Instituto Nacional de Pesquisas da Amazônia, Manaus, Brasil.
Universidade Federal do Amazonas, Manaus, Brasil.
Cad Saude Publica. 2019 Feb 11;35(2):e00020218. doi: 10.1590/0102-311X00020218.
Understanding the relations between rainfall and river water levels and malaria cases can provide important clues on modulation of the disease in the context of local climatic variability. In order to demonstrate how these relations can vary in the same endemic space, a coherence and wavelet phase analysis was performed between environmental and epidemiological variables from 2003 to 2010 for 8 municipalities (counties) in the state of Amazonas, Brazil (Barcelos, Borba, Canutama, Carauari, Coari, Eirunepé, Humaitá, and São Gabriel da Cachoeira). The results suggest significant coherences, mainly on the scale of annual variability, but scales of less than 1 year and of 2 years were also found. The analyses show that malaria cases display a peak at approximately 1 and a half months before or after peak rainfall and on average 1-4 months after peak river water levels in most of the municipalities studied. Each environmental variable displayed distinct local behavior in time and in space, suggesting that other local variables (e.g. topography) may control environmental conditions, favoring different patterns in each municipality. However, when the analyses were performed jointly it was possible to show a non-random order in these relations. Although environmental and climatic factors indicate a certain influence on malaria dynamics, surveillance, prevention, and control issues should not be overlooked, meaning that government public health interventions can mask possible relations with local hydrological and climatic conditions.
理解降雨量和河水位与疟疾之间的关系，可以为在当地气候多变的情况下控制疾病提供重要线索。为了展示在同一流行地区这些关系如何发生变化，对巴西亚马逊州 8 个市（县）（巴塞洛斯、博尔巴、卡努马塔、卡劳里、科阿里、埃鲁内佩、伊乌迈塔和圣加布里埃尔达卡乔埃拉）的环境和流行病学变量，从 2003 年至 2010 年进行了相干性和小波相位分析。结果表明，在年际变化尺度上，存在显著的相干性，但也存在不到 1 年和 2 年的尺度。分析表明，在大多数研究的市（县）中，疟疾病例的峰值出现在降雨量峰值前或后约 1 个半月和河水位峰值后 1 至 4 个月。每个环境变量在时间和空间上都表现出不同的局部行为，表明其他局部变量（如地形）可能控制环境条件，导致每个市（县）出现不同的模式。然而，当联合进行分析时，可以显示这些关系具有非随机的顺序。尽管环境和气候因素表明对疟疾动态有一定影响，但不应忽视监测、预防和控制问题，这意味着政府公共卫生干预措施可能掩盖了与当地水文和气候条件的可能关系。
