ArticleMalaria journal2017
A spatial agent-based model of Anopheles vagus for malaria epidemiology: examining the impact of vector control interventions.
Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Agent-based models of malaria transmission: a systematic review.Malaria journal · 2018Pooled it
- Malaria in Bangladesh, 2000-2025: Navigating the Headwinds From Control to Elimination.Health science reports · 2026Article
- Phylogeographic Patterns and Genetic Diversity ofTropical medicine and infectious disease · 2025Article
- Agent-based simulation of COVID-19 containment measures: the case of lockdowns in cities.Letters in spatial and resource sciences · 2023Article
- Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models.International journal of environmental research and public health · 2022Review
- Evaluation of different deployment strategies for larviciding to control malaria: a simulation study.Malaria journal · 2021Article
- An Agent-Based Modeling of COVID-19: Validation, Analysis, and Recommendations.Cognitive computation · 2021Article
- Epidemiological Predictive Modeling of COVID-19 Infection: Development, Testing, and Implementation on the Population of the Benelux Union.Frontiers in public health · 2021Article
- Precarity at the Margins of Malaria Control in the Chittagong Hill Tracts in Bangladesh: A Mixed-Methods Study.Pathogens (Basel, Switzerland) · 2020Article
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5 authors.
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Abstract
backgroundMalaria, 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.
methodsA 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.
resultsSimulated 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.
conclusionsOutput 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.
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