Asokan Dinesh, Bommu Siva Prasad Reddy, Mall Anjali, Pardeshi Geeta
Community Medicine, Grant Government Medical College and Sir JJ Group of Hospitals, Mumbai, IND.
Cureus. 2024 Aug 17;16(8):e67068. doi: 10.7759/cureus.67068. eCollection 2024 Aug.
Introduction This study examines the geographic distribution and temporal trends of Zika virus (ZIKV) outbreaks in India from 2016 to 2023 using data from the Integrated Disease Surveillance Programme (IDSP). The burden of ZIKV in India has risen due to its rapid spread and significant health impacts. Existing literature highlights seasonal and geographic patterns but lacks a comprehensive, long-term analysis specific to India. This study addresses this gap by analyzing trends over seven years to inform better public health responses. Methods A secondary data analysis was conducted using publicly available data from the IDSP on reported Zika cases from January 2016 to December 2023. Descriptive statistical methods and geographic information system (GIS) mapping techniques were employed to analyze the geographic distribution and temporal trends of ZIKV outbreaks in India. The data were analyzed and visualized using R software version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria), with heat maps and choropleth maps to identify hotspots, and line diagrams to identify temporal trends. Results Zika outbreaks predominantly occurred during the post-monsoon season, accounting for 47.62% (n = 10) of the total 21 outbreaks, followed by the monsoon season with 33.33% (n = 7), and summer with 19.05% (n = 4). Two deaths were reported during a significant outbreak in Madhya Pradesh in 2018. Temporal trends indicated notable spikes in cases in 2018 (131 cases) and 2021 (234 cases), with no cases reported in 2019 and 2020. The geographic distribution maps highlighted significant concentrations of ZIKV outbreaks in specific districts within Uttar Pradesh, Madhya Pradesh, and Kerala. Discussion The study identified seasonal patterns, with most cases occurring in the post-monsoon season. The geographic spread of the ZIKV was observed in eight states from 2016 to 2023. GIS identified three hotspots in Uttar Pradesh, Madhya Pradesh, and Kerala. Conclusion The study highlights the need for heightened surveillance and targeted intervention preparedness during high-risk seasons. Enhancing testing facilities and data reporting systems could improve outbreak identification, management, and response.
引言 本研究利用综合疾病监测计划（IDSP）的数据，调查了2016年至2023年印度寨卡病毒（ZIKV）疫情的地理分布和时间趋势。由于ZIKV的迅速传播和重大健康影响，印度的ZIKV负担有所上升。现有文献强调了季节性和地理模式，但缺乏针对印度的全面、长期分析。本研究通过分析七年的趋势来填补这一空白，为更好的公共卫生应对提供信息。方法 使用IDSP公开提供的2016年1月至2023年12月报告的寨卡病例数据进行二次数据分析。采用描述性统计方法和地理信息系统（GIS）绘图技术分析印度ZIKV疫情的地理分布和时间趋势。使用R软件版本4.3.2（奥地利维也纳的R统计计算基础）对数据进行分析和可视化，用热图和分级统计图识别热点地区，用折线图识别时间趋势。结果 寨卡疫情主要发生在季风后季节，占21次疫情总数的47.62%（n = 10），其次是季风季节，占33.33%（n = 7），夏季占19.05%（n = 4）。2018年在中央邦的一次重大疫情中报告了两例死亡病例。时间趋势表明，2018年（131例）和2021年（234例）病例数显著激增，2019年和2020年无病例报告。地理分布图突出显示了北方邦、中央邦和喀拉拉邦特定地区ZIKV疫情的显著集中情况。讨论 该研究确定了季节性模式，大多数病例发生在季风后季节。2016年至2023年期间，在八个邦观察到了ZIKV的地理传播。GIS在北方邦、中央邦和喀拉拉邦确定了三个热点地区。结论 该研究强调在高风险季节需要加强监测和有针对性的干预准备。加强检测设施和数据报告系统可以改善疫情识别、管理和应对。
