Stepwise Markov model: a good method for forecasting mechanical ventilator crisis in COVID-19 pandemic

Q3 Mathematics Epidemiologic Methods Pub Date : 2021-02-01 DOI:10.1515/em-2020-0021
P. Olmos, G. Borzone
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引用次数: 1

Abstract

Abstract Objectives One important variable influencing day-to-day decisions in COVID-19 pandemic has been an impending shortage of mechanical ventilators due to the large number of people that become infected with the virus due to its high contagiousness. We developed a stepwise Markov model (a) to make a short-term prediction of the number of patients on ventilator, and (b) to determine a possible date for a ventilator crisis. Methods Starting with the exponential curve of new cases in the previous 14 days, we calculated a Markov model every 5 days thereafter, resulting in a daily estimate of patients on ventilator for the following 25 days, which we compared with the daily number of devices in use to predict a date for ventilator crisis. Results During the modeled period, the observed and predicted Markov curves of patients on ventilator were very similar, a finding confirmed by both linear regression (r=0.984; p<0.0001) and the near coincidence with the identity line. Our model estimated ventilator shortage in Chile for June 1st, if the number of devices had remained stable. However, the crisis did not occur due to acquisition of new ventilators by the Ministry of Health. Conclusions In Chile as in many other countries experiencing several asynchronous local peaks of COVID-19, the stepwise Markov model could become a useful tool for predicting the date of mechanical ventilator crisis. We propose that our model could help health authorities to: (a) establish a better ventilator distribution strategy and (b) be ready to reinstate restrictions only when necessary so as not to paralyze the economy as much.
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逐步马尔可夫模型:预测COVID-19大流行中机械呼吸机危机的好方法
摘要目的影响COVID-19大流行日常决策的一个重要变量是,由于病毒的高传染性导致大量人群感染,机械呼吸机即将短缺。我们开发了一个逐步马尔可夫模型(a)来对使用呼吸机的患者数量进行短期预测,(b)来确定呼吸机危机的可能日期。方法从前14天新增病例的指数曲线出发,每隔5天计算一个马尔可夫模型,得出未来25天每天使用呼吸机的患者数量,并将其与每天使用的设备数量进行比较,预测呼吸机危机发生的日期。结果在建模期间,观察到的呼吸机患者的马尔可夫曲线与预测的马尔可夫曲线非常相似,线性回归证实了这一结果(r=0.984;P <0.0001),与同一性线接近重合。我们的模型估计,如果设备数量保持稳定,6月1日智利的呼吸机短缺。然而,危机的发生并不是因为卫生部购置了新的呼吸机。在智利和其他许多经历了几次非同步局部COVID-19高峰的国家,逐步马尔可夫模型可能成为预测机械呼吸机危机日期的有用工具。我们建议,我们的模型可以帮助卫生当局:(a)建立更好的呼吸机分配策略,(b)准备在必要时恢复限制,以免严重瘫痪经济。
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来源期刊
Epidemiologic Methods
Epidemiologic Methods Mathematics-Applied Mathematics
CiteScore
2.10
自引率
0.00%
发文量
7
期刊介绍: Epidemiologic Methods (EM) seeks contributions comparable to those of the leading epidemiologic journals, but also invites papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate methodology are strongly encouraged but not required. Topics. genetic epidemiology, infectious disease, pharmaco-epidemiology, ecologic studies, environmental exposures, screening, surveillance, social networks, comparative effectiveness, statistical modeling, causal inference, measurement error, study design, meta-analysis
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