Universidade de São Paulo, Faculdade de Medicina, Departamento de Moléstias Infecciosas e Parasitárias, São Paulo, São Paulo, Brazil.
Universidade de São Paulo, Faculdade de Saúde Pública, Departamento de Epidemiologia, São Paulo, São Paulo, Brazil.
Rev Inst Med Trop Sao Paulo. 2021 Sep 27;63:e70. doi: 10.1590/S1678-9946202163070. eCollection 2021.
Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. "Hot spots" are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil.
登革热在全球范围内再次出现，但这种新出现的原因尚未完全了解。我们的目标是报告巴西人口最多的州之一的登革热发病率，并使用包括地理气候、人口和社会经济特征在内的空间和时空年度模型评估高风险地区。在巴西东南部的圣保罗州进行了一项具有空间和时间成分的生态研究，时间范围为 2007 年 1 月 1 日至 2019 年 12 月 31 日。在考虑到各城市为分析单位的情况下，使用贝叶斯背景下的集成嵌套拉普拉斯近似法，计算了登革热病例的粗率和贝叶斯经验率，并考虑了标准化发病率比（SIR）。在研究期间共报告了 2027142 例登革热病例。空间模型根据 SIR 值将城市分配到四个组中：（I）SIR<0.8；（II）SIR 0.8<1.2；（III）SIR 1.2<2.0 和 SIR>2.0 确定了登革热暴发风险较高的城市。主题地图显示了“热点”。发现 SIR 与两个气候变量、两个人口变量和一个社会经济变量之间存在显著相关性。在时空模型中未发现显著相关性。登革热的发病率每年都呈现出不稳定和不可预测的变化。登革热的最高发病率集中在地理集群中，这些集群的表面压力、降雨量和海拔较低，但也集中在城市化程度较高和社会经济条件较好的城市。然而，气候特征的年际变化并不影响巴西东南部登革热的年度流行模式。
