Department of Epidemiology of Infectious Diseases and Surveillance, National Institute of Public Health-National Institute of Hygiene, 00-791 Warsaw, Poland.
Department of Population Health Monitoring and Analysis, National Institute of Public Health-National Institute of Hygiene, 00-791 Warsaw, Poland.
Int J Environ Res Public Health. 2018 Apr 4;15(4):677. doi: 10.3390/ijerph15040677.
During 1999–2012, 77% of the cases of tick-borne encephalitis (TBE) were recorded in two out of 16 Polish provinces. However, historical data, mostly from national serosurveys, suggest that the disease could be undetected in many areas. The aim of this study was to identify which routinely-measured meteorological, environmental, and socio-economic factors are associated to TBE human risk across Poland, with a particular focus on areas reporting few cases, but where serosurveys suggest higher incidence. We fitted a zero-inflated Poisson model using data on TBE incidence recorded in 108 NUTS-5 administrative units in high-risk areas over the period 1999–2012. Subsequently we applied the best fitting model to all Polish municipalities. Keeping the remaining variables constant, the predicted rate increased with the increase of air temperature over the previous 10–20 days, precipitation over the previous 20–30 days, in forestation, forest edge density, forest road density, and unemployment. The predicted rate decreased with increasing distance from forests. The map of predicted rates was consistent with the established risk areas. It predicted, however, high rates in provinces considered TBE-free. We recommend raising awareness among physicians working in the predicted high-risk areas and considering routine use of household animal surveys for risk mapping.
在 1999 年至 2012 年期间,波兰有 16 个省份中的 2 个省份记录了 77%的蜱传脑炎(TBE)病例。然而,历史数据(主要来自全国血清调查)表明,许多地区可能存在未被发现的病例。本研究的目的是确定哪些常规测量的气象、环境和社会经济因素与波兰各地的 TBE 人类风险相关,特别是在报告病例较少但血清调查表明发病率较高的地区。我们使用了 1999 年至 2012 年高风险地区的 108 个 NUTS-5 行政单位记录的 TBE 发病率数据,拟合了一个零膨胀泊松模型。随后,我们将最佳拟合模型应用于所有波兰市。在保持其余变量不变的情况下,预测发病率随着前 10-20 天空气温度的升高、前 20-30 天降水的增加、森林覆盖率、森林边缘密度、森林道路密度和失业率的增加而增加。预测发病率随着与森林距离的增加而降低。预测发病率图与已确定的风险区域一致。然而,它预测了被认为没有 TBE 的省份的高发病率。我们建议提高在预测高风险地区工作的医生的意识,并考虑常规使用家庭动物调查进行风险制图。