The Effect of Individual Movements and Interventions on the Spread of Influenza in Long-Term Care Facilities
The Effect of Individual Movements and Interventions on the Spread of Influenza in Long-Term Care Facilities
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DOI：
10.1177/0272989x17708564
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发表时间：
2017-11-01
影响因子：
3.6
通讯作者：
Moghadas, Seyed M.
中科院分区：
文献类型：
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作者：
Najafi, Mehdi;Laskowski, Marek;Moghadas, Seyed M.
背景医院感染流感对长期护理机构（LTCF）的居民构成严重风险。Objective.我们试图评估居民和工作人员的流动和接触模式对LTCF中流感控制的各种干预策略结果的影响。方法.我们收集了加拿大最大的退伍军人LTCF的接触频率数据，通过招募居民和工作人员参加一项研究，通过无线标签和信号接收器跟踪他们的运动。我们分析了数据，并将其拟合到基于代理的流感感染模拟模型中，并进行了蒙特-卡罗模拟，以评估在标准（基线）感染控制实践（即，居民和工作人员接种疫苗，加上有症状感染的居民的抗病毒治疗）。结果我们将模型校准为基线场景的20%、40%和60%的攻击率。对于数据驱动的运动，我们发现，当基线策略与所有居民在爆发期间的抗病毒预防相结合时，发病率下降最大（12.5%至27%; ANOVA P < 0.001）。隔离有症状感染的居民对居民的发病率影响很小或没有影响（2.3%至4.2%;方差分析P > 0.2）。相比之下，用随机移动参数化模型产生了不同的结果，表明通过患者隔离实现了最高的益处（69.6%至79.6%; ANOVA P < 0.001），而预防的额外益处在减少累积感染数量方面可以忽略不计。结论.我们的研究揭示了LTCF内高度结构化的接触和运动模式。在决策分析方法中，考虑到这种结构而不是假设随机性，可能会导致实质上不同的预测。
Background. Nosocomial influenza poses a serious risk among residents of long-term care facilities (LTCFs). Objective. We sought to evaluate the effect of resident and staff movements and contact patterns on the outcomes of various intervention strategies for influenza control in an LTCF. Methods. We collected contact frequency data in Canada's largest veterans' LTCF by enroling residents and staff into a study that tracked their movements through wireless tags and signal receivers. We analyzed and fitted the data to an agent-based simulation model of influenza infection, and performed Monte-Carlo simulations to evaluate the benefit of antiviral prophylaxis and patient isolation added to standard (baseline) infection control practice (i.e., vaccination of residents and staff, plus antiviral treatment of residents with symptomatic infection). Results. We calibrated the model to attack rates of 20%, 40%, and 60% for the baseline scenario. For data-driven movements, we found that the largest reduction in attack rates (12.5% to 27%; ANOVA P < 0.001) was achieved when the baseline strategy was combined with antiviral prophylaxis for all residents for the duration of the outbreak. Isolation of residents with symptomatic infection resulted in little or no effect on the attack rates (2.3% to 4.2%; ANOVA P > 0.2) among residents. In contrast, parameterizing the model with random movements yielded different results, suggesting that the highest benefit was achieved through patient isolation (69.6% to 79.6%; ANOVA P < 0.001) while the additional benefit of prophylaxis was negligible in reducing the cumulative number of infections. Conclusions. Our study revealed a highly structured contact and movement patterns within the LTCF. Accounting for this structureinstead of assuming randomnessin decision analytic methods can result in substantially different predictions.