Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    The effects of rain and flooding on leptospirosis incidence in sheep and cattle in New Zealand
    (Taylor and Francis Group on behalf of the New Zealand Veterinary Association, 2025-08-12) Sadler E; Vallee E; Watts J; Wada M
    Aims To describe the spatio-temporal patterns of leptospirosis case counts in sheep and cattle in New Zealand, and to assess their association with climate variables indicative of flooding and surface runoff. As livestock are a major reservoir of Leptospira spp. and an important source of zoonotic transmission, understanding these patterns is critical for informing livestock and public health interventions in the context of climate change. Methods Confirmed cases of bovine and ovine leptospirosis from January 2011 to December 2023 were extracted from the Ministry for Primary Industries’ Animal Health Surveillance programme. Climate data was sourced from the National Institute of Water and Atmospheric Research. Using the χ2 test and Poisson regression models, the association between district-level case counts and four climate indices were examined: seasonal mean rainfall, seasonal frequency of extreme rainfall, seasonal mean soil moisture, and seasonal frequency of estimated surface runoff. Results Findings indicated an average of 13 confirmed cases for sheep annually, with notable surges in 2017 (34 cases) and 2023 (36 cases), aligning with extreme climate events. Poisson regression models for sheep leptospirosis identified significant associations with extreme rainfall (incidence risk ratio (IRR) = 5.03; 95% CI = 1.18–21.45), mean rainfall (IRR = 1.25; 95% CI = 1.15–1.36), surface runoff (IRR = 1.09; 95% CI = 1.04–1.15), and soil moisture (IRR = 1.03; 95% CI = 1.02–1.03). Cattle leptospirosis was positively associated with surface runoff (IRR = 1.06; 95% CI = 1.02–1.10) and soil moisture (IRR = 1.01; 95% CI = 1.00–1.01). Associations with extreme rainfall (IRR = 1.46; 95% CI = 0.49–4.31) and mean rainfall (IRR = 1.07; 95% CI = 1.00–1.14) were not statistically significant. Conclusions The outcomes of this study provide new evidence linking extreme rainfall, surface runoff, and other climate variables with increased leptospirosis case counts in sheep, with less pronounced but notable associations in cattle. These findings highlight the vulnerability of livestock to climate-driven disease pressures and suggest that future extreme weather events may increase the risk of leptospirosis outbreaks. This has important implications for targeted vaccination, surveillance, and public health preparedness in flood-prone rural regions of New Zealand.
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    Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.
    (Cambridge University Press, 2024-04-15) Grout L; Hales S; Baker MG; French N; Wilson N
    Occurrence of cryptosporidiosis has been associated with weather conditions in many settings internationally. We explored statistical clusters of human cryptosporidiosis and their relationship with severe weather events in New Zealand (NZ). Notified cases of cryptosporidiosis from 1997 to 2015 were obtained from the national surveillance system. Retrospective space-time permutation was used to identify statistical clusters. Cluster data were compared to severe weather events in a national database. SaTScan analysis detected 38 statistically significant cryptosporidiosis clusters. Around a third (34.2%, 13/38) of these clusters showed temporal and spatial alignment with severe weather events. Of these, nearly half (46.2%, 6/13) occurred in the spring. Only five (38%, 5/13) of these clusters corresponded to a previously reported cryptosporidiosis outbreak. This study provides additional evidence that severe weather events may contribute to the development of some cryptosporidiosis clusters. Further research on this association is needed as rainfall intensity is projected to rise in NZ due to climate change. The findings also provide further arguments for upgrading the quality of drinking water sources to minimize contamination with pathogens from runoff from livestock agriculture.
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    Coastal Dynamics Initiate, Relocate and Terminate Short-Lived Wetlands of Dune Slacks, Manawatū, New Zealand
    (MDPI (Basel, Switzerland), 2022-07) Villacís Lozada SP; Rapson GL; Prisco I; Roscioni F; Marzialetti F
    Dunelands are one of the most dynamic environments on Earth, which greatly hinders their conservation and management. In the dune slacks along the Manawatū coast, New Zealand, lies a zone of small, temporary, freshwater wetlands that host early seral communities of rare turf plants. Analysis of historical aerial photos allowed determination of coastline movement, distance of the wetlands from the coast, and wetland movements through time. Study sites were around the coastal settlements of Tangimoana and Foxton Beach, both having major rivers debouching nearby, and Himatangi, amongst stabilising exotic pine plantations. The coastline is prograding (with seaward movement) generally by 0.7–1 m yr−1, but is more variable closer to river mouths, with episodes of movement of up to 15 m yr−1. Wetlands occur 200–400 m behind the strandline, are closer to the coast at Foxton Beach, and furthest away at Himatangi. Wetlands wobble in their position at 5.2 m yr−1 but migrate inland at an average of 2.7 m yr−1. Wetland size appears unrelated to rainfall, but may be related positively to coastal progradation rate, to which wetland movement is negatively related. Near the major rivers, dunes are less stable, and wetlands can be impacted both positively and negatively. Wetland existence and movement is balanced between stability and dynamism on the coast, and management will need to be proactive to maintain environments for early successional turfs.
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    Social Vulnerability Indicators for Flooding in Aotearoa New Zealand
    (MDPI (Basel, Switzerland), 2021-04-09) Mason K; Lindberg K; Haenfling C; Schori A; Marsters H; Read D; Borman B
    Social vulnerability indicators are a valuable tool for understanding which population groups are more vulnerable to experiencing negative impacts from disasters, and where these groups live, to inform disaster risk management activities. While many approaches have been used to measure social vulnerability to natural hazards, there is no single method or universally agreed approach. This paper proposes a novel approach to developing social vulnerability indicators, using the example of flooding in Aotearoa New Zealand. A conceptual framework was developed to guide selection of the social vulnerability indicators, based on previous frameworks (including the MOVE framework), consideration of climate change, and a holistic view of health and wellbeing. Using this framework, ten dimensions relating to social vulnerability were identified: exposure; children; older adults; health and disability status; money to cope with crises/losses; social connectedness; knowledge, skills and awareness of natural hazards; safe, secure and healthy housing; food and water to cope with shortage; and decision making and participation. For each dimension, key indicators were identified and implemented, mostly using national Census population data. After development, the indicators were assessed by end users using a case study of Porirua City, New Zealand, then implemented for the whole of New Zealand. These indicators will provide useful data about social vulnerability to floods in New Zealand, and these methods could potentially be adapted for other jurisdictions and other natural hazards, including those relating to climate change.