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. 2025 Jun 18;104(1-2):25–36. doi: 10.1111/avj.13465

A contemporary map of Fasciola hepatica distribution in sheep and cattle in New South Wales

SN Vyas 1, J Mckay‐Demeler 2, MP Ward 1, NED Calvani 1,3,✉
PMCID: PMC12875739  PMID: 40533840

Abstract

Fasciola hepatica is a global threat to livestock production, human health, and food security. Infection causes significant reductions in milk production and quality, feed conversion efficiency, wool quality, and reproductive performance. In New South Wales (NSW), Australia, data on the distribution of F. hepatica are more than 50 years out of date and lack species‐specific insights for cattle and sheep. Accurate, up‐to‐date distribution data are essential for livestock producers to implement targeted control programs, for veterinarians to provide timely and effective treatment recommendations, and for researchers to identify emerging trends, such as those influenced by climate change. This study addresses this knowledge gap by using diagnostic samples submitted to the Elizabeth MacArthur Agricultural Institute (EMAI) between 2019 and 2023 to update the distribution of F. hepatica in cattle and sheep in NSW. Diagnostic records were extracted, cleaned, analysed, and geospatially mapped at the postcode level to reveal temporal and spatial trends by livestock species. Our findings suggest that F. hepatica hotspots in sheep are concentrated in the southeastern regions of NSW, whereas in cattle, hotspots extend along the coast. These results reinforce the existing dogma of F. hepatica distribution in NSW, providing evidence‐based insights that are key to improved surveillance, refining precision parasite management, and mitigating the ongoing impacts of F. hepatica on animal health and production in NSW.

Keywords: clustering, diagnostics, liver Fluke, livestock, surveillance

Fasciola hepatica, commonly known as the liver fluke, is the most widely distributed helminth parasite globally, endemic in over 70 countries. 1 F. hepatica infects a wide range of mammalian hosts, including livestock, humans, macropods, and rodents. 1 , 2 A major cause of livestock production losses, infection manifests as acute, subacute or chronic fasciolosis. Migration of juvenile flukes through the liver parenchyma and the presence of adult flukes in bile ducts can cause severe anaemia, inflammation, cholestasis, jaundice, and sudden death, particularly in sheep. 3 Even subclinical infections, most commonly seen in cattle, lead to disruptions in animal growth rates, milk quality, and feed conversion efficiency. 4 , 5 In Australia, the estimated annual loss to the sheep meat industry from liver fluke alone rose from $25 million in 2015, to over $38 million in 2022. 5

The F. hepatica life cycle involves both a mammalian definitive host and a freshwater snail intermediate host. 6 Numerous factors, including climate and the availability of intermediate hosts, are known to influence liver fluke transmission dynamics, host–parasite interactions, shedding, and survival of infectious stages, all of which ultimately affect mammalian host morbidity and mortality. 2 , 7 , 8 Environmental risk factors for fasciolosis, which largely determine the geographical distribution of F. hepatica within a given region, include high rainfall, mean temperatures between 20 and 30°C, humidity exceeding 90%, and access to favourable water bodies. 9 Increased variation in these factors due to climate change has already been shown to impact infection risk in the UK. 10 Additionally, the impact of exotic snail intermediate hosts on the seasonality and distribution of infection is yet to be investigated since they were first detected in Australia in 1973, despite their known influence on the epidemiology and distribution of F. hepatica infection in New Zealand. 11 , 12 , 13

Pioneering research on the bionomics, ecology, and distribution of F. hepatica in Australia was conducted by Ian Clunies Ross and Herbert Seddon from the 1920s onwards. 14 , 15 Extensive studies into the ecology of intermediate snail hosts, development and efficacy of flukicides, livestock production impacts, and seasonality of infection were later led by Joseph Boray from the 1960s. 2 , 7 , 8 , 16 Collectively, their work out of the McMaster Laboratory of the C.S.I.R.O. – now part of the Sydney School of Veterinary Science at the University of Sydney – established that liver fluke was widely distributed in cattle and sheep, particularly in the Southeast, Northern Tablelands and North Coast of NSW, the southern border and coast of Queensland and most of Victoria. 15 This work formed the basis for government advice on the management of fasciolosis that exists to this day. 17 More recent studies have focused on the detection of drug‐resistant F. hepatica and determining prevalence on selected farms in prime dairy regions in Victoria. 18 , 19 While efforts have been made to map the distribution of infection in cattle, no large‐scale maps have been produced for both livestock species since the time of Clunies Ross, Seddon, and Boray, leaving a critical gap in our understanding of the current distribution and geographic trends of F. hepatica in cattle and sheep. 20 , 21 , 22 , 23 , 24

This study aims to update the current distribution of F. hepatica in cattle and sheep across NSW by using diagnostic samples submitted to the Elizabeth Macarthur Agricultural Institute (EMAI) over a five‐year period (2019–2023). Specifically, it seeks to identify species‐specific distributions highlighting temporal and spatial trends. Using spatial scan analysis and autocorrelation statistics, this study identifies liver fluke hotspots and global clustering patterns, offering evidence‐based insights to guide targeted interventions, improve surveillance, and support veterinarians in developing fasciolosis management strategies in NSW.

Materials and methods

Data collection

Results for cattle and sheep sample submissions requesting F. hepatica diagnostic tests spanning 1 January 2019, and 31 December 2023, were extracted from EMAI's ‘Sample Manager’ software onsite using the ‘Ad‐Hoc Reporter’ function. To ensure anonymity, each submission was assigned a unique ‘Job ID’ for cleaning prior to analysis at the postcode level. For each species and year, nine diagnostic test codes were analysed (Table 1). Results for antibody ELISAs or Western Australia (WA) export testing were excluded from the analysis as they do not accurately represent current F. hepatica infection status (Figure 1).

Table 1.

The nine F. hepatica diagnostic test codes extracted from EMAI's Sample Manager according to the test types available

EMAI test code Test type Data type
FEC_FLUKE Sedimentation individual Quantitative
WT_FLUKE_2 Sedimentation pooled 2 Quantitative
WT_FLUKE_5 Sedimentation pooled 5 Quantitative
FLUKE_QUAL Sedimentation individual Qualitative
FLU_QUAL_2 Sedimentation pooled 2 Qualitative
FLU_QUAL_5 Sedimentation pooled 5 Qualitative
FASC_AGEL Copro‐ELISA individual Qualitative
FASC_EL_2 Copro‐ELISA pooled 2 Qualitative
FASC_EL_5 Copro‐ELISA pooled 5 Qualitative
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‘Pooled 2/5’ indicates how individual samples are pooled (in groups of two or five) when multiple samples are received in one submission before being tested in bulk. ‘Individual’ indicates samples that are not pooled for testing. ‘Copro‐ELISA’ refers to a commercially available coprological antigen ELISA test. ‘Data type’ indicates whether a given test provides a quantitative or qualitative (positive/negative) result.

Figure 1.

Figure 1

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A schematic representation of the data cleaning and exclusion criteria for samples submitted to the Elizabeth Macarthur Agricultural Institute (EMAI) for Fasciola hepatica diagnostic testing. Submitters could request quantitative or qualitative tests, with samples tested individually or in bulk (pooled). Bulk tests were pooled into two (_2) or five (_5) aliquots, depending on the number of samples submitted. Tests that do not indicate current infection (antibody ELISA) or are biased towards negative results (WA export testing) were excluded from further analysis. Individual test codes included in the analysis are shown in coloured bubbles above the ‘test outcome’. If any of the test codes returned a positive result, F. hepatica was considered present on the property. Figure created in BioRender.

For sedimentation‐based diagnostics, a standard sedimentation protocol was followed. Briefly, 2 g (ovine) or 10 g (bovine) faeces were weighed out, sieved through a 150 μM mesh (washing step) and retained on a 45 μM sieve. The retained material was washed off the sieve into a plastic cone and allowed to sediment for 3 minutes, then the supernatant was removed, the cone was filled with water again and the sedimentation procedure was repeated (total 3–4 times). The final sediment was mixed with 1% Methylene Blue solution and transferred into a counting chamber. For the copro‐antigen ELISA, a commercially available kit was used (BioX, Belgium) and the manufacturer's protocol was followed. Cut‐off levels were adjusted for bovine samples (4.7) and samples submitted for pooled testing (6 for ovine, 3.2 for bovine).

The extracted dataset included the following columns: ‘Sample Type – Specific’, ‘Analysis’, ‘Date Job Received’, ‘Date Samples Collected’, ‘Analysis Description’, ‘Job Name’, ‘Lhpa District’, ‘Local gov area’, ‘Property postcode’, ‘Reason for Testing’, ‘Result’, ‘Worm classification’, ‘Sample number’, ‘Submitter ID’ and ‘Property ID’.

Data preparation and cleaning

Data cleaning was performed in Microsoft Excel (version 16.84). Submissions with unknown or grouped species classifications (e.g., “SHEEP/GOAT” or “CATTLE/HORSE”) were manually cross‐checked against the original submission details, and data for species other than cattle or sheep submissions were excluded.

Data were grouped at the postcode level using a pivot table to group ‘Job IDs’ under their corresponding ‘Property postcode’. This pivot table was combined with the ‘Collated Table’ to produce a ‘Final Table’, which summarised the number of tests submitted and the number of positive tests per postcode. From this ‘Final Table’, the proportion of F. hepatica positive tests per postcode was calculated for each species and year. Since we did not have access to unique property identification information, a summary ‘Collated Table’ containing unique ‘Job IDs’ and corresponding ‘Final results’, ‘Property postcodes’ and ‘Date received’ was created for each species per year (Supplementary Data 1) and spatial analysis was conducted at the postcode level.

To facilitate data analysis, all test results (quantitative and qualitative) for each submission were transformed into a binomial variable (‘Present’ (1) vs. ‘Absent’ (0)) in a new column (‘Final result’) using the IF function in Excel (Table 1, Figure 1). The nine test code datasheets were then merged into a single result sheet per species and year. If any of the test codes requested for an individual property were positive, F. hepatica was considered ‘Present’ on the property in that calendar year (Figure 1).

Mapping and statistical analyses

Summary data by postcode were imported into ArcPro (ESRI, Redlands CA) and joined to a shapefile (GDA1984) of NSW and Australian Capital Territory (ACT) postcodes. Choropleth maps were created of (a) the number of tests submitted per postcode and (b) the proportion of test positive samples per postcode. For both these quantitative spatial distributions, Moran's spatial autocorrelation statistic (using an inverse distance [Euclidean] squared weighting) and associated P‐values were calculated (Spatial Statistics. ArcPro). Maps were created for cattle and sheep, both annually (2019, 2020, 2021, 2022 and 2023) and cumulatively (2019–2023). The proportion of positive samples was calculated as the total number of positive test results (‘Present’) during the study period divided by the total number of tests submitted per postcode during the study period. For the number of samples, quartiles were used to display the distributions, whereas deciles were used for the proportion of test positive samples.

Hotspots of positive test results (‘Present’) were identified using a spatial scan statistic applied to the data from all years. A Bernoulli model was used in which for each postcode (centroid X, Y coordinates), the positive test results were cases and the negative test results were controls. The data was scanned for spatial clusters up to 50% of the study area. Within each scanning window, the expectation was calculated based on the overall number of cases in the dataset over the entire study area. 25 Statistical significance was estimated using Monte Carlo simulation (999 iterations). Clusters (X, Y coordinates and radius) were interpreted based on the number of positive tests reported in the cluster versus the number expected (observed‐to‐expected ratio). Identified clusters were mapped over their respective distributions.

Results

F. hepatica test intensity and distribution across NSW increased over time and differed according to livestock species

Between 2019 and 2023, the number and geographic distribution of samples submitted to EMAI for F. hepatica diagnostic testing increased for both cattle and sheep (Figures 2 and 3). The highest number and widest distribution of tests occurred in 2022 for both species (Tables 2 and 3). More tests were requested for sheep than cattle until 2021, when the number of requests for cattle dramatically increased from 384 tests to 1415 tests (Table 2). This increase was particularly evident in the Southwestern Sydney, Illawarra Shoalhaven, and the Southern NSW regions, where testing intensity in cattle rose from little/absent in 2019 to >300 samples submitted per postcode between 2021 and 2023. No samples were submitted from cattle in Far West NSW before 2022, while up to 14 samples were submitted for a single postcode in 2023. Autocorrelation analysis for 2023 revealed statistically significant moderate global clustering of cattle sample submissions (I = 0.1598, P = 0.0127), suggesting that testing activity was not randomly distributed, but rather spatially concentrated in specific regions (Figure 2(E)).

Figure 2.

Figure 2

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The distribution of cattle samples submitted to EMAI per year for Fasciola hepatica diagnostic testing. The number of tests submitted per postcode each year (A–E) is represented in blue according to quartiles based on total tests submitted that year. Postcodes coloured grey received no submissions. Statistically significant global clustering is indicated by a blue star for 2023 (I = 0.1598, p = 0.0127). The cumulative distribution of all tests submitted over the five‐year period is shown in (F). Maps were generated using ArcPro software (ESRI, Redlands CA).

Figure 3.

Figure 3

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The distribution of sheep samples submitted to EMAI per year for Fasciola hepatica diagnostic testing. The number of tests submitted per postcode each year is represented in orange according to quartiles based on the total number of tests submitted that year. Postcodes coloured grey received no submissions. Statistically significant global clustering in 2022 is indicated by an orange star (I = 0.3873, p = 0.0422). The cumulative distribution of all sheep samples submitted for testing over the five‐year period is shown in (F). Maps were generated using ArcPro software (ESRI, Redlands CA) software.

Table 2.

Summary of tests submitted and F. hepatica positive results from cattle in NSW for samples submitted for routine testing between 2019 and 2023

Year Number of positive job IDs/Total number of job IDs (%) Number of positive tests per postcode/Total number of tests per postcode (%)
2019 19/108 (17.6%) 94/458 (20.5%)
2020 24/114 (21.1%) 49/348 (14.1%)
2021 42/166 (25.3%) 80/384 (20.8%)
2022 118/466 (25.3%) 193/1415 (13.6%)
2023 98/420 (23.3%) 216/1175 (18.4%)
Average 60.2/254.8 (22.5%) 126.4/756 (17.5%)
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Table 3.

Summary of tests submitted and F. hepatica positive results from sheep in NSW for samples submitted for routine testing between 2019 and 2023

Year Number of positive job IDs/Total number of job IDs (%) Number of positive tests per postcode/Total number of tests per postcode (%)
2019 4/63 (6.3%) 8/153 (5.2%)
2020 49/91 (53.8%) 16/320 (5.0%)
2021 22/180 (12.2%) 33/399 (8.3%)
2022 37/234 (15.8%) 61/546 (11.2%)
2023 31/154 (20.1%) 60/344 (17.4%)
Average 28.6/144.4 (21.6%) 35.6/352.4 (9.4%)
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In contrast to cattle, testing for F. hepatica in sheep was more widely distributed across NSW throughout the study period (Figure 3). Testing intensity remained consistently high in the Southern and Western regions across all 5 years. In 2019 and 2020, sheep sample submissions were primarily concentrated around the Nepean, Western NSW (southern border), and the Southern Slopes and Tablelands (Figure 3A,B). In comparison, regions including the Far West, Murrumbidgee Irrigation area, and New England experienced an increase in testing intensity from 2021 (Figure 3C,E). Autocorrelation analysis revealed statistically significant global clustering of sheep testing in 2022 (I = 0.3873, P = 0.0422), which is stronger than observed for cattle (Figure 3D). The observed increases in testing for both species are likely influenced by an awareness campaign run in 2020 by EMAI in conjunction with District Veterinarians (DVs) and Local Land Services (LLS) to remind farmers of the importance of testing for liver fluke.

The distribution of F. hepatica in cattle extends along the coast of NSW

The proportion of F. hepatica positive test results in cattle remained consistent across the years analysed, averaging 22.5% (Table 2). Geospatial mapping revealed that F. hepatica infection in cattle is primarily concentrated along the Eastern coastline in the Southern, Murrumbidgee irrigation area (eastern border), Nepean, Hunter, and New England regions (Figure 4, Table 4). Spatial scan analysis identified five significant clusters of F. hepatica infection (Figure 5A, Table 4). Clusters 1B, 1D, and 1E (all north of Sydney) showed consistently high testing intensity and corresponding high proportions of positive test results across the 5 years, suggesting that F. hepatica is likely endemic in these areas, with environmental conditions supporting ongoing transmission (Figure 5A). In contrast, cluster 1C showed a high positive rate despite decreased testing intensity over time. This pattern may reflect targeted testing in high suspicion cases, where testing is focused on animals or properties with a history of infection. Cluster 1A was the largest of all identified clusters, encompassing 27 postcodes with a radius of 249.4 km in the southeastern corner of NSW along the coast and Victorian border, where the majority of the state's dairy production is concentrated (Table 4). 26 Outside these identified hotspots, areas within the Hunter, New England, and North Coast regions returned a low proportion of positive tests despite high testing density along the northeastern coastline (Figure 5A). These results suggest that F. hepatica infection in these regions is limited, potentially due to less favourable environmental conditions, fewer cattle, or more effective parasite management.

Figure 4.

Figure 4

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The geographic distribution of Fasciola hepatica positive cattle samples submitted to EMAI for diagnostic testing between 2019 and 2023. The proportion of tests returning positive results per postcode each year is represented in blue. Postcodes coloured grey received no submissions. Statistically significant global clustering is indicated by blue stars: 2019 (I = 1.0102, P = 0.001), 2023 (I = 0.2164, P value = 0.0033), All years (I = 0.1305, P = 0.0329). The cumulative distribution of F. hepatica positive test results across all years analysed is shown in (F). Maps were generated using ArcPro software (ESRI, Redlands CA).

Table 4.

Clusters of F. hepatica positive results identified by spatial scan analysis of samples from cattle (clusters 1A–E) and sheep (clusters 2A–C) submitted to EMAI for routine testing between 2019 and 2023

Cluster Regions Postcodes Radius (km) Observed cases Expected cases Observed/expected (p value)
1A Capitol, Western, southern highlands, Murrumbidgee irrigation, Illawarra 27 249.4 219 94.4 2.32 (P < 0.00001)
1B Newcastle and Lake Macquarie 2 8.2 20 6.0 3.33 (P = 0.00012)
1C Sydney 3 16.0 9 1.7 5.39 (P = 0.00032)
1D New England and northwest 1 N/A 9 2.0 4.49 (P = 0.0056)
1E Mid North Coast and Hunter Valley 6 44.0 56 31.9 1.76 (P = 0.0057)
2A Western 5 23.9 75 32.6 2.30 (P < 0.000091)
2B Murrumbidgee irrigation area 1 N/A 16 3.1 5.13 (P = 0.00000091)
2C Illawarra, southern highlands 4 54.3 15 4.3 3.48 (P = 0.0021)
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Figure 5.

Figure 5

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Spatial scan analysis of Fasciola hepatica positive test results in (A) cattle and (B) sheep in NSW based on samples submitted to EMAI for diagnostic testing between 2019 and 2023. Circles indicate the location of clusters, with bolded circles denoting primary clusters. For cattle, clusters were identified in the Capitol, Southern Highlands, Riverina, Illawarra, New Castle, Lake Macquarie, Sydney, New England, and Mid North Coast regions. For sheep, significant clusters were identified in the Central West, Riverina, Illawarra, and Sothern Highlands regions. Postcodes were acquired from NSW ‘Regions, Sub‐regions and Postcodes’ report 2022. 40 Maps were generated using ArcPro software (ESRI, Redlands CA) software.

Autocorrelation statistics confirmed significant global clustering of F. hepatica positive test results in cattle in 2019 (Figure 4A) (I = 1.0102, P = 0.001), 2023 (Figure 4E) (I = 0.2164, P = 0.0033) and the cumulative data for 2019–2023 (Figure 4F) (I = 0.1305, P = 0.0329).

The distribution of F. hepatica in sheep remains localised around the southeast corner of NSW

For sheep, the highest proportion of F. hepatica positive tests (17.4%) and the highest proportion of positive properties (53.8%) were both recorded in 2023 (Table 3). The distribution of F. hepatica positive test results in sheep was primarily concentrated in the Southern, Murrumbidgee (eastern border), Western (southern border), Illawarra, and Southwestern Sydney regions (Figure 6). Spatial scan analysis identified three significant hotspots in the southeastern corner of NSW (Table 4, Figure 5B). All three clusters exhibited consistently high testing intensity and a high proportion of positive test results except for one postcode in cluster 2C. This postcode maintained a high proportion of positive test results even when test intensity declined, suggesting targeted testing.

Figure 6.

Figure 6

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The geographic distribution of Fasciola hepatica positive sheep samples submitted to EMAI for diagnostic testing. The proportion of tests returning positive results submitted per postcode each year is represented in orange. Postcodes coloured grey received no submissions. Statistically significant global clustering for all years is represented by an orange star (I = 0.3103, P = 0.0052). Maps were generated using ArcPro software (ESRI, Redlands CA).

The proportion of positive test results varied between years, with only 6.3% of properties returning positive results in 2019, followed by a marked increase to 53.8% of properties in 2020 (Table 3). This variability may reflect fluctuations in diagnostic activity or environmental factors influencing F. hepatica survival and transmission.

Autocorrelation analysis confirmed statistically significant global clustering of F. hepatica positive test results in sheep for the cumulative dataset spanning 2019–2023 (I = 0.3103, P = 0.0052; Figure 5F). However, no statistically significant clustering was detected for individual years, suggesting a more consistent pattern of F. hepatica clustering across the entire study period in sheep.

Discussion

This study provides the first species‐specific update on F. hepatica distribution in NSW in over 50 years, offering critical insights for veterinarians and livestock producers. Using diagnostic submissions to EMAI between 2019 and 2023, our results confirm that F. hepatica remains endemic along the eastern and southeastern regions of NSW, with evidence of some westward expansion compared to historical estimates. 15 These findings emphasise the importance of ongoing diagnostic surveillance and data analysis to guide targeted parasite management strategies and reduce the economic burden of fasciolosis.

Our results show distinct differences in testing intensity and distribution between sheep and cattle. Testing intensity was consistently higher in sheep throughout the study period, likely reflecting the acute nature of fasciolosis in this species and an associated heightened awareness among producers and veterinarians. Sheep are highly susceptible to F. hepatica infection, often presenting with clinical signs such as anaemia, jaundice, diarrhoea, and sudden death that prompt diagnostic investigation. 2 The non‐specific nature of these clinical signs warrants differential diagnosis from Haemonchus contortus (Barber's Pole Worm), which may account for increased submissions in sheep in areas where the two parasite species are endemic.

In contrast, cattle exhibited lower testing intensity than sheep, potentially reflecting the subclinical presentation of fasciolosis in this species. Chronic infections, while often less overt, cause reductions in milk yield and quality, growth, and reproductive performance and warrant strategic treatment. 4 , 27 These losses may go unnoticed by livestock producers, reducing the perceived need for diagnostic testing. In dairy cattle, significant losses occur when within‐herd prevalence exceeds 25%. 4 A recent survey on grazier perceptions and management practices for liver fluke in northeastern NSW highlighted that 60% of producers in the region never perform liver fluke diagnostic testing. 28 While the relationship between livestock species and producer preferences in this study is unknown, all livestock producers are encouraged to adopt strategic testing and treatment regimens to mitigate financial and welfare impacts, particularly in areas affected by increasing reports of drug resistance. 29 , 30 Further awareness campaigns by LLS and DVs are encouraged to address this testing deficit.

Observed differences in testing distribution between cattle and sheep may be partially explained by underlying natural differences in the livestock demographics in NSW. According to the most recent data from Meat and Livestock Australia (MLA), NSW is home to 24.7 million sheep and 4.4 million cattle, representing 37% and 20% of the national herd, respectively. 31 , 32 Sheep outnumber cattle across all NSW production regions, with the highest sheep numbers found in the Riverina, Central West, and South East. In contrast, cattle dominate in areas such as the North Coast and Hunter, where tropical and humid climates are less suitable for sheep. 33 This disparity in species distribution likely influences testing intensity, as enterprise type, farm size, and production systems shape the demand for diagnostic services. While our study highlights spatial trends in F. hepatica infection in NSW, these broader agricultural practices and population baselines are critical contextual factors when interpreting passive surveillance data.

It is also important to note that diagnostic submissions included in this study were limited to faecal detection methods and did not include milk or serum antibody ELISA testing. Antibody‐based detection methods are commonly used in dairy settings, particularly for bulk milk samples. 4 , 34 , 35 As these antibodies take up to 90 days posttreatment to decline, they should not be considered diagnostic indicators of current infection, but rather a measure of exposure. 36 , 37 Furthermore, commercial antibody ELISA kits have limited sensitivity for large herd sizes (typically up to 150–200 animals, which is often exceeded in Australian settings), and in many instances, information on herd size, treatment history, or sample origin is not provided on submission paperwork. 26 , 36 Using single‐point antibody results without historical baseline data, especially for individual samples, further complicates interpretation. As such, while the exclusion of these results in the current study may have underestimated exposure in dairy regions, the limitations of this data type preclude reliable inclusion. A more standardised approach to surveillance of antibodies in milk, alongside producer and veterinarian education on the value of antibody‐based diagnostic methods, would support the future integration of serological data in F. hepatica prevalence and distribution modelling.

Historical records describe F. hepatica as being endemic along the southeastern and northeastern coastline, with inland limits near Wagga Wagga (~300 km inland) and Inverell (~250 km inland). 15 While the overall distribution of F. hepatica remains consistent with these historical estimates, our results demonstrate a westward expansion, particularly in cattle. Cattle infections were detected as far as Condobolin (~400 km inland) in the southeast and the Liverpool Plains (~300 km inland) in the northeast (Figure 5A). Sheep infections, in contrast, remained predominantly within historical endemic zones, though some westward expansion was observed in areas such as Urana (~415 km inland, Figure 5B). It is possible that a westward shift reflects a combination of true geographic spread and increased diagnostic activity in these areas compared to historical surveillance.

The distribution of F. hepatica is intrinsically linked to environmental conditions, particularly temperature, rainfall, and humidity. Intermediate snail hosts, such as Lymnaea tomentosa, thrive in regions with moderate temperatures (~25°C) and high relative humidity (>90%). 7 , 9 , 10 , 14 , 16 In arid regions such as western NSW, lower rainfall and extreme temperatures limit snail survival and the viability of F. hepatica life stages (miracidia and metacercariae). However, large‐scale irrigation projects, such as the Murrumbidgee irrigation area, can sustain F. hepatica transmission in areas that would otherwise be unsuitable. 38 Irrigation systems create microhabitats that protect snail populations and infective metacercariae from desiccation, extending the seasonal window for transmission. 16 , 38 Producers and veterinarians working in areas reliant on artificial irrigation should remain vigilant to the impact posed by these microenvironments on liver fluke seasonality and monitor accordingly. In addition, the potential role of invasive intermediate snail hosts (e.g. Pseudosuccinea columella, first recorded in NSW in 1973) in expanding the geographic range of F. hepatica has been documented in New Zealand and elsewhere, and thus its role in the epidemiology of liver fluke in Australia warrants further investigation. 11 , 12 , 13 , 39

While this study identified broader spatial trends, a detailed analysis of seasonal and annual variation in F. hepatica prevalence was constrained by low sample numbers in individual years. Regions with low testing intensity, such as Far West NSW, suggest potential gaps in surveillance. However, low numbers of submissions in these areas do not necessarily indicate the absence of F. hepatica. Producers and veterinarians may rely on alternative diagnostic services, or the environmental conditions may not favour parasite transmission. Expanding surveillance to include data from regional diagnostic laboratories (such as those available in Wagga Wagga and Armidale) and abattoirs will improve our ability to capture seasonal dynamics and regional prevalence patterns, ensuring veterinarians and producers are equipped with timely, actionable insights to mitigate the impacts of fasciolosis. This study was also constrained by the lack of individual herd/flock identification information – a common issue encountered when using passive surveillance data. A more detailed property‐level analysis of the approach primary producers take to F. hepatica control using recently mandated eID tags (in sheep) combined with abattoir data is recommended.

Conclusion

This study builds on the pioneering work of Clunies Ross, Seddon, and Boray by providing the first species‐specific mapping of F. hepatica distribution in NSW in over half a century. While the overall endemicity of F. hepatica remains largely consistent with historical records, evidence of a westward expansion serves as a timely reminder of the dynamic nature of liver fluke epidemiology and the need for ongoing surveillance and management. As the agricultural landscape continues to evolve under the influence of climate change, this study provides an important baseline for future surveillance that underscores the need for evidence‐based approaches to fasciolosis control.

Conflicts of interest and sources of funding

Data was provided to SNV under a ‘Visiting Student and Scientist Deed’ between NEDC at the University of Sydney and JMD at EMAI. At the time of signing, it was noted that no conflict of interest exists or is likely to arise during the term of the Deed. All authors declare no known competing financial interests or personal relationships that may influence the reported findings.

Supporting information

Data S1. Supporting information.

AVJ-104-25-s001.zip (2.8MB, zip)

Acknowledgments

NEDC is an ARC‐funded Discovery Early Career Researcher (DECRA) Fellow (DE240100295). This work was completed in partial fulfilment of the requirements for the Doctor of Veterinary Medicine degree, The University of Sydney (SNV). This research was in part funded by the Sydney School of Veterinary Science Research & Enquiry Unit of Study fund. SNV and NEDC designed the project, methodology, and data acquisition conducted by SNV, JM, and NEDC; data analysis, curation, and visualisation were conducted by SNV, MPW, and NEDC. The original draft of the manuscript was written by SNV and NEDC and reviewed and edited by all authors. MPW and NEDC supervised the project. Open access publishing facilitated by The University of Sydney, as part of the Wiley ‐ The University of Sydney agreement via the Council of Australian University Librarians.

Vyas, SN. , Mckay‐Demeler, J. , Ward, MP. and Calvani, NED. , A contemporary map of Fasciola hepatica distribution in sheep and cattle in New South Wales. Aust Vet J. 2026;104:25–36. 10.1111/avj.13465

Data availability statement

The data that support the findings of this study are openly available in Lab Archives at https://www.doi.org/10.25833/0fa3-tt24.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1. Supporting information.

AVJ-104-25-s001.zip (2.8MB, zip)

Data Availability Statement

The data that support the findings of this study are openly available in Lab Archives at https://www.doi.org/10.25833/0fa3-tt24.

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