National Institute of Women, Children and Adolescents Health Fernandes Figueira, Department of Clinical Research, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
PLoS One. 2018 Sep 4;13(9):e0202832. doi: 10.1371/journal.pone.0202832. eCollection 2018.
Influenza constitutes a major challenge to world health authorities due to high transmissibility and the capacity to generate large epidemics. This study aimed to characterize the diffusion process of influenza A (H1N1) by identifying the starting point of the epidemic as well as climatic and sociodemographic factors associated with the occurrence and intensity of transmission of the disease. The study was carried out in the Brazilian state of Paraná, where H1N1 caused the largest impact. The units of spatial and temporal analysis were the municipality of residence of the cases and the epidemiological weeks of the year 2009, respectively. Under the Bayesian paradigm, parametric inference was performed through a two-part spatiotemporal model and the integrated nested Laplace approximation (INLA) algorithm. We identified the most likely starting points through the effective distance measure based on mobility networks. The proposed estimation methodology allowed for rapid and efficient implementation of the spatiotemporal model, and provided evidence of different patterns for chance of occurrence and risk of influenza throughout the epidemiological weeks. The results indicate the capital city of Curitiba as the probable starting point, and showed that the interventions that focus on municipalities with greater migration and density of people, especially those with higher Human Development Indexes (HDIs) and the presence of municipal air and road transport, could play an important role in mitigation of effects of future influenza pandemics on public health. These results provide important information on the process of introduction and spread of influenza, and could contribute to the identification of priority areas for surveillance as well as establishment of strategic measures for disease prevention and control. The proposed model also allows identification of epidemiological weeks with high chance of influenza occurrence, which can be used as a reference criterion for creating an immunization campaign schedule.
流感对世界卫生当局构成了重大挑战,因为它具有高度的传染性和产生大流行的能力。本研究旨在通过确定流感 A(H1N1)的流行起点以及与疾病发生和传播强度相关的气候和社会人口因素,来描述流感 A(H1N1)的传播过程。该研究在巴西巴拉那州进行,该州的 H1N1 造成了最大的影响。空间和时间分析的单位分别是病例的居住市和 2009 年的流行病学周。在贝叶斯范式下,通过两部分时空模型和集成嵌套拉普拉斯近似(INLA)算法进行参数推断。我们通过基于移动网络的有效距离度量来识别最可能的起点。所提出的估计方法允许快速有效地实施时空模型,并提供了在整个流行病学周内流感发生概率和风险的不同模式的证据。结果表明,库里蒂巴市可能是最初的爆发点,并表明关注移民和人口密度较大的城市的干预措施,特别是那些人类发展指数(HDI)较高、存在市际航空和公路运输的城市,可能在减轻未来流感大流行对公共卫生的影响方面发挥重要作用。这些结果提供了关于流感传入和传播过程的重要信息,并有助于确定监测的优先领域以及制定疾病预防和控制的战略措施。所提出的模型还可以识别出流感发生概率高的流行病学周,这可以作为制定免疫接种计划时间表的参考标准。