Introduction
The circulation of avian influenza viruses (AIV) across Asia is complex,
involving the interplay of numerous risk factors. Reviewing the
scientific literature, Gilbert & Pfeiffer (2012) identified three
classes of variables associated with the incidence and spatio-temporal
trends of HPAI H5N1 across studies and regions: domestic waterfowl,
anthropogenic variables including factors such as human population
density and distance to roads, and indicators of water presence. Other
investigators reported associations with poultry population density
(chicken as well as ducks), human population and rice cropping intensity
(Pfeiffer et al., 2007; M. Gilbert et al., 2008; Loth et al., 2010,
2011). Once established, HPAI H5N1 virus spread is believed to be
influenced primarily by local trade patterns, density and practices in
wet markets or live bird markets (LBMs), the poultry production
structure and value chain, and disease prevention and control systems
(M. Gilbert et al., 2008). H5N1 HPAI outbreaks are highly seasonal in
areas of South and South East Asia. This observed seasonality has been
associated with higher temperature, poultry species, product movements
and trade, and other anthropogenic factors (Pfeiffer et al., 2007; Minh
et al., 2009; Tran et al., 2013).
Like many viral pathogens, HPAI H5N1 persists in multiple avian host
species. Domestic ducks have been implicated as an important virus
reservoir. Previous studies on Java reported them to be more than ten
times as likely as chicken flocks to have seropositive birds, with
scavenging being identified as a specific risk factor (Joerg Henning et
al., 2010, 2016; J. Henning et al., 2013). A consequence of such a
multihost system is that the identification reservoir hosts of
infection, and knowledge of how these hosts enable and maintain
persistence, is essential to inform targeted interventions (Haydon et
al., 2002; Viana et al., 2014). The investigation of multihost systems
is complex because they incorporate a number of interacting species,
populations, and production systems (Viana et al., 2014). Moreover, they
are influenced by a range of management practices, human behaviours and
trade patterns. Very little is known about the year-round persistence of
the H5N1 HPAI virus.
In Indonesia, Java has the highest density of both human and poultry
(Anon., 2019). HPAI is endemic across many parts of the country. Central
and West Java have been identified as hotspots for HPAI (Farnsworth et
al., 2011). The poultry production system in Indonesia is highly diverse
and is classified into four sectors. Sector 1 is comprised of vertically
integrated commercial poultry farms that implement high-level
biosecurity measures and always market the bird/products commercially.
Sector 2 represents somewhat smaller-scale commercial poultry farms with
moderate to high biosecurity; birds/products are sold through
slaughterhouses or poultry markets. Sector 3 consists of small
commercial poultry businesses which typically have lower levels of
biosecurity, with birds that are usually sold through live bird markets.
Sector 4 is classified as backyard poultry farms, often a subsistence or
side-business enterprise, with minimal biosecurity and products mainly
consumed locally (Azhar et al., 2010; Farnsworth et al., 2011; Hendra
Wibawa et al., 2018).
Trade, the value chain and human behaviours have been recognised as
influential drivers for the transmission of HPAI. In Indonesia, Indrawan
et al. (2018) applied value chain analysis (VCA) to investigate factors
related to biosecurity and HPAI control in Western Java. They identified
the co-existence of four different poultry value chains, ranging from
high levels of coordination, hierarchical governance, and regulated
marketing and distribution mechanisms (Sectors 1 and 2) to informal,
smaller-scale chains (Sectors 3 and 4) which had weaker HPAI prevention
and biosecurity measures. Sector 3 and Sector 4 production often occur
in close geographic proximity (Sims et al., 2005; Azhar et al., 2010),
and birds are likely to move between these two systems. It is therefore
suspected that HPAI is transmitted between these sectors, contributing
to the difficulty in controlling the disease (Farnsworth et al., 2011;
Indrawan et al., 2018). In a questionnaire-based study of poultry
traders at LBMs in Bali and Lombok, Kurscheid et al. (2015) found that
knowledge of viral transmission and biosecurity was generally low. Two
thirds of respondents were reluctant to report sudden or suspicious bird
deaths to authorities. The investigators established that there was a
correlation between knowledge of HPAI transmission and prevention and
the number of birds sold; education was strongly associated with better
knowledge but did not influence positive reporting behaviour. Elsewhere
in South East Asia, Fournié et al. (2012) recorded traders’ practices in
Vietnam and Cambodia likely to influence the virus circulation in LBMs.
These included factors related to trade patterns (e.g. the number of
days during which traders were active, the length of time they spent at
market in a day, the number of poultry sold within a day, the type of
poultry etc.) as well as factors related to supply management (purchase
and sale volumes, frequency and quantity of the surplus at the end of
trading days, management of unsold poultry including sale to traders
operating in other LBMs ). They showed that poultry traders with high
surplus frequency and volume represented a risk group for perpetuating
HPAI H5N1 in LBMs.
For a complex and multi-faceted disease such as HPAI H5N1, investigative
approaches focusing on a discrete area of interest are unlikely to
effectively generate conclusive insights. Hence, an integration of
methodologies incorporating elements including population studies,
surveillance techniques and data, pathogen genetics and an understanding
of production systems (including high risk points for transmission)
presents the best scope to further develop understanding. A consequence
of such an approach is that multiple sources of data and information
need to be combined. These may be extant, or such data may be collected
for the specific purpose of the investigation; these data may be
qualitative, quantitative or both. Integration of findings can be
performed using techniques such as meta-analysis, mathematical modelling
or mixed methods research. Triangulation of multiple sources is
performed to assess validity, synthesize findings and generalise
inferences (Farmer et al., 2006). Such methodologies are increasingly
being applied in the field of animal health. Commonly, qualitative
approaches include stakeholder interviews, questionnaires or focus group
discussions whereas quantitative techniques include data generated by
observational studies, animal health surveillance or disease control
programmes (e.g. Limon et al., 2017, 2014; Mosimann et al., 2017; Walker
et al., 2015; Wu, Kagoli, Kaasbøll, & Bjune, 2018).
The overall objectives of this study were to determine the drivers of
H5N1 HPAI persistence in endemic areas in Indonesia. Specific objectives
were to determine where H5N1 HPAI is maintained in poultry populations
in Indonesia, and how contact patterns between and within poultry
production systems and enterprise types contribute to the maintenance of
virus, including interactions between these systems and the populations
of birds. We also aimed to investigate the co-circulation of HPAI virus
with H9 LPAI viruses. Finally, the study aimed to profile and describe
the value chain and marketing systems of live bird marketing, including
collector yards and live bird markets. The ultimate objective of this
work was to provide the relevant authorities with information that could
be applied to develop recommendations for effective disease control.