Cryptosporidiosis and giardiasis are recognized as significant enteric diseases due to their long-term health effects in humans and their economic impact in agriculture and medical care. Molecular analysis is essential to identify species and genotypes causing these infectious diseases and provides a potential tool for monitoring. This study uses information on species and genetic variants to gain insights into the geographical distribution and spatial patterns of Cryptosporidium and Giardia parasites. Here, we describe the population heterogeneity of genotypic groups within Cryptosporidium and Giardia present in New Zealand using gp60 and gdh markers to compare the observed variation with other countries around the globe. Four species of Cryptosporidium (C. hominis, C. parvum, C. cuniculus and C. erinacei) and one species of Giardia (G. intestinalis) were identified. These species have been reported worldwide and there are not unique Cryptosporidium gp60 subtype families and Giardia gdh assemblages in New Zealand, most likely due to high gene flow of historical and current human activity (travel and trade) and persistence of large host population sizes. The global analysis revealed that genetic variants of these pathogens are widely distributed. However, genetic variation is underestimated by data biases (e.g. neglected submission of sequences to genetic databases) and low sampling. New genotypes are likely to be discovered as sampling efforts increase according to accumulation prediction analyses, especially for C. parvum. Our study highlights the need for greater sampling and archiving of genotypes globally to allow comparative analyses that help understand the population dynamics of these protozoan parasites. Overall our study represents a comprehensive overview for exploring local and global protozoan genotype diversity and advances our understanding of the importance for surveillance and potential risk associated with these infectious diseases. Infectious diseases threaten the health and well-being of wildlife, livestock and human populations and contribute to significant economic impact in agriculture and medical care. Cryptosporidium and Giardia are enteric protozoan pathogens that cause diarrhea and nutritional disorders on a global level. Using molecular analysis and a review framework we showed that species and genetic variants within genera Cryptosporidium and Giardia (including two species recently infecting humans) found in an island system are not different from other parts of the world. This similarity is likely due to high gene flow of historical and current human activity (travel and trade) and persistence of large host population sizes, such as cattle and people. We also show that, although species and genotypes are widely distributed, new variants will arise when sampling effort increase and their dispersal will be facilitated by human activity. These findings suggest that geographical distribution of species and genotypes within Cryptosporidium and Giardia parasites may yield important clues for designing effective surveillance strategies and identification of factors driving within and cross species transmission.

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security.

Dairy animals are an important source of income, food, and nutritional security, and improvements in the productivity of dairy animals substantially improve the wellbeing of smallholder dairy farmers. As in other developing countries, dairy animals are key for rural livelihoods in Nepal but often suffer from mastitis-a production disease causing economic losses to farmers, challenges to the dairy processing industry, and possible health hazards to consumers. Studies show that the prevalence of subclinical mastitis in Africa and Asia typically exceeds 50%, threatening animal wellbeing, farmers, dairy processors, and consumers. We conducted a study in Nepal to develop a technology training package to control mastitis in dairy animals. Following identification of knowledge gaps, a technology package consisting of (1) developing good husbandry practices, implementing mastitis detection and control technologies; and (2) training technicians and farmers was implemented. A strategy was subsequently established to provide feedback to farmers in dairy cooperatives on the subclinical mastitis status of their cows. The package was applied in the mid-western region of Nepal. Six months after implementation, we observed a reduction in subclinical mastitis prevalence: from 55% (baseline) to 28% (endline; n = 432) in dairy cows and from 78% to 18% (n = 216) in buffalo. These positive study outcomes strongly suggest that the mastitis technology training package should be scaled across smallholder farmers within and beyond Nepal to control mastitis in dairy animals.

Community-acquired carbapenem-resistant Enterobacterales (CA-CRE) are an important threat. In CRACKLE-2, we defined patients with CA-CRE as admitted from home, without pre-existing conditions, and a positive culture within 48 h of admission. Healthcare-associated CRE (HA-CRE) were those with the lowest likelihood of community acquisition, not admitted from home and cultured >48 h after admission. Specific genetic markers in carbapenemase-producing Klebsiella pneumoniae were evaluated through random forest modelling. CA-CRE and HA-CRE were detected in 83 (10%) and 208 (26%) of 807 patients. No significant differences were observed in bacterial species or strain type distribution. K. pneumoniae (204/291, 70%) was the most common CRE species, of these 184/204 (90%) were carbapenemase producers (CPKP). The top three genetic markers in random forest models were kpi_SA15, fimE, and kpfC. Of these, kpi_SA15 (which encodes a chaperone/usher system) was positively associated (OR 3.14, 95% CI 1.13–8.87, P = 0.026), and kpfC negatively associated (OR 0.21, 95% CI 0.05–0.72, P = 0.015) with CA-CPKP. Ten percent of CDC-defined CRE were CA. The true proportion of CA-CRE in hospitalized patients is likely lower as patients may have had unrecorded prior healthcare exposure. The kpi_SA15 operon was associated with the CA phenotype.

In 2016, there was a large-scale waterborne outbreak of campylobacteriosis in New Zealand, which was estimated to have affected over 5,000 people. This highlighted the need for a greater understanding of the sources of contamination of both surface and groundwater and risks associated with exposure to both drinking and recreational water. This study reports the prevalence and population structure of Campylobacter jejuni in six recreational waters of the Manawatu-Wanganui region of New Zealand and models the relationship between Campylobacter spp. and ruminant-associated Campylobacter and the parameters “sites,” “months,” and “river flow.” Here, we demonstrate that both low and high river flows, month of the year, and recreational sites could influence the Campylobacter isolation from recreational waters. The presence of genotypes associated with human infection allowed us to describe potential risks associated with recreational waters.

Antimicrobial resistance (AMR) in enteric bacteria continues to be detected in turkey flocks and retail products worldwide, including in Canada. However, studies assessing linkages between on-farm antimicrobial use (AMU) and the development of AMR are lacking. This study aims to identify AMU characteristics that impact the development of AMR in the indicator bacteria Escherichia coli in turkey flocks, building on the Canadian Integrated Program for Antimicrobial Resistance Surveillance methodology for farm-level AMU and AMR data integration. Two analytic approaches were used: (1) multivariable mixed-effects logistic regression models examined associations between AMU (any route, route-specific, and route-disease-specific indication) summarized as the number of defined daily doses in animals using Canadian standards ([nDDDvetCA]/1,000 kg-animal-days at risk) and AMR and (2) multivariable mixed-effects Poisson regression models studied the linkages between AMU and the number of classes to which an E. coli isolate was resistant (nCR_{E. coli}). A total of 1,317 E. coli isolates from a network of 16 veterinarians and 334 turkey producers across the five major turkey-producing provinces in Canada between 2016 and 2019 were used. Analysis indicated that AMR emerged with the use of related antimicrobials (e.g., tetracycline use-tetracycline resistance), however, the use of unrelated antimicrobial classes was also impacting AMR (e.g., aminoglycosides/streptogramins use-tetracycline resistance). As for studying AMU-nCR_{E. coli} linkages, the most robust association was between the parenteral aminoglycosides use and nCR_{E. coli}, though in-feed uses of four unrelated classes (bacitracin, folate pathway inhibitors, streptogramins, and tetracyclines) appear to be important, indicating that ongoing uses of these classes may slow down the succession from multidrug-resistant to a more susceptible E. coli populations. The analysis of AMU (route and disease-specific)-AMR linkages complemented the above findings, suggesting that treatment of certain diseases (enteric, late-stage septicemic conditions, and colibacillosis) are influential in the development of resistance to certain antimicrobial classes. The highest variances were at the flock level indicating that stewardship actions should focus on flock-level infection prevention practices. This study added new insights to our understanding of AMU-AMR linkages in turkeys and is useful in informing AMU stewardship in the turkey sector. Enhanced surveillance using sequencing technologies are warranted to explain molecular-level determinants of AMR.