Monitoring COVID-19 where capacity for testing is limited: use of a three-step analysis based on test positivity ratio.

Q2 Medicine
Sirenda Vong, Manish Kakkar
{"title":"Monitoring COVID-19 where capacity for testing is limited: use of a three-step analysis based on test positivity ratio.","authors":"Sirenda Vong,&nbsp;Manish Kakkar","doi":"10.4103/2224-3151.294308","DOIUrl":null,"url":null,"abstract":"<p><p>In an effort to monitor coronavirus disease 2019 (COVID-19), many countries have been calculating the ratio of cases confirmed to tests performed (test positivity ratio - TPR). While inferior to sentinel surveillance, TPR has the benefit of being easily calculated using readily available data; however, interpreting TPR and its trends can be complex because both the numerator and the denominator are constantly changing. We describe a three-step process where the ratio of relative increase in cases to relative increase in tests is accounted for in an adjusted TPR. This adjusted value more appropriately reflects the case number and factors out the effect of changes in the number of tests done. Unadjusted and adjusted TPRs are then assessed step-wise with reference to the epidemic curve and the cumulative numbers of cases and tests. Use of this three-step analysis and its potential use in guiding public health interventions are demonstrated for selected countries and subnational areas of the World Health Organization South-East Asia Region, together with the Republic of Korea as a reference. To date, application of the three-step analysis to data from countries of the region has signalled potential inadequacies of testing strategies. Further work is needed on approaches to support countries where testing capacity is likely to remain constrained. One example would be enumeration of the average number of tests needed to detect one COVID-19 case, which could be stratified by factors such as location and population. Such data would allow evidence-informed strategies that best balance the highest detection rate with the prevailing testing capacity.</p>","PeriodicalId":37393,"journal":{"name":"WHO South-East Asia journal of public health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WHO South-East Asia journal of public health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/2224-3151.294308","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 10

Abstract

In an effort to monitor coronavirus disease 2019 (COVID-19), many countries have been calculating the ratio of cases confirmed to tests performed (test positivity ratio - TPR). While inferior to sentinel surveillance, TPR has the benefit of being easily calculated using readily available data; however, interpreting TPR and its trends can be complex because both the numerator and the denominator are constantly changing. We describe a three-step process where the ratio of relative increase in cases to relative increase in tests is accounted for in an adjusted TPR. This adjusted value more appropriately reflects the case number and factors out the effect of changes in the number of tests done. Unadjusted and adjusted TPRs are then assessed step-wise with reference to the epidemic curve and the cumulative numbers of cases and tests. Use of this three-step analysis and its potential use in guiding public health interventions are demonstrated for selected countries and subnational areas of the World Health Organization South-East Asia Region, together with the Republic of Korea as a reference. To date, application of the three-step analysis to data from countries of the region has signalled potential inadequacies of testing strategies. Further work is needed on approaches to support countries where testing capacity is likely to remain constrained. One example would be enumeration of the average number of tests needed to detect one COVID-19 case, which could be stratified by factors such as location and population. Such data would allow evidence-informed strategies that best balance the highest detection rate with the prevailing testing capacity.

监测检测能力有限的COVID-19:使用基于检测阳性比率的三步分析。
为了监测2019年冠状病毒病(COVID-19),许多国家一直在计算确诊病例与进行检测的比率(检测阳性比率- TPR)。虽然TPR不如哨点监测,但它的好处是可以使用现成的数据轻松计算;然而,解释TPR及其趋势可能很复杂,因为分子和分母都在不断变化。我们描述了一个三步过程,其中在调整后的TPR中考虑了病例相对增加与测试相对增加的比率。这个调整后的值更恰当地反映了病例数,并排除了所做检测数量变化的影响。然后参照流行曲线以及病例和检测的累积数量,逐步评估未经调整和调整的tpr。在世界卫生组织东南亚区域的选定国家和次国家地区,并以大韩民国为参照,演示了这种三步分析的使用及其在指导公共卫生干预措施方面的潜在用途。迄今为止,对该区域各国数据的三步分析表明,检测战略可能存在不足之处。需要进一步研究支持检测能力可能仍然受到限制的国家的方法。一个例子是枚举检测一个COVID-19病例所需的平均检测次数,可以根据地点和人口等因素进行分层。这些数据将使循证战略能够最好地平衡最高检出率与现行检测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.10
自引率
0.00%
发文量
25
期刊介绍: The journal will cover technical and clinical studies related to health, ethical and social issues in field of Public Health, Epidemiology, primary health care, epidemiology, health administration, health systems, health economics, health promotion, public health nutrition, communicable and non-communicable diseases, maternal and child health, occupational and environmental health, social and preventive medicine. Articles with clinical interest and implications will be given preference.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信