Mwanja Herman, Waswa J P, Kiggundu Reuben, Mackline Hope, Bulwadda Daniel, Byonanebye Dathan M, Kambugu Andrew, Kakooza Francis
Centres for Antimicrobial Optimization Network (CAMO-Net), Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda.
Management Sciences for Health, Kampala, Uganda.
Front Microbiol. 2024 Oct 21;15:1493511. doi: 10.3389/fmicb.2024.1493511. eCollection 2024.
Globally, Healthcare-associated infections (HCAIs) pose a significant threat to patient safety and healthcare systems. In low- and middle-income countries (LMICs), the lack of adequate resources to manage HCAIs, as well as the weak healthcare system, further exacerbate the burden of these infections. Traditional surveillance methods that rely on laboratory tests are cost-intensive and impractical in these settings, leading to ineffective monitoring and delayed management of HCAIs. The rates of HCAIs in resource-limited settings have not been well established for most LMICs, despite their negative consequences. This is partly due to costs associated with surveillance systems. Syndromic surveillance, a part of active surveillance, focuses on clinical observations and symptoms rather than laboratory confirmation for HCAI detection. Its cost-effectiveness and efficiency make it a beneficial approach for monitoring HCAIs in LMICs. It provides for early warning capabilities, enabling timely identification and response to potential HCAI outbreaks. Syndromic surveillance is highly sensitive and this helps balance the challenge of low sensitivity of laboratory-based surveillance systems. If syndromic surveillance is used hand-in-hand with laboratory-based surveillance systems, it will greatly contribute to establishing the true burden of HAIs in resource-limited settings. Additionally, its flexibility allows for adaptation to different healthcare settings and integration into existing health information systems, facilitating data-driven decision-making and resource allocation. Such a system would augment the event-based surveillance system that is based on alerts and rumours for early detection of events of outbreak potential. If well streamlined and targeted, to monitor priority HCAIs such as surgical site infections, hospital-acquired pneumonia, diarrheal illnesses, the cost and burden of the effects from these infections could be reduced. This approach would offer early detection capabilities and could be expanded into nationwide HCAI surveillance networks with standardised data collection, healthcare worker training, real-time reporting mechanisms, stakeholder collaboration, and continuous monitoring and evaluation. Syndromic surveillance offers a promising strategy for combating HCAIs in LMICs. It provides early warning capabilities, conserves resources, and enhances patient safety. Effective implementation depends on strategic interventions, stakeholder collaboration, and ongoing monitoring and evaluation to ensure sustained effectiveness in HCAI detection and response.
在全球范围内,医疗保健相关感染(HCAIs)对患者安全和医疗保健系统构成重大威胁。在低收入和中等收入国家(LMICs),缺乏管理HCAIs的充足资源以及薄弱的医疗保健系统,进一步加重了这些感染的负担。依赖实验室检测的传统监测方法成本高昂且在这些环境中不切实际,导致对HCAIs的监测无效以及管理延迟。尽管资源有限环境中的HCAIs发生率会产生负面影响,但大多数低收入和中等收入国家尚未很好地确定这些发生率。部分原因是与监测系统相关的成本。症候群监测作为主动监测的一部分,侧重于临床观察和症状而非实验室确认来检测HCAI。其成本效益和效率使其成为低收入和中等收入国家监测HCAIs的有益方法。它具备早期预警能力,能够及时识别并应对潜在的HCAI暴发。症候群监测高度敏感,这有助于平衡基于实验室的监测系统敏感性较低的挑战。如果将症候群监测与基于实验室的监测系统结合使用,将极大有助于确定资源有限环境中HAIs的真实负担。此外,其灵活性允许适应不同的医疗保健环境并整合到现有的健康信息系统中,促进数据驱动的决策制定和资源分配。这样的系统将增强基于警报和谣言的基于事件的监测系统,以便早期发现具有暴发潜力的事件。如果进行了良好的精简和针对性设置,以监测诸如手术部位感染、医院获得性肺炎、腹泻病等重点HCAIs,这些感染所造成影响的成本和负担可能会降低。这种方法将提供早期检测能力,并可扩展为具有标准化数据收集、医护人员培训、实时报告机制、利益相关者协作以及持续监测和评估的全国性HCAI监测网络。症候群监测为低收入和中等收入国家抗击HCAIs提供了一个有前景的策略。它提供早期预警能力,节省资源并提高患者安全性。有效的实施取决于战略干预、利益相关者协作以及持续的监测和评估,以确保在HCAI检测和应对方面持续有效。