Oswaldo Cruz Foundation - FIOCRUZ. Av. Brasil, 4036/10° Andar, Prédio da Expansão, Manguinhos, 21040-361, Rio de Janeiro, Brazil; Production Engineering Program, Federal University of Rio de Janeiro - COPPE/UFRJ. Av. Horácio Macedo, 2030 - Bloco G - Sala 207 - Centro de Tecnologia, Cidade Universitária - Ilha do Fundão, 21941-914, Rio de Janeiro, Brazil.
Oswaldo Cruz Foundation - FIOCRUZ. Av. Brasil, 4036/10° Andar, Prédio da Expansão, Manguinhos, 21040-361, Rio de Janeiro, Brazil.
Appl Ergon. 2022 Feb;99:103632. doi: 10.1016/j.apergo.2021.103632. Epub 2021 Oct 30.
As COVID-19 spread across Brazil, it quickly reached remote regions including Amazon's ultra-peripheral locations where patient transportation through rivers is added to the list of obstacles to overcome. This article analyses the pandemic's effects in the access of riverine communities to the prehospital emergency healthcare system in the Brazilian Upper Amazon River region. To do so, we present two studies that by using a Resilience Engineering approach aimed to predict the functioning of the Brazilian Mobile Emergency Medical Service (SAMU) for riverside and coastal areas during the COVID-19 pandemic, based on the normal system functioning. Study I, carried out before the pandemic, applied ethnographic methods for data collection and the Functional Resonance Analysis Method - FRAM for data analysis in order to develop a model of the mobile emergency care in the region during typical conditions of operation. Study II then estimated how changes in variability dynamics would alter system functioning during the pandemic, arriving at three trends that could lead the service to collapse. Finally, the accuracy of predictions is discussed after the pandemic first peaked in the region. Findings reveal that relatively small changes in variability dynamics can deliver strong implications to operating care and safety of expeditions aboard water ambulances. Also, important elements that add to the resilient capabilities of the system are extra-organizational, and thus during the pandemic safety became jeopardized as informal support networks grew fragile. Using FRAM for modelling regular operation enabled prospective scenario analysis that accurately predicted disruptions in providing emergency care to riverine population.
随着 COVID-19 在巴西的传播，它迅速蔓延到包括亚马逊偏远地区在内的地区，在这些地区，通过河流运送病人成为克服的障碍之一。本文分析了大流行对巴西亚马逊河流域沿河社区获得院前急诊医疗系统的影响。为此，我们提出了两项研究，这两项研究通过使用韧性工程方法，旨在预测在 COVID-19 大流行期间，基于正常系统运行，河边和沿海地区的巴西流动紧急医疗服务（SAMU）的运作情况。第一项研究在大流行之前进行，采用民族志方法收集数据，并采用功能共振分析方法（FRAM）进行数据分析，以便在典型的操作条件下为该地区的流动紧急护理建立模型。然后，第二项研究估计了在大流行期间，变异性动态的变化如何改变系统的运作，并得出了可能导致服务崩溃的三种趋势。最后，在该地区大流行首次达到高峰后，讨论了预测的准确性。研究结果表明，变异性动态的相对较小变化会对水上救护车的运营护理和安全产生重大影响。此外，增加系统弹性能力的重要因素是组织外的，因此在大流行期间，随着非正式支持网络变得脆弱，安全受到威胁。使用 FRAM 对常规运营进行建模，可以进行前瞻性情景分析，准确预测向沿河地区提供紧急护理的中断情况。
