Seasonal dynamics of influenza in Brazil: the latitude effect
Seasonal dynamics of influenza in Brazil: the latitude effect
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DOI：
10.1186/s12879-018-3484-z
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发表时间：
2018-12-27
影响因子：
3.7
通讯作者：
Luz, Paula
中科院分区：
文献类型：
--
作者：
Almeida, Alexandra;Codeco, Claudia;Luz, Paula
研究背景流感是一种全球性传染病。它的动力学在温带气候中比在热带气候中更容易理解。我们的目标是关闭热带和温带地区之间的知识差距，显示流感的季节性如何在巴西，一个热带国家，包括广泛的纬度和六个气候sub-types.MethodsWe分析了国家一级，每周急性呼吸道疾病综合征（SARI）发病率数据范围从2010年到2016年的演变。我们结合两种技术层次：首先，小波分解技术检测年度周期性，然后循环统计描述的季节性措施的周期states.ResultsWe发现显着的年度周期性的44%的状态。对于这些，我们计算了几个季节性措施，如重心或活动的平均时间。季节特征与纬度之间的关系是明确的，具有统计学意义。具有季节性特征的州沿着海岸聚集。大多数亚马逊河流域和中西部的州没有表现出季节性行为。在季节性状态，流感开始在东北地区，向南传播。ConclusionsOur study advances the understanding of influenza seasonality in tropical areas and could be used to design more effective prevention and control strategies.
BackgroundInfluenza is a global transmissible disease. Its dynamics is far better understood in temperate climates than in the tropics. We aim to close this knowledge gap between tropical and temperate regions by showing how the influenza seasonality evolves in Brazil, a tropical country that encompasses a wide range of latitudes and six climatic sub-types.MethodsWe analyzed a state-level, weekly Syndrome of Acute Respiratory Disease (SARI) incidence data ranging from 2010 to 2016. We combined two techniques hierarchically: first the wavelet decomposition technique to detect annual periodicity and then circular statistics to describe seasonal measures of the periodic states.ResultsWe found significant annual periodicity in 44% of the states. For these, we calculated several seasonal measures such as the center of gravity or mean timing of activity. The relationship between the seasonal signatures and latitude was clear and statistically significant. States with seasonal signature are clustered along the coast. Most Amazonian and Central West states exhibit no seasonal behavior. Among the seasonal states, influenza starts in Northeast region, spreading southbound.ConclusionsOur study advances the comprehension of influenza seasonality in tropical areas and could be used to design more effective prevention and control strategies.