PDF(Pubmed)
Abstract：
UNASSIGNED: The Indian Council of Medical Research (ICMR) played a crucial role in streamlining testing and diagnosis, formulating guidelines, and devising management strategies during the COVID-19 pandemic. Additionally, ICMR designed and developed a comprehensive data management tool for collecting testing data in a standardized format from all laboratories across the country. The current report is a retrospective analysis of the testing data generated by the ICMR. The study\'s main objectives are to understand the probability of a person testing negative based on their age after an initial positive test and to assess the varied impact and duration of the disease in people of different age groups and genders.
UNASSIGNED: Anonymized data on the testing for COVID were analyzed. The P-to-P is the longest time interval between two consecutive positive tests for a patient without any negative test in between the positives. P-to-Plast is the time between the first positive and last positive test, as opposed to P-to-P, here we are looking at the first and last positive tests that might or might not be consecutive. P-to-N intervals is the time between the first positive and first negative test of a patient.
UNASSIGNED: India conducted 170,914,170 tests during the study-period (until December 29, 2020). After excluding invalid test results and duplicates, there were 11,101,603 (6.5%) positive and 156,542,352 (93.5%) negative test-results performed upon 150,086,257 unique individuals. A negative-report following a positive-test was available in 12.69%. Nearly three-fourths of the cases (78.29%) belonged to the working-age group (18-60 years). The proportion of patients >50 years old has risen from 26.06 to 35.03%, with a steep rise beyond September 2020. Gender-ratio among the positives was 1.73:1 which was neutral in neonates < 7-days (age). The gender ratio was skewed in-favor-of males in the initial months with a reverse trend thereafter and with increasing age of patients. The mean P-to-P, P-to-Plast, and P-to-N durations were 12.7 + 4.3, 13.3 + 4.6, and 14.2 + 4.9 days for individuals with P-to-P duration of 1-4 weeks. The probability of testing negative was 82 & 85% at 14 & 21 days after the first-positive-test respectively with no gender bias.
UNASSIGNED: The current study has highlighted some vital aspects of COVID-19 epidemiology in India. This study will add to the current understanding of the virus in the absence of pre- existing information on the novel virus and the disease per se.
UNASSIGNED: Anonymized data on the testing for COVID were analyzed. The P-to-P is the longest time interval between two consecutive positive tests for a patient without any negative test in between the positives. P-to-Plast is the time between the first positive and last positive test, as opposed to P-to-P, here we are looking at the first and last positive tests that might or might not be consecutive. P-to-N intervals is the time between the first positive and first negative test of a patient.
UNASSIGNED: India conducted 170,914,170 tests during the study-period (until December 29, 2020). After excluding invalid test results and duplicates, there were 11,101,603 (6.5%) positive and 156,542,352 (93.5%) negative test-results performed upon 150,086,257 unique individuals. A negative-report following a positive-test was available in 12.69%. Nearly three-fourths of the cases (78.29%) belonged to the working-age group (18-60 years). The proportion of patients >50 years old has risen from 26.06 to 35.03%, with a steep rise beyond September 2020. Gender-ratio among the positives was 1.73:1 which was neutral in neonates < 7-days (age). The gender ratio was skewed in-favor-of males in the initial months with a reverse trend thereafter and with increasing age of patients. The mean P-to-P, P-to-Plast, and P-to-N durations were 12.7 + 4.3, 13.3 + 4.6, and 14.2 + 4.9 days for individuals with P-to-P duration of 1-4 weeks. The probability of testing negative was 82 & 85% at 14 & 21 days after the first-positive-test respectively with no gender bias.
UNASSIGNED: The current study has highlighted some vital aspects of COVID-19 epidemiology in India. This study will add to the current understanding of the virus in the absence of pre- existing information on the novel virus and the disease per se.
摘要：
■印度医学研究委员会（ICMR）在简化测试和诊断方面发挥了至关重要的作用，制定指导方针，并在COVID-19大流行期间制定管理策略。此外,ICMR设计并开发了一个全面的数据管理工具，用于以标准化格式从全国所有实验室收集测试数据。本报告是对ICMR生成的测试数据的回顾性分析。该研究的主要目标是了解一个人在最初的阳性测试后根据其年龄测试为阴性的可能性，并评估该疾病在不同年龄段和性别人群中的不同影响和持续时间。
■分析了COVID测试的匿名数据。P到P是患者的两个连续阳性测试之间的最长时间间隔，而阳性之间没有任何阴性测试。P-to-Plast是第一个阳性测试和最后一个阳性测试之间的时间，而不是P-to-P,在这里，我们看到的是可能连续或不连续的第一个和最后一个阳性测试。P-N间隔是患者的第一次阳性和第一次阴性测试之间的时间。
■印度在研究期间进行了170,914,170次测试（直到2020年12月29日）。排除无效测试结果和重复项后，对150,086,257名独特个体进行了11,101,603名(6.5%)阳性和156,542,352名(93.5%)阴性测试结果.阳性测试后的阴性报告为12.69％。近四分之三的病例(78.29%)属于工作年龄组(18-60岁)。>50岁的患者比例从26.06%上升到35.03%,在2020年9月之后急剧上升。阳性中的性别比例为1.73：1，在<7天（年龄）的新生儿中是中性的。在最初的几个月中，性别比例偏向男性，此后趋势相反，并且随着患者年龄的增加。平均P对P，P-to-Plast,P-P持续时间为1-4周的个体的P-N持续时间分别为12.7+4.3、13.3+4.6和14.2+4.9天。在第一次阳性测试后14天和21天，测试阴性的概率分别为82％和85％，没有性别偏见。
■当前的研究强调了印度COVID-19流行病学的一些重要方面。在缺乏关于新病毒和疾病本身的预先存在的信息的情况下，这项研究将增加对病毒的当前理解。
■分析了COVID测试的匿名数据。P到P是患者的两个连续阳性测试之间的最长时间间隔，而阳性之间没有任何阴性测试。P-to-Plast是第一个阳性测试和最后一个阳性测试之间的时间，而不是P-to-P,在这里，我们看到的是可能连续或不连续的第一个和最后一个阳性测试。P-N间隔是患者的第一次阳性和第一次阴性测试之间的时间。
■印度在研究期间进行了170,914,170次测试（直到2020年12月29日）。排除无效测试结果和重复项后，对150,086,257名独特个体进行了11,101,603名(6.5%)阳性和156,542,352名(93.5%)阴性测试结果.阳性测试后的阴性报告为12.69％。近四分之三的病例(78.29%)属于工作年龄组(18-60岁)。>50岁的患者比例从26.06%上升到35.03%,在2020年9月之后急剧上升。阳性中的性别比例为1.73：1，在<7天（年龄）的新生儿中是中性的。在最初的几个月中，性别比例偏向男性，此后趋势相反，并且随着患者年龄的增加。平均P对P，P-to-Plast,P-P持续时间为1-4周的个体的P-N持续时间分别为12.7+4.3、13.3+4.6和14.2+4.9天。在第一次阳性测试后14天和21天，测试阴性的概率分别为82％和85％，没有性别偏见。
■当前的研究强调了印度COVID-19流行病学的一些重要方面。在缺乏关于新病毒和疾病本身的预先存在的信息的情况下，这项研究将增加对病毒的当前理解。
