassortment
potentially increasing zoonotic risk to those involved in the
transportation and slaughtering processes.

\textbf{(276 words)}

\textbf{Key words:} influenza A virus, H3N2, swine, value chains,
transmission dynamics, force of infection.

\textbf{Introduction} (Word count: 3910)

Emerging infectious diseases continue to be a major threat to public
health. Most emerging or re-emerging infectious diseases are caused by
RNA viruses and are zoonotic in origin, arising from domestic livestock
or wildlife. Understanding viral transmission dynamics in livestock
production and trade pathways can identify potential critical control
points that may be amenable to disease control interventions (Leung,
2012).

Swine are an intermediate host in the pathway of pandemic emergence
because they express receptors for both avian and human influenza virus
in their upper respiratory tract (Ito, 1998). The 2009 H1N1 pandemic
virus arose in Mexico through reassortment of gene segments from
Eurasian avian-like H1N1 and North American Triple Reassortant swine
viruses (Smith, 2009). The two precursor viruses were introduced into
Mexico via importation of swine, possibly as breeder-stock. Swine
husbandry, trading, marketing and slaughter provide opportunities for
the emergence of novel reassortants and zoonotic infections through
exposure of humans to swine influenza viruses. An example was H3N2
variant (H3N2v) influenza viruses causing over 300 infections in humans
with exposure to swine at agricultural fairs in USA (Jhung, 2013). In
Asia, the high densities and close proximity between swine, humans,
poultry and wild birds provides an even greater threat for interspecies
transmission.

In Hong Kong, over 90\% of the swine slaughtered at its abattoirs are
imported from mainland China with an annual importation of about 1.45
million swine in 2017 (Centre for Food Safety, 2019). Live pigs for
consumption are transported in trucks from the source farms in multiple
provinces to a transfer house at the Shenzhen-Hong Kong border where
they are held for inspection overnight, and are then transported by
trucks or lorries to a centralized abattoir in Hong Kong. Along this
transport chain, there is opportunity for virus transmission between
consignments of pigs originating from different farms, facilitated by
the stress of transport and the densely packed environment. Pigs may
also be held for hours to days in holding pens at the abattoir,
providing further opportunities for cross infection (details in
supporting information, Supplementary figure 1).

A previous study on the transmission dynamics of H1-subtype swine
influenza viruses (SIVs) in China (Strelioff, 2013) analyzed virologic
and serological data to infer the transmission risk over time. However,
the interaction and cross-reactivity between different lineages of H1
SIVs may have affected interpretation of the serology results from the
hemagglutination inhibition (HAI) test. There was a lack of
epidemiological information of imported swine population, such as source
farm or province and length of stay at abattoir.

Multiple swine influenza viruses (SwIV) are enzootic in swine in China,
including classical swine (CS), Eurasian avian-like swine (EA),
triple-reassortant swine (TRIG) and pandemic H1N1/2009 (H1N1pdm09)
lineage (Vijaykrishna, 2011). Infection with one H1 virus lineage could
broaden cross-reactive antibody to other H1-subtype SIVs (Perera, 2011)
and hence confound interpretation of sero-epidemiology of H1 swine
viruses. There was only one monophyletic H3 lineage (Binh Duong
(BD)-like H3N2 lineage) circulating in China since 2010 allowing
serology to accurately estimate past infection (Liang, 2014).

The objective of the current study was to understand the transmission
dynamics of swine H3N2 viruses at the farm, transport and abattoir stage
of the production chain. Focusing on swine H3N2 viruses allowed us to
interpret serological data in the context of molecular epidemiology to
infer transmission dynamics within the swine production system supplying
swine for slaughter in Hong Kong. We compared the risk of infection
during transportation and in the farm setting by estimating the force of
infection (FOI) and identified the role of factors, such as transport
distance and the length of stay at slaughterhouse.

\textbf{Materials and Methods}

\textbf{Surveillance and sample collection}

The Sheung Shui Slaughterhouse is the largest slaughterhouse in Asia,
able to accommodate 12,000 pigs and slaughter up to 5,000 pigs per day.
From 5\textsuperscript{th} January 2012 to
15\textsuperscript{th}December 2016, our surveillance team collected
paired serum and nasal swabs from randomly selected pigs soon after
slaughter, 50 paired pig sera and nasal swabs being collected at each
visit, which was increased to 75 paired samples since
19\textsuperscript{th} November 2015. Tracheal swabs were also collected
at post-mortem inspection. Information of the originating province and
farm was derived from pig tattoo identification numbers. We also
recorded the arrival date of the slaughtered pigs, from which the length
of stay at slaughterhouse was derived. Sampling was conducted twice per
month to allow identification of any potential seasonal pattern.

\textbf{Virus isolation and molecular screening}

Swab samples were inoculated into Madin Darby canine kidney (MDCK) cells
grown in 24-well plates in minimum essential medium (MEM) supplemented
with 2 \selectlanguage{greek}µ\selectlanguage{english}g/ml phenylalanyl chloromethyl ketone-treated tryspin
(TPCK-trypsin) for virus propagation on the same day and replaced with
fresh culture medium on the next day. On day 3 post-inoculation (DPI),
viral growth was determined by appearance of cytopathic effects (CPE) in
the MDCK cells and by a hemagglutination assay (HA) of cell supernatants
using 0.5\% turkey red blood cells (TRBCs). The cultures which gave
positive results on CPE and HA were further tested using a rapid antigen
detection test, Directigen\textsuperscript{TM} EZ Flu A+B (Becton,
Dickinson and Company, New Jersey, USA) to confirm influenza A virus
infection. Positive cultures were then passaged on MDCK cells again for
a second passage for virus isolation. Positive virus isolates were
aliquoted and stored at -80\selectlanguage{ngerman}°C.

Viral RNA was extracted from cell culture isolates using QIAmp Viral RNA
Mini Kit (QIAGEN, Hilden, Germany). The presence of SIVs was confirmed
by a one-step reverse transcription PCR (RT-PCR) targeting the conserved
influenza A matrix gene using PrimerScript II High Fidelity RT-PCR Kit
(Takara, Japan) (Fouchier, 2000). We adapted a duplex two-step RT-PCR
approach for HA and NA subtyping. Complementary DNA (cDNA) was
synthesized by reverse transcription using SuperScript III Reverse
Transcriptase (Invitrogen\textsuperscript{TM}) with Uni12 primer
(Hoffmann, 2001). Gene amplification of HA and NA gene segment was
performed using AmpliTaq Gold DNA Polymerase (Thermo Fisher Scientific,
Sweden) with subtype-specific primers (Supplementary table 1). PCR
products were analysed with 2\% agarose gel electrophoresis and virus
subtypes were determined.

\textbf{Serological assays}

Serum was extracted from clotted blood samples and stored at -20°C.
Hemagglutination inhibition (HAI) assays were performed on each of the
6,532 serum samples collected, with a representative swine H3 influenza
virus strain: A/Swine/Hong Kong/4348/2016 (BD-like H3N2). HAI tests were
performed following WHO recommendations for animal influenza diagnosis
(World Health Organization, 2011). Serum samples were first treated
overnight at 37°C with receptor destroying enzyme (RDE) (Denka Seiken Co
Ltd., Tokyo, Japan) and were heat-inactivated for 30 min at 56°C next
morning. Serum samples were then serially diluted two-fold (1:10 to
1:1,280) in 96-well plates and 25 \selectlanguage{greek}µ\selectlanguage{english}L of virus antigen with four
hemagglutination units was added to an equal volume of each serum
dilution in duplicate. After 1h incubation, 50\selectlanguage{greek}µ\selectlanguage{english}L of 0.5\% TRBCs was
added to each well and incubated for 30 min. The HAI titer was defined
as the highest serum dilution that inhibited complete hemagglutination.
For calculation of the geometric mean titer (GMT), serum samples with a
titer of \textless{}1:10 was assigned a value of 5 and those with
[?]1:1,280 were assigned a value of 1:1,280.

\textbf{Statistical analysis}

We fitted a logistic regression model to predict isolation of influenza
A(H3N2) subtype, considering factors such as length of stay at
slaughterhouse of the live pigs, transport distance from originating
farms to Hong Kong, HAI titer against the reference H3N2 strain
(A/swine/Hong Kong/4348/2016) of individual pigs, and H3 seroprevalence
of the specific originating farms.

The H3 seroprevalence of each originating farm was calculated as the
proportion of seropositive (HAI titer [?]1:40) samples in 2012-2016 and
only those samples collected from major source farms ([?]20 samples over
the study period) were analysed (n = 5,832) (Figure 1). We stratified
the individual anti-H3 HAI titer level into sero-negative
(\textless{}1:40) and sero-positive ([?]1:40).

The slaughtered pigs originated from more than 150 farms. While we had
the location of each farm to the level of the Province, exact
geo-spatial farm locations were not available. We estimated the
transport distance based on the originating province and stratified data
into 3 groups: a) nearest, from Shenzhen, Zhuhai and other cities of
Guangdong Provinces (within 150km from Hong Kong approximately); b) more
distant, from Guangxi, Hainan, Hunan and Jiangxi Provinces
(approximately 500-700 km), and c) most distant, from Hubei, Hebei,
Henan and Zhejiang Provinces (approximately \textgreater{}900 km). All
factors were tested in the multivariable analysis. P value
\textless{}0.05 was considered statistically significant. All
statistical analyses were conducted using R version 4.0.3 (R Foundation
for Statistical Computing, Vienna, Austria).

We further estimated the force of infection (FOI) in farms and during
transportation of swine respectively, based on the analysis of
virological and serological results on H3-subtype SIVs in the subset
where paired serum and swab samples were available. Prior to importation
of live pigs to Hong Kong, pigs from distant provinces were gathered by
local traders but without clear records. Therefore, the exact duration
of transportation of individual pigs were not available. Hence, we
performed the FOI analysis based on pigs from Guangdong only (n = 4,226,
65\% of the total samples) (Figure 1) from which pigs were transported
directly to Hong Kong from the farms, to minimise discrepancies between
actual and assumed exposure duration.

Paired viral isolation and serological data were utilized to deduce the
infection history of individual pigs. Previous studies had reported that
pigs would begin shedding virus in nasal swabs by 1-3 days post-exposure
and virus shedding would last for 4-5 days (Janke, 2013), whereas
circulating antibodies become detectable 10-14 days after infection
(Detmer, 2013). The time delay between virus shedding period and
seroconversion allowed us to deduce where infections had taken place.
Specifically, we defined the number of pigs which have experienced 4
possible infection histories: n\textsubscript{1}, na\selectlanguage{ngerman}ïve population
(negative virological and serological test results); n\textsubscript{2},
recent primary infection (positive virological and negative serological
test results); n\textsubscript{3}, previous infection (negative
virological and positive serological test results); and
n\textsubscript{4}, recent secondary or re-infection (positive
virological and serological test results). We estimated the probability
of infection during transport (p\textsubscript{t}) from the virus
isolation rate at the abattoir among swine naïve to H3N2 prior to
transportation i.e. sero-negative to H3 antigens, so p\textsubscript{t}=
n\textsubscript{2} / (n\textsubscript{1}+n\textsubscript{2}). The
probability of infection in farm (p\textsubscript{f}) was estimated by
the proportion of seropositive samples, i.e., p\textsubscript{f} =
(n\textsubscript{3}+n\textsubscript{4}) /
(n\textsubscript{1}+n\textsubscript{2}+n\textsubscript{3}+n\textsubscript{4}),
assuming recently infected pigs have not yet seroconverted.

The force of infection (FOI), defined as the instantaneous rate at which
a susceptible pig becomes infected, was used to quantify the
transmission potential. The relationship between FOI and probability of
infection p is given by:

\begin{equation}
p=1-exp(-\int_{t_{1}}^{t_{2}}{\lambda\left(t\right)\text{dt}})\nonumber \\
 \end{equation}

where t\textsubscript{1}, t\textsubscript{2} are the start and end times
of the exposure, \selectlanguage{greek}λ\selectlanguage{english}(t) is the FOI from infectious pigs in farms or
transport system. The probability of infection during transport depends
on the duration of travelling time for imported pigs. We assumed the
exposure duration related to transport (time before slaughtering,
including transportation, inspection and holding) is 3 days. The ages of
the pigs sampled were 28 to 36 weeks old (no individual data was
recorded) and pigs in farms were assumed to have 4 to 8 weeks of
protection by maternal antibodies (Markowska-Daniel, 2011). A previous
study on maternally derived antibodies suggested that the maternally
acquired immunity may only mask clinical illness of the pigs but not
protecting them from infection (Loeffen, 2003). Therefore, we considered
possible exposure durations of 20, 28 and 36 weeks for the estimation of
FOIs in farm.

\textbf{Whole-genome sequencing and assembly}

The whole-genome sequence of each influenza virus isolate was obtained
by using the Genome Sequencer Junior (Roche 454) or ABI 3730 genetic
analyzer (Applied Biosystems) as previously described (Vijaykrishna,
2011, Liang, 2014). Original reads that shared \textgreater{}90\%
sequence identity in a 40-nucleotide overlapping region were assembled
into contigs using Lasergene, version 9.0 (DNAStar).

\textbf{Phylogenetic analysis and molecular epidemiology}

Molecular epidemiology was used to define evidence of virus clustering
and thus the occurrence of swine-to-swine transmission. Analysis was
conducted on full genomes of all H3N2 swine influenza virus isolates
sequenced in our study (Figure 1). The influenza virus sequences were
analysed together with other existing Asian H3-subtype swine influenza
virus sequences retrieved from the NCBI Influenza Virus Resource
(Supplementary table 2) (Bao, 2008) and GISAID (Supplementary table 3)
(Shu, 2017). All Asian H3 SIVs with a complete set of segments in
full-length were included and identical sequences were collapsed. Each
genome segment was aligned separately using MAFFT version 7 (Katoh,
2013) and alignments were then trimmed to coding regions. The resultant
data sets contained a total of 353 full genome sequence sets.

The coding regions of gene segments PB2, PB1, PA, HA, NP, NA, MP and NS
were concatenated using Geneious 2019.2.1 (http://www.geneious.com).
Multiple alignment for the concatenated whole genomes was performed with
MAFFT version 7. We inferred the maximum-likelihood phylogenetic trees
using IQ-TREE (Nguyen, 2014) and the built-in ModelFinder
(Kalyaanamoorthy, 2017) to determine the best-fit substitution model.
Branch supports were obtained using approximate likelihood ratio test
(aLRT) (Guindon, 2010) to assess the robustness of the phylogenetic
tree. Branch support aLRT statistics were shown at major nodes with
values larger or equal to 0.8.

\textbf{Results}

\textbf{Virus isolation in pigs}

During the surveillance period from 2012 to 2016, a total of 8,954 nasal
swabs (NS), 18,026 tracheal swabs (TS) and 6,532 pig sera were collected
from pigs originated from 505 pig farms in 11 provinces in Mainland
China and Hong Kong. The median number of swab samples collected per
visit from the Sheung Shui slaughterhouse was 226 (range 102-291). H1N1
(n = 278), H3N2 (n = 174) and H1N2 (n = 51) subtype viruses were
isolated. Only H3N2 viruses are further analysed in this study. There
was a significantly higher influenza A H3-subtype virus isolation rate
in nasal swabs, compared with tracheal swabs (p = 0.014).

\textbf{Phylogenetic analysis and molecular epidemiology}

Whole-genome sequencing and phylogenetic analysis were carried out for
all 174 H3N2 viruses isolated from both nasal and tracheal swab samples
during the study period. Together with 179 reference H3 SIV genome
sequences retrieved from the existing databases (GenBank, GISAID), a
maximum likelihood phylogenetic tree of 353 concatenated genomes of H3
SIVs was constructed. All tattoo codes indicating farm of origin and
sampling dates of the H3 isolates were labelled in the tree (Figure 3).
The 174 sequences of the H3N2 virus isolates can be grouped into 9
clusters, numbered 1-9, of closely related virus sublineages within the
concatenated phylogenetic tree. Genetically similar viruses were
detected in pigs from multiple farms on the same sampling occasion. For
example, all H3N2 viruses collected on 3\textsuperscript{rd} July 2014
formed a subcluster of taxa with closely related evolutionary history
(subcluster 5). Interestingly, in subcluster 5, 18 nearly identical H3N2
viruses were isolated at the abattoir from pigs originating from 13
different farms in 3 different provinces (Guangdong, Hunan and Jiangxi).
Similarly, in subcluster 4, there were 17 highly related H3N2 viruses
isolated from pigs originated from 5 different farms in 2 provinces
(Jiangxi and Guangdong) on one sampling date
7\textsuperscript{th}January 2016. A similar phenomenon was found in
virus subclusters 6, 7 and 8. It was highly improbable that a
genetically identical virus was simultaneously circulating in multiple
farms and provinces at the same time period. Thus, the phylogeny was
strongly suggestive of a virus from a common source which transmitted to
swine from other farms during transportation or while being held within
the abattoir prior to slaughter.

One of these farms GD101 had similar but not identical viruses isolated
on 2\textsuperscript{nd} July 2015 and 7\textsuperscript{th} September
2016, suggesting that this virus sub-lineage was persisting within the
farm for over two years.

\textbf{Seroprevalence of H3N2 influenza virus in pigs}

There was only one monophyletic lineage of H3 SIVs isolated in our
samples, that being the BD-like H3 lineage. H3N2 seroprevalence was
assessed in 6,532 sets of paired nasal swabs and sera. The HAI
seroprevalence of BD-like H3 SIVs in this subset was 20.5\%
(1,340/6,532) with HAI titer [?]1:40 against the reference H3 strain
(A/swine/Hong Kong/4348/2016). The virus isolation rates and
seroprevalence of H3N2 in swine were shown in Figure 2. No seasonal
pattern was identified.

\textbf{Multivariable logistic regression on H3-SIV}

Of the 6,532 paired nasal swabs and pig sera collected over the study
period, 65\% of the swine originated from Guangdong province, followed
by Jiangxi (17\%), with relatively fewer isolates from other provinces
(Table 1). We isolated 63 H3N2 viruses from swabs and H3N2 antibodies
were detected in 1,340 pigs (Table 1), with 7 pigs having both virus
isolates and antibodies. Samples collected from farms (n = 5,832) which
provided [?]20 samples were included in our logistic regression.
Multivariable logistic regression was fitted to explain H3-subtype virus
infections (Table 2).

In the multivariable logistic regression model (Table 2), pigs with
anti-H3 HAI titers [?]1:40 were significantly associated (adjusted OR
{[}aOR{]} = 0.33, p = 0.012) with a lower risk of H3 virus detection in
the abattoir (i.e. presumed infection during transportation). This
reflected the protection against infection provided by the humoral
immune response. Swine from source farms with high H3 seroprevalence
(\textgreater{}30\%) showed significantly higher H3 virus isolation
rates (aOR = 2.24, p-value = 0.015). No significant difference was
observed in the virus isolation among pigs with different length of stay
at the slaughterhouse and transport distance.

\textbf{Force of Infection (FOI) in farms and during transport}

There were in total 4,226 paired pig sera and nasal swabs collected from
swine originating from Guangdong, with 46 (1.09\%) H3 viruses isolated
and 936 (22.1\%) having antibody titers [?]1:40 (sero-positive) to H3 SIV
(Table 1). Among the 3,290 sero-negative samples, there were 40 (1.22\%)
H3 viruses isolated. The mean weekly FOI \selectlanguage{greek}λ\selectlanguage{english}\textsubscript{t} during
transport for swine originating from Guangdong was estimated to be
0.0286 (95\% CI = 0.0211-0.0391), while the weekly force of infection in
farms were \selectlanguage{greek}λ\selectlanguage{english}\textsubscript{f} = 0.0125 (95\% CI = 0.0118-0.0134), 0.0089
(95\% CI = 0.0084-0.0095), and 0.0069 (95\% CI = 0.0065-0.0074)
respectively, assuming exposure durations of 20, 28 and 36 weeks in
farms. Hence, the relative FOI during transport was 229-414\% of that in
farms, indicating a noticeable increased transmission intensity during
transportation comparing to that within farms.

\textbf{Discussion}

Swine slaughtered in a large central abattoir in Hong Kong were sourced
from farms in multiple provinces of China. We utilized paired
virological and serological surveillance data, together with data on
farm of origin and date of sampling to assess the transmission risk in
the swine transport and marketing system in China. Our results showed
that pigs experienced a higher FOI (229\%-414\%) during transport
per-unit time, compared to that within the farms. This suggested that
the industrial scale swine production, transportation and marketing of
live pigs provide settings favorable to influenza transmission, though
the much longer stay in farms allow more infections over swine's
lifetime. The phylogenetic tree topology of the concatenated genomes
also provided clear molecular epidemiological evidence of
cross-transmission along the transport chain, between swine originating
from different parts of mainland China. Interestingly, the isolation of
similar though not identical viruses from the same farm over a two-year
period suggested that swine influenza virus lineages may be maintained
within a single source farm for over a year. We did not have detailed
farm management data to ascertain herd sizes or management practices, in
particular whether these large farms are ever completely emptied of
pigs, which was unlikely. The likelihood that sequential batches of
swine of different age groups are raised on the same farm increases the
possibility of a virus to maintain itself within farms with large herd
sizes.

We found that pigs were more likely to be infected with H3 virus during
transportation, if originating farms had a high seroprevalence over
30\%. The high farm-level seroprevalence implied a high circulation of
H3 SIV in farms. Hence, some pigs from the herd were more likely to be
infectious at the beginning of the transport chain and more likely to
transmit to others along the route (e.g. inspection or holding at the
transfer house and holding within the abattoir). However, the infection
risk during transportation for pigs with HAI titer of [?]1:40 reduced
substantially by 67\%, which is compatible with the protective effect of
humoral immune response for humans (Hobson, 1972).

Distance of transportation was not found to be associated with the risk
of transmission. We observed a lower transmission risk for swine from
farms further away from Hong Kong, though the difference was not
statistically significant (Table 2). There could be other economic
factors which may affect biosecurity measures during transport for these
farms. The extent of mixing with other swine during inspection, waiting
or holding at the transfer house, quarantine station and abattoir may
pose greater transmission risks than that during transportation, with
only about 40 pigs in a truck. Hence, the relative contribution of
transmission risk during transportation may be less, even with a long
trip from source farms to abattoir, than that associated with the mixing
taking place at the quarantine stations and other common transport hubs.
The isolation rate did not increase significantly for pigs staying
longer times in the abattoir in Hong Kong which may imply that
transmission within the abattoir was not a major driver of
cross-infection. This is possibly related to the short time pigs were
held in the abattoir prior to slaughter which may not provide adequate
time for transmission and incubation period for there to be detectable
virus at slaughter. The emergence of African swine fever in China since
2018 has led to a further shortening of the period of pigs being held in
the abattoir in Hong Kong prior to slaughter, likely further reducing
risk of cross-infection within the abattoir. The increased FOI during
transportation may be facilitated by the high-density and high-stress
environment at the transfer houses at the Shenzhen-Hong Kong border.
Limiting the number of pigs and time of travel may reduce
cross-infection.

There were several limitations in our study. First, the actual duration
and distance of transportation duration and distance for the live pigs
were not available. We used province as a proxy for duration of
transport. We could not rule out impacts arising from other activities
related to swine trading. Secondly, while pigs from farms not previously
infected with H3N2 virus got infected during the transport to the
abattoir, we did not have unequivocal evidence that new viruses were
introduced back to farms, although this could occur through contaminated
trucks. Third, our estimates focused on H3-subtype SIV only, giving us a
smaller sample size. The serological cross-reactivity between multiple
co-circulating H1 viruses make such an analysis difficult to interpret
with H1 swine viruses. Finally, our study deduced the infection history
of individual pigs based on surveillance in the slaughterhouse only. The
actual prevalence of infectious virus in individual farms or transfer
house were not available, which prevented us from estimating the
transmission risk at different points of transportation.

In conclusion, we used paired serological and virologic samples
collected from a swine slaughterhouse to examine the infection history
of the swine from farms and during transportation. We found that
transport and holding settings provided a favorable environment for
swine-to-swine cross transmission per unit time when compared with
farms. However, the longer period of time a pig spends on the farm means
that the cumulative risk of acquiring infection in the farm is higher.
The risk posed by the transport process was co-infection with new
viruses which may provide opportunities for virus reassortment providing
some risk to those involved in the transportation and slaughtering
processes. There may also be the possibility of viruses being introduced
back to na\selectlanguage{ngerman}ïve source farms via fomites and trucks, although this study
was not able to investigate this possibility. Further assessment of the
relative contribution of influenza transmission at different processes
during transportation is needed to identify high risk area for improving
disease control.

\textbf{Acknowledgments:} We acknowledge research funding from the
National Institute of Allergy and Infectious Diseases, National
Institutes of Health, Department of Health and Human Services, under
Contract No. 75N93021C00016, HHSN266200700005C and HHSN272201400006C and
the Theme Based Research grant (T11-712/19-N) from the Research Grants
Council of Hong Kong SAR and the Health Medical Research Fund (Ref no:
HKS-15-E02) from the Food and Health Bureau of Hong Kong SAR.

\textbf{Conflicts of interest:} The authors declare no conflicts of
interest.

Data availability statement: All data from this study have been
disclosed.

\textbf{Orchid:} Malik Peiris ID https://orcid.org/0000-0001-8217-5995

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\textbf{Table 1} . \textbf{Summary of the H3N2 virus isolate and H3
seropositive rates in samples from different origins, sorted by number
of samples.}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Province of origin} & \textbf{No. of samples} & \textbf{No. of
H3 virus isolates} & \textbf{No. (\%) H3 seropositive of those
tested}\tabularnewline
\midrule
\endhead
Jiangxi & 1,072 & 12 & 149 (13.9)\tabularnewline
Hunan & 530 & 2 & 108 (20.4)\tabularnewline
Hebei & 298 & 0 & 58 (19.5)\tabularnewline
Hubei & 170 & 1 & 36 (21.2)\tabularnewline
Guangxi & 110 & 1 & 25 (22.7)\tabularnewline
Hainan & 61 & 0 & 17 (27.9)\tabularnewline
Henan & 28 & 1 & 4 (14.3)\tabularnewline
Zhejiang & 13 & 0 & 1 (7.7)\tabularnewline
Zhuhai, Guangdong & 11 & 0 & 3 (27.3)\tabularnewline
Shenzhen, Guangdong & 13 & 0 & 3 (23.1)\tabularnewline
Guangdong, other & 4,226 & 46 & 936 (22.1)\tabularnewline
\textbf{Total} & \textbf{6,532} & \textbf{63 (1\%)} & \textbf{1340
(20.5)}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2} Summary of the influenza A virus isolation rates in
samples with different characteristics\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Characteristics}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{No of samples}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{No. (\%) H3 positive}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Adjusted OR}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{95\% confidence intervals}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{p-value}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Length of stay at slaughterhouse}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textless{} 1 day\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
3446\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
33 (1.0)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reference\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1-2 days\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
2183\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
23 (1.1)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1.30\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.76-2.25\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.339\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textgreater{}2 days\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
203\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
2 (1.0)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1.20\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.28-5.08\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.802\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Transport distance+}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Nearest\textbf{+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
3863\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
45 (1.2)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reference\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
More distant\textbf{+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1519\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
12 (0.8)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.77\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.39-1.15\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.449\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Most distant\textbf{+}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
450\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1 (0.2)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.18\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.02-1.34\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.094\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Anti-H3 HAI titer}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Sero-negative (\textless{}1:40)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
4625\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
52 (1.1)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reference\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Sero-positive ([?]1:40)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1207\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
6 (0.5)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.33\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.14-0.79\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.012\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Sero-prevalence of source farms}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Low (\textless{}10\%)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1963\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
16 (0.8)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reference\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Moderate (10-30\%)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
2047\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
16 (0.8)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
1.16\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.57-2.34\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.682\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
High (\textgreater{}30\%)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1822\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
26 (1.4)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
2.25\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1.17-4.32\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.150\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Total}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{5832}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{58 (1.0)}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{+} Nearest: Guangdong, including Shenzhen and Zhuhai; More
distant: Guangxi, Hainan, Hunan, Jiangxi; Most distant: Hubei, Hebei,
Henan, Zhejiang.

\textbf{Figure legends:}

\textbf{Figure 1.} Sample collection and plan of analyses.

\textbf{Figure 2.} Monthly H3N2 seropositive and virus isolation rate in
6,532 sets of paired nasal swabs and pig sera, 2012-2016.

\textbf{Figure 3.} Maximum likelihood phylogenetic tree of 174
concatenated genomes of H3N2 swine influenza viruses in 2012-16. The
tree was constructed using IQ-TREE and branch supports were obtained
with SH-aLRT test. Strain name is followed by pig tattoo codes and
sampling date. Scale bar is given in numbers of substitutions per site
and branch support aLRT statistics are shown at major nodes with value [?]
0.8.\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

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