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Insecticide resistance and malaria control: A genetics-epidemiology modeling approach
Jemal Mohammed-Awel1, Enahoro A Iboi2, Abba B Gumel2
1Department of Mathematics, Valdosta State University, Valdosta, GA 31698, USA.
Mathematical Biosciences
|May 22, 2020
Summary
High coverage of long-lasting insecticidal nets (LLINs) effectively controls malaria and manages insecticide resistance. Combining LLINs with indoor residual spraying (IRS) also works within specific coverage levels, but larviciding and initial resistance frequency can hinder control.
Area of Science:
- Mathematical modeling of infectious diseases
- Vector control and insecticide resistance
- Epidemiology and population genetics
Background:
- Malaria remains a significant global health threat, despite progress made through insecticide-based interventions like long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS).
- Widespread insecticide resistance in the malaria vector, Anopheles mosquitoes, poses a major challenge to current malaria eradication efforts.
- Understanding the interplay between insecticide resistance and malaria transmission is crucial for effective control strategies.
Purpose of the Study:
- To develop and analyze a novel mathematical model coupling malaria epidemiology with mosquito population genetics.
- To assess the impact of insecticide resistance on malaria transmission dynamics.
- To evaluate the effectiveness of LLINs and IRS, alone and in combination, in controlling malaria and managing insecticide resistance.
Main Methods:
- Development of a mathematical model integrating epidemiological and genetic factors of malaria transmission.
- Numerical simulations using data from the Jimma Zone, Southwestern Ethiopia.
- Analysis of model outputs to determine effective control strategies and identify critical parameters influencing resistance management.
Main Results:
- High LLINs coverage (over 90%) can effectively control malaria and manage insecticide resistance.
- Combined LLINs and IRS strategies are effective within a specific 'effective control window' of coverage levels, irrespective of larviciding.
- Larviciding coverage, female mosquito emergence rate, and initial resistant allele frequency negatively impact the size of this effective control window.
Conclusions:
- Sufficiently high coverage of LLINs alone is a viable strategy for both malaria control and insecticide resistance management.
- Integrated vector control programs using LLINs and IRS require careful calibration of coverage levels to ensure efficacy and prevent resistance.
- Key factors such as larviciding, vector population dynamics, and pre-existing resistance levels must be considered to avoid control failures.
