论文标题
CovidHunter：Covid-19通过季节性吸引建模的大流行波预测和缓解
COVIDHunter: COVID-19 pandemic wave prediction and mitigation via seasonality-aware modeling
论文作者
论文摘要
共同检测和隔离Covid-19患者对于成功实施缓解策略并最终遏制疾病扩散至关重要。在每个国家 /地区进行的每日共同19测试数量有限，模拟Covid-19的扩散以及当前每种缓解策略的潜在效果以及管理医疗保健系统和指导决策者的最有效方法之一。我们介绍了Covidhunter，这是一种灵活而准确的Covid-19爆发模拟模型，可评估当前适用于该地区的缓解措施，可预测Covid-19-19统计数据（病例，住院和死亡的日常数量，住院和死亡），并就即将到来的缓解措施的力量提出建议。 Covidhunter的关键思想是通过模拟考虑到外部因素的影响，例如环境条件（例如气候，温度，湿度），关注，疫苗关注率和缓解措施的不同变异，是由感染者（例如环境条件（例如，气候，温度，湿度），诸如环境条件，温度，湿度），诸如环境条件（例如，气候，温度，湿度），诸如环境条件（例如环境条件，温度，湿度），量化了Covid-19在地理区域的传播。 Covidhunter以瑞士为案例研究，估计我们正在经历一个致命的新浪潮，该浪潮将于2022年1月26日达到顶峰，这与我们在2020年2月的浪潮中非常相似。决策者只有一种选择，即提高当前应用缓解措施30天的强度。与现有模型不同，Covidhunter模型可以准确监视，并预测Covid-19引起的病例，住院和死亡的日常数量。我们的模型可以灵活地进行配置，并且可以易于修改，以在不同的环境条件和缓解措施下对不同方案进行建模。我们在https://github.com/cmu-safari/covidhunter上发布了covidhunter实现的源代码。
Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region, predicts COVID-19 statistics (the daily number of cases, hospitalizations, and deaths), and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity), different variants of concern, vaccination rate, and mitigation measures. Using Switzerland as a case study, COVIDHunter estimates that we are experiencing a deadly new wave that will peak on 26 January 2022, which is very similar in numbers to the wave we had in February 2020. The policy-makers have only one choice that is to increase the strength of the currently applied mitigation measures for 30 days. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures. We release the source code of the COVIDHunter implementation at https://github.com/CMU-SAFARI/COVIDHunter.
