Molecular-based surveillance of campylobacteriosis
in New Zealand – from source attribution to genomic
P Muellner (email@example.com)1,2, E Pleydell2, R Pirie3, M G Baker4, D Campbell5, P E Carter3, N P French2
1. Epi-interactive, Miramar, Wellington, New Zealand
2. mEpiLab, Institute of Animal, Biomedical and Veterinary Science, Massey University, Palmerston North, New Zealand
3. Institute of Environmental Science and Research, Kenepuru Science Centre, Porirua, New Zealand
4. Department of Public Health, University of Otago, Wellington, New Zealand
5. Ministry for Primary Industries, Wellington, New Zealand
Citation style for this article:
Muellner P, Pleydell E, Pirie R, Baker MG, Campbell D, Carter PE, French NP. Molecular-based surveillance of campylobacteriosis in New Zealand – from source
attribution to genomic epidemiology. Euro Surveill. 2013;18(3):pii=20365. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20365
Article submitted on 27 June 2012 / published on 17 January 2013
Molecular-based surveillance of campylobacteriosis
in New Zealand contributed to the implementation of
interventions that led to a 50% reduction in notified
and hospitalised cases of the country’s most impor-
tant zoonosis. From a pre-intervention high of 384
per 100,000 population in 2006, incidence dropped
by 50% in 2008; a reduction that has been sustained
since. This article illustrates many aspects of the suc-
cessful use of molecular-based surveillance, including
the distinction between control-focused and strategy-
focused surveillance and advances in source attri-
bution. We discuss how microbial genetic data can
enhance the understanding of epidemiological explan-
atory and response variables and thereby enrich the
epidemiological analysis. Sequence data can be fitted
to evolutionary and epidemiological models to gain
new insights into pathogen evolution, the nature of
associations between strains of pathogens and host
species, and aspects of between-host transmission.
With the advent of newer sequencing technologies
and the availability of rapid, high-coverage genome
sequence data, such techniques may be extended
and refined within the emerging discipline of genomic
epidemiology. The aim of this article is to summarise
the experience gained in New Zealand with molecu-
lar-based surveillance of campylobacteriosis and to
discuss how this experience could be used to further
advance the use of molecular tools in surveillance.
– recent successes
Molecular tools are being used increasingly to inform
the control of enteric zoonosis worldwide  and to
meet a wide range of public health aims and objec-
tives [2-4]. In New Zealand, a country with a histori-
cally high rate of campylobacteriosis notifications
[5,6], results from molecular-based surveillance in a
sentinel site founded in 2005 – where human cases
and potential sources were sampled and typed by mul-
tilocus sequence typing (MLST) simultaneously over
consecutive years [7,8] – provided strong evidence that
a large proportion of human cases were linked poul-
try meat consumption. These findings contributed to
a mounting body of evidence [5,9] and stimulated the
implementation of regulatory and voluntary control
strategies along the poultry supply chain. They were
announced in 2007 and fully implemented in 2008
(when they became mandatory) , resulting in a 50%
reduction in disease incidence of cases in 2008 com-
pared with the previous high level during 2002 to 2006
Campylobacteriosis notifications in humans were
markedly above the reference value until 2008, when
the incidence dropped considerably (Figure 1); a likely
effect of a reduction in poultry-associated cases due to
the implementation of the control strategies in the poul-
try supply chain [10,11]. No comparable changes in the
annual incidence of other enteric notifiable diseases
were observed over the same time period (2002–2011)
(Figure 1). Sustained decline in campylobacteriosis
case numbers has been shown to have additional
health and economic benefits by, for example reducing
the incidence of Guillain–Barré syndrome, an autoim-
mune condition associated with prior Campylobacter
spp. infection .
Furthermore, in the New Zealand sentinel surveillance
site, a dominant poultry-associated MLST sequence
type of C. jejuni (ST-474) was identified that, to date,
has been reported rarely from other countries. Before
the implementation of the poultry interventions,
ST-474 accounted for 30% of human cases in the sen-
tinel site [14,15], but in 2010–11, it was isolated from
less than 5% of cases . Figure 2 shows the dramatic
reduction in two major poultry-associated genotypes,
ST-474 and ST-48 (Figure 2, panel A), and provides a
comparison with other STs over the same time period
(Figure 2, panels B and C).
Focused molecular epidemiological studies have been
contributing to our understanding of the epidemiol-
ogy of this widespread disease both in New Zealand
and elsewhere [7,14,15,17]. For example, the associa-
tion between ruminant-associated genotypes and pre-
school-age children (0–5 years of age) in rural areas
has provided evidence for direct contact with faecal
material being the foremost infection route in this
high-incidence group .
This is of high relevance for the development and eval-
uation of appropriate, country-specific control strate-
gies to decrease the human disease burden. Since the
number of human cases linked to poultry has fallen
in New Zealand, there has been a relative increase in
importance of ruminant strains of C. jejuni, and ongo-
ing work is investigating the complex epidemiology of
Campylobacter in ruminant  and wildlife sources
. While this article describes the MLST-supported
Campylobacter surveillance conducted at the sentinel
site, other typing approaches are used to increase reso-
lution of the molecular analysis. For example, research
is currently underway to further differentiate between
exposure to ruminant-associated Campylobacter sub-
types of food and non-food origin to refine attribution
estimates using antigen gene sequence typing ,
ribosomal MLST  and targeted genes identified by
whole genome analysis . In this article, we summa-
rise the experience gained in New Zealand and discuss
how this experience could be used to further advance
the use of molecular tools in surveillance.
What have we learned?
Experience from New Zealand and elsewhere has pro-
vided insight into key aspects of molecular-based
surveillance. These include the following: (i) its appli-
cation to both control-focused and strategy-focussed
surveillance; (ii) a change in our definition of epidemio-
logical response variables; and (iii) the emergence of
Application of molecular tools
to disease surveillance
The framework developed by Baker et al. , which
differentiates between control-focused and strategy-
focused surveillance, provides a meaningful way to
Relative ratesa of notification of campylobacteriosis, cryptosporidiosis, salmonellosis and yersiniosis, New Zealand,
2002–2011 compared with 1999–2001
a Rates were calculated using a negative binomial model, which was used to estimate the change in incidence between each year from 2002 to
2011 and the reference period of interest, 1999–2001, as previously described by Henao et al. . Values above the reference line indicate
increases in notification incidence and points below the line show decreases, relative to the 1999–2001 reference period.
The pre- and post-intervention periods refer to the implementation of a number of control measures in the poultry supply chain by the
regulatory authority. The annual incidence of other enteric notifiable diseases (cryptosporidiosis, salmonellosis and yersiniosis)
over the same time period is displayed to show that notification rates were stable for other comparable disease and that the drop in
campylobacteriosis notifications was not a surveillance artefact.
Relative rate (log scale)
Pre-intervention periodPost-intervention period
1999−2001 200220032004 2005200620072008 200920102011
Human cases of campylobacteriosis caused by poultry- and ruminant-associated Campylobacter jejuni MLST types, as well
as a ubiquitous ST in a sentinel surveillance site, New Zealand, 2005–2011
MLST: multilocus sequence typing; ST: sequence type.
Panel A shows the time series of human campylobacteriosis cases with two poultry-associated genotypes, ST-474 and ST-48 and illustrates
the drop in the number of cases following interventions in the poultry production chain.
Panrel B shows the trend in human campylobacteriosis cases with ruminant-associated genotypes ST-61, ST-42, ST-422 and ST-53.
Panel C shows the time series of human campylobacteriosis cases with the ubiquitous ST-45.
Number of cases
Number of cases
Number of cases
Date (month, year)
200620072008 2009 20102011
2006 20072008 20092010 2011
Pre-intervention periodPost-intervention period
ST-61, ST-42, ST-422 and ST-53
categorise molecular approaches to disease surveil-
lance. Approaches that are suitable for control-focused
surveillance, such as those used in an outbreak setting,
are potentially of lesser value for strategy-focused sur-
veillance, where the aim is often to monitor long-term
changes in epidemiology [24,25], and vice versa.
The purpose of control-focused surveillance is ‘to iden-
tify each occurrence of a particular disease, hazard,
or other health-related event that requires a specific
response, and to support the delivery of an effective
intervention’ . Such surveillance requires methods
that have a high degree of timeliness, sensitivity and
security (i.e. that can be maintained on an ongoing
basis) . The molecular typing tools and associated
modelling approaches required for this objective need
to be capable of identifying genotypes that indicate
a common source of disease or highlight a particular
transmission pathway. Often, but not always, this is
achieved through highly discriminatory typing tools.
Using a recently developed model-based tool for iden-
tifying clusters of campylobacteriosis cases related in
space and time , eight cases in a small area of New
Zealand’s North Island were identified as having a high
probability (>0.8) of being part of an anomalous cluster
(i.e. they were more spatially and temporally localised
than would be expected given the average temporal
and spatial patterns). Inspection of the epidemiologi-
cal information linked to each case revealed that they
were reported within a single two-week period and
typing data showed that they were all the same MLST
sequence type (ST-520). When compared with a larger
database of over 3,000 sequence types isolated from
humans, animals and food in New Zealand it was
shown that this type was associated with ruminants in
New Zealand, but was a relatively uncommon cause of
human infection. This finding triggered a more detailed
investigation into the cases, requiring further contact
with some affected individuals, which revealed that
all cases had consumed unpasteurised (raw) milk – a
relatively rare risk factor – and that 7/8 cases reported
purchasing the milk from the same source farm. This
combination of epidemiological information and typ-
ing data lead to a local response and also informed the
ongoing debate on the national policy concerning the
sale of raw milk.
The purpose of strategy-focused surveillance is ‘to
provide information to support prevention strategies to
reduce population health risk, such as describing the
epidemiology of the annual influenza season and the
characteristics of the seasonal influenza viruses’ .
Such surveillance requires methods that have a high
degree of representativeness, completeness (refer-
ring to the data recorded with each event) and validity
. Different molecular and modelling approaches are
required in this instance, with the optimal tools pro-
viding information on the long-term epidemiology of a
pathogen rather than short-term changes. An example
is the recent emergence of new approaches to source
attribution using molecular subtyping, which has been
used successfully in several countries to understand
the relative contribution of different sources to the
burden of human campylobacteriosis and salmonello-
sis [27-30]. Source attribution models based on micro-
bial subtyping were initially developed in Denmark as
a tool for salmonellosis risk management ; they
provide estimates of the number of human cases origi-
nating from different sources or reservoirs based on a
comparison of genotypes [31,32].
In New Zealand, attribution models were adapted
to data from the MLST surveillance site. Two mod-
els were used, a population genetics-based attribu-
tion model  and the microbial subtyping-based
model by Hald et al. , to quantify the contribution
of selected sources to the human disease burden.
These studies revealed that between 2005 and 2008,
poultry was the leading source of human campylo-
bacteriosis, causing an estimated 58–76%, of notified
cases . Contributions by individual poultry suppliers
showed wide variation and supplier specific strains
were detected . The use of these models to monitor
changes over time and to assess the effectiveness of
interventions is ongoing [10,11].
Re-defining response and explanatory variables
using molecular tools – a new epidemiological
approach to inform surveillance?
A common starting point of epidemiology is seeking
non-random associations between response variables
and potential explanatory variables. Regression mod-
elling, for example, may be used to identify statisti-
cally significant predictors of increased risk of adverse
health effects . However, the use of such traditional
methods for quantifying the contribution of different
sources of campylobacteriosis to the disease burden
in New Zealand (notably case–control studies [9,34],
which identified poultry as the major source of human
infection) had not provided sufficient compelling evi-
dence for decision-makers to invest in controlling the
poultry source. The epidemiology of campylobacteri-
osis is challenging: as a multi-host pathogen, infection
with C. jejuni is associated with a large number of risk
factors  and human cases arising from exposure
to different sources may have very different risk fac-
tors, some of which may even be protective for some
sources and increase the risk for others.
Using molecular tools, pathogen genetics and evolu-
tion can be incorporated into epidemiological model-
ling to make inferences about disease or transmission
risks rather than simply relying on the association of
response and explanatory variables. Such tools can
be used to refine outcome variables, for example by
using case–case comparison of poultry- and ruminant-
associated cases of campylobacteriosis to identify
more subtle associations [14,17] or to investigate the
cause of a disease outbreak . However, greater
epidemiological gains are likely to be made when mod-
els combine pathogen evolution and transmission in
an integrated way [36,37]. This may be best achieved
by modelling a relatively low number of isolates with
high-coverage sequence data, such as increasingly
available full genome data  or a larger number of
isolates with low coverage such as a 7-locus MLST
scheme. The additional information provided even by
routinely applied molecular tools such as pulsed-field
gel electrophoresis (PFGE) adds to our understanding
of epidemiological variables. For example, the level of
similarity and relatedness of restriction-enzyme pro-
files in the analysis of a food-borne outbreak can be
directly used to refine epidemiological investigations.
It is the synergy between the epidemiological and typ-
ing information that makes molecular tools so power-
ful and novel modelling approaches are constantly
being developed to advance research at this interface
Into the future: genomic epidemiology
New modelling approaches are being adopted to utilise
the abundance of molecular data available [24,39,40].
Bell et al.  argue that the enormous volumes of
data that can be provided by new technology provides
many challenges for data management and analysis,
and that we have entered a new area of data-intensive
science that requires specialised skills and analytical
tools. This argument holds true in the area of molec-
ular epidemiology: next generation high throughput
sequencing has vastly increased the availability of
pathogen genome sequence data  and as the costs
decrease, these tools will be more frequently incorpo-
rated into epidemiological studies and surveillance. By
fitting statistical genetics and epidemiological models
to sequence data, and combining these within a single
framework , new insights can be gained into path-
ogen evolution, the nature of associations between
strains of pathogens and host species, the timing of
emergence, origin and geographical spread of patho-
gens, and aspects of between-host transmission .
Furthermore, advances in statistical methods for mod-
elling evolutionary ancestry are resulting in better
reconstructions of pathogen genealogies and improved
estimates of evolutionary parameters. Although com-
plex in nature, these models can be extremely valuable
– for example, they can be used to enable the contribu-
tion of different sources and transmission pathways to
the human disease burden to be determined .
In New Zealand, whole genome sequencing is being
used to understand the evolution of epidemiologi-
cally important strains of C. jejuni and identify poten-
tial markers for host association . This may help
to improve the discrimination of sources of human
infection, such as between cattle and sheep, and
result in more precise source attribution estimates.
Similarly, full genome sequence data from multiple
Campylobacter isolates and Escherichia coli O157 are
being combined with phenotypic microarray data to
improve the understanding of the relationship between
phenotype and genotype. The identification of genetic
markers for stress resistance, such as pH, temperature,
oxidative stress, and freeze-thaw , could help to
determine which sources and transmission pathways
strains isolated from humans have been acquired
from, further refining attribution studies and strategy-
By furthering our understanding of host associations
with particular strains of pathogens, and the relative
rates of transmission between animals and humans,
the melding of statistical genetics and epidemiology
with partial and full genome sequence data will further
inform and refine control strategies for enteric patho-
gens in New Zealand and elsewhere.
New Zealand provides a distinctive island ecosystem
in which to study infectious diseases . The rela-
tive isolation and management of farmed livestock
has contributed to the epidemiology and population
structure of microbial pathogens. For example, the
country’s poultry industry is structured in a way that
is different to most countries, with no importation of
untreated poultry products and freedom from several
important poultry diseases such as Newcastle dis-
ease and Salmonella enterica serovar Enteritidis PT4.
Furthermore, the production of poultry meat is highly
integrated, with three companies supplying about 90%
of all chicken meat . In addition a risk management
strategy developed by the regulator supports a strong
collaboration with researchers and science-based deci-
sion-making . While the situation in other countries
is likely to be more complex, for example through the
presence of federal regulations or the risks associated
with poultry importations, lessons learned from New
Zealand can be applied elsewhere.
The New Zealand approach, which includes the first
large scale implementation of effective regulatory
Campylobacter control measures in broilers, is of high
relevance internationally, including Europe. Findings
have been incorporated in scientific opinions of the
European Food Safety Authority. In 2008, it was
acknowledged that the MLST approach to source attri-
bution developed in New Zealand may be the way for-
ward  and the approach is being used in several
European countries, including the Netherlands and
Scotland [2,49]. The New Zealand experience was also
included in an assessment of the extent to which meat
derived from broilers contributes to human campylo-
bacteriosis at the European Union level .
The molecular tools deployed in epidemiological
and evolutionary analyses clearly need to be fit-for-
purpose. Ideally, during their development phase,
measures of their utility in specific settings, such as
discriminatory power and the strength of association
between genotype and host, should be considered
and attempts made to optimise their performance for
the outcome in mind. In the case of 7-locus MLST, for
example, retrospective analyses have shown this to be
a valuable approach for certain types of surveillance,
including reservoir attribution, but the method was not
designed for this purpose and an alternative approach
based on a different set of gene targets may perform
better and be more cost-effective. Equally important
are rigorous sampling size considerations and guid-
ance on the number of samples from different sources
to acquire a desired level of precision – for example, in
source attribution estimates. Further work will be nec-
essary to develop expert agreement and sound work-
ing principles on these matters.
The field of molecular epidemiology is continually
evolving and its role in advancing our ability to under-
stand and control infectious diseases will also keep
increasing. Its interdisciplinary nature will provide key
support to One Health approaches to disease control,
by supplementing medical and veterinary expertise
with an in-depth understanding of the molecular biol-
ogy of pathogens. As genotyping approaches and ana-
lytical models continue to evolve, an understanding
of the complex interface of both disciplines becomes
a crucial element of molecular-based disease surveil-
lance. In New Zealand, we have learned that close col-
laboration between laboratories and epidemiologists
is extremely important for the success of molecular-
based surveillance: in our example, this started when
the sentinel surveillance site was first set up. In a
small and geographically isolated country, such early
collaboration is likely to be more easily achieved; nev-
ertheless, the general principle still applies and could
add value to molecular surveillance in other countries.
The authors are thankful to all members of the Hopkirk
Molecular Epidemiology Team, Environmental Science and
Research (ESR), MidCentral Health, Public Health Services,
Science and Risk Assessment, Ministry for Primary Industries
(MPI) and MedLab Central (in particular Lynn Rogers) for
their contributions. This work was supported by MPI through
their Postgraduate PhD Program ‘Estimating the contribution
of different food sources to the burden of human campylo-
bacteriosis in the Manawatu’ and the project ‘Enhancing
surveillance of potentially foodborne enteric diseases in
New Zealand: human campylobacteriosis in the Manawatu’
(FDI / 236 / 2005).
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