Awine Timothy, Malm Keziah, Bart-Plange Constance, Silal Sheetal P
a Modelling and Simulation Hub, Africa, Department of Statistical Sciences , University of Cape Town , Cape Town , South Africa.
b South African Department of Science and Technology/National Research Foundation Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA) , University of Stellenbosch , Stellenbosch , South Africa.
Glob Health Action. 2017;10(1):1381471. doi: 10.1080/16549716.2017.1381471.
Ghana is classified as being in the malaria control phase, according to the global malaria elimination program. With many years of policy development and control interventions, malaria specific mortality among children less than 5 years old has declined from 14.4% in 2000 to 0.6% in 2012. However, the same level of success has not been achieved with malaria morbidity. The recently adopted 2015-2020 Ghana strategic action plan aims to reduce the burden of malaria by 75.0%. Planning and policy development has always been guided by evidence from field studies, and mathematical models that are able to investigate malaria transmission dynamics have not played a significant role in supporting policy development. The objectives of this study are to describe the malaria situation in Ghana and give a brief account of how mathematical modelling techniques could support a more informed malaria control effort in the Ghanaian context. A review is carried out of some mathematical models investigating the dynamics of malaria transmission in sub-Saharan African countries, including Ghana. The applications of these models are then discussed, considering the gaps that still remain in Ghana for which further mathematical model development could be supportive. Because of the collaborative approach adopted in their development, some model examples Ghana could benefit from are also discussed. Collaboration between malaria control experts and modellers will allow for more appropriate mathematical models to be developed. Packaging these models with user-friendly interfaces and making them available at various levels of malaria control management could help provide the decision making tools needed for planning and a platform for monitoring and evaluation of interventions in Ghana.
根据全球疟疾消除计划，加纳被归类为处于疟疾控制阶段。经过多年的政策制定和控制干预，5岁以下儿童的疟疾特异性死亡率已从2000年的14.4%降至2012年的0.6%。然而，在疟疾发病率方面尚未取得同样程度的成功。最近通过的《2015 - 2020年加纳战略行动计划》旨在将疟疾负担降低75.0%。规划和政策制定一直以实地研究的证据为指导，而能够研究疟疾传播动态的数学模型在支持政策制定方面尚未发挥重要作用。本研究的目的是描述加纳的疟疾情况，并简要说明数学建模技术如何能够在加纳背景下支持更明智的疟疾控制工作。对一些研究包括加纳在内的撒哈拉以南非洲国家疟疾传播动态的数学模型进行了综述。然后讨论了这些模型的应用，考虑到加纳仍然存在的差距，进一步的数学模型开发可能会对此有帮助。由于在模型开发中采用了协作方法，还讨论了加纳可能受益的一些模型示例。疟疾控制专家和建模人员之间的合作将有助于开发更合适的数学模型。将这些模型与用户友好的界面打包，并在疟疾控制管理的各个层面提供这些模型，有助于提供规划所需的决策工具以及加纳干预措施监测和评估的平台。
