ArticleEcological modelling2015
An agent-based model to simulate tsetse fly distribution and control techniques: a case study in Nguruman, Kenya.
Article in Ecological modelling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 29 citations in OpenAlex.
- Life history traits of the target pest and transmission routes of the biocide are critical for the success of the boosted Sterile Insect Technique.Current research in insect science · 2024Article
- A Bayesian maximum entropy model for predicting tsetse ecological distributions.International journal of health geographics · 2023Article
- Mapping the potential distribution of the principal vector of Crimean-Congo haemorrhagic fever virus Hyalomma marginatum in the Old World.PLoS neglected tropical diseases · 2023Article
- Evidence-based advice on timing and location of tsetse control measures in Shimba Hills National reserve, Kenya.PLoS neglected tropical diseases · 2023Article
- Livestock, pathogens, vectors, and their environment: A causal inference-based approach to estimating the pathway-specific effect of livestock on human African trypanosomiasis risk.PLOS global public health · 2023Article
- Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models.PLoS neglected tropical diseases · 2021Article
- Satellite-based modelling of potential tsetse (Glossina pallidipes) breeding and foraging sites using teneral and non-teneral fly occurrence data.Parasites & vectors · 2021Article
- Does Counting Different Life Stages Impact Estimates for Extinction Probabilities for Tsetse (Glossina spp)?Bulletin of mathematical biology · 2021Article
- Dispersal in heterogeneous environments drives population dynamics and control of tsetse flies.Proceedings. Biological sciences · 2021Article
- Article
- The impact of vector migration on the effectiveness of strategies to control gambiense human African trypanosomiasis.PLoS neglected tropical diseases · 2019Article
- Geostatistical models using remotely-sensed data predict savanna tsetse decline across the interface between protected and unprotected areas in Serengeti, Tanzania.The Journal of applied ecology · 2018Article
- Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal.Parasites & vectors · 2018Article
- An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates.PLoS neglected tropical diseases · 2018Article
- Temporal genetic differentiation in Glossina pallidipes tsetse fly populations in Kenya.Parasites & vectors · 2017Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAfrican trypanosomiasis, also known as "sleeping sickness" in humans and "nagana" in livestock is an important vector-borne disease in Sub-Saharan Africa. Control of trypanosomiasis has focused on eliminating the vector, the tsetse fly ( METHODOLOGY/
resultsWe developed an Agent-Based Model (ABM) to provide timing and location information for tsetse fly control without presence/absence training data. The model is driven by daily remotely-sensed environment data. The model provides a flexible tool linking environmental changes with individual biology to analyze tsetse control methods such as aerial insecticide spraying, wild animal control, releasing irradiated sterile tsetse males, and land use and cover modification. SIGNIFICANCE: This is a bottom-up process-based model with freely available data as inputs that can be easily transferred to a new area. The tsetse population simulation more closely approximates real conditions than those using traditional statistical models making it a useful tool in tsetse fly control planning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.