Unité Malaria : Parasites Et Hôtes, Département Parasites Et Insectes Vecteurs, Institut Pasteur, Paris, France.
Sorbonne Université, Collège Doctoral, Paris, France.
Malar J. 2023 Mar 4;22(1):75. doi: 10.1186/s12936-023-04515-4.
Over the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster.
Data were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-prick blood samples from participants were tested for Plasmodium infection by PCR. Cohort studies from Brazil and Thailand with monthly sampling over a year from 2013 until 2014 were also included. The prevalence of PCR-confirmed infections was calculated at increasing distance around index infections (and growing time intervals in the cohort studies). Statistical significance was defined as prevalence outside of a 95%-quantile interval of a bootstrap null distribution after random re-allocation of locations of infections.
Prevalence of Plasmodium vivax and Plasmodium falciparum infections was elevated in close proximity around index infections and decreased with distance in most study sites, e.g. from 21.3% at 0 km to the global study prevalence of 6.4% for P. vivax in the Cambodian survey. In the cohort studies, the clustering decreased with longer time windows. The distance from index infections to a 50% reduction of prevalence ranged from 25 m to 3175 m, tending to shorter distances at lower global study prevalence.
The spatial signatures of P. vivax and P. falciparum infections demonstrate spatial clustering across a diverse set of study sites, quantifying the distance within which the clustering occurs. The method offers a novel tool in malaria epidemiology, potentially informing reactive intervention strategies regarding radius choices of operations around detected infections and thus strengthening malaria elimination endeavours.
在过去的几十年里,全球在降低疟疾负担方面取得了巨大成就。在拉丁美洲、东南亚和西太平洋,许多国家现在都追求到 2030 年消除疟疾的目标。人们普遍认识到,疟原虫感染呈空间聚集性,因此干预措施需要具有空间信息,例如,采用具有空间针对性的反应性病例检测策略。在这里,引入了空间特征方法来量化围绕索引感染的距离,在该距离内,其他感染显著聚集。
本研究的数据来自巴西、泰国、柬埔寨和所罗门群岛在 2012 年至 2018 年期间进行的横断面调查。家庭住址通过 GPS 记录,参与者的指血样本通过 PCR 检测疟原虫感染。本研究还包括巴西和泰国的队列研究,这些研究从 2013 年到 2014 年进行了为期一年的每月采样。在索引感染周围的距离(以及在队列研究中逐月增加的时间间隔)逐渐增大的情况下,计算 PCR 确认感染的患病率。统计显著性定义为在感染位置随机重新分配后的自举零分布 95%分位数间隔之外的患病率。
在大多数研究地点,靠近索引感染的地方,间日疟原虫和恶性疟原虫感染的患病率较高,随着距离的增加而降低,例如在柬埔寨的调查中,从 0km 处的 21.3%到全球研究中间日疟原虫的流行率为 6.4%。在队列研究中,随着时间窗口的延长,聚集性降低。从索引感染到患病率降低 50%的距离范围从 25m 到 3175m,在全球研究中流行率较低的情况下,距离倾向于更短。
间日疟原虫和恶性疟原虫感染的空间特征表明,在一组不同的研究地点存在空间聚集性,量化了聚集发生的距离。该方法为疟疾流行病学提供了一种新工具,可能为反应性干预策略提供信息,包括围绕检测到的感染选择操作半径,从而加强消除疟疾的努力。