论文标题
COVID-19从与报告案件相关联的相关呼叫中的轻度案例确定
COVID-19 mild cases determination from correlating COVID-line calls to reported cases
论文作者
论文摘要
背景：了解Covid-19的最具挑战性的关键之一是对那些从未经过测试的轻度病例进行衡量，因为它们的少数症状很柔软和/或很快消失。问题不仅是它们难以识别和测试，而且还认为它们可能构成大部分案件，并且在大流行方程中可能至关重要。 方法：我们提出了一种新型算法，通过将与给定地区的案例相关联的呼叫通过将共同呼叫相关联，以提取这些温和病例的数量。关键假设是要意识到，作为一种高度传染性的疾病，温和病例的呼叫数量应与报告病例的数量成正比。而与受感染者无关的电话背景应与地区人口成正比。 结果：我们发现，对于布宜诺斯艾利斯省而言，除背景外，每个报告的Covid-11案件中还有信号6.6 +/- 0.4次数。使用此信息，我们在布宜诺斯艾利斯省20 +/- 2 COVID-11的有症状病例中估计。 结论：一种非常简单的算法，该算法将Covid-Line称为信号之和的背景之和允许估计给定地区中报告的COVID-19案例的症状率的关键数量。该方法的结果是早期且廉价的估计值，应与其他方法（例如血清学和/或大规模测试）形成鲜明对比。
Background: One of the most challenging keys to understand COVID-19 evolution is to have a measure on those mild cases which are never tested because their few symptoms are soft and/or fade away soon. The problem is not only that they are difficult to identify and test, but also that it is believed that they may constitute the bulk of the cases and could be crucial in the pandemic equation. Methods: We present a novel algorithm to extract the number of these mild cases by correlating a COVID-line calls to reported cases in given districts. The key assumption is to realize that, being a highly contagious disease, the number of calls by mild cases should be proportional to the number of reported cases. Whereas a background of calls not related to infected people should be proportional to the district population. Results: We find that for Buenos Aires Province, in addition to the background, there are in signal 6.6 +/- 0.4 calls per each reported COVID-19 case. Using this we estimate in Buenos Aires Province 20 +/- 2 COVID-19 symptomatic cases for each one reported. Conclusions: A very simple algorithm that models the COVID-line calls as sum of signal plus background allows to estimate the crucial number of the rate of symptomatic to reported COVID-19 cases in a given district. The result from this method is an early and inexpensive estimate and should be contrasted to other methods such as serology and/or massive testing.
