Suppr超能文献

利用基于卫生机构的血清学监测预测消除地区疟疾暴发的高风险地区。

Using health facility-based serological surveillance to predict receptive areas at risk of malaria outbreaks in elimination areas.

机构信息

Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK.

Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Medika, Yogyakarta, 55281, Indonesia.

出版信息

BMC Med. 2020 Jan 28;18(1):9. doi: 10.1186/s12916-019-1482-7.

Abstract

BACKGROUND

In order to improve malaria burden estimates in low transmission settings, more sensitive tools and efficient sampling strategies are required. This study evaluated the use of serological measures from repeated health facility-based cross-sectional surveys to investigate Plasmodium falciparum and Plasmodium vivax transmission dynamics in an area nearing elimination in Indonesia.

METHODS

Quarterly surveys were conducted in eight public health facilities in Kulon Progo District, Indonesia, from May 2017 to April 2018. Demographic data were collected from all clinic patients and their companions, with household coordinates collected using participatory mapping methods. In addition to standard microscopy tests, bead-based serological assays were performed on finger-prick bloodspot samples from 9453 people. Seroconversion rates (SCR, i.e. the proportion of people in the population who are expected to seroconvert per year) were estimated by fitting a simple reversible catalytic model to seroprevalence data. Mixed effects logistic regression was used to examine factors associated with malaria exposure, and spatial analysis was performed to identify areas with clustering of high antibody responses.

RESULTS

Parasite prevalence by microscopy was extremely low (0.06% (95% confidence interval 0.03-0.14, n = 6) and 0 for P. vivax and P. falciparum, respectively). However, spatial analysis of P. vivax antibody responses identified high-risk areas that were subsequently the site of a P. vivax outbreak in August 2017 (62 cases detected through passive and reactive detection systems). These areas overlapped with P. falciparum high-risk areas and were detected in each survey. General low transmission was confirmed by the SCR estimated from a pool of the four surveys in people aged 15 years old and under (0.020 (95% confidence interval 0.017-0.024) and 0.005 (95% confidence interval 0.003-0.008) for P. vivax and P. falciparum, respectively). The SCR estimates in those over 15 years old were 0.066 (95% confidence interval 0.041-0.105) and 0.032 (95% confidence interval 0.015-0.069) for P. vivax and P. falciparum, respectively.

CONCLUSIONS

These findings demonstrate the potential use of health facility-based serological surveillance to better identify and target areas still receptive to malaria in an elimination setting. Further implementation research is needed to enable integration of these methods with existing surveillance systems.

摘要

背景

为了提高低传播地区疟疾负担的估算水平,需要更敏感的工具和更有效的抽样策略。本研究评估了在印度尼西亚一个即将消除疟疾的地区,利用基于医疗机构的重复横断面调查中的血清学指标来研究恶性疟原虫和间日疟原虫的传播动态。

方法

2017 年 5 月至 2018 年 4 月,在印度尼西亚古隆普罗戈区的 8 个公共卫生机构每季度进行一次调查。从所有就诊患者及其陪同人员收集人口统计学数据,并使用参与式绘图方法收集家庭坐标。除了标准显微镜检查外,还对 9453 人的指血斑样本进行基于珠的血清学检测。通过拟合简单的可逆催化模型来估计血清转换率(SCR,即每年预期血清转换人群的比例)。采用混合效应逻辑回归分析疟疾暴露的相关因素,并进行空间分析以确定抗体反应高的聚集区。

结果

显微镜寄生虫患病率极低(分别为 0.06%(95%置信区间 0.03-0.14,n=6)和 0 对间日疟原虫和恶性疟原虫)。然而,间日疟原虫抗体反应的空间分析确定了高风险地区,随后该地区于 2017 年 8 月爆发了间日疟(通过被动和反应性检测系统检测到 62 例)。这些地区与恶性疟原虫高风险地区重叠,并在每次调查中都有发现。通过对 4 次调查的人群(年龄在 15 岁及以下)的血清学指标进行汇总,SCR 估计值较低,确认了一般低传播情况(间日疟原虫和恶性疟原虫分别为 0.020(95%置信区间 0.017-0.024)和 0.005(95%置信区间 0.003-0.008))。15 岁以上人群的 SCR 估计值分别为 0.066(95%置信区间 0.041-0.105)和 0.032(95%置信区间 0.015-0.069)。

结论

这些发现表明,利用医疗机构的血清学监测可以更好地识别和确定在消除环境中仍对疟疾敏感的地区。需要进一步开展实施研究,以便将这些方法与现有的监测系统相结合。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验