Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outb...Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outbreak. Method: Lassa fever dataset from January 2014 to December 2019 was obtained from the State Ministry of Health. Variables analyzed include date of onset of symptom, age, gender, place (Local Government Area, LGA) and outcome of laboratory test. Data were summarized using frequencies, proportions, chart and maps. Results: From January 2014 and December 2019, 2141 suspected LF cases were reported. Of these, 551 cases were laboratory confirmed with 134 deaths recorded. The LF cases (suspected vs. confirmed) reported increased in 2016 (73 vs. 19), 2017 (207 vs. 76), 2018 (452 vs. 159) and 2019 (856 vs. 285) respectively. Most of the confirmed cases (89.5%) were ≥15 years while more than half (53.7%) were males. Prior to 2016, only two LGAs (Owo and Ose) recorded continued transmission of the disease. However, between 2016 and 2019, the disease had spread to 8 neighboring LGAs (P < 0.001) with the CFR declining from 67% in 2015 to 20% in 2019. Conclusion: We found an unusual increase in the suspected LF cases reported between January 2016 and December 2019 with a corresponding increase in the confirmed cases and high annual case fatality rates. Hence, we recommend intensified surveillance activities to enhance timely reporting of cases and laboratory confirmation to ensure early commencement of treatment to reduce the case fatality rate.展开更多
中国森林生物灾害发生频繁,整理与制作相关灾害数据集对森林生物灾害系统监测布局、风险评估及防控决策具有重要的科学意义。本数据集在整合《中国林业统计年鉴》(1998–2017)和《中国林业和草原统计年鉴》(2018–2019)发布的年度森林...中国森林生物灾害发生频繁,整理与制作相关灾害数据集对森林生物灾害系统监测布局、风险评估及防控决策具有重要的科学意义。本数据集在整合《中国林业统计年鉴》(1998–2017)和《中国林业和草原统计年鉴》(2018–2019)发布的年度森林生物灾害面积数据及森林资源面积数据基础上,构建并计算得到全国及各省区灾害总体及不同类型生物灾害的森林生物灾害发生指数(Forest Pest Outbreak index,FPOI)、灾害发生率(Forest Pest Occurrence Area Rate,FPOAR)两个系列指标集。验证表明,上述两个指标及距平数据集能够较好地反映出不同尺度中国森林生物灾害时空分布及变化特征,可为森林生物灾害格局与趋势分析及影响因素研究、精准地防控决策提供有效数据支撑。展开更多
文摘Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outbreak. Method: Lassa fever dataset from January 2014 to December 2019 was obtained from the State Ministry of Health. Variables analyzed include date of onset of symptom, age, gender, place (Local Government Area, LGA) and outcome of laboratory test. Data were summarized using frequencies, proportions, chart and maps. Results: From January 2014 and December 2019, 2141 suspected LF cases were reported. Of these, 551 cases were laboratory confirmed with 134 deaths recorded. The LF cases (suspected vs. confirmed) reported increased in 2016 (73 vs. 19), 2017 (207 vs. 76), 2018 (452 vs. 159) and 2019 (856 vs. 285) respectively. Most of the confirmed cases (89.5%) were ≥15 years while more than half (53.7%) were males. Prior to 2016, only two LGAs (Owo and Ose) recorded continued transmission of the disease. However, between 2016 and 2019, the disease had spread to 8 neighboring LGAs (P < 0.001) with the CFR declining from 67% in 2015 to 20% in 2019. Conclusion: We found an unusual increase in the suspected LF cases reported between January 2016 and December 2019 with a corresponding increase in the confirmed cases and high annual case fatality rates. Hence, we recommend intensified surveillance activities to enhance timely reporting of cases and laboratory confirmation to ensure early commencement of treatment to reduce the case fatality rate.
文摘中国森林生物灾害发生频繁,整理与制作相关灾害数据集对森林生物灾害系统监测布局、风险评估及防控决策具有重要的科学意义。本数据集在整合《中国林业统计年鉴》(1998–2017)和《中国林业和草原统计年鉴》(2018–2019)发布的年度森林生物灾害面积数据及森林资源面积数据基础上,构建并计算得到全国及各省区灾害总体及不同类型生物灾害的森林生物灾害发生指数(Forest Pest Outbreak index,FPOI)、灾害发生率(Forest Pest Occurrence Area Rate,FPOAR)两个系列指标集。验证表明,上述两个指标及距平数据集能够较好地反映出不同尺度中国森林生物灾害时空分布及变化特征,可为森林生物灾害格局与趋势分析及影响因素研究、精准地防控决策提供有效数据支撑。
