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鉴定疟疾传播热点以进行有针对性的疟疾控制。

Identification of hot spots of malaria transmission for targeted malaria control.

机构信息

Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom.

出版信息

J Infect Dis. 2010 Jun 1;201(11):1764-74. doi: 10.1086/652456.

Abstract

BACKGROUND

Variation in the risk of malaria within populations is a frequently described but poorly understood phenomenon. This heterogeneity creates opportunities for targeted interventions but only if hot spots of malaria transmission can be easily identified.

METHODS

We determined spatial patterns in malaria transmission in a district in northeastern Tanzania, using malaria incidence data from a cohort study involving infants and household-level mosquito sampling data. The parasite prevalence rates and age-specific seroconversion rates (SCRs) of antibodies against Plasmodium falciparum antigens were determined in samples obtained from people attending health care facilities.

RESULTS

Five clusters of higher malaria incidence were detected and interpreted as hot spots of transmission. These hot spots partially overlapped with clusters of higher mosquito exposure but could not be satisfactorily predicted by a probability model based on environmental factors. Small-scale local variation in malaria exposure was detected by parasite prevalence rates and SCR estimates for samples of health care facility attendees. SCR estimates were strongly associated with local malaria incidence rates and predicted hot spots of malaria transmission with 95% sensitivity and 85% specificity.

CONCLUSIONS

Serological markers were able to detect spatial variation in malaria transmission at the microepidemiological level, and they have the potential to form an effective method for spatial targeting of malaria control efforts.

摘要

背景

人群中疟疾风险的变化是一个经常被描述但却理解甚少的现象。这种异质性为有针对性的干预措施创造了机会,但前提是疟疾传播的热点能够被轻易识别。

方法

我们利用在坦桑尼亚东北部一个地区开展的一项涉及婴儿的队列研究的疟疾发病率数据和家庭层面的蚊子抽样数据,确定疟疾传播的空间模式。在前往医疗机构就诊的人群样本中,我们确定了针对恶性疟原虫抗原的抗体的寄生虫流行率和特定年龄的血清转化率(SCR)。

结果

检测到五个疟疾发病率较高的聚集区,并将其解释为传播热点。这些热点部分与蚊子暴露率较高的聚集区重叠,但无法通过基于环境因素的概率模型进行令人满意的预测。寄生虫流行率和医疗机构就诊人群样本的 SCR 估计值检测到了疟疾暴露的小规模局部变化。SCR 估计值与当地疟疾发病率之间存在强烈关联,以 95%的灵敏度和 85%的特异性预测疟疾传播的热点。

结论

血清学标志物能够在微观流行病学水平上检测到疟疾传播的空间变化,并且有可能成为疟疾控制工作空间靶向的有效方法。

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