Identifying clustering of cholera cases using geospatial analysis in Kolkata and surrounding districts: data from patients at tertiary care referral hospitals

IF 5 Q1 HEALTH CARE SCIENCES & SERVICES The Lancet regional health. Southeast Asia Pub Date : 2024-11-21 DOI:10.1016/j.lansea.2024.100510
Rounik Talukdar , Suman Kanungo , Kei Kitahara , Goutam Chowdhury , Debmalya Mitra , Asish Kumar Mukhopadhyay , Alok Kumar Deb , Pallavi Indwar , Biswanath Sharma Sarkar , Sandip Samanta , Basilua Andre Muzembo , Ayumu Ohno , Shin-ichi Miyoshi , Shanta Dutta
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Abstract

Background

Cholera cases have increased globally across the Eastern Mediterranean, Africa, Southeast Asia, and parts of Europe since early 2024. This study aims to identify cholera hotspots and understand the spatial distribution of cholera in Kolkata and surrounding regions, a key cholera reservoir. Additionally, we examine sociodemographic factors and aspects related to water, sanitation, and hygiene (WASH).

Methods

Cholera clusters were detected using kernel density estimation and spatial autocorrelation through Global Moran’s-I statistics, with local cluster patterns examined using Local Moran’s-I statistics. Cholera cases from August 2021 to December 2023, treated at two tertiary care facilities in Kolkata: Infectious Diseases and Beleghata General Hospital and Dr. B C Roy Post Graduate Institute of Paediatric Sciences Hospital were included. Additionally, through a case–control study, 196 culture-confirmed cholera cases and 764 age/sex-matched neighborhood controls were enrolled, to investigate cholera risk factors.

Findings

Spatial analysis revealed a concentration of 196 cholera cases in Kolkata and its surrounding regions of Howrah, Hooghly, and North and South 24 Parganas. Hotspot analysis showed significant clustering in several Kolkata wards (31, 33, 56, 46, 57, 58, 59, 61, 66, 71, and 107), particularly in the northern, central, and east Kolkata wetlands areas (Global Moran’s I statistic = 0.14, p < 0.001). These clusters had proximity between cases, with a median distance of 187.7 m, and 25.5% of cases as close as 73.9 m apart, suggesting localized transmission. Hotspots were identified with an average distance of 1600 m between them. Local Moran’s I analysis found dense “high–high” clusters in these areas (p < 0.01), with a mean Moran’s I index of 0.3, (range 0.1–4.6). The case–control study revealed that males were more likely to contract cholera, with an adjusted odds ratio of 2.4 (p < 0.01). There was no significant association found between cholera infection and sociodemographic factors or various WASH practices.

Interpretation

The findings emphasize the importance of targeted interventions, especially in identified hotspots, to mitigate cholera transmission. Addressing Socio-economic, and environmental factors especially improvement in WASH practices may further enhance prevention effects.

Funding

The author KK, received funding from the program of the Japan Initiative for Global Research Network on Infectious Diseases, (grant id: JP23wm0125004), from the Ministry of Education, Culture, Sports, Science and Technology in Japan, and Japan Agency for Medical Research and Development.
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利用地理空间分析识别加尔各答及周边地区的霍乱病例群:来自三级转诊医院患者的数据
背景自 2024 年初以来,全球东地中海、非洲、东南亚和欧洲部分地区的霍乱病例有所增加。本研究旨在确定霍乱热点地区,并了解霍乱主要聚集地加尔各答及周边地区的霍乱空间分布情况。此外,我们还考察了社会人口因素以及与水、环境卫生和个人卫生(WASH)相关的方面。方法使用核密度估计和空间自相关性(通过全局莫兰 I 统计法)检测霍乱集群,并使用局部莫兰 I 统计法考察局部集群模式。研究纳入了 2021 年 8 月至 2023 年 12 月在加尔各答两家三级医疗机构治疗的霍乱病例:传染病与贝勒加塔综合医院和 B.C.Roy 博士儿科研究生院。此外,通过病例对照研究,还纳入了 196 例经培养确诊的霍乱病例和 764 例年龄/性别匹配的邻近地区对照者,以调查霍乱风险因素。热点分析表明,加尔各答的几个区(31、33、56、46、57、58、59、61、66、71 和 107),尤其是加尔各答北部、中部和东部的湿地地区(全球莫兰 I 统计量 = 0.14,p <0.001)有明显的聚集现象。这些集群的病例之间距离很近,中位距离为 187.7 米,25.5% 的病例之间相距 73.9 米,这表明存在局部传播。热点地区之间的平均距离为 1600 米。局部莫兰 I 指数分析发现,这些地区存在密集的 "高-高 "聚集区(p < 0.01),平均莫兰 I 指数为 0.3(范围 0.1-4.6)。病例对照研究显示,男性更容易感染霍乱,调整后的几率比为 2.4(p < 0.01)。霍乱感染与社会人口因素或各种讲卫生运动之间没有明显的关联。作者KK获得了日本文部科学省和日本医学研究开发机构的日本全球传染病研究网络计划(资助编号:JP23wm0125004)的资助。
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