Comprehensive public health surveillance identifies novel human cryptosporidiosis subtypes and genetic diversity associated with swimming pool outbreaks in Australia, Victoria (2018-2024)

Comprehensive public health surveillance identifies novel human cryptosporidiosis subtypes and genetic diversity associated with swimming pool outbreaks in Australia, Victoria (2018-2024) | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Confirmatory Results Comprehensive public health surveillance identifies novel human cryptosporidiosis subtypes and genetic diversity associated with swimming pool outbreaks in Australia, Victoria (2018-2024) View ORCID Profile Marielle Babineau , View ORCID Profile Anson V. Koehler , View ORCID Profile Michelle L. Sait , View ORCID Profile Karolina Mercoulia , Sally Dougall , Jane McAllister , Evelyn Wong , Norelle L. Sherry , View ORCID Profile Robin B. Gasser , View ORCID Profile Benjamin P. Howden doi: https://doi.org/10.1101/2025.10.23.684085 Marielle Babineau 1 Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne , Parkville, Victoria 3010, Australia 2 Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne , Parkville, Victoria 3010, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Marielle Babineau Anson V. Koehler 2 Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne , Parkville, Victoria 3010, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anson V. Koehler Michelle L. Sait 3 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Michelle L. Sait Karolina Mercoulia 3 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Karolina Mercoulia Sally Dougall 4 Department of Health , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jane McAllister 4 Department of Health , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Evelyn Wong 4 Department of Health , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Norelle L. Sherry 1 Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne , Parkville, Victoria 3010, Australia 3 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Robin B. Gasser 2 Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne , Parkville, Victoria 3010, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robin B. Gasser Benjamin P. Howden 1 Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne , Parkville, Victoria 3010, Australia 3 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity , Melbourne, Victoria, Australia 5 Centre for Pathogen Genomics, The University of Melbourne , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Benjamin P. Howden For correspondence: bhowden{at}unimelb.edu.au Abstract Full Text Info/History Metrics Preview PDF ABSTRACT Cryptosporidium and Giardia are major causes of gastrointestinal illness globally. In Australia, cryptosporidiosis is a nationally notifiable disease, yet molecular characterisation of clinical cases is rarely performed, limiting the capacity to identify outbreaks, trace sources and assess zoonotic risk. During 2024 there was a 273% cases increase in Australia, the third country with the highest increase. We present the first comprehensive molecular investigation of human Cryptosporidium and Giardia infections in the state of Victoria, Australia. We analysed faecal samples collected between 2018 and 2024. Positive samples were subtyped and parasite load was estimated. Of the 2,330 samples tested, 225 were positive for Cryptosporidium and nine for Giardia . Seven Cryptosporidium species and 24 subtypes were identified, including multiple novel or regionally unique subtypes. C. hominis was the predominant species (85%), and three subtypes associated with 11 recreational water outbreaks in 2024. Based on spatiotemporal overlap and subtypes, 52 cases were inferred to represent undetected outbreak-associated infections. Several C. parvum subtypes reflected probable zoonotic transmission, two subtypes were associated with a childcare and camp outbreak. Six C. hominis subtypes and eight subtypes overall were reported for the first time in Australia. Globally novel subtypes of C. occultus , C. fayeri and C. meleagridis in human hosts is reported. The study reveals high diversity of Cryptosporidium subtypes in human infections in Victoria. This study demonstrates the potential for molecular surveillance to inform public health interventions when integrated with epidemiological data. These findings support One Health approaches to outbreak detection and source attribution. IMPORTANCE Cryptosporidium is a nationally notifiable pathogen in Australia, yet routine genotyping is not performed, limiting outbreak detection and source attribution. This study represents the first large-scale molecular surveillance of human Cryptosporidium and Giardia infections in southern Australia. By integrating species- and subtype-level typing with epidemiological metadata, we demonstrate the substantial diversity of infective lineages, including several novel or zoonotic genotypes. Our findings highlight the critical role of molecular tools in tracking transmission pathways, supporting outbreak investigation and informing public health responses. These data provide a foundation for incorporating routine genotyping into national surveillance strategies for parasitic enteropathogens. This study presents the first epidemiological study of the 2024 outbreaks in Australia. The global comparison of cases during this period also highlights potential large-scale disease dynamic of public health importance. INTRODUCTION Cryptosporidium and Giardia are among the commonest protistan pathogens causing gastrointestinal illnesses globally, associated with substantial disease burden in both developed and developing countries ( 1 , 2 ). Cryptosporidiosis is a nationally notifiable disease in Australia, whereas giardiasis is only notifiable in some states and territories, and remains underreported and often unquantified. Recent surveillance studies have documented marked increases in cryptosporidiosis notifications in 2023 and 2024 in Germany, Norway, Belgium, Spain, France and England ( 3 – 8 ). In Australia, an increase in cases linked to swimming pools has been observed, leading to multiple health warnings from public health authorities ( 9 – 12 ). However, the increase of cryptosporidiosis cases in Australia has not yet been comprehensively investigated. A comparison of cases between Australia and other countries during this period has also not been explored. Such a comparison might allow the magnitude of the outbreaks locally and abroad to be quantified, which could identify large-scale patterns of transmission, subtype-specific disease dynamic or common risk factors. Cryptosporidiosis and giardiasis are primarily transmitted via the faecal–oral route, often through contaminated recreational or drinking water ( 13 , 14 ). In Australia, infections occur predominantly in children and display marked seasonal peaks during warmer months ( 15 – 17 ). Most reported outbreaks have occurred in urban areas and are linked to recreational water exposure ( 18 – 30 ), although sporadic cases and occasional outbreaks linked to animals ( 31 , 32 ), drinking water ( 33 – 35 ), unpasteurised milk ( 36 , 37 ) and overseas travel ( 38 , 39 ) have also been documented. Routine clinical diagnosis for Cryptosporidium and Giardia in Australia relies on qualitative detection in faecal samples using PCR or microscopy, which are unable to differentiate between species or subtypes. There is currently no systematic referral of test-positive samples to reference laboratories for further genetic characterisation, limiting the ability to identify potential outbreaks and to guide targeted public health interventions. This has impeded efforts to resolve transmission pathways, identify outbreak sources and characterise the diversity of human-infective species, genotypes and subtypes. A wide range of Cryptosporidium and Giardia species and subtypes are known to infect humans, each differing in host range, ecological niche and potential for zoonotic or waterborne transmission ( 13 , 14 , 40 ). To date, 46 Cryptosporidium species have been described, with 19 species and more than 60 subtypes reported in humans globally ( 41 , 42 ). In Victoria, only four species and ten subtypes have previously been recorded from humans (Jex et al., 2007; Koehler et al., 2014). There is no comprehensive study of Cryptosporidium subtypes in clinical cases in southern Australia. The identity of Cryptosporidium species and subtypes infecting humans remains largely unknown. Of the eight recognised Giardia species, G. duodenalis is the principal agent of human infection, with sub-assemblages AI and AII (Assemblage A) and BIII and BIV (Assemblage B) being the most common in humans ( 40 , 45 , 46 ). While these assemblages have been reported in human cases in other states of Australia ( 47 – 55 ), no published data exist on human Giardia assemblages in southern Australia, limiting our ability to understand transmission dynamics, identify potential zoonotic sources and assess local public health risk. In contrast to the limited data for humans, Cryptosporidium and Giardia species and subtypes have been extensively characterised in non-human hosts across Australia, including wildlife, livestock and companion animals ( 56 – 61 ). In Victoria alone, 24 Cryptosporidium species and 31 subtypes have been reported from 16 animal hosts ( 43 , 44 , 62 – 68 ). Giardia assemblages have similarly been recorded in a range of animals in Victoria and nationally ( 52 , 54 , 63 , 64 , 69 ). This disparity in surveillance limits the assessment of zoonotic risk and obscures the true sources of infection in human populations. Specific subtypes have been associated with particular transmission routes and risk factors. For example, C. cuniculus and C. fayeri subtypes have been linked to wildlife contact, and C. hominis subtypes IbA10G2, IbA12G3, IgA17 and IdA15G1 are frequently associated with recreational water outbreaks ( 30 , 31 , 70 , 71 ), C. parvum subtypes are often associated with livestock exposure ( 71 , 72 ). Accurate species and subtype identification is essential for outbreak resolution, source attribution and the assessment of resistance to antimicrobial drugs. The most widely applied molecular targets for subtyping are the small subunit rRNA ( SSU ) and the 60 kDa glycoprotein ( gp60 ) loci for Cryptosporidium , and the triosephosphate isomerase ( tpi ) locus for Giardia ( 13 , 14 , 40 ). However, these methods have not yet been widely applied to understand outbreaks and transmission, and guide public health policies and interventions. In this study, we aimed to screen retrospective untested clinical samples to establish the prevalence of these two parasitic infections, we then aimed to subtype all current and retrospective positive clinical samples available, quantify oo/cysts load, and finally integrate subtyping data, parasite load and epidemiology data to identify potential sources and transmission clusters. MATERIALS AND METHODS Sample set A total of 2,330 human faecal samples were available to test for Cryptosporidium and Giardia and genetically characterise these protists ( Table 1 ). A total of 2,329 samples were received at the Microbiological Diagnostic Unit Public Health Laboratory (MDU PHL), Melbourne, between 2020 and 2024, and originated from residents of Victoria (population 6.9 million in 2024 ( 73 )), Australia. Samples were categorised as: (i) Cryptosporidium -positive (n = 219), (ii) Giardia -positive (n = 9), and (iii) untested samples from symptomatic patients (n = 2,102). One additional Giardia -positive sample from 2018 was also included. View this table: View inline View popup Table 1. Number of human clinical faecal samples processed by year, sample type, and detection rate of Cryptosporidium and Giardia . Detected - Cryptosporidium ; samples in which Cryptosporidium was previously detected by PCR or microscopy, Detected - Giardia ; samples in which Giardia was previously detected by PCR or microscopy, Untested; samples from patients with gastroenteric symptoms previously not tested for Cryptosporidium or Giardia . Cryptosporidium -positive human faecal samples (identified by PCR and/or microscopy) were sent to MDU PHL from multiple diagnostic laboratories. Notified cases are not currently routinely referred for further molecular analysis. Untested samples were submitted from individuals with symptoms of gastroenteritis with the majority of these associated with notified gastroenteritis outbreaks possibly from foodborne or waterborne source, but not previously tested for Cryptosporidium or Giardia . All samples were stored at –20 °C or –70 °C prior to processing. Isolation of genomic DNA Human faecal samples were thawed at 4 °C and homogenised using a FastPrep®-96 (MP Biomedicals) at 1400 rpm for 10 min. Total genomic DNA was extracted using the QIAamp PowerFecal Pro DNA Kit on the QIAsymphony SP platform (Qiagen, Germany), following the manufacturer’s protocol. Between 0.1–0.4 g of human faecal material (mean: 0.25 g) was used per extraction. To monitor PCR inhibition and DNA recovery, qPCR Extraction Control Red (Meridian Bioscience, USA) was spiked into 1,571 samples across all years. Eluted DNA (85 µl) was stored at – 20 °C. No-template extraction controls were included in each batch (48–96 samples). PCR and Sanger sequencing Nested PCR was used to amplify Cryptosporidium small subunit rRNA ( SSU ) and 60 kDa glycoprotein gene ( gp60 ) loci, and Giardia triosephosphate isomerase ( tpi ) loci, using GoTaq® G2 Hot Start Taq polymerase (Promega, USA) and established protocols ( 64 ). SSU primers were sourced from previous publications ( 74 – 76 ) and yielded ∼800 bp amplicons. Amplification of gp60 from C. meleagridis or C. occultus followed established methods ( 77 , 78 ). Amplicons were treated with ExoSAP-IT Express (Applied Biosystems, USA) and sequenced bidirectionally using BigDye Terminator v3.1 chemistry (Applied Biosystems). Chromatograms were inspected and trimmed manually using Geneious Prime 2025 v2.1 ( 79 ). Phylogenetic analysis Sequences were aligned using MUSCLE ( 80 ) in Geneious and refined manually. Sequence identities were assessed via BLASTn using GenBank. Subtypes of gp60 were assigned according to established nomenclature ( 78 , 81 ). Substitution models were selected using MEGA v11.0.13 ( 82 ) based on the lowest AIC score: GTR+G+I for SSU and gp60 ; K2+G+I for tpi . Bayesian inference was performed using MrBayes v3.2.7 ( 83 ) with 10–50 million generations (depending on locus), four chains, and sampling every 1,000 generations. The first 25% of trees were discarded as burn-in. Convergence was confirmed by split frequency standard deviation (<0.01) and a scale reduction factor of 1.0. Outgroups included C. muris , C. fayeri , and G. muris . Phylogenetic trees were visualised and annotated using iTOL ( 84 ). Quantification of oocysts and cysts by multiplex qPCR A validated multiplex qPCR assay (S1. Supplementary Methods) was used to estimate Cryptosporidium oocyst and Giardia cyst numbers (per gram of faeces) in PCR test-positive samples. The assay targeted SSU ( Cryptosporidium ) and the gdh gene ( Giardia ) and was calibrated using standard curves from serially diluted DNA derived from C. parvum IOWA strain (subtype IIaA15G2R1; Bunchgrass Farms) and G. duodenalis (wildtype strain WB1B). Samples were screened in triplicate and samples with Ct values <37 were retained. The mean genome copy number per gram was calculated. The qPCR-based estimates were cross-validated with counts from immunomagnetic separation followed by direct enumeration in a haemocytometer. Assay development and validation protocols are described in the Supplementary Methods. Epidemiological data analysis Epidemiological data were obtained from the Victorian Department of Health for all notified cases of cryptosporidiosis between 2019 and 2024. Data included patient age, sex, hospitalisation status, notification and sample collection dates, outbreak linkage, outbreak setting, and outbreak ID. Age was categorised into 10 years brackets. Cases were categorised as hospitalised if they were admitted to hospital or presented to the hospital emergency. The sample postcodes were matched to local government areas (LGAs) using the Australian Statistical Geography Standard (Australian Bureau of Statistics, July 2011). If a postcode spanned multiple LGAs, the first listed alphabetically was selected. Spatial, temporal and subtype data were used to identify additional cases potentially linked to outbreaks. If a case could be potentially linked to multiple outbreaks, the earliest outbreak was selected. Travel history data and the immune status of the notified cases was not obtained. Statistical correlation between Cryptosporidium oocyst load, species, subtypes, and with patient age, sex, hospitalisation status and by outbreak setting were analysed using ANOVA. Cryptosporidiosis cases nationally and internationally The annual summary of cryptosporidiosis cases from 2019 to 2024 was obtained from a total of 32 countries from North America (USA and Canada), Oceania (Australia, with all jurisdictions, and New Zealand), and 28 countries in Europe including the European Union as a whole (S1. Supplementary Methods). Regions with less than ten cases in 2023 or 2024 were excluded. Regions with no data for two or more years in the period were excluded. To the best of our knowledge, the regions identified above are the only ones worldwide where cryptosporidiosis is a reportable disease and have a surveillance system with publicly available data. Regions were classified into three categories based on the increase in cases observed in 2023 or 2024 compared to the previous year; sharp (>50% increase in cases), moderate (15-50% increase), none (< 15%). The percentage of increase for 2023 or 2024 was calculated as: ((latest year case number - previous year case number)/previous year case number)*100. Comparison of the case number for 2023/2024 against the mean of the four previous years was misleading due to global decrease of cases during the COVID-19 pandemic. The comparison of 2023 in the Northern hemisphere with 2024 in the Southern hemisphere reflects the shift in the high-risk summer season across those regions. Ethics Ethical approval to conduct the study was received from the University of Melbourne Human Research Ethics Committee (approval number 2025-30320-66468-5). Data availability Sequences are deposited in NCBI under accession PV981441 - PV981665 ( SSU ), PX092398-PX092617 and PX048014 ( gp60 ), PX048005-PX048013 ( tpi ). RESULTS Detection of parasites in human faecal samples Of 2,330 human faecal samples tested, 225 were test-positive for Cryptosporidium and nine for Giardia by PCR-based sequencing ( Table 1 ). One sample from 2024 showed a mixed infection of Cryptosporidium and Giardia . The detection rate among previously known positive samples was 98%. Detection levels for untested samples ranged from 0% in 2022–2023 to 2.6% in 2024 ( Table 1 ). Cryptosporidium hominis is the most common species identified among six others Seven Cryptosporidium species were identified using SSU : C. hominis (n = 191), C. parvum (n = 25), C. meleagridis (n = 3), C. sp. mink genotype (n = 3), C. fayeri (n = 1), C. occultus (n = 1), and C. sp. OTUi (n = 1) ( Fig. 1 ). SSU sequences of C. hominis showed variation in a T nucleotide repeat region near position 428 bp: 165 had 11T, seven had 8T, and 19 had 9T. The 8T variant also exhibited a downstream Y (C/T) ambiguity at a diagnostic position. Aside from these features, all C. hominis SSU sequences were identical. All C. parvum sequences were identical to the IOWA strain (OR421305; ( 85 )). One C. meleagridis sequence had a single T>A substitution; all three were otherwise identical and matched the UKMEL3 reference ( 86 ). The C. sp. mink genotype sequences (n = 3, from 2020) were identical and matched two shorter Australian human-derived sequences ( 87 , 88 ). These human sequences clustered in a polytomy distinct from animal-derived sequences, which grouped with C. sciurinum . The conserved nature of the SSU locus limited interspecies resolution. Download figure Open in new tab Figure 1. Phylogenetic tree reconstructed from the bayesian topology using GTR +G+I model based on the dereplicated alignment of the small subunit ribosomal RNA gene ( SSU ) with 10M generations for Cryptosporidium . Sequences generated in this study are shown in bold with the number of samples identified within parenthesis (n). Posterior probabilities are shown below the branch. Cryptosporidium muris used as outgroup. The Cryptosporidium sp. OTUi sequence (2024) matched sequences from a returned traveller and a bat from the Philippines ( 38 , 89 ) and was 98.9% similar to C. wrairi . The C. fayeri sequence matched one from a kangaroo in Victoria ( 64 ). The C. occultus sequence (2021) was identical to that of a deer in Victoria and contained a species-specific motif distinguishing it from C. suis ( 90 ). High intraspecific gp60 subtype diversity and novelty Ten gp60 subtypes were detected among C. hominis samples: IaA12R3 (n = 52), IaA14R3 (n = 3), IaA16R3 (n = 1), IaA16R4 (n = 2), IaA24R1 (n = 1), IbA8G4 (n = 1), IdA15G1 (n = 13), IeA11G3T3 (n = 92), IfA12G1R5 (n = 12), and IfA13G1R4 (n = 1) ( Fig. 2 ). Two samples were not amplified. The 9T SSU repeat variant was always associated with subtype IeA11G3T3, but this subtype also occurred in 8T and 11T samples. All sequences within each subtype were identical. Several subtypes matched previously reported sequences in Australian or international datasets (e.g., IaA12R3, IdA15G1, IeA11G3T3, IfA12G1R5), while IbA8G4 showed only 90–91% identity to other Australian Ib subtypes. Subtype clades formed strongly supported monophyletic groups by subfamily but lacked resolution at deeper nodes. Download figure Open in new tab Figure 2. Phylogenetic tree reconstructed from the bayesian topology using GTR +G+I model based on 60kD glycoprotein gene ( gp60 ) with 50M generations for C. hominis subtypes. Sequences generated in this study are shown in bold. Posterior probability equal to or above 0.90 are shown below the branch. Cryptosporidium fayeri used as outgroup. Taxa labels highlighted by gp60 subfamily identity. Additional data shown as coloured strips; epidemiological link (Epi Link), outbreak setting, outbreak identification number (Outbreak ID). Epi Link: cases classified as sporadic, outbreak related, not notified to Victorian Department of Health as of 18/06/2025. In the 25 samples containing C. parvum , seven gp60 subtypes were detected: IIaA16G1R1 (n = 1), IIaA16G3R1 (n = 1), IIaA17G2R1 (n = 3), IIaA18G3R1 (n = 9), IIaA19G3R1 (n = 4), IIaA19G4R1 (n = 3), and IIaA20G3R1 (n = 2) (Supplementary Figure S1). Two samples were not amplified. All sequences within each subtype were identical. Most matched cattle- or wildlife-derived Australian sequences ( 32 , 62 , 91 ), while IIaA16G1R1 matched cattle sequences from overseas ( 92 ). Three gp60 sequences from C. sp. mink genotype (subtype A14) were identical to each other and to prior human-derived sequences. One previously published sequence from cattle clustered within the same clade. These sequences were distinct from non-Australian mink sequences, supporting a regional divergence. All non-Australian C. sp. mink genotype gp60 sequences available originate from China. The sequences were more closely related to C. equi ( Fig. 3 ). Download figure Open in new tab Fig 3. Phylogenetic tree reconstructed from the bayesian topology using GTR +G+I model based on 60kD glycoprotein gene ( gp60 ) with 10M generations for C. sp. mink genotype sequences. Sequences generated in this study are shown in bold. Posterior probability equal to or above 0.90 are shown below the branch. Cryptosporidium cuniculus used as outgroup. Three C. meleagridis subtypes were identified: IIIjA4T1, IIIA19G1, and IIIgA31G4 (Supplementary Figure S2). IIIjA4T1 was 88% similar to a wallaby-derived sequence ( 93 ). The IIIA19G1 sequence was not assignable to a known subfamily and contained a unique 33 bp insertion. IIIgA31G4 was 98% similar to a sequence from a human in Sweden ( 77 ). The C. fayeri subtype IVfA10G1T1 was 98% similar to sequences from kangaroos ( 91 , 94 ). The C. sp. OTUi gp60 sequence (subtype A12G1) was 96% similar to a 2014 human-derived sequence (A15G1) and showed a synonymous SNP and a three-repeat deletion. The C. occultus subtype was identified as XXIVa and was most similar (94%) to a sequence from a Swedish rat (GenBank accession number PV067140 ). Four Giardia tpi assemblages identified Nine sequences representing Giardia duodenalis were assigned to assemblages AI (n = 1), AII (n = 2), BIII (n = 2), and BIV (n = 4) (Supplementary Figure S3). Six were from previously untested symptomatic patients. The AI sequence matched the reference genome strain WB C6 and sequences from a rabbit and kangaroo in Victoria ( 64 ). The AII sequences were identical to a previously reported Australian human-derived sequence ( 88 ). Four BIV sequences matched samples from Spain and USA wastewater ( 95 ). One additional BIV-related sequence clustered within BIII, and two BIII-like sequences (2020 and 2023) showed high similarity (99.1%) to international human-derived sequences. Oocyst and cyst load independent of subtypes Of the 225 Cryptosporidium test-positive samples, 194 were subjected to qPCR to estimate parasite load ( Table 2 ). Of the excluded 31 samples, 22 yielded no Ct value and nine had Ct > 37. Oocyst load did not differ significantly by species (F = 0.565, p = 0.758) or subtype (F = 1.247, p = 0.212). Only one Giardia -positive sample (from 2018) yielded quantifiable cysts; the remainder failed amplification or exceeded the Ct threshold. Cyst load in the Giardia sample was low relative to Cryptosporidium . qPCR-based estimates of oocyst load differed by 1–2% from haemocytometer counts following purification via immunomagnetic separation. View this table: View inline View popup Table 2. Cryptosporidium subtypes and Giardia sub assemblages found in this study with respective oocysts and cysts, referred to as oo/cysts, load quantification based on multiplex qPCR. Note: Two C. hominis samples and one C. parvum sample could not be assigned a subtype but were successfully quantified. Subtyping differentiates between swimming pool outbreaks and other outbreak settings Of 225 Cryptosporidium -positive cases, 173 were notified while 52 were previously not notified to public health authorities. Six of the notified cases were notified for a foodborne or waterborne illness other than cryptosporidiosis as they were part of the untested category of samples from 2024, no epidemiological data was available for these six cases. Two cases were positive for rotavirus, one was positive for norovirus while no bacterial or viral pathogens were detected in the other four cases. Four of the non-notified cases, the three C. sp. mink genotype and C. occultus cases, were newly detected in this study. The 216 subtyped samples from 2024 represented 6.6% of all notified cryptosporidiosis cases in Victoria in this year (notified between 19 February and 18 September; Fig. 4 ). Children <10 years accounted for 95 cases, followed by adults aged 31–40 (n = 51). Females comprised 65% (n = 143) of subtyped cases. Subtype identity was not correlated to patient age (F = 0.57, df = 3, p = 0.7). Download figure Open in new tab Figure 4. Epidemiological curve of 216 subtyped cases of cryptosporidiosis in 2024 in Victoria. Among the 167 cryptosporidiosis notified cases with subtype data, 140 (84%) were classified as sporadic and 26 (16%) were epidemiologically linked to 13 outbreaks out of a total of 39 outbreaks ongoing or declared in 2024 in Victoria (11 outbreaks in swimming pools, one outbreak in a childcare, one outbreak in a camp; Fig. 2 ; Table 3 ; Supplementary Figure S1). Oocyst load was higher in children <10 years (F = 4.8, df = 201, p = 0.03). Oocysts load was similar between sporadic and outbreak-linked cases, including swimming pool outbreak cases (F = 2.9, df = 2, p = 0.06). No significant difference in oocyst load was observed between sexes (F = 2.1, df = 1, p = 0.15) or hospitalisation status (F = 0.2, df = 4, p = 0.91). Of the 167 cryptosporidiosis notified and subtyped cases, 16 cases (8 females, 8 males) were hospitalized, 15 of which were infected with C. hominis - IeA11G3T3 (n=10), IaA12R3 (n=2), IaA14R3 (n=1), IfA12G1R5 (n=1), unknown subtype (n=1) -and the remaining case infected with C. parvum (unknown subtype). Only three hospitalized cases were below the age of 10 years old, the majority of subtyped hospitalized cases (n=12) were between the age of 21 to 40. View this table: View inline View popup Table 3. Cryptosporidiosis cases subtyped and epidemiologically linked to outbreaks in Victoria from 2019 to 2024. Possible additional cases are based on cases with the same subtype, notified during the same outbreak period from residents of the same, or directly adjacent, local government areas. All pool-linked cases were caused by C. hominis subtypes IeA11G3T3, IaA12R3 or IdA15G1 ( Table 3 ). The childcare outbreak case involved C. parvum subtype IIaA19G3R1 while the case linked to a camp outbreak was C. parvum IIaA20G3R1. Two swimming pool outbreaks, o4 and o12, were linked to two subtypes ( Table 3 ). Seven swimming pool outbreaks were linked to subtype IeA11G3T3 and five to IaA12R3. Other subtypes (e.g., IfA12G1R5, IaA16R4, IIIjA4T1R1, IIIgA31G4R1, OTUi A12G1, IIaA18G3R1, IIaA16G1R1) were identified in sporadic cases. Based on spatiotemporal overlap and shared subtypes, 52 additional cases not formally linked to outbreaks were inferred to represent undetected outbreak-associated infections ( Fig. 5 ; Table 3 ). Two cases could be potentially linked to two different outbreaks; o18 or o20, and another either o4 or o23. The case infected with C. sp. OTUi was a female between the age of 21-30. The cases infected by C. fayeri and C. occultus were not notified and found in a female (61-70 yo) and a male (0-10 yo) respectively, both from the same regional area. Download figure Open in new tab Figure 5. Epidemiological curve of cryptosporidiosis subtype IaA12R3 and IeA11G3T3 cases identified in 2024 in Victoria, classified by epidemiologic links: cases confirmed to be part of an outbreak (e.g. “o12 confirmed” - case part of outbreak o12), cases designated as possibly part of an outbreak, and cases designated as sporadic. Australia among the top three countries recording highest rise in cryptosporidiosis cases in 2023-2024 Nationally, Australia recorded a 273% increase in cases in 2024 compared to 2023. Except for the Northern Territory (NT), the number of cases in 2024 from all Australian jurisdictions showed a >200% increase ( Fig. 6A ). The highest percentage of case increase was in the Australian Capital Territory, Tasmania and Queensland with 793%, 360% and 327% respectively. The highest case numbers were in the Eastern states of Queensland, New South Wales and Victoria. Apart from NT, the number of cases reported in 2024 in all jurisdictions was the highest ever recorded since cryptosporidiosis became notifiable in 2001. Internationally, Australia placed third, behind Iceland and Spain, in countries reporting the sharpest increase in cases in 2023-2024 ( Fig. 6B , Supplementary Table 1). A sharp increase in cryptosporidiosis cases in 2023-2024 was also observed in England, Ireland, Belgium, Poland, France, Luxembourg, Slovenia, Malta and Czechia. Australia was the only non-European country to record a sharp increase in cryptosporidiosis during this period. There was no geographical pattern within the European countries which reported a sharp increase in cases. Moderate increases were observed in New Zealand, Canada, Portugal, Latvia, Greece, and Germany. The USA was excluded due to unpublished data for 2023 and 2024. Download figure Open in new tab Figure 6. Cryptosporidiosis cases in Australia and abroad. A; annual number of notified cases in each Australian jurisdictions, B; percentage of increase in reported cases from 18 countries (and the European Union as a whole) for the 2023/2024 period compared to the previous year. Abbreviations for Australian states and territories: ACT; Australian Capital Territory, NSW; New South Wales, NT; Northern Territory, QLD; Queensland, SA; South Australia, TAS; Tasmania, VIC; Victoria, WA; Western Australia. DISCUSSION This study presents the first comprehensive molecular investigation of Cryptosporidium and Giardia infections in people in the state of Victoria, Australia. Of 2,330 faecal samples analysed, 225 were test-positive for Cryptosporidium and nine for Giardia . The screening of 2,102 untested symptomatic cases did not reveal evidence of large cryptic outbreaks. Low detection rates in 2020–2022 likely reflect reduced transmission under COVID-19 public health restrictions in Australia ( 96 ). In 2024, despite multiple cryptosporidiosis outbreaks, there was a very low number of cases, and no evidence of large cryptic outbreaks, related to notified foodborne or waterborne outbreaks based on the untested cases screened in this study. Novel taxa within three Cryptosporidium species Three Cryptosporidium subtypes identified in this study are taxonomically uncertain and may represent novel lineages. The C. meleagridis subtype IIIA19G1 is genetically distinct and not assigned to a known subfamily. The C. hominis IbA8G4 sequence differs markedly from the only other published IbA8G4 record and sits on a long branch in the Ib clade, potentially indicating a divergent subfamily. Subtype A12G1 of C. sp. OTUi is novel, with a similar subtype from the traveller returning from Indonesia (2014) but no gp60 sequence from the bat in the Philippines (2025). The Cryptosporidium sp. “mink genotype” detected in three patients in 2020 is also distinct compared to other C. sp . mink genotype from abroad. The SSU and gp60 sequences from these cases clustered separately from all known animal-derived sequences, supporting the possibility of a regionally divergent Australian lineage. Previous reports in Australians ( 87 , 88 ) also revealed ambiguous placement in phylogenies. Notably, all three cases here occurred within 48 h during strict COVID-19 lockdown, recorded within different household situated in two suburbs of Melbourne, limiting possible exposure routes. The immune status of these individuals is unknown, one of the cases also tested positive to Staphylococcus aureus . Overall, the infection source, transmission route and taxonomic position of this genotype remain unresolved. First reports of human infection and subtypes in Australia This study identified three Cryptosporidium subtypes not previously detected in the human host – namely C. occultus XXIVa, C. fayeri IVfA10G1T1 and C. meleagridis IIIjA4T1, previously found only in rats, macropods and rock-wallabies, respectively ( 78 , 93 , 94 ). The identification of C. meleagridis IIIjA4T1 in a human raises questions about potential zoonotic or anthroponotic exchange in captive marsupial settings, and the issue of parasite detection in likely passive hosts from zoos and other captive environments. Subtype XXIVa is the first record in a human, previous records being made in animals (mostly rats and a cattle) from Sweden ( 78 ). Additionally, seven subtypes were reported for the first time in Australia, including C. meleagridis IIIgA31G4. Six of the ten C. hominis subtypes (IaA12R3, IaA14R3, IaA16R3, IaA16R4, IaA24R1, IfA13G1R4) had not been documented in Australia. The highly common subtype IaA12R3 found in this study to be associated with multiple swimming pool outbreaks had not been previously linked to outbreaks worldwide ( 97 ). In contrast, all C. parvum and Giardia subtypes identified herein had been reported previously. Subtype dynamics and cryptic outbreak Cryptosporidium hominis was the dominant species (85%), consistent with prior Australian reports ( 30 , 39 ) and observations from South Asia and sub-Saharan Africa ( 98 , 99 ). This contrasts with Europe and North America, where C. parvum is more common ( 81 , 100 – 102 ). The most frequent subtypes were IeA11G3T3 (41%) and IaA12R3 (23%). While both have been reported previously, neither has been linked to large outbreaks previously ( 97 ). Subtype IfA12G1R5, found in 5% of samples in this study, has caused outbreaks in the USA and Spain ( 5 , 103 ) and was dominant in Western Australia in 2017 ( 104 ). Although no outbreak linkage was identified here, its frequency suggests a cryptic transmission cluster. The previously dominant IbA10 subtype was absent, which may reflect evolving strain competition or incomplete sample referral. Only C. parvum subfamily IIa was detected, consistent with zoonotic exposure. Seven subtypes were recorded, several of which (e.g., IIaA16G1R1, IIaA18G3R1, IIaA20G3R1) have been associated with livestock or wildlife in Australia. The absence of subtype IIaA15G2R1, which predominates in Europe and North America ( 105 ), further illustrates regional divergence in subtype distribution. Zoonotic and environmental infection risk Multiple subtypes identified here have previously been reported in a restricted host range in Australia (e.g., C. occultus in deer, IVfA10G1T1 and IIaA19G4R1 in kangaroos, IIaA16G1R1 in cattle). Internationally, these same subtypes have been detected in diverse hosts, suggesting broad zoonotic potential ( 41 , 106 ). Thus, local infections may arise via zoonotic or environmental transmission or overseas acquisition. Ongoing One Health surveillance across humans, animals and environments is essential to clarify source attribution. Molecular surveillance should incorporate spatiotemporal and epidemiological data, including travel history. The absence of travel information in this dataset limits source inference. The case of C. sp. OTUi, previously reported in a traveller from Indonesia and a Southeast Asian bat, highlights the importance of contextualising findings with travel and wildlife exposure. Quantification and transmission dynamics Oocyst loads estimated by qPCR were consistent with previous reports from Australian patients ( 107 , 108 ). No species or subtype-specific differences in load were observed, suggesting that all are capable of high shedding and transmission. Higher loads were observed in children, supporting prior studies indicating increased susceptibility and transmission potential in young age groups ( 109 , 110 ). Oocysts loads did not appear to be a marker of disease severity based on hospitalisation data available. However, hospitalisation is likely to be under-reported as not all sporadic cases could be followed up due to limited resources at the time. Outbreaks and public health risk Recurring outbreaks linked to swimming pools are well documented in Australia ( 18 – 30 ). The continued detection of C. hominis subtypes in pool-linked outbreaks here highlights persistent issues in infection prevention and water quality control. Risk factors include pool design, filtration efficacy, hygiene compliance and microbiological monitoring ( 111 , 112 ). Subtype overlap across geographically dispersed outbreaks suggests wider or sustained transmission. Notably, IeA11G3T3 and IaA12R3 were involved in 11 outbreaks and also identified in many other sporadic cases from adjacent LGAs during the same period, suggesting potential under- detection of outbreak scale. The detection of two different subtypes within outbreaks suggests either cases belonging to two different outbreaks or a mixed population as outbreak initial infection source. The two outbreaks linked to C. parvum suggest a primary zoonotic infection source and possibly secondary anthroponotic transmission between children. Subtype IIaA19G3R1 and IIaA20G3R1 have previously been recorded in Victoria from deer, alpaca and cattle hosts ( 62 , 113 , 114 ). Many C. parvum subtypes (e.g., IIaA18G3R1, IIaA19G4R1) occurred in multiple sporadic cases and may represent cryptic zoonotic outbreaks. Strengthening the One Health approach would improve identification of such linkages. This study presents the first Australian molecular and epidemiological data from the 2023- 2024 period which saw multiple outbreaks across Australia and the highest number of cases recorded in the last 24 years. Additional data from that period from other jurisdictions would allow further assessment of the scale of Cryptosporidium transmission and identify common sources of infection. Previous reviews have found a greater number of Cryptosporidium outbreaks from North America and New Zealand ( 115 , 116 ) compared to other regions suggesting a different disease dynamic during the 2023/2024 period, however the lack of data from the USA limits interpretation from North America. The role of swimming pools in other Australian jurisdictions has yet to be quantified and compared to the Victorian data. The sharp increase in cases observed in several European countries suggest common risk factors specifically increased during this period. The European studies published indicated outbreaks also linked to swimming pools and international travel ( 4 – 8 ). The rise of cases globally during the 2023-2024 summers could be due to this period being one of the warmest on record ( 117 – 119 ). Cryptosporidiosis infections have been shown to increase in warmer months ( 16 , 101 , 120 ) suggesting an increasing risk from this disease in the future. The association between increased temperature and increased cryptosporidiosis cases linked to swimming pools indicate a need for public health authorities to increase prevention and surveillance of cryptosporidiosis in this setting globally. The association with international travel and the worldwide increase in cases suggests that outbreaks could have an increasingly international scale. Worldwide transmission of C. parvum subtype has been documented previously ( 105 ). Genotyping methods and future directions The gp60 gene is the most widely used subtyping marker but has limited discriminatory power for outbreak resolution ( 103 , 121 , 122 ). Higher-resolution tools, including MLVA ( 123 ), multilocus sequence typing ( 124 ), RNA-bait ( 125 ), and whole genome sequencing ( 105 , 121 , 126 ), are increasingly being used. However, few are routinely applied to the full taxonomic range of Cryptosporidium infecting humans. Whole genome sequencing offers the highest resolution but is not yet adopted for routine typing. Given its status as a nationally reportable disease in Australia, PCR- based subtyping tools, employing SSU and gp60 as markers, are already available, practical and should be systematically applied to notified cases of cryptosporidiosis. Conclusion This study identified seven Cryptosporidium species and 24 subtypes, and four Giardia assemblages from human clinical samples in Victoria over a five-year period. The observed diversity and subtype distribution suggest multiple transmission pathways – including undetected outbreaks and zoonotic reservoirs – operating concurrently. High sequence identity with animal and environmental isolates supports the need for integrated One Health surveillance. The subtyping of clinical samples, linked to metadata, provides a powerful foundation for improving cryptosporidiosis and giardiasis control and prevention in Australia. SUPPLEMENTAL MATERIAL Supplementary Methods Supplementary Table 1 Supplementary Figure S1, S2, and S3 ACKNOWLEDGEMENTS We thank Louise Baker (Walter and Eliza Hall Institute of Medical Research) for providing the purified Cryptosporidium oocysts and Giardia trophozoites. We thank all the Victorian microbiology laboratories who forwarded positive Cryptosporidium samples in 2024, and the laboratory technical staff at Microbiological Diagnostic Unit Public Health Laboratory for sample reception and pre-processing. We thank Damien Costa and Loic Favennec (University Hospital of Rouen) and the French National Network on Surveillance of Human Cryptosporidiosis for providing case data for France. We thank Guy Robinson ( Cryptosporidium Reference Unit, Public Health Wales Microbiology) for providing subtyping technical information in relation to C. occultus . Funding provided by the University of Melbourne’s co-contribution to Australian Pathogen Genomics Program, funded by the Medical Research Future Fund Genomics Health Future Mission – Pathogen Genomics Grant FSPGN00049 (B.P.H.) and from R.B.G.’s research program which include the Australian Research Council (ARC; LP220200614 and LP180101085) and Oz Omics Pty Ltd. Footnotes ↵ Ŧ co-senior authors REFERENCES 1. ↵ Shirley D-AT , Moonah SN , Kotloff KL . 2012 . Burden of disease from cryptosporidiosis: Current Opinion in Infectious Diseases 25 : 555 – 563 . OpenUrl PubMed 2. ↵ Gibney KB , O’Toole J , Sinclair M , Leder K . 2014 . Disease burden of selected gastrointestinal pathogens in Australia, 2010 . International Journal of Infectious Diseases 28 : 176 – 185 . OpenUrl CrossRef PubMed 3. ↵ ECDC . 2023 . Communicable Disease Threats Report. Week 42. Surveillance Report . 4. ↵ Peake L , Inns T , Jarvis C , King G , Rabie H , Henderson J , Wensley A , Jarratt R , Roberts C , Williams C , Orife O , Browning L , Neilson M , McCarthy C , Millar P , Love N , Elwin K , Robinson G , Mannes T , Young N , Chalmers R , Elson R , Vivancos R . 2023 . Preliminary investigation of a significant national Cryptosporidium exceedance in the United Kingdom, August 2023 and ongoing . Eurosurveillance 28 . 5. ↵ Peñuelas Martinez M , Carmena D , Guzmán Herrador BR , Palau Miguel M , Saravia Campelli G , García Álvarez RM , Guerrero-Vadillo M , Dashti A , Köster PC , Guevara Alemany E , Simón Soria F , Fuentes Corripio I , Varela Martínez C , Sierra Moros MJ , working group for the National Surveillance Network . 2024 . Marked increase in cryptosporidiosis cases, Spain, 2023 . Eurosurveillance 29 . 6. Schoeps A , Röbl K , Walter N , Neute A , Walter B , Freudenau I , Jurke A , Klier C , Heinmüller P , Saeed S , Metz J , Wilking H , Zanger P. 2024 . Increased number of cryptosporidiosis cases with travel history to Croatia might be related to swimming pools, Germany, 2023 . Eurosurveillance 29 . 7. Tipu JH , Sivertsen A , Afset J-E , Sandven L , Brekke H , Lund HM , Elburg LS , Gaustad P , Lier T , Tverelv LR , Johansen ØH , Robertson LJ , Hanevik K . 2024 . Cryptosporidium species and subtypes in Norway: predominance of C. parvum and emergence of C. mortiferum . Emerging Microbes & Infections 13 : 2412624 . OpenUrl PubMed 8. ↵ Williams SV , Matthews E , Inns T , Roberts C , Matizanadzo J , Cleary P , Elson R , Williams CJ , Jarratt R , Chalmers RM , Vivancos R. 2025 . Retrospective case–case study investigation of a significant increase in Cryptosporidium spp. in England and Wales, August to September 2023 . Eurosurveillance 30 . 9. ↵ Murphy H . 2024 . Gastro cases in Australia are at a 20-year high and health officials don’t know why . ABC News . 10. NSW Health . 2024 . Cryptosporidiosis alert for NSW . Media Release . 11. Queensland Health . 2024 . Rapid increase in cryptosporidiosis cases hits Queensland . Media Release . 12. ↵ Victorian Department of Health . 2025 . Reduce the risk of cryptosporidiosis this summer . Media Release . 13. ↵ Cacciò SM , Chalmers RM . 2016 . Human cryptosporidiosis in Europe . Clinical Microbiology and Infection 22 : 471 – 480 . OpenUrl CrossRef PubMed 14. ↵ Gharpure R , Perez A , Miller AD , Wikswo ME , Silver R , Hlavsa MC . 2019 . Cryptosporidiosis Outbreaks — United States, 2009–2017 68 . 15. ↵ Menzies R . 2002 . EpiReview: Cryptosporidiosis in NSW, 1990–2000 . NSW Public Health Bull 13:54. 16. ↵ Lal A , Cornish LM , Fearnley E , Glass K , Kirk M . 2015 . Cryptosporidiosis: A Disease of Tropical and Remote Areas in Australia . PLoS Negl Trop Dis 9 : e0004078 . OpenUrl PubMed 17. ↵ Greenwood KP , Reid SA . 2020 . Clustering of cryptosporidiosis in Queensland, Australia, is not defined temporally or by spatial diversity . International Journal for Parasitology 50 : 209 – 216 . OpenUrl PubMed 18. ↵ Lemmon JM , McAnulty JM , Bawden-Smith J. 1996 . Outbreak of cryptosporidiosis linked to an indoor swimming pool . Medical Journal of Australia 165 : 613 – 616 . OpenUrl PubMed 19. Heilard ME , Sinclair MI , Andrews RM , Bailey M , Black J , Dharmage SC , Kirk MD , Fairley CK . 2000 . An outbreak of cryptosporidiosis in an urban swimming pool: why are such outbreaks difficult to detect? Australian and New Zealand Journal of Public Health 24 : 272 – 275 . OpenUrl CrossRef PubMed Web of Science 20. Stafford R , Neville G , Towner C , McCall B . 2000 . A community outbreak of Cryptosporidium infection associated with a swimming pool complex . Commun Diss Intell 24 : 236 : 239 . OpenUrl 21. Puech MC , McANULTY JM , Lesjak M , Shaw N , Heron L , Watson JM . 2001 . A statewide outbreak of cryptosporidiosis in New South Wales associated with swimming at public pools . Epidemiol Infect 126 : 389 – 396 . OpenUrl CrossRef PubMed 22. Tobin S. 2001 . Victorian Infectious Diseases Bulletin . 23. Robertson B , Sinclair MI , Forbes AB , Veitch M , Kirk M , Cunliffe D , Willis J , Fairley CK . 2002 . Case-control studies of sporadic cryptosporidiosis in Melbourne and Adelaide, Australia . Epidemiol Infect 128 : 419 – 431 . OpenUrl CrossRef PubMed Web of Science 24. Begg K , Roche P , Owen R , Liu C , Kaczmarek M , Hii A , Stirzaker S , McDonald A , Fitzsimmons G , McIntyre P , Menzies R , East I , Coleman D , O’Neil K. 2006 . AUSTRALIA’S NOTIFIABLE DISEASES STATUS, 2006: ANNUAL REPORT OF THE NATIONAL NOTIFIABLE DISEASES SURVEILLANCE SYSTEM . Annual report 32. 25. Black M , McAnulty J . 2006 . The investigation of an outbreak of cryptosporidiosis in New South Wales in 2005 . NSW Public Health Bull 17 : 76 . OpenUrl CrossRef 26. Dale K , Kirk M , Sinclair M , Hall R , Leder K . 2010 . Reported waterborne outbreaks of gastrointestinal disease in Australia are predominantly associated with recreational exposure . Australian and New Zealand Journal of Public Health 34 : 527 – 530 . OpenUrl CrossRef PubMed 27. Kent L , Higgins N , McPherson M . 2011 . The Epidemiology of Cryptosporidiosis in Victoria , 2001-2009. Victorian Infectious Diseases Bulletin 14. 28. Mayne DJ , Ressler K-A , Smith D , Hockey G , Botham SJ , Ferson MJ . 2011 . A Community Outbreak of Cryptosporidiosis in Sydney Associated with a Public Swimming Facility: A Case- Control Study . Interdisciplinary Perspectives on Infectious Diseases 2011 : 1 – 6 . OpenUrl 29. de Gooyer TE , Gregory J , Easton M , Stephens N , Fearnley E , Kirk M. 2017 . Waterparks are high risk for cryptosporidiosis: A case-control study in Victoria , 2015 41 . OpenUrl 30. ↵ Braima K , Zahedi A , Egan S , Austen J , Xiao L , Feng Y , Witham B , Pingault N , Perera S , Oskam C , Reid S , Ryan U . 2021 . Molecular analysis of cryptosporidiosis cases in Western Australia in 2019 and 2020 supports the occurrence of two swimming pool associated outbreaks and reveals the emergence of a rare C. hominis IbA12G3 subtype . Infection, Genetics and Evolution 92 : 104859 . OpenUrl 31. ↵ Waldron LS , Cheung-Kwok-Sang C , Power ML . 2010 . Wildlife-associated Cryptosporidium fayeri in Human, Australia . Emerg Infect Dis 16 : 2006 – 2007 . OpenUrl CrossRef PubMed 32. ↵ Braima K , Zahedi A , Oskam C , Austen J , Egan S , Reid S , Ryan U . 2021 . Zoonotic infection by Cryptosporidium fayeri IVgA10G1T1R1 in a Western Australian human . Zoonoses and Public Health 68 : 358 – 360 . OpenUrl 33. ↵ Lester R . 1992 . A mixed outbreak of cryptosporidiosis and giardiasis. Update. Quaterly Bulletin of Infectious Diseases , Health Department Victoria 1 : 14 – 15 . OpenUrl 34. Weinstein P , Macaitis M , Walker C , Cameron S . 1993 . Cryptosporidial diarrhoea in South Australia. An exploratory case-control study of risk factors for transmission . Med J Aust 158 : 117 – 119 . OpenUrl PubMed Web of Science 35. ↵ NSW Public Health . 1998 . The Sydney Water Incident: July-September 1998 . NSW Public Health Bulletin 9. 36. ↵ Harper CM , Cowell NK , Adams BC , Langley AJ , Woglsen TD . 2002 . Outbreak of Cryptosporidium linked to drinking unpasteurised milk . Commun Dis Intell (2018) 26:449–450. 37. ↵ Gregory K . 2020 . Six years after a toddler died after drinking it, advocates want raw milk back on the table . ABC News . 38. ↵ Koehler AV , Whipp M , Hogg G , Haydon SR , Stevens MA , Jex AR , Gasser RB . 2014 . First genetic analysis of Cryptosporidium from humans from Tasmania, and identification of a new genotype from a traveller to Bali . Electrophoresis 35 : 2600 – 2607 . OpenUrl PubMed 39. ↵ Ng-Hublin JSY , Combs B , Reid S , Ryan U . 2018 . Comparison of three cryptosporidiosis outbreaks in Western Australia: 2003, 2007 and 2011 . Epidemiol Infect 146:1413–1424. 40. ↵ Ryan U , Cacciò SM . 2013 . Zoonotic potential of Giardia . International Journal for Parasitology 43 : 943 – 956 . OpenUrl CrossRef PubMed 41. ↵ Ryan U , Zahedi A , Feng Y , Xiao L . 2021 . An Update on Zoonotic Cryptosporidium Species and Genotypes in Humans . Animals 11 : 3307 . OpenUrl PubMed 42. ↵ Jann HW , Cabral-Castro MJ , Costa JVB , Alencar ACM de B , Peralta JM , Peralta RHS. 2022 . Prevalence of human cryptosporidiosis in the Americas: systematic review and meta-analysis . Rev Inst Med trop S Paulo 64 : e70 . OpenUrl PubMed 43. ↵ Jex A , Whipp M , Campbell BE , Cacciò S , Stevens M , Hogg G , Gasser RB . 2007 . A practical and cost-effective mutation scanning-based approach for investigating genetic variation in Cryptosporidium . Electrophoresis 28 : 3875 – 3883 . OpenUrl CrossRef PubMed Web of Science 44. ↵ Koehler AV , Whipp MJ , Haydon SR , Gasser RB. 2014 . Cryptosporidium cuniculus - new records in human and kangaroo in Australia . 45. ↵ Feng Y , Xiao L . 2011 . Zoonotic Potential and Molecular Epidemiology of Giardia Species and Giardiasis . Clin Microbiol Rev 24 : 110 – 140 . OpenUrl Abstract / FREE Full Text 46. ↵ Ryan U , Hijjawi N , Feng Y , Xiao L . 2019 . Giardia: an under-reported foodborne parasite . International Journal for Parasitology 49 : 1 – 11 . OpenUrl CrossRef PubMed 47. ↵ Meloni BP , Thompson RCA , Strandén AM , Köhler P , Eckert J . 1991 . Critical comparison of Giardia duodenalis from Australia and Switzerland using isoenzyme electrophoresis . Acta Tropica 50 : 115 – 124 . OpenUrl CrossRef PubMed 48. Meloni BP , Lymbery AJ , Thompson RCA . 1995 . Genetic Characterization of Isolates of Giardia duodenalis by Enzyme Electrophoresis: Implications for Reproductive Biology, Population Structure, Taxonomy, and Epidemiology . The Journal of Parasitology 81 : 368 . OpenUrl CrossRef PubMed 49. Hopkins RM , Meloni BP , Groth DM , Wetherall JD , Reynoldson JA , Thompson RCA . 1997 . RIBOSOMAL RNA SEQUENCING REVEALS DIFFERENCES BETWEEN THE GENOTYPES OF GIARDIA ISOLATES RECOVERED FROM HUMANS AND DOGS LIVING IN THE SAME LOCALIT . J Parasitol 83 : 44 – 51 . OpenUrl CrossRef PubMed Web of Science 50. Read C , Walters J , Robertson ID , Thompson RCA . 2002 . Correlation between genotype of Giardia duodenalis and diarrhoea . International Journal for Parasitology 32 : 229 – 231 . OpenUrl CrossRef PubMed Web of Science 51. Read CM , Monis PT , Andrew Thompson RC . 2004 . Discrimination of all genotypes of Giardia duodenalis at the glutamate dehydrogenase locus using PCR-RFLP. Infection , Genetics and Evolution 4 : 125 – 130 . OpenUrl 52. ↵ Yang R , Lee J , Ng J , Ryan U . 2010 . High prevalence Giardia duodenalis assemblage B and potentially zoonotic subtypes in sporadic human cases in Western Australia . International Journal for Parasitology 40 : 293 – 297 . OpenUrl CrossRef PubMed 53. Asher AJ , Holt DC , Andrews RM , Power ML . 2014 . Distribution of Giardia duodenalis Assemblages A and B among Children Living in a Remote Indigenous Community of the Northern Territory, Australia . PLoS ONE 9 : e112058 . OpenUrl PubMed 54. ↵ Asher AJ , Hose G , Power ML . 2016 . Giardiasis in NSW: Identification of Giardia duodenalis assemblages contributing to human and cattle cases, and an epidemiological assessment of sporadic human giardiasis . Infection, Genetics and Evolution 44 : 157 – 161 . OpenUrl 55. ↵ Zahedi A , Field D , Ryan U . 2017 . Molecular typing of Giardia duodenalis in humans in Queensland – first report of Assemblage E . Parasitology 144 : 1154 – 1161 . OpenUrl PubMed 56. ↵ Appelbee AJ , Thompson RCA , Olson ME . 2005 . Giardia and Cryptosporidium in mammalian wildlife – current status and future needs . Trends in Parasitology 21 : 370 – 376 . OpenUrl CrossRef PubMed Web of Science 57. Thompson J , Yang R , Power M , Hufschmid J , Beveridge I , Reid S , Ng J , Armson A , Ryan U . 2008 . Identification of zoonotic Giardia genotypes in marsupials in Australia . Experimental Parasitology 120 : 88 – 93 . OpenUrl CrossRef PubMed Web of Science 58. Thompson RCA , Smith A , Lymbery AJ , Averis S , Morris KD , Wayne AF . 2010 . Giardia in Western Australian wildlife . Veterinary Parasitology 170 : 207 – 211 . OpenUrl CrossRef PubMed 59. Ryan U , Power M . 2012 . Cryptosporidium species in Australian wildlife and domestic animals . Parasitology 139 : 1673 – 1688 . OpenUrl CrossRef PubMed 60. Zahedi A , Monis P , Aucote S , King B , Paparini A , Jian F , Yang R , Oskam C , Ball A , Robertson I , Ryan U . 2016 . Zoonotic Cryptosporidium Species in Animals Inhabiting Sydney Water Catchments . PLoS ONE 11 : e0168169 . OpenUrl CrossRef PubMed 61. ↵ Barbosa AD , Egan S , Feng Y , Xiao L , Balogun S , Ryan U . 2024 . Zoonotic Cryptosporidium and Giardia in marsupials—an update . Parasitol Res 123 : 107 . OpenUrl PubMed 62. ↵ Nolan MJ , Jex AR , Koehler AV , Haydon SR , Stevens MA , Gasser RB . 2013 . Molecular-based investigation of Cryptosporidium and Giardia from animals in water catchments in southeastern Australia . Water Research 47 : 1726 – 1740 . OpenUrl 63. ↵ Yang R , Jacobson C , Gardner G , Carmichael I , Campbell AJD , Ryan U . 2014 . Development of a quantitative PCR (qPCR) for Giardia and analysis of the prevalence, cyst shedding and genotypes of Giardia present in sheep across four states in Australia . Experimental Parasitology 137 : 46 – 52 . OpenUrl PubMed 64. ↵ Koehler AV , Haydon SR , Jex AR , Gasser RB . 2016 . Cryptosporidium and Giardia taxa in faecal samples from animals in catchments supplying the city of Melbourne with drinking water (2011 to 2015) . Parasites Vectors 9 : 315 . OpenUrl PubMed 65. Koehler AV , Wang T , Haydon SR , Gasser RB . 2018 . Cryptosporidium viatorum from the native Australian swamp rat Rattus lutreolus - An emerging zoonotic pathogen? International Journal for Parasitology: Parasites and Wildlife 7 : 18 – 26 . OpenUrl 66. Koehler AV , Rashid MH , Zhang Y , Vaughan JL , Gasser RB , Jabbar A . 2018 . First cross-sectional, molecular epidemiological survey of Cryptosporidium , Giardia and Enterocytozoon in alpaca (Vicugna pacos) in Australia. Parasites Vectors 11 : 498 . OpenUrl PubMed 67. Koehler AV , Scheelings TF , Gasser RB . 2020 . Cryptosporidium cf. avium in an inland-bearded dragon (Pogona vitticeps) – A case report and review of the literature . International Journal for Parasitology: Parasites and Wildlife 13 : 150 – 159 . OpenUrl 68. ↵ Koehler AV , Wang T , Stevens MA , Haydon SR , Gasser RB . 2025 . Long-term molecular surveillance of Cryptosporidium and Giardia in wildlife in protected drinking water catchments . Parasites Vectors 18 : 413 . OpenUrl PubMed 69. ↵ Zahedi A , Odgers T , Ball A , Watkinson A , Robertson I , Ryan U . 2020 . Longitudinal analysis of Giardia duodenalis assemblages in animals inhabiting drinking water catchments in New South Wales and Queensland – Australia (2013–2015) . Science of The Total Environment 718 : 137433 . OpenUrl PubMed 70. ↵ O’Brien E , McInnes L , Ryan U . 2008 . Cryptosporidium GP60 genotypes from humans and domesticated animals in Australia, North America and Europe . Experimental Parasitology 118 : 118 – 121 . OpenUrl CrossRef PubMed 71. ↵ Ng JSY , Pingault N , Gibbs R , Koehler A , Ryan U . 2010 . Molecular characterisation of Cryptosporidium outbreaks in Western and South Australia . Experimental Parasitology 125 : 325 – 328 . OpenUrl CrossRef PubMed 72. ↵ Waldron LS , Ferrari BC , Power ML . 2009 . Glycoprotein 60 diversity in C. hominis and C. parvum causing human cryptosporidiosis in NSW, Australia . Experimental Parasitology 122 : 124 – 127 . OpenUrl CrossRef PubMed 73. ↵ Australian Bureau of Statistics . 2024 . National, state and territory population, March 2024. Australian Goverment, Centre for Population . 74. ↵ Xiao L , Bern C , Limor J , Sulaiman I , Roberts J , Checkley W , Cabrera L , Gilman RH , Lal AA . 2001 . Identification of 5 Types of Cryptosporidium Parasites in Children in Lima, Peru . J INFECT DIS 183 : 492 – 497 . OpenUrl CrossRef PubMed Web of Science 75. Jiang J , Alderisio KA , Xiao L . 2005 . Distribution of Cryptosporidium Genotypes in Storm Event Water Samples from Three Watersheds in New York . Appl Environ Microbiol 71 : 4446 – 4454 . OpenUrl Abstract / FREE Full Text 76. ↵ Wang R , Wang H , Sun Y , Zhang L , Jian F , Qi M , Ning C , Xiao L . 2011 . Characteristics of Cryptosporidium Transmission in Preweaned Dairy Cattle in Henan, China . J Clin Microbiol 49 : 1077 – 1082 . OpenUrl Abstract / FREE Full Text 77. ↵ Stensvold CR , Beser J , Axén C , Lebbad M . 2014 . High Applicability of a Novel Method for gp60- Based Subtyping of Cryptosporidium meleagridis . J Clin Microbiol 52 : 2311 – 2319 . OpenUrl Abstract / FREE Full Text 78. ↵ Robinson G , Chalmers RM , Elwin K , Guy RA , Bessonov K , Troell K , Xiao L . 2025 . Deciphering a cryptic minefield: A guide to Cryptosporidium gp60 subtyping . Current Research in Parasitology & Vector-Borne Diseases 7 : 100257 . OpenUrl 79. ↵ Kearse M , Moir R , Wilson A , Stones-Havas S , Cheung M , Sturrock S , Buxton S , Cooper A , Markowitz S , Duran C , Thierer T , Ashton B , Meintjes P , Drummond A . 2012 . Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data . Bioinformatics 28 : 1647 – 1649 . OpenUrl CrossRef PubMed Web of Science 80. ↵ Edgar RC . 2004 . MUSCLE: multiple sequence alignment with high accuracy and high throughput . Nucleic Acids Research 32 : 1792 – 1797 . OpenUrl CrossRef PubMed Web of Science 81. ↵ Chalmers RM , Robinson G , Elwin K , Elson R . 2019 . Analysis of the Cryptosporidium spp. And gp60 subtypes linked to human outbreaks of cryptosporidiosis in England and Wales, 2009 to 2017 . Parasites Vectors 12:95. 82. ↵ Tamura K , Stecher G , Kumar S . 2021 . MEGA11: Molecular Evolutionary Genetics Analysis Version 11 . Molecular Biology and Evolution 38 : 3022 – 3027 . OpenUrl CrossRef PubMed 83. ↵ Huelsenbeck JP , Ronquist F , Nielsen R , Bollback JP . 2001 . Bayesian Inference of Phylogeny and Its Impact on Evolutionary Biology . Science 294 : 2310 – 2314 . OpenUrl Abstract / FREE Full Text 84. ↵ Letunic I , Bork P . 2024 . Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool . Nucleic Acids Research 52 : W78 – W82 . OpenUrl CrossRef PubMed 85. ↵ Huang W , Tang K , Chen C , Arrowood MJ , Chen M , Guo Y , Li N , Roellig DM , Feng Y , Xiao L . 2024 . Sequence introgression from exogenous lineages underlies genomic and biological differences among Cryptosporidium parvum IOWA lines . Water Research 254 : 121333 . OpenUrl CrossRef PubMed 86. ↵ Nader JL , Mathers TC , Ward BJ , Pachebat JA , Swain MT , Robinson G , Chalmers RM , Hunter PR , van Oosterhout C , Tyler KM. 2019 . Evolutionary genomics of anthroponosis in Cryptosporidium . Nat Microbiol 4 : 826 – 836 . OpenUrl PubMed 87. ↵ Ng-Hublin JSY , Combs B , MacKenzie B , Ryan U . 2013 . Human Cryptosporidiosis Diagnosed in Western Australia: a Mixed Infection with Cryptosporidium meleagridis, the Cryptosporidium Mink Genotype, and an Unknown Cryptosporidium Species . J Clin Microbiol 51 : 2463 – 2465 . OpenUrl Abstract / FREE Full Text 88. ↵ Ebner J , Koehler AV , Robertson G , Bradbury RS , Jex AR , Haydon SR , Stevens MA , Norton R , Joachim A , Gasser RB . 2015 . Genetic analysis of Giardia and Cryptosporidium from people in Northern Australia using PCR-based tools . Infection, Genetics and Evolution 36 : 389 – 395 . OpenUrl 89. ↵ Xu L , Fukuda Y , Murakoshi F , Alviola P , Masangkay J , Recuenco FC , Shehata A , Omatsu T , Bando H , Fujii H , Une Y , Kato K . 2025 . Molecular characterization and zoonotic risk assessment of Cryptosporidium spp. in Philippine bats . Food and Waterborne Parasitology 38 : e00249 . OpenUrl 90. ↵ Stensvold CR , Martí-Marco A , Moratal S , Lebbad M , Carmena D . 2024 . Cryptosporidium occultus in disguise . Journal of Microbiological Methods 222 : 106957 . OpenUrl PubMed 91. ↵ Zahedi A , Monis P , Gofton AW , Oskam CL , Ball A , Bath A , Bartkow M , Robertson I , Ryan U . 2018 . Cryptosporidium species and subtypes in animals inhabiting drinking water catchments in three states across Australia . Water Research 134 : 327 – 340 . OpenUrl 92. ↵ Peng MM , Wilson ML , Holland RE , Meshnick SR , Lal AA , Xiao L . 2003 . Genetic diversity of Cryptosporidium spp. in cattle in Michigan: implications for understanding the transmission dynamics . Parasitol Res 90 : 175 – 180 . OpenUrl CrossRef PubMed Web of Science 93. ↵ Vermeulen ET , Ashworth DL , Eldridge MDB , Power ML . 2015 . Diversity of Cryptosporidium in brush-tailed rock-wallabies (Petrogale penicillata) managed within a species recovery programme . International Journal for Parasitology: Parasites and Wildlife 4 : 190 – 196 . OpenUrl 94. ↵ Power ML , Cheung-Kwok-Sang C , Slade M , Williamson S . 2009 . Cryptosporidium fayeri: Diversity within the GP60 locus of isolates from different marsupial hosts . Experimental Parasitology 121 : 219 – 223 . OpenUrl CrossRef PubMed 95. ↵ Sulaiman IM , Jiang J , Singh A , Xiao L . 2004 . Distribution of Giardia duodenalis Genotypes and Subgenotypes in Raw Urban Wastewater in Milwaukee, Wisconsin . Appl Environ Microbiol 70 : 3776 – 3780 . OpenUrl Abstract / FREE Full Text 96. ↵ Sohail A , Cheng AC , McGuinness SL , Leder K . 2024 . The epidemiology of notifiable diseases in Australia and the impact of the COVID-19 pandemic, 2012–2022 . BMC Global Public Health 2:1. 97. ↵ Oladele DB , Swain M , Robinson G , Clare A , Chalmers RM . 2025 . A review of recent Cryptosporidium hominis and Cryptosporidium parvum gp60 subtypes . Current Research in Parasitology & Vector-Borne Diseases 100292 . 98. ↵ Khalil S , Mirdha BR , Panda A , Singh Y , Makharia G , Paul J . 2017 . Cryptosporidium species subtypes and associated clinical manifestations in Indian patients . Gastroenterology and Hepatology From Bed to Bench 10 : 311 – 318 . OpenUrl 99. ↵ Gilchrist CA , Cotton JA , Burkey C , Arju T , Gilmartin A , Lin Y , Ahmed E , Steiner K , Alam M , Ahmed S , Robinson G , Zaman SU , Kabir M , Sanders M , Chalmers RM , Ahmed T , Ma JZ , Haque R , Faruque ASG , Berriman M , Petri WA . 2018 . Genetic Diversity of Cryptosporidium hominis in a Bangladeshi Community as Revealed by Whole-Genome Sequencing . The Journal of Infectious Diseases 218 : 259 – 264 . OpenUrl CrossRef PubMed 100. ↵ Ayres Hutter J , Dion R , Irace-Cima A , Fiset M , Guy R , Dixon B , Aguilar JL , Trépanier J , Thivierge K . 2020 . Cryptosporidium spp.: Human incidence, molecular characterization and associated exposures in Québec, Canada (2016-2017) . PLoS ONE 15:e0228986. 101. ↵ Costa D , Razakandrainibe R , Valot S , Vannier M , Sautour M , Basmaciyan L , Gargala G , Viller V , Lemeteil D , Ballet J-J , French National Network on Surveillance of Human Cryptosporidiosis , Dalle F , Favennec L. 2020 . Epidemiology of Cryptosporidiosis in France from 2017 to 2019 . Microorganisms 8:1358. 102. ↵ Hijjawi N , Zahedi A , Al-Falah M , Ryan U . 2022 . A review of the molecular epidemiology of Cryptosporidium spp. and Giardia duodenalis in the Middle East and North Africa (MENA) region. Infection , Genetics and Evolution 98 : 105212 . OpenUrl 103. ↵ Huang W , Guo Y , Lysen C , Wang Y , Tang K , Seabolt MH , Yang F , Cebelinski E , Gonzalez-Moreno O , Hou T , Chen C , Chen M , Wan M , Li N , Hlavsa MC , Roellig DM , Feng Y , Xiao L . 2023 . Multiple introductions and recombination events underlie the emergence of a hyper-transmissible Cryptosporidium hominis subtype in the USA . Cell Host & Microbe 31 : 112 – 123 .e4. OpenUrl PubMed 104. ↵ Braima K , Zahedi A , Oskam C , Reid S , Pingault N , Xiao L , Ryan U . 2019 . Retrospective analysis of Cryptosporidium species in Western Australian human populations (2015–2018), and emergence of the C. hominis IfA12G1R5 subtype . Infection, Genetics and Evolution 73 : 306 – 313 . OpenUrl 105. ↵ Bellinzona G , Nardi T , Castelli M , Batisti Biffignandi G , Adjou K , Betson M , Blanchard Y , Bujila I , Chalmers R , Davidson R , D’Avino N , Enbom T , Gomes J , Karadjian G , Klotz C , Östlund E , Plutzer J , Rimhanen-Finne R , Robinson G , Sannella AR , Sroka J , Stensvold CR , Troell K , Vatta P , Zalewska B , Bandi C , Sassera D , Cacciò SM . 2024 . Comparative genomics of Cryptosporidium parvum reveals the emergence of an outbreak-associated population in Europe and its spread to the United States . Genome Res 34 : 877 – 887 . OpenUrl Abstract / FREE Full Text 106. ↵ Holubová N , Zikmundová V , Kicia M , Zajączkowska Ż , Rajský M , Konečný R , Rost M , Mravcová K , Sak B , Kváč M. 2024 . Genetic diversity of Cryptosporidium spp., Encephalitozoon spp. and Enterocytozoon bieneusi in feral and captive pigeons in Central Europe . Parasitol Res 123 : 158 . OpenUrl PubMed 107. ↵ Waldron LS , Dimeski B , Beggs PJ , Ferrari BC , Power ML . 2011 . Molecular Epidemiology, Spatiotemporal Analysis, and Ecology of Sporadic Human Cryptosporidiosis in Australia . Appl Environ Microbiol 77 : 7757 – 7765 . OpenUrl Abstract / FREE Full Text 108. ↵ Yang R , Paparini A , Monis P , Ryan U . 2014 . Comparison of next-generation droplet digital PCR (ddPCR) with quantitative PCR (qPCR) for enumeration of Cryptosporidium oocysts in faecal samples . International Journal for Parasitology 44 : 1105 – 1113 . OpenUrl CrossRef PubMed 109. ↵ Kotloff KL , Nataro JP , Blackwelder WC , Nasrin D , Farag TH , Panchalingam S , Wu Y , Sow SO , Sur D , Breiman RF , Faruque AS , Zaidi AK , Saha D , Alonso PL , Tamboura B , Sanogo D , Onwuchekwa U , Manna B , Ramamurthy T , Kanungo S , Ochieng JB , Omore R , Oundo JO , Hossain A , Das SK , Ahmed S , Qureshi S , Quadri F , Adegbola RA , Antonio M , Hossain MJ , Akinsola A , Mandomando I , Nhampossa T , Acácio S , Biswas K , O’Reilly CE , Mintz ED , Berkeley LY , Muhsen K , Sommerfelt H , Robins-Browne RM , Levine MM . 2013 . Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study . The Lancet 382 : 209 – 222 . OpenUrl CrossRef 110. ↵ Kyu HH , Vongpradith A , Dominguez R-MV , Ma J , Albertson SB , Novotney A , Khalil IA , Troeger CE , Doxey MC , Ledesma JR , Sirota SB , Bender RG , Swetschinski LR , Cunningham M , Spearman S , Abate YH , Abd Al Magied AHA , Abd ElHafeez S , Abdoun M , Abera B , Abidi H , Aboagye RG , Abtew YD , Abualruz H , Abu-Gharbieh E , Abukhadijah HJ , Aburuz S , Addo IY , Adekanmbi V , Adetunji COO , Adeyeoluwa TE , Adhikary RK , Adnani QES , Adra S , Adzigbli LA , Afolabi AA , Afzal MS , Afzal S , Agampodi SB , Agide FD , Ahinkorah BO , Ahmad A , Ahmad S , Ahmed A , Ahmed A , Ahmed H , Ahmed S , Akinosoglou K , Akter E , Al Awaidy S , Alajlani MM , Alam K , Albakri A , Albashtawy M , Aldhaleei WA , Algammal AM , Al-Gheethi AAS , Ali A , Ali SS , Ali W , Alif SM , Aljunid SM , Al-Marwani S , Almazan JU , Al-Mekhlafi HM , Almustanyir S , Alqahatni SA , Alrawashdeh A , Al-Rifai RH , Alsabri MA , Altaf A , Altirkawi KA , Alvis-Guzman N , Alvis-Zakzuk NJ , Alyahya MSI , Al-Zyoud WA , Amugsi DA , Andrei CL , Antoni S , Anuoluwa BS , Anuoluwa IA , Anwar S , Anwari P , Apostol GLC , Arabloo J , Arafat M , Aravkin AY , Areda D , Aregawi BB , Aremu A , Arndt MB , Asgedom AA , Ashraf T , Athari SS , Atreya A , Ayele F , Azadi D , Azhar GS , Aziz S , Azzam AY , Babu GR , Bahrami Taghanaki P , Bahramian S , Balakrishnan S , Banik B , Bante SA , Bardhan M , Bärnighausen TW , Barqawi HJ , Barrow A , Basharat Z , Bassat Q , Bastan M-M , Basu S , Bathini PP , Behzadi P , Beiranvand M , Bello MB , Bello OO , Beloukas A , Beran A , Bhandari D , Bhardwaj P , Bhutta ZA , Borhany H , Bouaoud S , Brauer M , Buonsenso D , Butt ZA , Çakmak Barsbay M , Cámera LA , Capodici A , Castañeda-Orjuela CA , Cenderadewi M , Chakraborty C , Chakraborty S , Chattu VK , Chaudhary AA , Chichagi F , Ching PR , Chirinos-Caceres JL , Chopra H , Choudhari SG , Chowdhury EK , Chu D-T , Chukwu IS , Chutiyami M , Cruz-Martins N , Dadras O , Dai X , Dandona L , Dandona R , Darcho SD , Das JK , Dash NR , Delgado-Enciso I , Desye B , Devanbu VGC , Dhama K , Dhimal M , Diaz MJ , Do TC , Dohare S , Dorostkar F , Doshi OP , Doshmangir L , Dsouza HL , Duraisamy S , Durojaiye OC , E’mar AR , Ed-Dra A , Edinur HA , Efendi D , Efendi F , Eghbali F , Ekundayo TC , El Sayed I , Elhadi M , El-Metwally AA , Elshaer M , Elsohaby I , Eltaha C , Eshrati B , Eslami M , Fahim A , Fakhradiyev IR , Fakhri-Demeshghieh A , Farahmand M , Fasina FO , Fasina MM , Feizkhah A , Fekadu G , Ferreira N , Fetensa G , Fischer F , Fukumoto T , Fux B , Gadanya MA , Gaihre S , Gajdács M , Galali Y , Gandhi AP , Gautam RK , Gebregergis MW , Gebrehiwot M , Gebremeskel TG , Getachew ME , Getahun GK , Getie M , Ghasemzadeh A , Ghazy RM , Ghozy S , Gil AU , Girmay AA , Gizaw ATT , Golechha M , Goleij P , Gona PN , Grada A , Guarducci G , Gudeta MD , Gupta VK , Habteyohannes AD , Hadi NR , Hamidi S , Hamilton EB , Harapan H , Hasan MdK , Hasan SMM , Hasani H , Hasnain MS , Hassan II , He J , Hemmati M , Hezam K , Hosseinzadeh M , Huang J , Huynh H-H , Ibitoye SE , Ikuta KS , Ilesanmi OS , Ilic IM , Ilic MD , Inamdar S , Isa MA , Islam MdR , Islam SMS , Ismail NE , Iwu CD , Jacobsen KH , Jahrami H , Jain A , Jain N , Jairoun AA , Jakovljevic M , Jalilzadeh Yengejeh R , Javidnia J , Jayaram S , Jokar M , Jonas JB , Joseph A , Joseph N , Jozwiak JJ , Kabir H , Kadir DHH , Kamal MM , Kamal VK , Kamireddy A , Kanchan T , Kanmodi KK , Kannan S S , Kantar RS , Karami J , Karki P , Kasraei H , Kaur H , Keykhaei M , Khader YS , Khalilian A , Khamesipour F , Khan G , Khan MJ , Khan ZA , Khanal V , Khatab K , Khatatbeh MM , Khater AM , Kheirallah KA , Khidri FF , Khosla AA , Kim K , Kim YJ , Kisa A , Kissoon N , Klu D , Kochhar S , Kolahi A-A , Kompani F , Kosen S , Krishan K , Kuate Defo B , Kuddus MA , Kuddus M , Kulimbet M , Kumar GA , Kumar R , Kyei-Arthur F , Lahariya C , Lal DK , Le NHH , Lee SW , Lee W-C , Lee YY , Li M-C , Ligade VS , Liu G , Liu S , Liu X , Liu X , Lo C-H , Lucchetti G , Lv L , Malhotra K , Malik AA , Marasini BP , Martorell M , Marzo RR , Masoumi-Asl H , Mathur M , Mathur N , Mediratta RP , Meftah E , Mekene Meto T , Meles HN , Melese EB , Mendoza W , Merati M , Meretoja TJ , Mestrovic T , Mettananda S , Minh LHN , Mishra V , Mithra P , Mohamadkhani A , Mohamed AI , Mohamed MFH , Mohamed NS , Mohammed M , Mohammed S , Monasta L , Moni MA , Motappa R , Mougin V , Mubarik S , Mulita F , Munjal K , Munkhsaikhan Y , Naghavi P , Naik G , Nair TS , Najmuldeen HHR , Nargus S , Narimani Davani D , Nashwan AJ , Natto ZS , Nazri-Panjaki A , Nchanji GT , Ndishimye P , Ngunjiri JW , Nguyen DH , Nguyen NNY , Nguyen VT , Nigatu YT , Nikoobar A , Niranjan V , Nnaji CA , Noman EA , Noor NM , Noor STA , Nouri M , Nozari M , Nri-Ezedi CA , Nugen F , Odetokun IA , Ogunfowokan AA , Ojo-Akosile TR , Okeke IN , Okekunle AP , Olorukooba AA , Olufadewa II , Oluwatunase GO , Orish VN , Ortega-Altamirano DV , Ortiz-Prado E , Osuagwu UL , Osuolale O , Ouyahia A , Padubidri JR , Pandey A , Pandey A , Pando-Robles V , Pardhan S , Parikh RR , Patel J , Patil S , Pawar S , Peprah P , Perianayagam A , Perna S , Petcu I-R , Philip AK , Polibin RV , Postma MJ , Pourtaheri N , Pradhan J , Prates EJS , Pribadi DRA , Qasim NH , Qazi AS , R D , Radhakrishnan V , Rahim F , Rahman M , Rahman MA , Rahmani S , Rahmanian M , Rahmanian N , Ramadan MM , Ramasamy SK , Ramazanu S , Rameto MAA , Ramteke PW , Rana K , Ranabhat CL , Rasella D , Rashidi M-M , Rasouli-Saravani A , Rathish D , Rauniyar SK , Rawaf S , Redwan EMM , Regmi AR , Rengasamy KR , Rezaei N , Rezaei N , Rezaeian M , Riad A , Rodrigues M , Rodriguez JAB , Roever L , Rohilla R , Ronfani L , Rony MKK , Ross AG , Roudashti S , Roy B , Runghien T , Sachdeva Dhingra M , Saddik BA , Sadeghi E , Safari M , Sahoo SS , Sajadi SM , Salami AA , Saleh MA , Samadi Kafil H , Samodra YL , Sanabria J , Sanjeev RK , Sarkar T , Sartorius B , Sathian B , Satpathy M , Sawhney M , Schumacher AE , Sebsibe MA , Serban D , Shafie M , Shahid S , Shahid W , Shaikh MA , Sham S , Shamim MA , Shams-Beyranvand M , Shamshirgaran MA , Shanawaz M , Shannawaz M , Sharifan A , Sharma M , Sharma V , Shenoy SM , Sherchan SP , Shetty M , Shetty PH , Shiferaw D , Shittu A , Shorofi SA , Siddig EE , Silva LMLR , Singh B , Singh JA , Sinto R , Socea B , Soeters HM , Sokhan A , Sood P , Soraneh S , Sreeramareddy CT , Srinivasamurthy SK , Srivastava VK , Stanikzai MH , Subedi N , Subramaniyan V , Sulaiman SK , Suleman M , Swain CK , Szarpak L , T Y SS , Tabatabaei SM , Tabche C , Taha ZM-A , Talukder A , Tamuzi JL , Tan K-K , Tandukar S , Temsah M-H , Thakali O , Thakur R , Thirunavukkarasu S , Thomas J , Thomas NK , Ticoalu JHV , Tiwari K , Tovani-Palone MR , Tram KH , Tran AT , Tran NM , Tran TH , Tromans SJ , Truyen TTTT , Tumurkhuu M , Udoakang AJ , Udoh A , Ullah S , Umair M , Umar M , Unim B , Unnikrishnan B , Vahdati S , Vaithinathan AG , Valizadeh R , Verma M , Verras G-I , Vinayak M , Waheed Y , Walde MT , Wang Y , Waqas M , Weerakoon KG , Wickramasinghe ND , Wolde AA , Wu F , Yaghoubi S , Yaya S , Yezli S , Yiğit V , Yin D , Yon DK , Yonemoto N , Yusuf H , Zahid MH , Zakham F , Zaki L , Zare I , Zastrozhin M , Zeariya MGM , Zhang H , Zhang Z-J , Zhumagaliuly A , Zia H , Zoladl M , Mokdad AH , Lim SS , Vos T , Platts-Mills JA , Mosser JF , Reiner RC , Hay SI , Naghavi M , Murray CJL. 2025 . Global, regional, and national age-sex-specific burden of diarrhoeal diseases, their risk factors, and aetiologies, 1990–2021, for 204 countries and territories: a systematic analysis for the Global Burden of Disease Study 2021 . The Lancet Infectious Diseases 25:519– 536. 111. ↵ Wood M , Simmonds L , MacAdam J , Hassard F , Jarvis P , Chalmers RM . 2019 . Role of filtration in managing the risk from Cryptosporidium in commercial swimming pools – a review . Journal of Water and Health 17 : 357 – 370 . OpenUrl PubMed 112. ↵ Braima K , Harvie S , Trew I , Tan H , Gore C , Zahedi A , Oskam C , Lawler S , Reid S , Ryan U . 2022 . Knowledge, Attitude and Practices Towards Cryptosporidium Among Public Swimming Pool Patrons and Staff in Western Australia . Acta Parasit 67 : 460 – 467 . OpenUrl 113. ↵ Nolan MJ , Jex AR , Mansell PD , Browning GF , Gasser RB . 2009 . Genetic characterization of Cryptosporidium parvum from calves by mutation scanning and targeted sequencing – zoonotic implications . Electrophoresis 30 : 2640 – 2647 . OpenUrl PubMed 114. ↵ Pangasa A . 2010 . Highly sensitive non-isotopic restriction endonuclease fingerprinting of nucleotide variability in the gp60 gene within Cryptosporidium species, genotypes and subgenotypes infective to humans, and its implications . Electrophoresis 31 : 1637 – 1647 . OpenUrl PubMed 115. ↵ Efstratiou A , Ongerth JE , Karanis P . 2017 . Waterborne transmission of protozoan parasites: Review of worldwide outbreaks - An update 2011–2016 . Water Research 114 : 14 – 22 . OpenUrl CrossRef PubMed 116. ↵ Bourli P , Eslahi AV , Tzoraki O , Karanis P . 2023 . Waterborne transmission of protozoan parasites: a review of worldwide outbreaks – an update 2017–2022 . Journal of Water and Health 21 : 1421 – 1447 . OpenUrl CrossRef PubMed 117. ↵ 2025 . Australia’s Annual Climate Statement 2024. Australian Goverment, Bureau of Meteorology . 118. Esper J , Torbenson M , Büntgen U . 2024 . 2023 summer warmth unparalleled over the past 2,000 years . Nature 631 : 94 – 97 . OpenUrl PubMed 119. ↵ European Commission . 2023 . Summer 2023: the hottest on record. August Climate Report. Copernicus, Bonn . 120. ↵ Chalmers RM , Elwin K , Thomas AL , Guy EC , Mason B. 2009 . Long-term Cryptosporidium typing reveals the aetiology and species-specific epidemiology of human cryptosporidiosis in England and Wales, 2000 to 2003 . Eurosurveillance 14. 121. ↵ Morris A , Robinson G , Swain MT , Chalmers RM . 2019 . Direct Sequencing of Cryptosporidium in Stool Samples for Public Health . Front Public Health 7 : 360 . OpenUrl PubMed 122. ↵ Khan A , Alves-Ferreira EVC , Vogel H , Botchie S , Ayi I , Pawlowic MC , Robinson G , Chalmers RM , Lorenzi H , Grigg ME . 2024 . Phylogenomic reconstruction of Cryptosporidium spp . Captured directly from clinical samples reveals extensive genetic diversity doi: 10.1101/2024.04.17.589752 . OpenUrl Abstract / FREE Full Text 123. ↵ Robinson G , Pérez-Cordón G , Hamilton C , Katzer F , Connelly L , Alexander CL , Chalmers RM. 2022 . Validation of a multilocus genotyping scheme for subtyping Cryptosporidium parvum for epidemiological purposes . Food and Waterborne Parasitology 27 : e00151 . OpenUrl 124. ↵ Yang Z , Yang F , Wang J , Cao J , Zhao W , Gong B , Yan J , Zhang W , Liu A , Shen Y . 2018 . Multilocus sequence typing and population genetic structure of Cryptosporidium cuniculus in rabbits in Heilongjiang Province, China. Infection , Genetics and Evolution 64 : 249 – 253 . OpenUrl 125. ↵ Bayona-Vásquez N , Sullivan A , Beaudry M , Khan A , Baptista R , Petersen K , Bhuiyan M , Brunelle B , Robinson G , Chalmers R , Alves-Ferreira E , Grigg M , Kissinger J , Glenn T . 2024 . Whole Genome Targeted Enrichment and Sequencing of Human-Infecting Cryptosporidium spp . doi: 10.21203/rs.3.rs-4294842/v1 . OpenUrl CrossRef 126. ↵ 2025 . CryptoNet: Tracking Cryptosporidium in the U.S. Atlanta, Georgia, United States . View the discussion thread. Back to top Previous Next Posted October 23, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Comprehensive public health surveillance identifies novel human cryptosporidiosis subtypes and genetic diversity associated with swimming pool outbreaks in Australia, Victoria (2018-2024) Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. 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