Department of Tropical Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Department of Epidemiology, Institute of Malariology, Parasitology, and Entomology Quy Nhon, Quy Nhon, Binh Dinh, Vietnam.
Malar J. 2024 Aug 24;23(1):258. doi: 10.1186/s12936-024-05074-y.
Despite the successful efforts in controlling malaria in Vietnam, the disease remains a significant health concern, particularly in Central Vietnam. This study aimed to assess correlations between environmental, climatic, and socio-economic factors in the district with malaria cases.
The study was conducted in 15 provinces in Central Vietnam from January 2018 to December 2022. Monthly malaria cases were obtained from the Institute of Malariology, Parasitology, and Entomology Quy Nhon, Vietnam. Environmental, climatic, and socio-economic data were retrieved using a Google Earth Engine script. A multivariable Zero-inflated Poisson regression was undertaken using a Bayesian framework with spatial and spatiotemporal random effects with a conditional autoregressive prior structure. The posterior random effects were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling.
There was a total of 5,985 Plasmodium falciparum and 2,623 Plasmodium vivax cases during the study period. Plasmodium falciparum risk increased by five times (95% credible interval [CrI] 4.37, 6.74) for each 1-unit increase of normalized difference vegetation index (NDVI) without lag and by 8% (95% CrI 7%, 9%) for every 1ºC increase in maximum temperature (TMAX) at a 6-month lag. While a decrease in risk of 1% (95% CrI 0%, 1%) for a 1 mm increase in precipitation with a 6-month lag was observed. A 1-unit increase in NDVI at a 1-month lag was associated with a four-fold increase (95% CrI 2.95, 4.90) in risk of P. vivax. In addition, the risk increased by 6% (95% CrI 5%, 7%) and 3% (95% CrI 1%, 5%) for each 1ºC increase in land surface temperature during daytime with a 6-month lag and TMAX at a 4-month lag, respectively. Spatial analysis showed a higher mean malaria risk of both species in the Central Highlands and southeast parts of Central Vietnam and a lower risk in the northern and north-western areas.
Identification of environmental, climatic, and socio-economic risk factors and spatial malaria clusters are crucial for designing adaptive strategies to maximize the impact of limited public health resources toward eliminating malaria in Vietnam.
尽管越南在控制疟疾方面取得了成功，但该疾病仍然是一个重大的健康问题，尤其是在越南北部地区。本研究旨在评估该地区环境、气候和社会经济因素与疟疾发病之间的相关性。
本研究于 2018 年 1 月至 2022 年 12 月在越南北部 15 个省份进行。每月的疟疾病例数据来自越南 Quy Nhon 寄生虫学、疟疾学和昆虫学研究所。使用 Google Earth Engine 脚本检索环境、气候和社会经济数据。采用贝叶斯框架下的多变量零膨胀泊松回归，具有空间和时空随机效应，条件自回归先验结构。使用贝叶斯马尔可夫链蒙特卡罗模拟和吉布斯抽样估计后验随机效应。
在研究期间，共发生 5985 例恶性疟原虫和 2623 例间日疟原虫病例。无滞后的归一化差异植被指数（NDVI）每增加 1 个单位，风险增加 5 倍（95%可信区间[CrI] 4.37，6.74），滞后 6 个月的最高温度（TMAX）每增加 1°C，风险增加 8%（95%CrI 7%，9%）。然而，滞后 6 个月的降水量每增加 1 毫米，风险降低 1%（95%CrI 0%，1%）。滞后 1 个月的 NDVI 每增加 1 个单位，间日疟原虫的风险增加 4 倍（95%CrI 2.95，4.90）。此外，滞后 6 个月的白天陆面温度和滞后 4 个月的 TMAX 每增加 1°C，风险分别增加 6%（95%CrI 5%，7%）和 3%（95%CrI 1%，5%）。空间分析显示，两种疟疾病种在越南北部高原和中南部的平均疟疾风险较高，而在北部和西北部地区的风险较低。
识别环境、气候和社会经济风险因素以及空间疟疾聚集区对于制定适应性策略以最大限度地利用有限的公共卫生资源消除越南的疟疾至关重要。
