Jin Raymond
Farragut High School, Knoxville, TN.
J Public Health Res. 2021 Mar 9;10(3):2049. doi: 10.4081/jphr.2021.2049.
The Coronavirus disease 2019 (Covid-19) has infected millions and killed tens of thousands of people. Public health measures put in place by governments are essential to the success of controlling this disease. However, governments may not feel as incentivized to implement these measures when deaths are not rising along with cases. However, it is known that a delay exists between the time of infection and the time of death. This study attempted to find how long that lag is and how the age of people infected may affect that lag.
A descriptive and correlational study was carried out to investigate the length of the lag and the relationship between lag and age.
The average lag between daily Covid-19 cases and deaths was 8.053 days with a standard deviation of 4.116 days for nineteen regions. After excluding data from three more regions due to unavailable age data, the regression yielded an equation of lag = 14.015 - 0.153 (% cases above 60) with a p-value of 0.066. Because the p-value of 0.066 is lower than the 0.10 significance level, there is evidence that a relationship exists between the lag and the age of cases.
The results show that regions must remain vigilant when Covid-19 cases rapidly increase without similar increases in deaths since there exists a significant lag between the two. Additionally, a younger demographic of cases may lead to an increased lag, further pushing regions into a false sense of security that should be avoided.
2019年冠状病毒病（Covid-19）已感染数百万人，并导致数万人死亡。政府实施的公共卫生措施对于控制这种疾病的成功至关重要。然而，当死亡人数没有随着病例数增加时，政府可能没有那么大的动力去实施这些措施。然而，已知感染时间和死亡时间之间存在延迟。本研究试图找出这种延迟有多长，以及感染人群的年龄可能如何影响这种延迟。
开展了一项描述性和相关性研究，以调查延迟的时长以及延迟与年龄之间的关系。
19个地区Covid-19每日病例数与死亡数之间的平均延迟为8.053天，标准差为4.116天。由于年龄数据不可用，在排除另外三个地区的数据后，回归得出延迟的方程为：延迟=14.015 - 0.153（60岁以上病例的百分比），p值为0.066。由于0.066的p值低于0.10的显著性水平，有证据表明延迟与病例年龄之间存在关系。
结果表明，当Covid-19病例迅速增加而死亡人数没有类似增加时，各地区必须保持警惕，因为两者之间存在显著延迟。此外，较年轻的病例人群可能会导致延迟增加，进一步使各地区陷入应避免的虚假安全感之中。
