Kaneko Yuji
General Medicine, HITO Medical Center, Ehime, JPN.
Cureus. 2025 May 16;17(5):e84208. doi: 10.7759/cureus.84208. eCollection 2025 May.
Background Understanding regional disparities in COVID-19 incidence and the factors influencing them is essential for effective public health responses. In Japan, particularly in Hokkaido, significant differences in case burden have been observed across municipalities. This study aimed to describe the epidemiological patterns of COVID-19 in Hokkaido by adjusting for age structure and to examine the association between railway-based population mobility and regional case burden. Method We categorized all municipalities in Hokkaido into five public health center jurisdictions: Sapporo, Otaru, Asahikawa, Hakodate, and Other Areas. COVID-19 incidence was assessed across the third to sixth waves of the pandemic (November 2020 to June 2022). To account for demographic differences, age-standardized incidence ratios (SIR) were calculated using national age-specific incidence rates and the indirect standardization method. Data on confirmed cases were obtained from government open datasets, and population mobility was measured using railway transport density from the Hokkaido Railway Company. Statistical analyses included chi-square tests and multiple regression analysis, including both full and simplified models to assess statistical associations, with the latter addressing multicollinearity among demographic variables. Results A total of 378,281 cases were reported during the study period, with the highest burden in Sapporo. SIR exceeded 1.0 in Sapporo, Otaru, and Asahikawa during multiple waves, indicating higher-than-expected incidence after age adjustment. Notably, Sapporo exhibited elevated SIR, particularly among older adults, while Otaru and Asahikawa showed higher rates among those aged 20-50 years. In regression analyses, railway transport density showed a statistically significant positive association with SIR in both univariable (p = 0.002) and simplified multivariable models that included the effective reproduction number (Rt). In the multivariable model, railway transport density remained positively associated (p < 0.001), while Rt showed a negative association (p = 0.032), with an adjusted R² of 0.524. These findings suggest that railway-based mobility and real-time transmission dynamics jointly influence regional disparities in COVID-19 burden. Conclusion This study highlights the significant impact of railway-based population mobility on COVID-19 transmission within Hokkaido, Japan. Age-standardized comparisons revealed regional variations in risk, likely influenced by urban proximity and transport infrastructure. These findings support the incorporation of geographic and mobility-related metrics into geographically tailored public health policies. Further research using larger datasets and multimodal transport indicators is recommended to validate and expand upon these insights.
背景 了解新冠疫情发病率的地区差异及其影响因素对于有效的公共卫生应对至关重要。在日本,尤其是北海道,各自治市的病例负担存在显著差异。本研究旨在通过调整年龄结构来描述北海道新冠疫情的流行模式,并研究基于铁路的人口流动与地区病例负担之间的关联。方法 我们将北海道的所有自治市分为五个公共卫生中心辖区:札幌、小樽、旭川、函馆和其他地区。在疫情的第三至第六波(2020年11月至2022年6月)期间评估新冠疫情发病率。为了考虑人口统计学差异,使用全国特定年龄发病率和间接标准化方法计算年龄标准化发病率比(SIR)。确诊病例数据来自政府开放数据集,使用北海道铁路公司的铁路运输密度来衡量人口流动。统计分析包括卡方检验和多元回归分析,包括完整模型和简化模型以评估统计关联,后者用于解决人口统计学变量之间的多重共线性问题。结果 在研究期间共报告了378,281例病例,札幌的负担最重。在多波疫情期间,札幌、小樽和旭川的SIR超过1.0,表明年龄调整后发病率高于预期。值得注意的是,札幌的SIR升高,尤其是在老年人中,而小樽和旭川在20至50岁人群中的发病率较高。在回归分析中,铁路运输密度在单变量分析(p = 0.002)和包括有效再生数(Rt)的简化多变量模型中均与SIR呈统计学显著正相关。在多变量模型中,铁路运输密度仍呈正相关(p < 0.001),而Rt呈负相关(p = 0.032),调整后的R²为0.524。这些发现表明,基于铁路的流动性和实时传播动态共同影响新冠疫情负担的地区差异。结论 本研究强调了基于铁路的人口流动对日本北海道内新冠疫情传播的重大影响。年龄标准化比较揭示了风险的地区差异,可能受城市距离和交通基础设施的影响。这些发现支持将地理和流动性相关指标纳入因地制宜的公共卫生政策。建议使用更大的数据集和多式联运指标进行进一步研究,以验证和扩展这些见解。