A simple Stochastic model for the SARS-CoV-2 Epidemic curve

A. Diógenes, D. Tedesco
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Abstract

An epidemic curve is a graphic depiction of the number of outbreak cases by date of illness onset, ordinarily constructed after the disease outbreak is over. However, a good estimate of the epidemic curve early in an outbreak would be invaluable to health care officials. On the other hand, from the end of February, the SARS-CoV-2 epidemic in Brazil seems to not following the Europe, or in particular, Italy or Spain. Even if less tests have been applied, there are less deaths occurring in Brazil than in both cited countries. However, due to the few applied tests, there is no certain planning on the real number of active cases. To estimate the number of future cases, epidemiologists make an educated guess as to how many people might become affected. We have proposed a simple fitting model using a simulated annealing technique, testing it with the South Korea data. We have tested and discussed the uncertainties of the model. We also have analyzed the trends in the confirmed cases using this model for the five most affected countries plus Brazil along several epidemic weeks.
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SARS-CoV-2流行曲线的简单随机模型
流行病曲线是按发病日期描述暴发病例数的图形,通常在疾病暴发结束后绘制。然而,在疫情爆发的早期对疫情曲线的准确估计对卫生保健官员来说是非常宝贵的。另一方面,从2月底开始,巴西的SARS-CoV-2疫情似乎没有跟随欧洲,特别是意大利和西班牙。即使应用的检测较少,巴西的死亡人数也比上述两个国家少。然而,由于应用的测试很少,对实际活跃病例的数量没有确定的计划。为了估计未来病例的数量,流行病学家对有多少人可能受到影响做出了有根据的猜测。我们使用模拟退火技术提出了一个简单的拟合模型,并用韩国的数据进行了测试。我们对模型的不确定性进行了检验和讨论。我们还使用该模型分析了五个受影响最严重的国家加上巴西在几个流行周内确诊病例的趋势。
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