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证据更新对麻疹疫苗接种效果关键决定因素的影响:十个高负担国家的 DynaMICE 建模研究。

Effect of evidence updates on key determinants of measles vaccination impact: a DynaMICE modelling study in ten high-burden countries.

机构信息

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Public Health Foundation of India, New Delhi, India.

出版信息

BMC Med. 2021 Nov 17;19(1):281. doi: 10.1186/s12916-021-02157-4.

Abstract

BACKGROUND

Model-based estimates of measles burden and the impact of measles-containing vaccine (MCV) are crucial for global health priority setting. Recently, evidence from systematic reviews and database analyses have improved our understanding of key determinants of MCV impact. We explore how representations of these determinants affect model-based estimation of vaccination impact in ten countries with the highest measles burden.

METHODS

Using Dynamic Measles Immunisation Calculation Engine (DynaMICE), we modelled the effect of evidence updates for five determinants of MCV impact: case-fatality risk, contact patterns, age-dependent vaccine efficacy, the delivery of supplementary immunisation activities (SIAs) to zero-dose children, and the basic reproduction number. We assessed the incremental vaccination impact of the first (MCV1) and second (MCV2) doses of routine immunisation and SIAs, using metrics of total vaccine-averted cases, deaths, and disability-adjusted life years (DALYs) over 2000-2050. We also conducted a scenario capturing the effect of COVID-19 related disruptions on measles burden and vaccination impact.

RESULTS

Incorporated with the updated data sources, DynaMICE projected 253 million measles cases, 3.8 million deaths and 233 million DALYs incurred over 2000-2050 in the ten high-burden countries when MCV1, MCV2, and SIA doses were implemented. Compared to no vaccination, MCV1 contributed to 66% reduction in cumulative measles cases, while MCV2 and SIAs reduced this further to 90%. Among the updated determinants, shifting from fixed to linearly-varying vaccine efficacy by age and from static to time-varying case-fatality risks had the biggest effect on MCV impact. While varying the basic reproduction number showed a limited effect, updates on the other four determinants together resulted in an overall reduction of vaccination impact by 0.58%, 26.2%, and 26.7% for cases, deaths, and DALYs averted, respectively. COVID-19 related disruptions to measles vaccination are not likely to change the influence of these determinants on MCV impact, but may lead to a 3% increase in cases over 2000-2050.

CONCLUSIONS

Incorporating updated evidence particularly on vaccine efficacy and case-fatality risk reduces estimates of vaccination impact moderately, but its overall impact remains considerable. High MCV coverage through both routine immunisation and SIAs remains essential for achieving and maintaining low incidence in high measles burden settings.

摘要

背景

基于模型的麻疹负担和含麻疹疫苗(MCV)的影响估计对于全球卫生重点设定至关重要。最近,来自系统评价和数据库分析的证据提高了我们对 MCV 影响关键决定因素的理解。我们探讨了在麻疹负担最高的十个国家中,这些决定因素的代表性如何影响基于模型的疫苗接种影响估计。

方法

我们使用动态麻疹免疫计算引擎(DynaMICE),为五个 MCV 影响决定因素的证据更新建模:病死率风险、接触模式、年龄相关疫苗效力、对零剂量儿童的补充免疫活动(SIAs)的提供,以及基本繁殖数。我们使用 2000-2050 年期间总疫苗预防病例、死亡和残疾调整生命年(DALYs)的指标,评估了常规免疫和 SIAs 的第一(MCV1)和第二(MCV2)剂量的增量疫苗接种效果。我们还进行了一个场景,以捕捉与 COVID-19 相关的中断对麻疹负担和疫苗接种影响的影响。

结果

当在十个高负担国家实施 MCV1、MCV2 和 SIA 剂量时,DynaMICE 结合更新的数据来源预测,在 2000-2050 年期间将发生 2.53 亿例麻疹病例、380 万例死亡和 2.33 亿例 DALYs。与无疫苗接种相比,MCV1 导致累计麻疹病例减少 66%,而 MCV2 和 SIAs 将这一比例进一步降低至 90%。在更新的决定因素中,从固定到线性随年龄变化的疫苗效力以及从静态到随时间变化的病死率风险的转变对 MCV 影响的影响最大。虽然改变基本繁殖数的影响有限,但其他四个决定因素的更新综合导致病例、死亡和 DALYs 避免的疫苗接种影响分别减少 0.58%、26.2%和 26.7%。与麻疹疫苗接种相关的 COVID-19 中断不太可能改变这些决定因素对 MCV 影响的影响,但可能导致 2000-2050 年期间病例增加 3%。

结论

纳入更新的证据,特别是关于疫苗效力和病死率风险的证据,适度降低了疫苗接种影响的估计,但总体影响仍然相当大。通过常规免疫和 SIAs 实现高 MCV 覆盖率仍然是在高麻疹负担环境中实现和维持低发病率的关键。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6947/8597239/eb8489bc4a97/12916_2021_2157_Fig1_HTML.jpg

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