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巴西流感的季节性动态:纬度效应。

Seasonal dynamics of influenza in Brazil: the latitude effect.

机构信息

Escola Nacional de Saúde Pública, FIOCRUZ, Rio de Janeiro, Brazil.

Programa de Computação Científica, FIOCRUZ, Rio de Janeiro, Brasil.

出版信息

BMC Infect Dis. 2018 Dec 27;18(1):695. doi: 10.1186/s12879-018-3484-z.

Abstract

BACKGROUND

Influenza 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSIONS

Our study advances the comprehension of influenza seasonality in tropical areas and could be used to design more effective prevention and control strategies.

摘要

背景

流感是一种全球性传染病。其动态在温带气候下比在热带地区了解得更为透彻。我们旨在通过展示流感季节性在巴西(一个涵盖广泛纬度和六种气候亚型的热带国家)的演变,缩小热带和温带地区之间的知识差距。

方法

我们分析了 2010 年至 2016 年期间每周的急性呼吸道疾病综合征(SARI)发病率的州级数据。我们采用了两种技术的层次组合:首先是小波分解技术来检测年度周期性,然后是循环统计来描述周期性状态的季节性度量。

结果

我们发现 44%的州存在显著的年度周期性。对于这些州,我们计算了几个季节性度量,如重心或活动的平均时间。季节性特征与纬度之间的关系清晰且具有统计学意义。具有季节性特征的州沿着海岸聚集。大多数亚马逊和中西部州没有季节性行为。在季节性州中,流感始于东北地区,向南传播。

结论

我们的研究增进了对热带地区流感季节性的理解,并可用于设计更有效的预防和控制策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33b1/6307116/4324eed04139/12879_2018_3484_Fig1_HTML.jpg

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