辽宁省洪水对菌痢影响的定量研究及超额发病数的预估

发布时间：2018-01-18 14:23

本文关键词：辽宁省洪水对菌痢影响的定量研究及超额发病数的预估　出处：《山东大学》2016年硕士论文　论文类型：学位论文

【摘要】：研究背景洪水已经成为全球范围内公认的发生最为频繁、造成损失最大的自然灾害类型之一,约占全球自然灾害发生总数的百分之四十。洪水被认为会增加全球疾病负担并会给全球公共卫生服务体系造成持续的压力。洪水对人类健康的影响主要包括死亡、伤害、引起灾后传染病流行和心理健康等问题,其中洪水引起的灾后传染病的流行是主要问题之一。我国地域辽阔,气候类型分布复杂,洪水的发生具有种类多、影响范围广、时空分布不均匀、发生频率高和造成的损失严重的特点。虽然洪水的发生会严重危害灾区人群生命安全和健康状况,但国内外定量评价洪水对健康危害的研究相对较少且研究方法比较局限。同时,在联合国政府间气候变化专门委员会的第五次报告中曾指出,由于未来全球海平面上升以及极端降雨事件发生频率的升高,全球范围内洪水的发生频率以及强度也会随之加强；有研究指出,在全球气候变化的大背景下辽宁省洪水的发生频率以及强度也将进一步加大。随着我国经济社会的发展和城镇人口数量的快速增加,我国有越来越多的人口暴露在洪水这一危险因素之下。研究目的本研究以辽宁省2004-2010年作为基准时间段,选定细菌性痢疾为研究的目标疾病,应用面板Poisson回归模型定量评价辽宁省洪水事件对细菌性痢疾发病的影响；同时,在确定的基准时间段洪水与菌痢定量关系的基础上,在一定的假设条件并考虑未来人口变化的前提下,预估辽宁省2020、2030、2050、2100年洪水导致的细菌性痢疾的超额发病数,为辽宁省当前及未来时间洪水事件过后菌痢的防治政策和控制措施提供依据和参考。本研究主要目的包括以下几点：1.收集整理辽宁省2004-2010年细菌性痢疾月发病数据、气象数据和人口数据,在控制气象因素、长期趋势、季节效应和滞后效应等因素的影响下,利用面板Poisson回归模型定量评价辽宁省洪水事件对细菌性痢疾的影响,为当地灾后针对该种传染病的预防和控制提供依据。2.利用地理信息系统软件,整理预估得到的RCP4.5和RCP8.5情境下2020、2030、2050、2100年日降水的网格数据,根据国家科委全国重大自然灾害综合研究组有关洪水的定义,统计辽宁省2020、2030、2050、2100年洪水发生的具体情况；同时,根据联合国所发布的中国地区未来人口自然增长率,以2010年人口数为基准,预估得到2020、2030、2050、2100年辽宁省人口数据。3.在一定的假设条件下,预估未来时间段洪水导致的细菌性痢疾的超额发病数,为未来时间当地政府和公共卫生机构对洪水过后加强针对该种疾病的公共卫生投入和准备提供一定启示和依据。研究方法本研究利用Spearman相关分别在滞后0-2月对细菌性痢疾发病率和研究因素进行相关性分析,将其中具有统计学意义且最大的相关系数所在的滞后月作为最佳滞后期；在调整了滞后效应、气象因素、长期趋势和季节趋势等因素的影响后,利用面板Poisson回归模型定量评价2004-2010年辽宁省洪水事件对细菌性痢疾发病的影响并计算IRR(Incidence Rate Ratio)及其95%可信区间；然后采用国家科委全国重大自然灾害综合研究组有关洪水的定义统计得到辽宁省RCP4.5和RCP8.5两种情景下2020、2030、2050、2100年具体的洪水发生情况,在一定的假设并考虑未来人口变化的条件下预估辽宁省2020、2030、2050、2100年洪水事件致传染病的超额发病数。研究结果1.Spearman相关分析结果显示,辽宁省洪水事件对细菌性痢疾发病影响的最佳滞后期为0月,即洪水的发生对细菌性痢疾发病的影响不存在滞后效应。2.利用面板数据模型定量评价洪水事件对细菌性痢疾发病的影响,结果显示,辽宁省洪水事件对细菌性痢疾发病存在显著影响,IRR值为1.383(95%CI:1.353-1.414)。同时,模型结果还表明气象因素对细菌性痢疾发病也存在影响,月平均温度和月平均相对湿度的升高可以使细菌性痢疾发病的风险增加。3.本研究在一定的假设条件下预估得到了辽宁省2020、2030、2050、2100年洪水事件致细菌性痢疾的超额发病数。结果显示,在RCP4.5情景并低生育率情景下辽宁省2020、2030、2050、2100年洪水事件致细菌性痢疾的超额发病数分别为1111、355、453、658；中生育率情景下分别为1117、357、455、669；高生育率情景下分别为1131、362、466、694；在RCP8.5情景并低生育率情景下辽宁省2020、2030、2050、2100年洪水事件致细菌性痢疾的超额发病数分别为330、1108、616、292；中生育率情景下分别为332、1114、619、296；高生育率情景下分别为336、1127、634、308。研究结论本研究应用面板Poisson回归模型定量评价辽宁省洪水事件对细菌性痢疾发病的影响,且在一定的假设条件并考虑未来人口变化的前提下,预估辽宁省2020、2030、2050、2100洪水导致的细菌性痢疾的超额发病数。结果表明,辽宁省洪水事件对细菌性痢疾发病存在显著影响,洪水事件的发生可增加灾区人群罹患细菌性痢疾的风险,定量评价辽宁省洪水事件对细菌性痢疾发病的影响可为当地灾后细菌性痢疾的预防和控制以及灾后卫生资源的分配提供依据。在RCP4.5情景并低生育率情景下,辽宁省2020、2030、2050、2100年洪水事件致细菌性痢疾的超额发病数分别为1111、355、453、658；中生育率情景下分别为1117、357、455、669；高生育率情景下分别为1131、362、466、694；在RCP8.5情景并低生育率情景下,辽宁省2020、2030、2050、2100年洪水事件致细菌性痢疾的超额发病数分别为330、1108、616、292；中生育率情景下分别为332、1114、619、296；高生育率情景下分别为336、1127、634、308。未来辽宁省洪水事件的发生仍会对当地人群健康造成影响并给当地的公共卫生服务带来一定的压力,提示当地应在洪水发生后加强对灾区细菌性痢疾的监测,做好灾后卫生防疫工作,及时为灾区群众提供安全卫生的饮用水以及食物；建立基础卫生设施并保障灾民日常生活有条不紊的进行,以期尽量减少洪水对人民群众健康造成的威胁。研究局限性由于月尺度数据的局限性可能无法准确估计出洪水对菌痢发病影响的滞后效应；许多其他的因素如不同地区的社会经济水平未纳入到研究当中；同时,本研究中的预估是在一定假设条件下进行的,这也是本研究的主要局限性之一。
[Abstract]:On the background of the flood has become recognized worldwide occurred most frequently, the loss caused by one of the biggest natural disaster type, accounting for about forty percent of the total global occurrence of natural disasters. The flood is expected to increase in the global burden of disease and may cause sustained pressure to the global public health service system. The flood impact on human health including death damage caused by the disaster, epidemic of infectious diseases and mental health problems, which caused the flood disaster after the epidemic of infectious diseases is one of the main problems. China's vast territory, climate type complex distribution, flooding has many kinds, affecting a wide range, the distribution is not uniform, the occurrence characteristics of high frequency and caused serious damage to the although the occurrence of flood disaster will seriously endanger the safety of life and health of people, but the domestic and foreign research on quantitative evaluation of flood hazard. Compare the limitations of less and research methods. At the same time, in the fifth report of the United Nations Intergovernmental Panel on climate change has pointed out that, due to the increase of future global sea-level rise and extreme precipitation event frequency, the frequency of occurrence of worldwide flood and strength will also strengthen; studies have pointed out that in the background the global climate change in Liaoning Province under the flood frequency and intensity will also further increase. With the rapid increase in the number of China's economic and social development and urban population, more and more people are exposed to the flood risk factors. The study in Liaoning province 2004-2010 years as the benchmark period, the selected bacteria the research target of dysentery disease, using panel Poisson regression model for quantitative evaluation of influence of Liaoning province flood events on the incidence of bacillary dysentery; at the same time, Based on the relationship between the reference time and the quantitative determination of the flood dysentery, in certain conditions and considering the future population changes under the excess incidence prediction of bacillary dysentery caused flood in Liaoning province for 2020203020502100 years, and provides reference for the Liaoning Province, the current and future time after the flood event and dysentery prevention policy control measures. The main purpose of this study include the following: 1. collect the monthly incidence of bacillary dysentery in Liaoning province 2004-2010 data, meteorological data and population data, the long-term trend in the control of meteorological factors, seasonal effect and hysteresis effect of other factors, using the panel Poisson regression model for quantitative evaluation of influence of Liaoning Province on flood events bacterial dysentery, local post disaster for the prevention and control of the infectious diseases and provide the basis for.2. using geographic information system software, pre finishing We assessed RCP4.5 and RCP8.5 under the situation of daily precipitation data grid for 2020203020502100 years, according to the definition of the State Science and Technology Commission national comprehensive research group of major natural disasters of flood, flood situation statistics in Liaoning province for 2020203020502100 years; at the same time, according to United Nations Chinese in the future the natural population growth rate, the 2010 population of reference Liaoning Province, estimated the population data of.3. under certain assumptions for 2020203020502100 years, the incidence of abnormal prediction of bacillary dysentery in the future period of time the flood, the time for the future of local government and public health institutions to strengthen the investment in public health and disease to provide reference and basis for the research method after the floods. Study on the use of Spearman in 0-2 were related to the month lag factors of bacillary dysentery incidence and research Analysis, which has the largest correlation coefficient and statistical significance as the best month lag lag; in the adjustment of the lagged effect of meteorological factors, effects of long-term trends and seasonal trends and other factors, using the panel Poisson regression model for quantitative evaluation of influence of Liaoning province flood event in 2004-2010 on the incidence of bacillary dysentery and calculation IRR (Incidence Rate Ratio) and 95% confidence interval; then in Liaoning province by RCP4.5 and RCP8.5 two scenarios of occurrence of floods in the next 2020203020502100 years, the specific definition of statistics of State Science and Technology Commission national comprehensive research group of major natural disasters of flood, under certain assumptions and consider the excess incidence of infectious disease caused by the flood event 2020203020502100 years in Liaoning province prediction of future population changes under the conditions. The results showed that 1.Spearman correlation analysis results, Liaoning province flood. The best lag on the incidence of bacillary dysentery effects for 0 months, is the impact of floods on the incidence of bacillary dysentery has no effect, the lag effect.2. using the panel data model to quantitative evaluation of flood events on the incidence of bacillary dysentery in Liaoning province showed that the flood event has significant impact on the incidence of bacillary dysentery. The value of IRR was 1.383 (95%CI:1.353-1.414). At the same time, the model results show that the meteorological factors had effects on the incidence of bacterial dysentery, average relative humidity monthly average temperature and monthly increase can make the incidence of bacillary dysentery increased risk of the.3. estimate under certain assumptions the excess incidence of flood events in 2020203020502100 years Liaoning Province, caused by bacterial dysentery. The results showed that in the RCP4.5 scenario and low birth rate scenarios of flood events in 2020203020502100 years in Liaoning Province caused by bacterial dysentery The excess incidence was 1111355453658; in the fertility rate scenarios were 1117357455669; high fertility scenarios were 1131362466694; the excess incidence of RCP8.5 in the scene and the low fertility scenario flood event in 2020203020502100 years in Liaoning Province caused by bacterial dysentery respectively in 3301108616292; fertility scenarios were 3321114619296 higher; the fertility rate scenarios respectively for the quantitative evaluation of the impact of Liaoning province flood events on the incidence of bacillary dysentery 3361127634308. research conclusions of this study using panel Poisson regression model, and considering the future population changes under certain assumptions, the excess incidence of bacillary dysentery in Liaoning Province, estimated 2020203020502100 flood. The results showed that in Liaoning provincial flood events have significant influence on the incidence of bacillary dysentery, flood event. The disaster affected population can increase the occurrence of bacillary dysentery risk, quantitative evaluation of the impact of Liaoning province flood events on the incidence of bacillary dysentery can provide basis for the prevention and control of bacterial dysentery and allocation of health resources of local post disaster after disaster. In the RCP4.5 scenario and low fertility scenario, the excess incidence of flood events in 2020203020502100 years Liaoning Province, caused by bacterial dysentery was 1111355453658; in the fertility rate scenarios were 1117357455669; high fertility scenario was 1131362466694; in the RCP8.5 scenario and low fertility scenario, the excess incidence of flood events in 2020203020502100 years in Liaoning Province caused by bacterial dysentery was 3301108616292; in the fertility rate scenarios respectively. 3321114619296; high birth rates were 3361127634308. future scenarios in Liaoning province flood events still occur Impact and bring some pressure to the local public health services to the local population health, suggesting that local monitoring should be strengthened in the disaster stricken areas of bacillary dysentery in the flood occurred, good health and epidemic prevention work after the disaster, in time for the people in the disaster areas to provide safe drinking water to health and food; establish basic health facilities and protection of victims daily life in order to reduce everything in good order and well arranged, caused by the flood of people's health threat. The limitations of the study due to the limitation of the monthly scale data may not accurately estimate the lagged effects of flood on the incidence of bacillary dysentery; many other factors such as social economic level in different regions were not included in the study; at the same time, this study estimated in some conditions are, this is also one of the major limitations of this study.

【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：R516.4

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