School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
College of Health Sciences, University of KwaZulu-Natal, Howard Campus, Durban, South Africa.
Malar J. 2017 Sep 30;16(1):393. doi: 10.1186/s12936-017-2036-0.
Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed.
Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables.
There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior.
As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.
疟疾是津巴布韦的一个公共卫生问题。尽管许多研究表明气候变化可能会影响疟疾的分布，但关于其趋势及其与津巴布韦气候变量的关系的信息却很少。为了解决这一不足，评估了 2005 年 1 月至 2015 年 4 月期间津巴布韦农村格万达疟疾发病率的趋势及其与气候变量的相互作用。
对三个选定的格万达区农村病房（布武马、恩塔莱莱和塞隆加）报告的疟疾病例进行回顾性数据分析。疟疾病例数据从区卫生信息系统和病房诊所收集，降水和温度数据分别从气候危害组红外降水与台站数据（CHIRPS）数据库和中分辨率成像光谱辐射计（MODIS）卫星数据获得。分布式滞后非线性模型（DLNLM）用于确定每月疟疾发病率与每月气候变量之间的时间滞后关联。
三个病房共有 246 例确诊疟疾病例，平均发病率为 0.16/1000 人/月。大多数疟疾病例（95%）发生在>5 岁年龄组。结果表明，在所有三个研究病房中，临床疟疾（未确诊）和确诊疟疾病例的趋势之间没有相关性。布武马和塞隆加病房的疟疾发病率与气候变量之间存在显著关联，在特定的滞后期。在恩塔莱莱病房，只有降水（1 个月和 3 个月滞后）和平均温度（1 个月和 2 个月滞后）与特定滞后期的发病率显著相关（p<0.05）。DLNM 结果表明，当前月基于前 1-4 个月的关键气候条件，存在一个关键的高风险期。
由于高疟疾风险期与季节性周期前 1-4 个月的降水和温度有关，因此在这一时期加强疟疾控制活动可能有助于降低季节性疟疾发病率。
