估计检测能力和社交距离在预测每日新冠病例增长率方面的可能作用。

Estimating The Possible Role Of Testing Capacity And Social Distancing In Predicting The Growth Rate Of Daily Covid-19 Cases.

机构信息

Department of Community Medicine, Ayub Medical College, Abbottabad, Pakistan.

Ayub Teaching Hospital, Abbottabad, Pakistan.

出版信息

J Ayub Med Coll Abbottabad. 2020 Oct-Dec;32(Suppl 1)(4):S686-S690.

PMID:33754532

Abstract

BACKGROUND

The purpose of this study was to estimate the effect of social distancing (days since the imposition of a lock-down) and the number of daily tests conducted per million population on the daily growth rate of COVID-19 cases.

METHODS

After excluding the first 30 days since the announcement of an index case in a country, relevant data for the next forty days was collected from four countries: Belgium, Italy, South Korea and United Kingdom. Two online databases: Our World in Data and worldometer were used for the collection of data which included the number of new COVID-19 cases and the number of tests conducted on a given day. The acquired figures were transformed into per million population of the given country. The growth rate of daily COVID-19 cases was derived and was used as the regress and in a multiple linear regression with the number of tests per million population per day and the number of days since a lock-down was imposed as the regressors.

RESULTS

It was found that the growth rate of daily COVID-19 cases decreased by .051% when the number of daily tests conducted per million population increased by 1. A .532% decrease in the growth rate of daily COVID-19 cases was observed with each passing day of a lock-down, which essentially represented the most effective form of social distancing. A significant regression was calculated (F (2, 155) = 35.191, p=.014), with an R2 of .054. Neither the daily number of tests conducted per million population nor the number of days of maintaining social distancing (lock-down) was individually significant contributors to the prediction of the growth rate of daily COVID-19 cases (p=.267 and p=.554 respectively).

CONCLUSION

An extensive and rapid increase in the daily number of testing capacity and maintaining social distancing can decrease the growth rate of daily COVID-19 cases. Depending on the availability of the required resources, timely implementation of these measures can lead to better outcomes for a given population.

摘要

背景

本研究旨在估计社交距离（从实施封锁起的天数）和每日每百万人进行的检测数量对 COVID-19 病例日增长率的影响。

方法

排除一个国家宣布首例病例后的头 30 天，从四个国家（比利时、意大利、韩国和英国）收集接下来 40 天的数据：Our World in Data 和 worldometer 这两个在线数据库用于收集数据，包括每日新的 COVID-19 病例数和当日进行的检测次数。获取的数字转换为给定国家的每百万人。推导出每日 COVID-19 病例增长率，并将其作为回归量，在多元线性回归中，每日每百万人进行的检测次数和实施封锁的天数作为回归量。

结果

发现当每日每百万人进行的检测次数增加 1 时，每日 COVID-19 病例增长率下降 0.051%。实施封锁的每一天，COVID-19 病例增长率下降 0.532%，这是最有效的社交距离形式。计算出一个显著的回归（F (2, 155) = 35.191，p=.014），R2 为 0.054。每日每百万人进行的检测次数和维持社交距离（封锁）的天数都不能单独显著预测每日 COVID-19 病例增长率（p=.267 和 p=.554）。