TY - JOUR
T1 - Insecticide resistance and malaria control
T2 - A genetics-epidemiology modeling approach
AU - Mohammed-Awel, Jemal
AU - Iboi, Enahoro A.
AU - Gumel, Abba B.
N1 - Funding Information:
Two of the authors (ABG and JMA) are grateful to National Institute for Mathematical and Biological Synthesis (NIMBioS), USA for funding the Working Group on Climate Change and Vector-borne Diseases (VBDs). NIMBioS is an Institute sponsored by the National Science Foundation, USA, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Award #EF-0832858, with additional support from The University of Tennessee, Knoxville, USA. ABG also acknowledges the support, in part, of the Simons Foundation, USA (Award #585022). The authors are very grateful to the two anonymous reviewers for their very constructive comments, which have significantly enhanced the manuscript.
Funding Information:
Two of the authors (ABG and JMA) are grateful to National Institute for Mathematical and Biological Synthesis (NIMBioS), USA for funding the Working Group on Climate Change and Vector-borne Diseases (VBDs). NIMBioS is an Institute sponsored by the National Science Foundation, USA , the U.S. Department of Homeland Security , and the U.S. Department of Agriculture through NSF Award # EF-0832858 , with additional support from The University of Tennessee, Knoxville, USA . ABG also acknowledges the support, in part, of the Simons Foundation, USA (Award 585022 ). The authors are very grateful to the two anonymous reviewers for their very constructive comments, which have significantly enhanced the manuscript.
Publisher Copyright:
© 2020
PY - 2020/7
Y1 - 2020/7
N2 - Malaria, a deadly infectious disease caused by the protozoan Plasmodium, remains a major public health menace affecting at least half the human race. Although the large-scale usage of insecticides-based control measures, notably long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), have led to a dramatic reduction of the burden of this global scourge between the period 2000 to 2015, the fact that the malaria vector (adult female Anopheles mosquito) has become resistant to all currently-available insecticides potentially makes the current laudable global effort to eradicate malaria by 2040 more challenging. This study presents a novel mathematical model, which couples malaria epidemiology with mosquito population genetics, for assessing the impact of insecticides resistance on malaria epidemiology. Numerical simulations of the model, using data relevant to malaria transmission dynamics in the Jimma Zone of Southwestern Ethiopia, show that the implementation of a control strategy based on using LLINs alone can lead to the effective control of malaria, while also effectively managing insecticide resistance, if the LLINs coverage in the community is high enough (over 90%). It is further shown that combining LLINs with IRS (both at reduced and realistically-attainable coverage levels) can lead to the aforementioned effective control of malaria and effective management of insecticide resistance if their coverage levels lie within a certain effective control window in the LLINs-IRS coverage parameter space (this result generally holds regardless of whether or not larviciding is implemented in the community). The study identifies three key parameters of the model that negatively affect the size of the effective control window, namely parameters related with the coverage level of larviciding, the number of new adult mosquitoes that are females and the initial size of the frequency of resistant allele in the community. For the coverage of LLINs and IRS within the effective control window, an additional increase in the values of the aforementioned three parameters may lead to a shrinkage in the size of the effective control window (thereby causing the failure of the insecticides-based control).
AB - Malaria, a deadly infectious disease caused by the protozoan Plasmodium, remains a major public health menace affecting at least half the human race. Although the large-scale usage of insecticides-based control measures, notably long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), have led to a dramatic reduction of the burden of this global scourge between the period 2000 to 2015, the fact that the malaria vector (adult female Anopheles mosquito) has become resistant to all currently-available insecticides potentially makes the current laudable global effort to eradicate malaria by 2040 more challenging. This study presents a novel mathematical model, which couples malaria epidemiology with mosquito population genetics, for assessing the impact of insecticides resistance on malaria epidemiology. Numerical simulations of the model, using data relevant to malaria transmission dynamics in the Jimma Zone of Southwestern Ethiopia, show that the implementation of a control strategy based on using LLINs alone can lead to the effective control of malaria, while also effectively managing insecticide resistance, if the LLINs coverage in the community is high enough (over 90%). It is further shown that combining LLINs with IRS (both at reduced and realistically-attainable coverage levels) can lead to the aforementioned effective control of malaria and effective management of insecticide resistance if their coverage levels lie within a certain effective control window in the LLINs-IRS coverage parameter space (this result generally holds regardless of whether or not larviciding is implemented in the community). The study identifies three key parameters of the model that negatively affect the size of the effective control window, namely parameters related with the coverage level of larviciding, the number of new adult mosquitoes that are females and the initial size of the frequency of resistant allele in the community. For the coverage of LLINs and IRS within the effective control window, an additional increase in the values of the aforementioned three parameters may lead to a shrinkage in the size of the effective control window (thereby causing the failure of the insecticides-based control).
KW - Effective control window
KW - Equilibria
KW - Insecticide resistance
KW - Malaria
KW - Population genetics
KW - Stability
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U2 - 10.1016/j.mbs.2020.108368
DO - 10.1016/j.mbs.2020.108368
M3 - Article
C2 - 32437715
AN - SCOPUS:85085731557
SN - 0025-5564
VL - 325
JO - Mathematical Biosciences
JF - Mathematical Biosciences
M1 - 108368
ER -