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大规模流行病学建模：探寻巴西蚊媒疾病的时空模式

Large-scale epidemiological modelling: scanning for mosquito-borne diseases spatio-temporal patterns in Brazil.

作者信息

Araujo Eduardo C, Codeço Cláudia T, Loch Sandro, Vacaro Luã B, Freitas Laís Picinini, Lana Raquel M, Bastos Leonardo S, de Almeida Iasmim F, Valente Fernanda, Carvalho Luiz Max, Coelho Flávio C

机构信息

School of Applied Mathematics, Getulio Vargas Foundation, Rio de Janeiro, Brazil.

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

出版信息

R Soc Open Sci. 2025 May 28;12(5):241261. doi: 10.1098/rsos.241261. eCollection 2025 May.

DOI:10.1098/rsos.241261
PMID:40438543
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12115816/
Abstract

The influence of climate on mosquito-borne diseases like dengue and chikungunya is well established, but comprehensively tracking long-term spatial and temporal trends across large areas has been hindered by fragmented data and limited analysis tools. This study presents an unprecedented analysis, in terms of breadth, estimating the susceptible-infectious-recovered transmission parameters from incidence data in all 5570 municipalities in Brazil over 14 years (2010-2023) for both dengue and chikungunya. We describe the Episcanner computational pipeline, developed to estimate these parameters, producing a reusable dataset characterizing all dengue and chikungunya epidemics that have taken place in this period in Brazil. The analysis reveals new insights into the climate-epidemic nexus: we identify distinct geographical and temporal patterns of arbovirus disease incidence across Brazil, highlighting how climatic factors like temperature and precipitation influence the timing and intensity of dengue and chikungunya epidemics. The innovative Episcanner tool empowers researchers and public health officials to explore these patterns in detail, facilitating targeted interventions and risk assessments. This research offers the possibility of exploring the main characteristics of dengue and chikungunya epidemics and their geographical specificities linked to the effects of global temperature fluctuations such as those captured by the El Niño-Southern Oscillation index.

摘要

气候对登革热和基孔肯雅热等蚊媒疾病的影响已得到充分证实，但由于数据分散和分析工具有限，全面追踪大面积地区的长期时空趋势受到了阻碍。本研究进行了一项前所未有的广度分析，根据巴西5570个城市14年（2010 - 2023年）期间登革热和基孔肯雅热的发病数据，估算易感 - 感染 - 康复传播参数。我们描述了为估算这些参数而开发的Episcanner计算流程，生成了一个可重复使用的数据集，该数据集刻画了这一时期巴西发生的所有登革热和基孔肯雅热疫情。分析揭示了气候与疫情关系的新见解：我们确定了巴西各地虫媒病毒疾病发病率的不同地理和时间模式，突出了温度和降水等气候因素如何影响登革热和基孔肯雅热疫情的时间和强度。创新的Episcanner工具使研究人员和公共卫生官员能够详细探索这些模式，促进有针对性的干预措施和风险评估。这项研究提供了探索登革热和基孔肯雅热疫情主要特征及其与全球温度波动影响相关的地理特异性的可能性，例如厄尔尼诺 - 南方涛动指数所反映的那些影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2449/12115816/29f093062b74/rsos.241261.f009.jpg
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