Department of Geography, University of Calcutta, Kolkata, 700019, India.
Malar J. 2024 Jun 17;23(1):189. doi: 10.1186/s12936-024-05015-9.
Malaria, a prominent vector borne disease causing over a million annual cases worldwide, predominantly affects vulnerable populations in the least developed regions. Despite their preventable and treatable nature, malaria remains a global public health concern. In the last decade, India has faced a significant decline in malaria morbidity and mortality. As India pledged to eliminate malaria by 2030, this study examined a decade of surveillance data to uncover space-time clustering and seasonal trends of Plasmodium vivax and Plasmodium falciparum malaria cases in West Bengal.
Seasonal and trend decomposition using Loess (STL) was applied to detect seasonal trend and anomaly of the time series. Univariate and multivariate space-time cluster analysis of both malaria cases were performed at block level using Kulldorff's space-time scan statistics from April 2011 to March 2021 to detect statistically significant space-time clusters.
From the time series decomposition, a clear seasonal pattern is visible for both malaria cases. Statistical analysis indicated considerable high-risk P. vivax clusters, particularly in the northern, central, and lower Gangetic areas. Whereas, P. falciparum was concentrated in the western region with a significant recent transmission towards the lower Gangetic plain. From the multivariate space-time scan statistics, the co-occurrence of both cases were detected with four significant clusters, which signifies the regions experiencing a greater burden of malaria cases.
Seasonal trends from the time series decomposition analysis show a gradual decline for both P. vivax and P. falciparum cases in West Bengal. The space-time scan statistics identified high-risk blocks for P. vivax and P. falciparum malaria and its co-occurrence. Both malaria types exhibit significant spatiotemporal variations over the study area. Identifying emerging high-risk areas of P. falciparum malaria over the Gangetic belt indicates the need for more research for its spatial shifting. Addressing the drivers of malaria transmission in these diverse clusters demands regional cooperation and strategic strategies, crucial steps towards overcoming the final obstacles in malaria eradication.
疟疾是一种主要通过媒介传播的疾病,每年在全球造成超过 100 万例病例,主要影响最不发达国家的脆弱人群。尽管疟疾可以预防和治疗,但它仍然是全球公共卫生关注的问题。在过去的十年中,印度的疟疾发病率和死亡率显著下降。随着印度承诺到 2030 年消除疟疾,本研究调查了十年的监测数据,以揭示西孟加拉邦间日疟原虫和恶性疟原虫疟疾病例的时空聚类和季节性趋势。
采用局部多项式拟合(Loess)季节和趋势分解(STL)来检测时间序列的季节性趋势和异常。从 2011 年 4 月至 2021 年 3 月,采用 Kulldorff 的时空扫描统计,对两种疟疾病例进行了单变量和多变量时空聚类分析,以检测具有统计学意义的时空聚类。
从时间序列分解可以看出,两种疟疾病例都有明显的季节性模式。统计分析表明,高危间日疟原虫病例主要集中在北部、中部和恒河下游地区。而恶性疟原虫则集中在西部地区,最近向恒河下游平原的传播明显增加。从多变量时空扫描统计来看,两种病例同时发生,共检测到 4 个显著聚类,表明这些地区疟疾病例负担较重。
时间序列分解分析的季节性趋势显示,西孟加拉邦间日疟原虫和恶性疟原虫病例数量逐渐减少。时空扫描统计确定了间日疟原虫和恶性疟原虫疟疾以及两者同时发生的高危区块。两种疟疾类型在研究区域内都表现出显著的时空变化。在恒河带发现恶性疟原虫疟疾的新的高危地区,表明需要对其空间转移进行更多的研究。解决这些不同聚类中疟疾传播的驱动因素需要区域合作和战略策略,这是消除疟疾的最后障碍的关键步骤。