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|Title:||An analysis of the influence of the local effects of climatic and hydrological factors affecting new malaria cases in riverine areas along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil|
|Authors:||Coutinho, Paulo Eduardo Guzzo|
Cândido, Luiz Antônio
Tadei, Wanderli Pedro
Silva Junior, Urbano Lopes da
Correa, Honorly Katia Mestre
Rio Negro [south America]
|metadata.dc.publisher.journal:||Environmental Monitoring and Assessment|
|metadata.dc.relation.ispartof:||Volume 190, Número 5|
|Abstract:||A study was conducted at three sampling regions along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil. The aim was to determine the influence of the local effects of climatic and hydrological variables on new malaria cases. Data was gathered on the river level, precipitation, air temperature, and the number of new cases of autochthonous malaria between January 2003 and December 2013. Monthly averages, time series decompositions, cross-correlations, and multiple regressions revealed different relationships at each location. The sampling region in the upper Rio Negro indicated no statistically significant results. However, monthly averages suggest that precipitation and air temperature correlate positively with the occurrence of new cases of malaria. In the mid Rio Negro and Puraquequara Lake, the river level positively correlated, and temperature negatively correlated with new transmissions, while precipitation correlated negatively in the mid Rio Negro and positively on the lake. Overall, the river level is a key variable affecting the formation of breeding sites, while precipitation may either develop or damage them. A negative temperature correlation is associated with the occurrence of new annual post-peak cases of malaria, when the monthly average exceeds 28.5 °C. This suggests that several factors contribute to the occurrence of new malaria cases as higher temperatures are reached at the same time as precipitation and the river levels are lowest. Differences between signals and correlation lags indicate that local characteristics have an impact on how different variables influence the disease vector’s life cycle, pathogens, and consequently, new cases of malaria. © 2018, Springer International Publishing AG, part of Springer Nature.|
|Appears in Collections:||Artigos|
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