Sadler E, Vallee E, Watts J, Wada M
EpiCentre, Tāwharau Ora - School of Veterinary Science, Massey University, Palmerston North, New Zealand.
Biosecurity Surveillance (Animal Health), Ministry for Primary Industries, Wellington, New Zealand.
N Z Vet J. 2025 Aug 12:1-13. doi: 10.1080/00480169.2025.2540324.
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 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.
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 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.
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.
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.
ICC: Intra-class correlation coefficient; IRR: Incidence risk ratio; MPI: Ministry for Primary Industries; NIWA: National Institute of Water and Atmospheric Research.
描述新西兰绵羊和牛群中钩端螺旋体病病例数的时空模式，并评估其与表明洪水和地表径流的气候变量之间的关联。由于家畜是钩端螺旋体的主要宿主以及人畜共患病传播的重要来源，了解这些模式对于在气候变化背景下为家畜和公共卫生干预措施提供信息至关重要。
从初级产业部的动物健康监测计划中提取2011年1月至2023年12月确诊的牛和羊钩端螺旋体病病例。气候数据来自国家水与大气研究所。使用检验和泊松回归模型，研究了地区层面病例数与四个气候指数之间的关联：季节性平均降雨量、极端降雨的季节性频率、季节性平均土壤湿度和估计地表径流的季节性频率。
研究结果表明，绵羊每年平均有13例确诊病例，在2017年（34例）和2023年（36例）出现显著激增，与极端气候事件相符。绵羊钩端螺旋体病的泊松回归模型确定与极端降雨（发病风险比（IRR）=5.03；95%置信区间=1.18-21.45）、平均降雨（IRR=1.25；95%置信区间=1.15-1.36）、地表径流（IRR=1.09；95%置信区间=1.04-1.15）和土壤湿度（IRR=1.03；95%置信区间=1.02-1.03）存在显著关联。牛钩端螺旋体病与地表径流（IRR=1.06；95%置信区间=1.02-1.10）和土壤湿度（IRR=1.01；95%置信区间=1.00-1.01）呈正相关。与极端降雨（IRR=1.46；95%置信区间=0.49-4.31）和平均降雨（IRR=1.07；95%置信区间=1.00-1.14）的关联无统计学意义。
本研究结果提供了新的证据，将极端降雨、地表径流和其他气候变量与绵羊中钩端螺旋体病病例数增加联系起来，在牛中关联虽不那么明显但也值得注意。这些发现凸显了家畜对气候驱动的疾病压力的脆弱性，并表明未来极端天气事件可能增加钩端螺旋体病暴发的风险。这对新西兰易发生洪水的农村地区的针对性疫苗接种、监测和公共卫生准备具有重要意义。
ICC：组内相关系数；IRR：发病风险比；MPI：初级产业部；NIWA：国家水与大气研究所
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