Research School of Earth Sciences, Australian National University, Acton, Canberra, ACT 2601, Australia.
Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong SAR, China.
Int J Environ Res Public Health. 2022 Sep 22;19(19):12006. doi: 10.3390/ijerph191912006.
Malaria remains a serious public health challenge in Ghana including the Greater Accra Region. This study aimed to quantify the spatial, temporal and spatio-temporal patterns of malaria in the Greater Accra Region to inform targeted allocation of health resources. Malaria cases data from 2015 to 2019 were obtained from the Ghanaian District Health Information and Management System and aggregated at a district and monthly level. Spatial analysis was conducted using the Global Moran's I, Getis-Ord Gi*, and local indicators of spatial autocorrelation. Kulldorff's space-time scan statistics were used to investigate space-time clustering. A negative binomial regression was used to find correlations between climatic factors and sociodemographic characteristics and the incidence of malaria. A total of 1,105,370 malaria cases were reported between 2015 and 2019. Significant seasonal variation was observed, with June and July being the peak months of reported malaria cases. The hotspots districts were Kpone-Katamanso Municipal District, Ashaiman Municipal Districts, Tema Municipal District, and La-Nkwantanang-Madina Municipal District. While La-Nkwantanang-Madina Municipal District was high-high cluster. The Spatio-temporal clusters occurred between February 2015 and July 2017 in the districts of Ningo-Prampram, Shai-Osudoku, Ashaiman Municipal, and Kpone-Katamanso Municipal with a radius of 26.63 km and an relative risk of 4.66 ( < 0.001). Malaria cases were positively associated with monthly rainfall (adjusted odds ratio [AOR] = 1.01; 95% confidence interval [CI] = 1.005, 1.016) and the previous month's cases (AOR = 1.064; 95% CI 1.062, 1.065) and negatively correlated with minimum temperature (AOR = 0.86, 95% CI = 0.823, 0.899) and population density (AOR = 0.996, 95% CI = 0.994, 0.998). Malaria control and prevention should be strengthened in hotspot districts in the appropriate months to improve program effectiveness.
疟疾仍然是加纳，包括大阿克拉地区面临的严重公共卫生挑战。本研究旨在量化大阿克拉地区疟疾的时空模式，为有针对性地分配卫生资源提供信息。从加纳地区卫生信息和管理系统中获取 2015 年至 2019 年的疟疾病例数据，并按地区和每月汇总。使用全局 Moran's I、Getis-Ord Gi*和局部空间自相关指标进行空间分析。Kulldorff 的时空扫描统计用于调查时空聚类。使用负二项回归分析气候因素和社会人口特征与疟疾发病率之间的相关性。2015 年至 2019 年期间共报告了 1105370 例疟疾病例。观察到明显的季节性变化，6 月和 7 月是报告疟疾病例的高峰期。热点地区是科蓬-卡特曼索市、阿散蒂曼市、特马市和拉-恩昆坦南-马迪纳市。而拉-恩昆坦南-马迪纳市则属于高-高聚集区。时空聚类发生在 2015 年 2 月至 2017 年 7 月期间，涉及宁戈-普拉姆普拉姆、沙伊-奥苏多库、阿散蒂曼和科蓬-卡特曼索等地区，半径为 26.63 公里，相对风险为 4.66（<0.001）。疟疾病例与每月降雨量呈正相关（调整后的优势比[OR] = 1.01；95%置信区间[CI] = 1.005，1.016），与上月病例呈正相关（OR = 1.064；95% CI 1.062，1.065），与最低温度呈负相关（OR = 0.86，95% CI = 0.823，0.899），与人口密度呈负相关（OR = 0.996，95% CI = 0.994，0.998）。应在适当月份加强热点地区的疟疾控制和预防工作，以提高项目效果。
