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An agent-based model of the population dynamics of Anopheles gambiae.

Arifin SM, Zhou Y, Davis GJ, Gentile JE, Madey GR, Collins FH - Malar. J. (2014)

Bottom Line: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles.A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages.The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques).

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. niazarifin@gmail.com.

ABSTRACT

Background: Agent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypothetical vector control interventions (HVCIs) are implemented to target specific activities in the mosquito life cycle, and their impacts are evaluated.

Methods: The core model is described in terms of the complete An. gambiae mosquito life cycle. Primary features include the development and mortality rates in different aquatic and adult stages, the aquatic habitats and oviposition. The density- and age-dependent larval and adult mortality rates (vector senescence) allow the model to capture the age-dependent aspects of the mosquito biology. Details of hypothetical interventions are also described.

Results: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles. Thus, these stages may be the most effective points of target for newly developed and novel interventions. A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages. It is emphasized that although the model described in this paper is designed specifically around the mosquito An. gambiae, it could effectively apply to many other major malaria vectors in the world (including the three most efficient nominal anopheline species An. gambiae, Anopheles coluzzii and Anopheles arabiensis) by incorporating a variety of factors (seasonality cycles, rainfall, humidity, etc.). Thus, the model can essentially be treated as a generic Anopheles model, offering an excellent framework for such extensions. The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques).

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Impact of varying coverage (C) on abundance and potentially infectious female with hypothetical vector control interventions. (a)-(c) depict abundance, and (d)-(f) depict PIF. Each column represents a specific coverage (C) for HVCIs (e.g., C =50%). The legend at the bottom shows the HVCIs modelled. Each colour-coded plot represents a specific HVCI, with colour keys presented in the legend. The x-axis denotes simulation time (in days), and the y-axis denotes abundance or PIF. HVCIs are applied on day 100, and continued up to the end of the simulation. The first 100 days, which constitute the warm-up period necessary to reach a steady state, is omitted from the one-year simulation results.
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Fig3: Impact of varying coverage (C) on abundance and potentially infectious female with hypothetical vector control interventions. (a)-(c) depict abundance, and (d)-(f) depict PIF. Each column represents a specific coverage (C) for HVCIs (e.g., C =50%). The legend at the bottom shows the HVCIs modelled. Each colour-coded plot represents a specific HVCI, with colour keys presented in the legend. The x-axis denotes simulation time (in days), and the y-axis denotes abundance or PIF. HVCIs are applied on day 100, and continued up to the end of the simulation. The first 100 days, which constitute the warm-up period necessary to reach a steady state, is omitted from the one-year simulation results.

Mentions: The impact of varying coverage (C) on mosquito abundance and PIF abundance of seven HVCIs, applied in isolation in five stages (L, IA, BMS, BMD, and G) of the mosquito life cycle, is shown in Figure 3. Three levels of C are simulated: low (C =25%), moderate (C =50%), and high (C =75%), with killing K and ambient temperature T being fixed at 50% (except for the special case of BMSForaging, K=0%) and 25°C, respectively. Figures 3a-c show adult female abundance. As shown in Figure 3a with low (C =25%) coverage, LUpdating performs the best in reducing abundance by ≈ 72%, and is followed by GForaging, IAResting, BMDResting, and BMSForaging. As C is increased to 50 and 75% (Figure 3b and c), LUpdating reduces abundance to zero and essentially eliminates the adult mosquito populations, and the differences in impact between BMSForaging and BMDResting are gradually diminished. Both LUpdating and GForaging perform better than other interventions due to the fact that they impose additional killing effects for much longer durations: the impact of LUpdating occurs over every hour in the entire larval development stage (which is the longest life cycle stage), and the impact of GForaging, which occurs over every hour during the habitat-seeking period, is also further increased by: 1) multiple oviposition attempts, i.e., skip-oviposition, and 2) being applied multiple times in multiple gonotrophic cycles (see below). However, for any coverage level, BMSForaging, K=0% and LEntering produce no visible impacts, as can be seen in Figures 3a-c. This is not surprising, because BMSForaging, K=0% imposes no additional mortality on the host seeking female, and LEntering is applied (to a larva) for only a single hourly time step.Figure 3


An agent-based model of the population dynamics of Anopheles gambiae.

Arifin SM, Zhou Y, Davis GJ, Gentile JE, Madey GR, Collins FH - Malar. J. (2014)

Impact of varying coverage (C) on abundance and potentially infectious female with hypothetical vector control interventions. (a)-(c) depict abundance, and (d)-(f) depict PIF. Each column represents a specific coverage (C) for HVCIs (e.g., C =50%). The legend at the bottom shows the HVCIs modelled. Each colour-coded plot represents a specific HVCI, with colour keys presented in the legend. The x-axis denotes simulation time (in days), and the y-axis denotes abundance or PIF. HVCIs are applied on day 100, and continued up to the end of the simulation. The first 100 days, which constitute the warm-up period necessary to reach a steady state, is omitted from the one-year simulation results.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4233045&req=5

Fig3: Impact of varying coverage (C) on abundance and potentially infectious female with hypothetical vector control interventions. (a)-(c) depict abundance, and (d)-(f) depict PIF. Each column represents a specific coverage (C) for HVCIs (e.g., C =50%). The legend at the bottom shows the HVCIs modelled. Each colour-coded plot represents a specific HVCI, with colour keys presented in the legend. The x-axis denotes simulation time (in days), and the y-axis denotes abundance or PIF. HVCIs are applied on day 100, and continued up to the end of the simulation. The first 100 days, which constitute the warm-up period necessary to reach a steady state, is omitted from the one-year simulation results.
Mentions: The impact of varying coverage (C) on mosquito abundance and PIF abundance of seven HVCIs, applied in isolation in five stages (L, IA, BMS, BMD, and G) of the mosquito life cycle, is shown in Figure 3. Three levels of C are simulated: low (C =25%), moderate (C =50%), and high (C =75%), with killing K and ambient temperature T being fixed at 50% (except for the special case of BMSForaging, K=0%) and 25°C, respectively. Figures 3a-c show adult female abundance. As shown in Figure 3a with low (C =25%) coverage, LUpdating performs the best in reducing abundance by ≈ 72%, and is followed by GForaging, IAResting, BMDResting, and BMSForaging. As C is increased to 50 and 75% (Figure 3b and c), LUpdating reduces abundance to zero and essentially eliminates the adult mosquito populations, and the differences in impact between BMSForaging and BMDResting are gradually diminished. Both LUpdating and GForaging perform better than other interventions due to the fact that they impose additional killing effects for much longer durations: the impact of LUpdating occurs over every hour in the entire larval development stage (which is the longest life cycle stage), and the impact of GForaging, which occurs over every hour during the habitat-seeking period, is also further increased by: 1) multiple oviposition attempts, i.e., skip-oviposition, and 2) being applied multiple times in multiple gonotrophic cycles (see below). However, for any coverage level, BMSForaging, K=0% and LEntering produce no visible impacts, as can be seen in Figures 3a-c. This is not surprising, because BMSForaging, K=0% imposes no additional mortality on the host seeking female, and LEntering is applied (to a larva) for only a single hourly time step.Figure 3

Bottom Line: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles.A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages.The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques).

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. niazarifin@gmail.com.

ABSTRACT

Background: Agent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypothetical vector control interventions (HVCIs) are implemented to target specific activities in the mosquito life cycle, and their impacts are evaluated.

Methods: The core model is described in terms of the complete An. gambiae mosquito life cycle. Primary features include the development and mortality rates in different aquatic and adult stages, the aquatic habitats and oviposition. The density- and age-dependent larval and adult mortality rates (vector senescence) allow the model to capture the age-dependent aspects of the mosquito biology. Details of hypothetical interventions are also described.

Results: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles. Thus, these stages may be the most effective points of target for newly developed and novel interventions. A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages. It is emphasized that although the model described in this paper is designed specifically around the mosquito An. gambiae, it could effectively apply to many other major malaria vectors in the world (including the three most efficient nominal anopheline species An. gambiae, Anopheles coluzzii and Anopheles arabiensis) by incorporating a variety of factors (seasonality cycles, rainfall, humidity, etc.). Thus, the model can essentially be treated as a generic Anopheles model, offering an excellent framework for such extensions. The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques).

Show MeSH
Related in: MedlinePlus