The Kids Research Institute of Australia, Perth, WA, Australia.
Curtin University, Bentley, WA, Australia.
Malar J. 2024 Oct 5;23(1):297. doi: 10.1186/s12936-024-05103-w.
Namibia, a low malaria transmission country targeting elimination, has made substantial progress in reducing malaria burden through improved case management, widespread indoor residual spraying and distribution of insecticidal nets. The country's diverse landscape includes regions with varying population densities and geographical niches, with the north of the country prone to periodic outbreaks. As Namibia approaches elimination, malaria transmission has clustered into distinct foci, the identification of which is essential for deployment of targeted interventions to attain the southern Africa Elimination Eight Initiative targets by 2030. Geospatial modelling provides an effective mechanism to identify these foci, synthesizing aggregate routinely collected case counts with gridded environmental covariates to downscale case data into high-resolution risk maps.
This study introduces innovative infectious disease mapping techniques to generate high-resolution spatio-temporal risk maps for malaria in Namibia. A two-stage approach is employed to create maps using statistical Bayesian modelling to combine environmental covariates, population data, and clinical malaria case counts gathered from the routine surveillance system between 2018 and 2021.
A fine-scale spatial endemicity surface was produced for annual average incidence, followed by a spatio-temporal modelling of seasonal fluctuations in weekly incidence and aggregated further to district level. A seasonal profile was inferred across most districts of the country, where cases rose from late December/early January to a peak around early April and then declined rapidly to a low level from July to December. There was a high degree of spatial heterogeneity in incidence, with much higher rates observed in the northern part and some local epidemic occurrence in specific districts sporadically.
While the study acknowledges certain limitations, such as population mobility and incomplete clinical case reporting, it underscores the importance of continuously refining geostatistical techniques to provide timely and accurate support for malaria elimination efforts. The high-resolution spatial risk maps presented in this study have been instrumental in guiding the Namibian Ministry of Health and Social Services in prioritizing and targeting malaria prevention efforts. This two-stage spatio-temporal approach offers a valuable tool for identifying hotspots and monitoring malaria risk patterns, ultimately contributing to the achievement of national and sub-national elimination goals.
纳米比亚是一个疟疾传播水平较低的国家，目标是消除疟疾。通过改善病例管理、广泛使用室内滞留喷洒和分发驱虫蚊帐，该国在降低疟疾负担方面取得了重大进展。该国的地形多样，包括人口密度和地理小生境各不相同的地区，北部地区容易周期性爆发疟疾。随着纳米比亚向消除疟疾迈进，疟疾传播已经集中到不同的焦点地区，确定这些焦点地区对于部署有针对性的干预措施以实现到 2030 年实现南部非洲消除疟疾倡议的目标至关重要。地理空间建模提供了一种有效的机制，可以确定这些焦点地区，将常规收集的病例汇总数据与网格化环境协变量结合起来，将病例数据缩小到高分辨率的风险图中。
本研究引入了创新的传染病制图技术，为纳米比亚的疟疾生成高分辨率的时空风险图。使用统计贝叶斯模型的两阶段方法来创建地图，该方法结合了环境协变量、人口数据和 2018 年至 2021 年期间从常规监测系统收集的临床疟疾病例计数。
制作了年度平均发病率的精细空间流行表面，然后对每周发病率的季节性波动进行时空建模，并进一步汇总到地区级别。推断出该国大部分地区的季节性概况，病例从 12 月底/1 月初开始上升，到 4 月初达到高峰，然后从 7 月到 12 月迅速下降到低水平。发病率存在高度的空间异质性，北部地区的发病率要高得多，一些地区偶尔会出现局部流行。
尽管该研究承认存在一些局限性，例如人口流动和不完全的临床病例报告，但它强调了不断改进地质统计学技术的重要性，以提供及时、准确的支持，助力消除疟疾工作。本研究中提出的高分辨率空间风险图对于指导纳米比亚卫生部和社会服务部优先考虑和针对疟疾预防工作起到了重要作用。这种两阶段时空方法为识别热点和监测疟疾风险模式提供了有价值的工具，最终有助于实现国家和次国家消除疟疾的目标。
