衡量大流行严重程度在人口普查年份、变异毒株和干预措施之间的不平等分布。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Quang Dang Nguyen, Sheryl L Chang, Christina M Jamerlan, Mikhail Prokopenko
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引用次数: 0

摘要

背景:由于出现了几种高度传播的变异毒株,新冠肺炎大流行给全球公共卫生系统带来了压力。过去几年部署的多样化和复杂的干预政策在控制疫情方面表现出了不同的有效性。然而,由于缺乏适当的疫情不平等和非线性影响衡量标准,对不同病毒谱系和复杂干预政策的综合影响进行系统分析和建模仍然是一项挑战。方法:使用大规模基于代理的建模和高分辨率计算模拟匹配澳大利亚基于人口统计的人口统计,我们对几个新冠肺炎大流行情景进行了系统的比较分析。这些情景涵盖了最近两个澳大利亚人口普查年(2016年和2021年)、三种变异毒株(祖先、德尔塔和奥密克戎)和五种具有代表性的干预政策。我们引入了流行病洛伦兹曲线,该曲线测量了流行病严重程度在局部地区的不平等分布。我们还量化了流行病的生物形态,区分了城市和地区的波动,并测量了干预措施有效性的差异。结果:我们量化了人口异质性对大流行严重程度的非线性影响,强调(i)人口增长放大了大流行峰值,(ii)人口规模的变化比密度的变化更放大了峰值发病率,(iii)大流行严重程度在局部地区分布不均。我们还研究并描绘了城市化对发病率双峰的影响,区分了城市和区域疫情浪潮。最后,我们量化并研究了学校关闭的影响,辅以部分干预措施,并确定了纳入学校关闭可能决定性控制传播的条件。结论:必须经常审查公共卫生对长期流行病的反应,并使其适应人口变化。为了控制复发性浪潮,大规模疫苗接种需要部分NPI的补充。医疗保健和疫苗接种资源需要优先用于人口增长率高和/或密度高的地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions.

Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions.

Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions.

Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions.

Background: The COVID-19 pandemic stressed public health systems worldwide due to emergence of several highly transmissible variants of concern. Diverse and complex intervention policies deployed over the last years have shown varied effectiveness in controlling the pandemic. However, a systematic analysis and modelling of the combined effects of different viral lineages and complex intervention policies remains a challenge due to the lack of suitable measures of pandemic inequality and nonlinear effects.

Methods: Using large-scale agent-based modelling and a high-resolution computational simulation matching census-based demographics of Australia, we carried out a systematic comparative analysis of several COVID-19 pandemic scenarios. The scenarios covered two most recent Australian census years (2016 and 2021), three variants of concern (ancestral, Delta and Omicron), and five representative intervention policies. We introduced pandemic Lorenz curves measuring an unequal distribution of the pandemic severity across local areas. We also quantified pandemic biomodality, distinguishing between urban and regional waves, and measured bifurcations in the effectiveness of interventions.

Results: We quantified nonlinear effects of population heterogeneity on the pandemic severity, highlighting that (i) the population growth amplifies pandemic peaks, (ii) the changes in population size amplify the peak incidence more than the changes in density, and (iii) the pandemic severity is distributed unequally across local areas. We also examined and delineated the effects of urbanisation on the incidence bimodality, distinguishing between urban and regional pandemic waves. Finally, we quantified and examined the impact of school closures, complemented by partial interventions, and identified the conditions when inclusion of school closures may decisively control the transmission.

Conclusions: Public health response to long-lasting pandemics must be frequently reviewed and adapted to demographic changes. To control recurrent waves, mass-vaccination rollouts need to be complemented by partial NPIs. Healthcare and vaccination resources need to be prioritised towards the localities and regions with high population growth and/or high density.

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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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