Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach.

Q1 Mathematics
Zachary McCarthy, Safia Athar, Mahnaz Alavinejad, Christopher Chow, Iain Moyles, Kyeongah Nah, Jude D Kong, Nishant Agrawal, Ahmed Jaber, Laura Keane, Sam Liu, Myles Nahirniak, Danielle St Jean, Razvan Romanescu, Jessica Stockdale, Bruce T Seet, Laurent Coudeville, Edward Thommes, Anne-Frieda Taurel, Jason Lee, Thomas Shin, Julien Arino, Jane Heffernan, Ayman Chit, Jianhong Wu
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引用次数: 8

Abstract

Background: Seasonal influenza poses a significant public health and economic burden, associated with the outcome of infection and resulting complications. The true burden of the disease is difficult to capture due to the wide range of presentation, from asymptomatic cases to non-respiratory complications such as cardiovascular events, and its seasonal variability. An understanding of the magnitude of the true annual incidence of influenza is important to support prevention and control policy development and to evaluate the impact of preventative measures such as vaccination.

Methods: We use a dynamic disease transmission model, laboratory-confirmed influenza surveillance data, and randomized-controlled trial (RCT) data to quantify the underestimation factor, expansion factor, and symptomatic influenza illnesses in the US and Canada during the 2011-2012 and 2012-2013 influenza seasons.

Results: Based on 2 case definitions, we estimate between 0.42-3.2% and 0.33-1.2% of symptomatic influenza illnesses were laboratory-confirmed in Canada during the 2011-2012 and 2012-2013 seasons, respectively. In the US, we estimate between 0.08-0.61% and 0.07-0.33% of symptomatic influenza illnesses were laboratory-confirmed in the 2011-2012 and 2012-2013 seasons, respectively. We estimated the symptomatic influenza illnesses in Canada to be 0.32-2.4 million in 2011-2012 and 1.8-8.2 million in 2012-2013. In the US, we estimate the number of symptomatic influenza illnesses to be 4.4-34 million in 2011-2012 and 23-102 million in 2012-2013.

Conclusions: We illustrate that monitoring a representative group within a population may aid in effectively modelling the transmission of infectious diseases such as influenza. In particular, the utilization of RCTs in models may enhance the accuracy of epidemiological parameter estimation.

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量化季节性流感的年发病率和低估:建模方法。
背景:季节性流感与感染的结果和由此产生的并发症有关,构成重大的公共卫生和经济负担。由于表现形式广泛,从无症状病例到心血管事件等非呼吸系统并发症,以及其季节性变化,因此难以掌握该病的真正负担。了解流感每年真实发病率的大小,对于支持预防和控制政策的制定以及评估疫苗接种等预防措施的影响非常重要。方法:采用动态疾病传播模型、实验室确认的流感监测数据和随机对照试验(RCT)数据,量化2011-2012年和2012-2013年流感季节美国和加拿大的低估因子、扩大因子和有症状的流感疾病。结果:根据两种病例定义,我们估计2011-2012年和2012-2013年加拿大实验室确诊的症状性流感疾病分别为0.42-3.2%和0.33-1.2%。在美国,我们估计在2011-2012年和2012-2013年,分别有0.08-0.61%和0.07-0.33%的有症状的流感疾病是实验室确诊的。我们估计2011-2012年加拿大有症状的流感患者为32- 240万,2012-2013年为180 - 820万。在美国,我们估计2011-2012年有症状的流感疾病的数量为440 - 3400万,2012-2013年为2300 - 1.02亿。结论:我们表明,监测人口中的代表性群体可能有助于有效地模拟传染病(如流感)的传播。特别是,在模型中使用随机对照试验可以提高流行病学参数估计的准确性。
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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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