Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering & Technology (BUET), ECE Building, West Palasi, Dhaka, 1205, Bangladesh.
Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, 46556, USA.
Malar J. 2017 Oct 27;16(1):432. doi: 10.1186/s12936-017-2075-6.
Malaria, being a mosquito-borne infectious disease, is still one of the most devastating global health issues. The malaria vector Anopheles vagus is widely distributed in Asia and a dominant vector in Bandarban, Bangladesh. However, despite its wide distribution, no agent based model (ABM) of An. vagus has yet been developed. Additionally, its response to combined vector control interventions has not been examined.
A spatial ABM, denoted as ABM[Formula: see text], was designed and implemented based on the biological attributes of An. vagus by modifying an established, existing ABM of Anopheles gambiae. Environmental factors such as temperature and rainfall were incorporated into ABM[Formula: see text] using daily weather profiles. Real-life field data of Bandarban were used to generate landscapes which were used in the simulations. ABM[Formula: see text] was verified and validated using several standard techniques and against real-life field data. Using artificial landscapes, the individual and combined efficacies of existing vector control interventions are modeled, applied, and examined.
Simulated female abundance curves generated by ABM[Formula: see text] closely follow the patterns observed in the field. Due to the use of daily temperature and rainfall data, ABM[Formula: see text] was able to generate seasonal patterns for a particular area. When two interventions were applied with parameters set to mid-ranges, ITNs/LLINs with IRS produced better results compared to the other cases. Moreover, any intervention combined with ITNs/LLINs yielded better results. Not surprisingly, three interventions applied in combination generate best results compared to any two interventions applied in combination.
Output of ABM[Formula: see text] showed high sensitivity to real-life field data of the environmental factors and the landscape of a particular area. Hence, it is recommended to use the model for a given area in connection to its local field data. For applying combined interventions, three interventions altogether are highly recommended whenever possible. It is also suggested that ITNs/LLINs with IRS can be applied when three interventions are not available.
疟疾是一种由蚊子传播的传染病，仍然是全球最具破坏性的健康问题之一。疟疾病媒按蚊广泛分布于亚洲，是孟加拉国班达班的主要媒介。然而，尽管分布广泛，但尚未开发出基于代理的安蚊模型（ABM）。此外，其对联合媒介控制干预措施的反应也没有得到检查。
设计并实现了一个空间 ABM，称为 ABM[公式：见文本]，通过修改现有的冈比亚按蚊的 ABM 来设计和实现，以安蚊的生物学特性为基础。ABM[公式：见文本]使用每日天气概况将温度和降雨量等环境因素纳入其中。使用班达班的实际现场数据生成景观，用于模拟。使用几种标准技术和实际现场数据对 ABM[公式：见文本]进行了验证和验证。使用人工景观对现有媒介控制干预措施的单独和联合效果进行建模、应用和检查。
ABM[公式：见文本]生成的模拟雌性丰度曲线与实地观察到的模式密切吻合。由于使用了每日温度和降雨数据，ABM[公式：见文本]能够为特定区域生成季节性模式。当两种干预措施以中值参数应用时，与其他情况相比，使用 ITNs/LLINs 和 IRS 产生了更好的结果。此外，任何干预措施与 ITNs/LLINs 相结合都会产生更好的结果。毫不奇怪，与任何两种干预措施相结合相比，三种干预措施相结合产生的结果最佳。
ABM[公式：见文本]的输出对特定区域的环境因素和景观的实际现场数据非常敏感。因此，建议在连接到其本地现场数据的情况下，在给定区域使用该模型。对于联合干预措施，只要可能，强烈建议总共使用三种干预措施。还建议在无法使用三种干预措施时，可以使用带有 IRS 的 ITNs/LLINs。
