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2020 年至 2022 年间昆士兰州地区地理和社会经济因素与 SARS-CoV-2 感染的本地发病率。

Area-level geographic and socioeconomic factors and the local incidence of SARS-CoV-2 infections in Queensland between 2020 and 2022.

机构信息

School of Public Health, University of Queensland, Herston, Australia.

School of Public Health, University of Queensland, Herston, Australia.

出版信息

Aust N Z J Public Health. 2023 Dec;47(6):100094. doi: 10.1016/j.anzjph.2023.100094. Epub 2023 Oct 20.

Abstract

OBJECTIVE

Calculate the incidence of SARS-CoV-2 (COVID-19) infection notifications and the influence of area-level geographic and socioeconomic factors in Queensland using real-time data from the COVID-19 Real-time Information System for Preparedness and Epidemic Response (CRISPER) project.

DESIGN AND SETTING

Population-level ecological study and spatial mapping of the incidence of COVID-19 infection notifications in Queensland, by postcode, 2020-2022.

MAIN OUTCOME MEASURES

Proportions and distribution of COVID-19 infection notifications by year, age-group, socioeconomic disadvantage, and geospatial mapping. Incidence rate ratios (IRRs) were calculated.

RESULTS

Between 28 January 2020 and 30 June 2022, a total of 609,569 cases of COVID-19 associated with a Queensland postcode were recorded. The highest proportion of cases occurred in 2022 (96.5%), and in the 20- to 24-year age category (IRR = 1.787). In non-Major City areas, there was also a higher incidence of COVID-19 cases in lower socioeconomic areas (IRR = 0.84) than in higher socioeconomic areas (IRR = 0.66).

CONCLUSIONS

Queensland experienced its highest proportion of COVID-19 cases once domestic and international borders opened. However, geographic and socioeconomic factors may have still contributed to a higher incidence of COVID-19 cases across some Queensland areas.

IMPLICATIONS FOR PUBLIC HEALTH

Although Australia has moved from the emergency response phase of the COVID-19 pandemic, we need to ensure ongoing prevention strategies target groups and areas that we have identified with the highest incidence.

摘要

目的

利用 COVID-19 实时信息系统(CRISPER)项目的实时数据,计算昆士兰州 SARS-CoV-2(COVID-19)感染通知的发生率,并分析地区地理和社会经济因素的影响。

设计和设置

2020 年至 2022 年,在昆士兰州,按邮政编码进行 COVID-19 感染通知发生率的人群水平生态研究和空间映射。

主要观察指标

每年、年龄组、社会经济劣势和地理空间映射的 COVID-19 感染通知的比例和分布。计算发病率比(IRR)。

结果

2020 年 1 月 28 日至 2022 年 6 月 30 日期间,共记录了 609569 例与昆士兰州邮政编码相关的 COVID-19 病例。2022 年的病例比例最高(96.5%),20-24 岁年龄组的发病率最高(IRR=1.787)。在非主要城市地区,社会经济水平较低地区的 COVID-19 发病率(IRR=0.84)高于社会经济水平较高地区(IRR=0.66)。

结论

昆士兰州在国内和国际边界开放后经历了 COVID-19 病例比例最高的时期。然而,地理和社会经济因素可能仍然导致昆士兰州一些地区 COVID-19 病例的发生率更高。

公共卫生意义

尽管澳大利亚已从 COVID-19 大流行的紧急应对阶段过渡,但我们需要确保持续的预防策略针对我们确定的发病率最高的人群和地区。

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