Savi Merveille Koissi, Pandey Bhartendu, Swain Anshuman, Lim Jeongki, Callo-Concha Daniel, Azondekon Gbedegnon Roseric, Wahjib Mohammed, Borgemeister Christian
Center for Development Research (ZEF), University of Bonn, North Rhine-Westphalia, Germany.
Department of Medical Oncology, Dana Farber Cancer Institute, Harvard School of Medicine, Boston, Massachusetts, United States of America.
PLOS Glob Public Health. 2024 May 30;4(5):e0002871. doi: 10.1371/journal.pgph.0002871. eCollection 2024.
In West Africa, malaria is one of the leading causes of disease-induced deaths. Existing studies indicate that as urbanization increases, there is corresponding decrease in malaria prevalence. However, in malaria-endemic areas, the prevalence in some rural areas is sometimes lower than in some peri-urban and urban areas. Therefore, the relationship between the degree of urbanization, the impact of living in urban areas, and the prevalence of malaria remains unclear. This study explores this association in Ghana, using epidemiological data at the district level (2015-2018) and data on health, hygiene, and education. We applied a multilevel model and time series decomposition to understand the epidemiological pattern of malaria in Ghana. Then we classified the districts of Ghana into rural, peri-urban, and urban areas using administratively defined urbanization, total built areas, and built intensity. We converted the prevalence time series into cross-sectional data for each district by extracting features from the data. To predict the determinant most impacting according to the degree of urbanization, we used a cluster-specific random forest. We find that prevalence is impacted by seasonality, but the trend of the seasonal signature is not noticeable in urban and peri-urban areas. While urban districts have a slightly lower prevalence, there are still pockets with higher rates within these regions. These areas of high prevalence are linked to proximity to water bodies and waterways, but the rise in these same variables is not associated with the increase of prevalence in peri-urban areas. The increase in nightlight reflectance in rural areas is associated with an increased prevalence. We conclude that urbanization is not the main factor driving the decline in malaria. However, the data indicate that understanding and managing malaria prevalence in urbanization will necessitate a focus on these contextual factors. Finally, we design an interactive tool, 'malDecision' that allows data-supported decision-making.
在西非，疟疾是疾病导致死亡的主要原因之一。现有研究表明，随着城市化进程加快，疟疾流行率相应下降。然而，在疟疾流行地区，一些农村地区的流行率有时低于一些城郊和城市地区。因此，城市化程度、城市生活影响与疟疾流行率之间的关系仍不明确。本研究利用加纳地区层面的流行病学数据（2015 - 2018年）以及健康、卫生和教育数据，探讨了加纳的这种关联。我们应用了多层次模型和时间序列分解来了解加纳疟疾的流行病学模式。然后，我们根据行政定义的城市化、建成区总面积和建筑密度，将加纳各地区划分为农村、城郊和城市地区。我们通过从数据中提取特征，将各地区的流行率时间序列转换为横截面数据。为了根据城市化程度预测影响最大的决定因素，我们使用了特定集群的随机森林。我们发现流行率受季节性影响，但在城市和城郊地区，季节性特征的趋势并不明显。虽然城市地区的流行率略低，但这些地区仍有一些流行率较高的区域。这些高流行率地区与靠近水体和水道有关，但在城郊地区，这些相同变量的增加与流行率的上升并无关联。农村地区夜光反射率的增加与流行率的上升有关。我们得出结论，城市化不是推动疟疾下降的主要因素。然而，数据表明，要了解和管理城市化进程中的疟疾流行率，需要关注这些背景因素。最后，我们设计了一个交互式工具“malDecision”，它能支持基于数据的决策制定。
