Scholarlink

Objectives <p>To analyze spatiotemporal clustering patterns of severe hand foot and mouth disease (HFMD) in children aged ≤ 5 years, quantify the associations between meteorological factors and severe HFMD incidence, and evaluate incidence shifts associated with the COVID-19 pandemic in Shandong Province, China, during 2013–2023.</p> Methods <p>Spatial autocorrelation analysis (Moran’s I) and spatiotemporal cluster detection (SaTScan) identified high-risk zones. Generalized additive models (GAM) assessed nonlinear associations between meteorological factors (temperature, humidity, precipitation) and severe HFMD incidence. QGIS visualized geographic patterns.</p> Results <p>Among 763,191 HFMD cases (17,212 severe, 2.32%), annual incidence declined from 121.70/100,000 (2014) to 15.81/100,000 (2022) during COVID-19, with partial resurgence in 2023 (46.63/100,000). Severe cases exhibited significant spatial clustering (Moran’s I = 0.219–0.415; <i>p</i> ≤ 0.05) with westward-to-eastward high-risk cluster migration. Seasonal peaks (April–September) showed 62%–79% reductions post-2021 (<i>p</i> &lt; 0.01). Temperature (ρ = 0.689, <i>p</i> &lt; 0.01) and humidity (optimal threshold: 55%–60%, EDF = 2.43, <i>p</i> = 0.023) were the factors most strongly associated with incidence, supported by GAM: near-linear temperature effects (EDF = 1.41, <i>p</i> &lt; 0.001), precipitation saturation (&gt; 20&#xa0;mm/week, EDF = 1.24, <i>p</i> = 0.045), and persistent seasonality (EDF = 4.02, <i>p</i> &lt; 0.001).</p> Conclusions <p>Severe HFMD epidemiology in Shandong is jointly influenced by meteorological factors (nonlinear humidity effects) and spatiotemporal dynamics, with west-to-east transmission patterns and post-pandemic behavioral-environmental interactions. Targeted vaccination and climate-adaptive surveillance during April–September peaks in identified clusters are critical for mitigation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

West-to-East transmission clusters and meteorological associations for severe hand foot and mouth disease in Shandong Province: a geospatial and GAM analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月30日

查看全文
  • Xiaoying Xu,
  • Jianxing Wang,
  • Huifeng Sun,
  • Zequn Wang,
  • Zhen Dong,
  • Zengqiang Kou,
  • Hongling Wen

摘要

Objectives

To analyze spatiotemporal clustering patterns of severe hand foot and mouth disease (HFMD) in children aged ≤ 5 years, quantify the associations between meteorological factors and severe HFMD incidence, and evaluate incidence shifts associated with the COVID-19 pandemic in Shandong Province, China, during 2013–2023.

Methods

Spatial autocorrelation analysis (Moran’s I) and spatiotemporal cluster detection (SaTScan) identified high-risk zones. Generalized additive models (GAM) assessed nonlinear associations between meteorological factors (temperature, humidity, precipitation) and severe HFMD incidence. QGIS visualized geographic patterns.

Results

Among 763,191 HFMD cases (17,212 severe, 2.32%), annual incidence declined from 121.70/100,000 (2014) to 15.81/100,000 (2022) during COVID-19, with partial resurgence in 2023 (46.63/100,000). Severe cases exhibited significant spatial clustering (Moran’s I = 0.219–0.415; p ≤ 0.05) with westward-to-eastward high-risk cluster migration. Seasonal peaks (April–September) showed 62%–79% reductions post-2021 (p < 0.01). Temperature (ρ = 0.689, p < 0.01) and humidity (optimal threshold: 55%–60%, EDF = 2.43, p = 0.023) were the factors most strongly associated with incidence, supported by GAM: near-linear temperature effects (EDF = 1.41, p < 0.001), precipitation saturation (> 20 mm/week, EDF = 1.24, p = 0.045), and persistent seasonality (EDF = 4.02, p < 0.001).

Conclusions

Severe HFMD epidemiology in Shandong is jointly influenced by meteorological factors (nonlinear humidity effects) and spatiotemporal dynamics, with west-to-east transmission patterns and post-pandemic behavioral-environmental interactions. Targeted vaccination and climate-adaptive surveillance during April–September peaks in identified clusters are critical for mitigation.