During the first two decades of the 21st century, Brazil carried out massive public investments on infrastructure projects, such as large hydropower dams, with potential impact on population health. Here we characterize local malaria transmission and its potential spread during the construction of three large hydropower dams in the Brazilian Amazon. We focus on Porto Velho (PVH), in Rondônia state, where the Santo Antônio and Jirau dams were built (2008-2013), and Altamira region (ATM), in Pará state, where the construction of the Belo Monte dam took place (2011-2016). Analyzed data cover 4 years before, 6 years during, and 4 years after each dam construction. In total, we utilized malaria case notifications entered into the electronic malaria notification system of the Ministry of Health of Brazil between January 2004 and December 2020 (n = 39,977,167 malaria notifications). First, we used Interrupted Time-Series Analysis (ITSA) to assess temporal changes in malaria notifications in the study sites. Then, we conducted a space-time cluster analysis to investigate the potential of malaria spread from the study sites (sources) to elsewhere (sinks). Finally, we present the sociodemographic characteristics of exported cases over time using multivariate logistic regressions. Our results show that there was no upsurge in malaria cases in the study sites and exported cases did not trigger outbreaks in other localities. Exported malaria infections originating from PVH and ATM were typically found in working age literate males involved in mining, farming or traveling. We suggest that efficient control measures, such as ensuring timely diagnosis and treatment; fostering integrated vector control; promoting health education; and prevention, detection and containment of outbreaks, if properly implemented and sustained, may prevent local and introduced malaria outbreaks during and after hydropower dam construction in the Amazon.
Copyright: © 2023 Johansen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.