Dam-mediated flooding impact on outpatient attendance and diarrhoea cases in northern Ghana: a mixed methods study.
Dam-mediated flooding impact on outpatient attendance and diarrhoea cases in northern Ghana: a mixed methods study.
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DOI：
10.1186/s12889-022-14568-w
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发表时间：
2022-11-17
影响因子：
4.5
通讯作者：
中科院分区：
文献类型：
--
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洪水是最经常发生的自然灾害，构成重大的公共卫生风险。一些运行中的卫星洪水探测系统对洪水程度进行了量化，但不清楚卫星洪水产品的选择在多大程度上影响了相关公共卫生风险的流行病学研究结果。很少有关于洪水对健康影响的研究使用混合方法来丰富对这些影响的理解。因此，本研究旨在评估两个卫星衍生的洪水产品与加纳北方的门诊就诊率和腹泻病之间的关系，通过定性访谈确定观察到的关系的合理原因。一个收敛的并行混合方法设计结合了生态时间序列与焦点小组讨论和关键线人访谈。通过生态时间序列组成部分，2016 - 2020年两个洪水易发区卫生设施的每月门诊就诊率和腹泻病例计数与通过中分辨率成像光谱仪（MODIS）和陆地卫星传感器分类的每月洪水地图图层相结合。报告的腹泻和门诊就诊与洪水之间的关系进行了研究，使用泊松回归，控制季节性和设施集水区人口。与受影响社区成员的四次焦点小组讨论和与卫生专业人员的四次关键知情人访谈探讨了洪水对医疗服务提供和获取的影响。通过陆地卫星检测到的洪水比通过中分辨率成像分光仪检测到的洪水更好地预测了门诊就诊和腹泻。随着每个设施集水区的LandSat-derived洪水面积增加，门诊就诊率显著降低（调整后的发病率比= 0.78，95%CI：0.61 - 0.99，p <0.05），而报告的腹泻随着每个设施集水区的洪水面积显著增加（调整后的发病率比= 4.27，95%CI：2.74 - 6.63，p <0.001）。关键的信息提供者指出，洪水如何影响获得保健服务，因为病人和保健专业人员无法到达保健设施，紧急转诊也无法前往。洪水期间门诊就诊人数的显著减少表明，洪水损害了医疗服务。这种关系对卫星衍生洪水产品的选择很敏感，因此未来的研究应考虑整合多个卫星图像来源，以进行更可靠的暴露评估。卫生工作队和社区应规划明确解决人口和劳动力流动问题的有空间针对性的洪水缓解和卫生系统适应战略。 在线版本包含补充材料，可通过10.1186/s12889 - 022 - 14568-w获得。
Floods are the most frequently occurring natural disaster and constitute a significant public health risk. Several operational satellite-based flood detection systems quantify flooding extent, but it is unclear how far the choice of satellite-based flood product affects the findings of epidemiological studies of associated public health risks. Few studies of flooding’s health impacts have used mixed methods to enrich understanding of these impacts. This study therefore aims to evaluate the relationship between two satellite-derived flood products with outpatient attendance and diarrhoeal disease in northern Ghana, identifying plausible reasons for observed relationships via qualitative interviews. A convergent parallel mixed methods design combined an ecological time series with focus group discussions and key informant interviews. Through an ecological time series component, monthly outpatient attendance and diarrhoea case counts from health facilities in two flood-prone districts for 2016–2020 were integrated with monthly flooding map layers classified via the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite sensors. The relationship between reported diarrhoea and outpatient attendance with flooding was examined using Poisson regression, controlling for seasonality and facility catchment population. Four focus group discussions with affected community members and four key informant interviews with health professionals explored flooding’s impact on healthcare delivery and access. Flooding detected via Landsat better predicted outpatient attendance and diarrhoea than flooding via MODIS. Outpatient attendance significantly reduced as LandSat-derived flood area per facility catchment increased (adjusted Incidence Rate Ratio = 0.78, 95% CI: 0.61–0.99, p < 0.05), whilst reported diarrhoea significantly increased with flood area per facility catchment (adjusted Incidence Rate Ratio = 4.27, 95% CI: 2.74—6.63, p < 0.001). Key informants noted how flooding affected access to health services as patients and health professionals could not reach the health facility and emergency referrals were unable to travel. The significant reduction in outpatient attendance during flooding suggests that flooding impairs healthcare delivery. The relationship is sensitive to the choice of satellite-derived flood product, so future studies should consider integrating multiple sources of satellite imagery for more robust exposure assessment. Health teams and communities should plan spatially targeted flood mitigation and health system adaptation strategies that explicitly address population and workforce mobility issues. The online version contains supplementary material available at 10.1186/s12889-022-14568-w.
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DOI：
10.1111/tmi.13460
发表时间：
2020-09
期刊：
Tropical medicine & international health : TM & IH
影响因子：
--
作者：
Dotse-Gborgbortsi W;Tatem AJ;Alegana V;Utazi CE;Ruktanonchai CW;Wright J
通讯作者：
Wright J
影响因子：
5.4
作者：
Codjoe, Samuel N. A.;Gough, Katherine, V;Griffiths, Paula L.
通讯作者：
Griffiths, Paula L.
影响因子：
4.6
作者：
Li C;Dash J;Asamoah M;Sheffield J;Dzodzomenyo M;Gebrechorkos SH;Anghileri D;Wright J
通讯作者：
Wright J
影响因子：
10.8
作者：
Assan A;Takian A;Aikins M;Akbarisari A
通讯作者：
Akbarisari A
带有站点的气候危害红外降水 - 一种新的环境记录，用于监测极端。
影响因子：
9.8
作者：
Funk C;Peterson P;Landsfeld M;Pedreros D;Verdin J;Shukla S;Husak G;Rowland J;Harrison L;Hoell A;Michaelsen J
通讯作者：
Michaelsen J