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2019 年冠状病毒病在印度钦奈的第二波和第三波期间的流行病学:对 2019 年冠状病毒病监测系统的分析,2021 年 2 月-2022 年 2 月。

Epidemiology of Coronavirus Disease 2019 during the Second and Third Wave in Chennai, India: An Analysis of the Coronavirus Disease 2019 Surveillance System, February 2021-February 2022.

机构信息

Scientist-E, Division of Noncommunicable Diseases, ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India.

Consultant, Division of Noncommunicable Diseases, ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India.

出版信息

Indian J Public Health. 2024 Jan 1;68(1):60-65. doi: 10.4103/ijph.ijph_821_23. Epub 2024 Apr 4.

Abstract

INTRODUCTION

Analysis of the coronavirus disease 2019 (COVID-19) surveillance system in the first wave indicated that the data-driven approach helped in resource allocation and public health interventions.

OBJECTIVES

We described the epidemiology of COVID-19 cases in Chennai, Tamil Nadu, India, from February 2021 to February 2022.

MATERIALS AND METHODS

We analyzed the COVID-19 surveillance data from Chennai City, Tamil Nadu, India's Greater Chennai Corporation. We described the deidentified line list of COVID-19 cases and deaths by months, zones, age, and gender. We estimated the incidence of COVID-19 cases per million population, test positivity rate (TPR), and case fatality ratio (CFR).

RESULTS

Of the 434,040 cases reported in Chennai from February 1, 2021, to February 28, 2022, 53% were male. The incidence per million peaked in May 2021 (19,210) and January 2022 (15,881). Age groups more than 60 years reported maximum incidence. Southern region zones reported higher incidence. Overall TPR was 5.8%, peaked in May 2021 (17.5%) and January 2022 (15.1%). Over half of the 4929 reported deaths were in May 2021 (56%). Almost half of the deaths were 61-80 years (52%), followed by 41-60 years (26%). Overall CFR was 1%, which peaked in June 2021 (4%).

CONCLUSION

We conclude that Chennai city experienced a surge in COVID-19 due to delta and omicron variants. Understanding descriptive epidemiology is vital for planning the public health response, resource allocation, vaccination policies, and risk communication to the community.

摘要

引言

对 2019 年冠状病毒病(COVID-19)监测系统的第一波分析表明,数据驱动方法有助于资源分配和公共卫生干预。

目的

我们描述了 2021 年 2 月至 2022 年 2 月印度泰米尔纳德邦钦奈市 COVID-19 病例的流行病学情况。

材料和方法

我们分析了来自印度泰米尔纳德邦钦奈市的 COVID-19 监测数据。我们描述了 COVID-19 病例和死亡的匿名线列表,按月份、区域、年龄和性别进行了描述。我们估计了每百万人口的 COVID-19 病例发生率、检测阳性率(TPR)和病例病死率(CFR)。

结果

在 2021 年 2 月 1 日至 2022 年 2 月 28 日期间,在钦奈报告的 434040 例病例中,有 53%为男性。发病率最高的是 2021 年 5 月(19210)和 2022 年 1 月(15881)。60 岁以上年龄组报告的发病率最高。南部区域的发病率最高。总 TPR 为 5.8%,2021 年 5 月(17.5%)和 2022 年 1 月(15.1%)达到峰值。在 4929 例报告的死亡病例中,超过一半发生在 2021 年 5 月(56%)。几乎一半的死亡病例发生在 61-80 岁(52%),其次是 41-60 岁(26%)。总 CFR 为 1%,2021 年 6 月(4%)达到峰值。

结论

我们的结论是,钦奈市因 delta 和 omicron 变体而出现 COVID-19 疫情激增。了解描述性流行病学对于规划公共卫生应对措施、资源分配、疫苗接种政策以及向社区进行风险沟通至关重要。

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