Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA 30602, USA.
Epidemics. 2009 Sep;1(3):185-95. doi: 10.1016/j.epidem.2009.09.001.
Influenza infections often predispose individuals to consecutive bacterial infections. Both during seasonal and pandemic influenza outbreaks, morbidity and mortality due to secondary bacterial infections can be substantial. With the help of a mathematical model, we investigate the potential impact of such bacterial infections during an influenza pandemic, and we analyze how antiviral and antibacterial treatment or prophylaxis affect morbidity and mortality. We consider different scenarios for the spread of bacteria, the emergence of antiviral resistance, and different levels of severity for influenza infections (1918-like and 2009-like). We find that while antibacterial intervention strategies are unlikely to play an important role in reducing the overall number of cases, such interventions can lead to a significant reduction in mortality and in the number of bacterial infections. Antibacterial interventions become even more important if one considers the--very likely--scenario that during a pandemic outbreak, influenza strains resistant to antivirals emerge. Overall, our study suggests that pandemic preparedness plans should consider intervention strategies based on antibacterial treatment or prophylaxis through drugs or vaccines as part of the overall control strategy. A major caveat for our results is the lack of data that would allow precise estimation of many of the model parameters. As our results show, this leads to very large uncertainty in model outcomes. As we discuss, precise assessment of the impact of antibacterial strategies during an influenza pandemic will require the collection of further data to better estimate key parameters, especially those related to the bacterial infections and the impact of antibacterial intervention strategies.
流感感染通常使个体易患连续的细菌感染。在季节性和大流行性流感爆发期间,继发细菌感染导致的发病率和死亡率可能相当高。借助数学模型,我们研究了流感大流行期间此类细菌感染的潜在影响,并分析了抗病毒和抗菌治疗或预防如何影响发病率和死亡率。我们考虑了细菌传播的不同情况、抗病毒药物耐药性的出现以及流感感染(1918 型和 2009 型)的不同严重程度。我们发现,虽然抗菌干预策略不太可能在减少总病例数方面发挥重要作用,但此类干预措施可显著降低死亡率和细菌感染数量。如果考虑到(极有可能出现的)在大流行爆发期间出现对抗病毒药物耐药的流感株这一情景,抗菌干预措施就变得更加重要。总体而言,我们的研究表明,大流行准备计划应考虑基于抗菌治疗或预防的干预策略,包括通过药物或疫苗进行治疗或预防,作为整体控制策略的一部分。我们研究结果的一个主要警告是缺乏数据,这使得模型结果存在很大的不确定性。正如我们所展示的,这导致模型结果存在非常大的不确定性。正如我们所讨论的,要准确评估流感大流行期间抗菌策略的影响,需要收集更多数据以更好地估计关键参数,特别是与细菌感染和抗菌干预策略影响相关的参数。