大流行准备提高了国家级 SARS-CoV-2 感染和死亡数据的完整性:一项跨国生态分析。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Jorge R Ledesma, Irene Papanicolas, Michael A Stoto, Stavroula A Chrysanthopoulou, Christopher R Isaac, Mark N Lurie, Jennifer B Nuzzo
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引用次数: 0

摘要

背景:各国 SARS-CoV-2 感染监测能力的差异可能会影响 COVID-19 病例和死亡病例的全球统计和跟踪,并使对该流行病死亡人数的分析出现偏差。因此,考虑到数据完整性的异质性可能有助于澄清 COVID-19 结果与标准防备措施之间关系的分析:我们研究了全球卫生安全(GHS)指数和联合外部评估(JEE)的大流行准备能力清单与 SARS-CoV-2 感染和 COVID-19 死亡数据完成率之间的国家级关联,并对收入进行了调整。分析按每个国家首次报告病例后 100 天、100-300 天、300-500 天和 500-700 天进行分层。随后,我们重新评估了大流行准备程度与 SARS-CoV-2 感染率和年龄标准化 COVID-19 死亡率之间的关系,并对前疫苗时代的数据完整性的跨国差异进行了调整:在整个观察期间,GHS 指数每增加 10%,SARS-CoV-2 感染完成率就会增加 14.9%(95% 置信区间为 8.34-21.8%),死亡完成率就会增加 10.6%(5.91-15.4%)。疾病预防(感染:β = 1.08 [1.05-1.10],死亡:β = 1.05 [1.04-1.07])、检测(感染:β = 1.04 [1.01-1.06],死亡:β = 1.03 [1.01-1.05])、应对(感染:β = 1.06 [1.00-1.13],死亡:β = 1.感染:β = 1.06 [1.00-1.13],死亡:β = 1.05 [1.00-1.10])、卫生系统(感染:β = 1.06 [1.03-1.10],死亡:β = 1.05 [1.03-1.07])和风险环境(感染:β = 1.27 [1.15-1.41],死亡:β = 1.15 [1.08-1.23])均与数据完整性结果相关。GHS 指数对感染完成率(低收入:β = 1.18 [1.04-1.34];中低收入:β = 1.41 [1.16-1.71])和死亡完成率(低收入:β = 1.19 [1.09-1.31];中低收入:β = 1.25 [1.10-1.43])的影响大小在低收入和中等收入国家最大。在对数据完整性的国家间差异进行调整后,GHS 指数每增加 10%,SARS-CoV-2 感染率在 100 天内降低 13.5%(4.80-21.4%),在 300 天内降低 9.10%(1.07-16.5%)。就年龄标准化 COVID-19 死亡率而言,GHS 指数每增加 10%,100 天内的死亡率就会下降 15.7% (5.19-25.0%),300 天内的死亡率就会下降 10.3% (- 0.00-19.5%):结果支持大流行前的假设,即大流行准备能力越强的国家,SARS-CoV-2 感染和死亡数据完整率越高,COVID-19 疾病负担越低。需要更多基于直接测量的 COVID-19 影响的高质量数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pandemic preparedness improves national-level SARS-CoV-2 infection and mortality data completeness: a cross-country ecologic analysis.

Background: Heterogeneity in national SARS-CoV-2 infection surveillance capabilities may compromise global enumeration and tracking of COVID-19 cases and deaths and bias analyses of the pandemic's tolls. Taking account of heterogeneity in data completeness may thus help clarify analyses of the relationship between COVID-19 outcomes and standard preparedness measures.

Methods: We examined country-level associations of pandemic preparedness capacities inventories, from the Global Health Security (GHS) Index and Joint External Evaluation (JEE), on SARS-CoV-2 infection and COVID-19 death data completion rates adjusted for income. Analyses were stratified by 100, 100-300, 300-500, and 500-700 days after the first reported case in each country. We subsequently reevaluated the relationship of pandemic preparedness on SARS-CoV-2 infection and age-standardized COVID-19 death rates adjusted for cross-country differentials in data completeness during the pre-vaccine era.

Results: Every 10% increase in the GHS Index was associated with a 14.9% (95% confidence interval 8.34-21.8%) increase in SARS-CoV-2 infection completion rate and a 10.6% (5.91-15.4%) increase in the death completion rate during the entire observation period. Disease prevention (infections: β = 1.08 [1.05-1.10], deaths: β = 1.05 [1.04-1.07]), detection (infections: β = 1.04 [1.01-1.06], deaths: β = 1.03 [1.01-1.05]), response (infections: β = 1.06 [1.00-1.13], deaths: β = 1.05 [1.00-1.10]), health system (infections: β = 1.06 [1.03-1.10], deaths: β = 1.05 [1.03-1.07]), and risk environment (infections: β = 1.27 [1.15-1.41], deaths: β = 1.15 [1.08-1.23]) were associated with both data completeness outcomes. Effect sizes of GHS Index on infection completion (Low income: β = 1.18 [1.04-1.34], Lower Middle income: β = 1.41 [1.16-1.71]) and death completion rates (Low income: β = 1.19 [1.09-1.31], Lower Middle income: β = 1.25 [1.10-1.43]) were largest in LMICs. After adjustment for cross-country differences in data completeness, each 10% increase in the GHS Index was associated with a 13.5% (4.80-21.4%) decrease in SARS-CoV-2 infection rate at 100 days and a 9.10 (1.07-16.5%) decrease at 300 days. For age-standardized COVID-19 death rates, each 10% increase in the GHS Index was with a 15.7% (5.19-25.0%) decrease at 100 days and a 10.3% (- 0.00-19.5%) decrease at 300 days.

Conclusions: Results support the pre-pandemic hypothesis that countries with greater pandemic preparedness capacities have larger SARS-CoV-2 infection and mortality data completeness rates and lower COVID-19 disease burdens. More high-quality data of COVID-19 impact based on direct measurement are needed.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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