气候变量对尼日利亚河流州Oyigbo L.G.A地区疟疾时间格局的影响

Ogidi Margaret, Egbom, Sylvia Ezinne, Arene, F.O. I., Nduka, Florence Onyemachi, Nzeako, Sidney Obidimma
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摘要

本研究采用回顾性设计,研究了2007-2017年奥伊博地区疟疾发病的时间格局,并探讨了温度和降雨对奥伊博地区疟疾发病格局的影响。2007年至2017年的疟疾发病率数据来自河流州卫生部综合疾病监测和应对系统,2007年至2017年的温度和降雨记录来自阿布贾的尼日利亚气象局(NIMET)。产生的数据使用SPSS 22.0进行分析,并采用描述性统计和推理统计。研究区在研究期间共报告疟疾病例43,662例,平均发病率为330.77。平均气温27.32℃,平均降雨量137.13毫米。气温与疟疾呈负相关,且在2012年和2014年呈显著负相关。降雨量与发病率呈显著正相关,仅在2012年呈显著正相关。各月份气温与疟疾发病率呈不显著负相关。降雨量与5月疟疾发病呈显著正相关。疟疾在研究地区的当地受试者中仍然是地方病。在研究期间,总体研究显示疟疾发病率与温度和降雨量之间没有显著关系。这就是说,气候变量不是研究地区疟疾发病率的主要驱动因素。因此,建议开展更多的流行病学研究,以确定疟疾传播的驱动因素,以帮助采取循证干预措施
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Impact of Climatic Variables on the Temporal Patterns of Malaria in Oyigbo L.G.A, Rivers State, Nigeria
The study used a retrospective design to examine the temporal patterns of malaria morbidity in Oyigbo LGA and investigate the relationship between temperature and rainfall on patterns of malaria morbidity in Oyigbo L.G.A. from 2007-2017. Malaria morbidity data from 2007 to 2017 were obtained from the Integrated Disease Surveillance and Response System of Rivers State Ministry of Health while temperature and rainfall records from year 2007 to 2017 were obtained from Nigeria Meteorological Agency (NIMET), Abuja. Data generated were analyzed using SPSS 22.0 and presented using descriptive and inferential statistics. A total of 43,662 malaria cases was recorded in the study area within during the study period with mean morbidity of 330.77. Mean temperature of 27.32oC and mean rainfall of 137.13mm were recorded. Temperature showed a negative relationship with malaria which was significant in the years 2012 and 2014. Rainfall and morbidity showed a positive relationship which was significant only in year 2012. Across the months, temperature and malaria morbidity showed a negative insignificant relationship. However, rainfall showed a positive and significant relationship with malaria morbidity in May. Malaria remains endemic among the local subjects in the study area. During the study period, overall study showed no significant relationship between malaria morbidity, temperature and rainfall. This is to say that climatic variables are not the major drivers of malaria morbidity in the study area. It is therefore recommended that more epidemiological studies be carried out to determine the drivers of malaria transmission to aid evidence-based interventions
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