Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique.

Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique.
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DOI:
10.1038/s41598-018-27537-4
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发表时间:
2018-06-18
期刊:
影响因子:
4.6
通讯作者:
Colborn JM
Colborn JM
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Colborn KL;Giorgi E;Monaghan AJ;Gudo E;Candrinho B;Marrufo TJ;Colborn JM

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疟疾是莫桑比克发病率和死亡率的一个主要原因。我们提出了一个疟疾预警系统(MEWS)为莫桑比克通报了7年的每周病例报告的疟疾在5岁以下的儿童从142个区。根据解释性气候变量开发了一个时空模型,以绘制疟疾发病概率图,其定义是某一地区某一周疟疾发病率的相对风险超过预定阈值的预测概率。与大多数空间离散模型不同,我们的方法在推导空间协方差结构时考虑了每个地区的地理范围,以考虑行政边界随时间的变化。因此,MEWS可用于及早预测疟疾传播可能超过预期水平的地区,以便在爆发之前实施预防和应对措施。我们提出的框架也适用于其他气候敏感性疾病。
Malaria is a major cause of morbidity and mortality in Mozambique. We present a malaria early warning system (MEWS) for Mozambique informed by seven years of weekly case reports of malaria in children under 5 years of age from 142 districts. A spatio-temporal model was developed based on explanatory climatic variables to map exceedance probabilities, defined as the predictive probability that the relative risk of malaria incidence in a given district for a particular week will exceed a predefined threshold. Unlike most spatially discrete models, our approach accounts for the geographical extent of each district in the derivation of the spatial covariance structure to allow for changes in administrative boundaries over time. The MEWS can thus be used to predict areas that may experience increases in malaria transmission beyond expected levels, early enough so that prevention and response measures can be implemented prior to the onset of outbreaks. The framework we present is also applicable to other climate-sensitive diseases.
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