Mizumoto Kenji, Endo Akira, Chowell Gerardo, Miyamatsu Yuichiro, Saitoh Masaya, Nishiura Hiroshi
Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo, 1538902, Japan.
Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 1130033, Japan.
BMC Med. 2015 Sep 30;13:228. doi: 10.1186/s12916-015-0468-3.
An outbreak of the Middle East respiratory syndrome (MERS), comprising 185 cases linked to healthcare facilities, occurred in the Republic of Korea from May to July 2015. Owing to the nosocomial nature of the outbreak, it is particularly important to gain a better understanding of the epidemiological determinants characterizing the risk of MERS death in order to predict the heterogeneous risk of death in medical settings.
We have devised a novel statistical model that identifies the risk of MERS death during the outbreak in real time. While accounting for the time delay from illness onset to death, risk factors for death were identified using a linear predictor tied to a logit model. We employ this approach to (1) quantify the risks of death and (2) characterize the temporal evolution of the case fatality ratio (CFR) as case ascertainment greatly improved during the course of the outbreak.
Senior persons aged 60 years or over were found to be 9.3 times (95% confidence interval (CI), 5.3-16.9) more likely to die compared to younger MERS cases. Patients under treatment were at a 7.8-fold (95% CI, 4.0-16.7) significantly higher risk of death compared to other MERS cases. The CFR among patients aged 60 years or older under treatment was estimated at 48.2% (95% CI, 35.2-61.3) as of July 31, 2015, while the CFR among other cases was estimated to lie below 15%. From June 6, 2015, onwards, the CFR declined 0.3-fold (95% CI, 0.1-1.1) compared to the earlier epidemic period, which may perhaps reflect enhanced case ascertainment following major contact tracing efforts.
The risk of MERS death was significantly associated with older age as well as treatment for underlying diseases after explicitly adjusting for the delay between illness onset and death. Because MERS outbreaks are greatly amplified in the healthcare setting, enhanced infection control practices in medical facilities should strive to shield risk groups from MERS exposure.
2015年5月至7月,韩国爆发中东呼吸综合征(MERS),185例病例与医疗机构有关。鉴于此次疫情的医院感染性质,为预测医疗机构中死亡的异质性风险,更好地了解表征MERS死亡风险的流行病学决定因素尤为重要。
我们设计了一种新型统计模型,可实时识别疫情期间MERS死亡风险。在考虑从发病到死亡的时间延迟的同时,使用与logit模型相关的线性预测器确定死亡风险因素。我们采用这种方法来(1)量化死亡风险,以及(2)描述病死率(CFR)的时间演变,因为在疫情期间病例确诊率大幅提高。
发现60岁及以上的老年人死亡可能性比年轻的MERS病例高9.3倍(95%置信区间(CI),5.3 - 16.9)。正在接受治疗的患者死亡风险比其他MERS病例高7.8倍(95%CI,4.0 - 16.7),具有显著差异。截至2015年7月31日,正在接受治疗的60岁及以上患者的CFR估计为48.2%(95%CI,35.2 - 61.3),而其他病例的CFR估计低于15%。从2015年6月6日起,与早期流行期相比,CFR下降了0.3倍(95%CI,0.1 - 1.1),这可能反映了在大规模接触者追踪工作后病例确诊率的提高。
在明确调整发病与死亡之间的延迟后,MERS死亡风险与年龄较大以及基础疾病治疗显著相关。由于MERS疫情在医疗机构中会大幅扩大,医疗机构加强感染控制措施应努力保护风险群体免受MERS感染。