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海地低传播环境中的疟疾热点检测。

Detecting Malaria Hotspots in Haiti, a Low-Transmission Setting.

机构信息

1Centers for Disease Control and Prevention, Division of Global Health Protection, Atlanta, Georgia.

2Ministry of Public Health and Population, National Malaria Control Program, Port-au-Prince, Haiti.

出版信息

Am J Trop Med Hyg. 2021 Apr 19;104(6):2108-2116. doi: 10.4269/ajtmh.20-0465.

DOI:10.4269/ajtmh.20-0465
PMID:33872208
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8176511/
Abstract

In 2006, Haiti committed to malaria elimination when the transmission was thought to be low, but before robust national parasite prevalence estimates were available. In 2011, the first national population-based survey confirmed the national malaria parasite prevalence was < 1%. In both 2014 and 2015, Haiti reported approximately 17,000 malaria cases identified passively at health facilities. To detect malaria transmission hotspots for targeting interventions, the National Malaria Control Program (NMCP) piloted an enhanced geographic information surveillance system in three departments with relatively high-, medium-, and low-transmission areas. From October 2014-September 2015, NMCP staff abstracted health facility records of confirmed malaria cases from 59 health facilities and geo-located patients' households. Household locations were aggregated to 1-km2 grid cells to calculate cumulative incidence rates (CIRs) per 1,000 persons. Spatial clustering of CIRs were tested using Getis-Ord Gi* analysis. Space-time permutation models searched for clusters up to 6 km in distance using a 1-month malaria transmission window. Of the 2,462 confirmed cases identified from health facility records, 58% were geo-located. Getis-Ord Gi* analysis identified 43 1-km2 hotspots in coastal and inland areas that overlapped primarily with 13 space-time clusters (size: 0.26-2.97 km). This pilot describes the feasibility of detecting malaria hotspots in resource-poor settings. More data from multiple years and serological household surveys are needed to assess completeness and hotspot stability. The NMCP can use these pilot methods and results to target foci investigations and malaria interventions more accurately.

摘要

2006 年,海地在认为传播率较低的时候就承诺消除疟疾,但当时还没有可靠的全国寄生虫流行率估计数。2011 年,第一次全国人口为基础的调查证实全国疟原虫流行率<1%。2014 年和 2015 年,海地报告了约 17000 例在医疗机构被动发现的疟疾病例。为了发现疟疾传播热点以进行干预,国家疟疾控制规划(NMCP)在三个部门试点了一个强化地理信息监测系统,这些部门的传播率相对较高、中等和较低。2014 年 10 月至 2015 年 9 月,NMCP 工作人员从 59 个医疗机构的记录中提取了确诊疟疾病例的信息,并对患者家庭进行了地理定位。家庭位置被汇总到 1 平方公里的网格单元,以计算每 1000 人累计发病率(CIR)。利用 Getis-Ord Gi分析测试了 CIR 的空间聚类。时空置换模型使用 1 个月的疟疾传播窗口搜索距离达 6 公里的集群。从医疗机构记录中发现的 2462 例确诊病例中,58%进行了地理定位。Getis-Ord Gi分析在沿海和内陆地区发现了 43 个 1 平方公里的热点,这些热点主要与 13 个时空集群(大小:0.26-2.97 公里)重叠。该试点描述了在资源匮乏环境中检测疟疾热点的可行性。需要来自多年和血清家庭调查的更多数据来评估完整性和热点稳定性。NMCP 可以使用这些试点方法和结果,更准确地针对重点调查和疟疾干预。

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