Burgos Fátima, Saavedra-Samillán Milagros, Bustamante-Chauca Pershing, Vera-Ponce Victor, Gutierrez Carmen, Rascón Jesús, Tapia-Limonchi Rafael, Chenet Stella M
Instituto de Investigación de Enfermedades Tropicales (IET), Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas, Peru.
Dirección Regional de Salud de Amazonas (DIRESA), Chachapoyas, Peru.
Acta Trop. 2025 Jul;267:107659. doi: 10.1016/j.actatropica.2025.107659. Epub 2025 May 17.
Peru experienced its most severe dengue outbreak on record, with the Amazonas region reporting 3502 dengue cases in 2022. This study aimed to examine the distribution of dengue cases across Amazonas from 2000 to 2023, while exploring the influence of climate factors. Monthly incidence was aggregated into four consecutive six-year blocks to identify incidence trends, and space-time scan statistics identified high and low-risk clusters. Spearman correlations with distributed lags (0 - 2 months) evaluated the association between incidence and climatic data from NASA-POWER, stratified by season. Until 2005, transmission was restricted to Bagua and Utcubamba provinces. A major increase in cases from 2008 to 2011 was recorded in the endemic provinces of Condorcanqui, Bagua, and Utcubamba forming a high-risk cluster in the latter two (LLR = 287.88, RR = 3.79). After a decrease during 2012-2017, incidence resurged creating a Bagua mega-cluster (LLR = 1112.28, RR = 3.20) and expanding to Jazán and Balsas districts, with the latter characterized by lower temperatures compared to endemic areas. Significant correlations were found between climatic variables and incidence. Specifically, minimum temperature significantly influenced dengue dynamics and expansion into Balsas (rho = 0.23, P = 0.03), with a two-month lag during the wet season. These findings underscore the importance of climate monitoring in guiding public health interventions. However, a comprehensive approach that considers environmental and behavioral factors, tailored to the specific conditions of each province, is essential for effective control of future outbreaks.
秘鲁经历了有记录以来最严重的登革热疫情,2022年亚马孙地区报告了3502例登革热病例。本研究旨在调查2000年至2023年期间亚马孙地区登革热病例的分布情况,同时探讨气候因素的影响。将月发病率汇总为四个连续的六年区间,以确定发病率趋势,时空扫描统计确定高风险和低风险聚集区。通过Spearman分布滞后相关性(0 - 2个月)评估发病率与美国国家航空航天局动力气象数据中心(NASA-POWER)气候数据之间的关联,并按季节分层。直到2005年,传播仅限于巴瓜省和乌图班巴省。2008年至2011年,康多坎基、巴瓜和乌图班巴等流行省份的病例大幅增加,后两个省份形成了一个高风险聚集区(对数似然比 = 287.88,相对风险 = 3.79)。在2012年至2017年有所下降之后,发病率再次上升,形成了一个巴瓜超级聚集区(对数似然比 = 1112.28,相对风险 = 3.20),并扩展到哈赞和巴尔萨斯地区,后者的温度低于流行地区。发现气候变量与发病率之间存在显著相关性。具体而言,最低温度显著影响登革热动态以及向巴尔萨斯地区的扩散(斯皮尔曼等级相关系数 = 0.23,P = 0.03),在雨季有两个月的滞后。这些发现强调了气候监测在指导公共卫生干预措施方面的重要性。然而,采取综合方法,考虑环境和行为因素,并根据每个省份的具体情况量身定制,对于有效控制未来疫情至关重要。