Malaria is among the greatest public health threats in Mozambique, with over 10 million cases reported annually since 2018. Although the relationship between seasonal trends in environmental parameters and malaria cases is well established, the role of climate in deviations from the annual cycle is less clear. To investigate this and the potential for leveraging inter‐annual climate variability to predict malaria outbreaks, weekly district‐level malaria incidence spanning 2010–2017 were processed for a cross‐analysis with climate data. An empirical orthogonal function analysis of district‐level malaria incidence revealed two dominant spatiotemporal modes that collectively account for 81% of the inter‐annual variability of malaria: a mode dominated by variance over the southern half of Mozambique (64%), and another dominated by variance in the northern third of the country (17%). These modes of malaria variability are shown to be closely related to precipitation. Linear regression of global sea surface temperatures onto local precipitation indices over these variance maxima links the leading mode of inter‐annual malarial variability to the El Niño‐Southern Oscillation, such that La Niña leads to wetter conditions over southern Mozambique and, therefore, higher malaria prevalence. Similar analysis of spatiotemporal patterns of precipitation over a longer time period (1979–2019) indicate that the Subtropical Indian Ocean Dipole is both a strong predictor of regional precipitation and the climatic mechanism underlying the second mode of malarial variability. These results suggest that skillful malaria early warning systems may be developed that leverage quasi‐predictable modes of inter‐annual climate variability in the tropical oceans.

中文翻译：

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莫桑比克的年际气候变化与疟疾

疟疾是莫桑比克最大的公共卫生威胁之一，自2018年以来，每年报告的病例超过1000万例。尽管环境参数的季节性趋势与疟疾病例之间的关系已经很好地建立，但气候在偏离年度周期的作用中的作用尚不清楚。为了调查这一点以及利用年际气候变化来预测疟疾暴发的潜力，我们对2010-2017年每周一次的地区级疟疾发病率进行了处理，以与气候数据进行交叉分析。区域级疟疾发病率的经验正交函数分析显示，两种占主导的时空模式共同构成了疟疾年际变化的81％：一种以莫桑比克南半部的方差为主导的模式（64％），另一个以该国北部三分之一的地区为主（17％）。这些疟疾变异性的模式与降水密切相关。在这些方差最大值上，全球海表温度到局部降水指数的线性回归将年际疟疾变异的主导模式与厄尔尼诺-南方涛动联系在一起，这样拉尼娜导致莫桑比克南部的湿润条件，因此疟疾发病率更高患病率。对较长时期（1979-2019年）降水时空分布模式的类似分析表明，亚热带印度洋偶极子既是区域降水的有力预测指标，也是第二种疟疾变异性模式的气候机制。