Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination.
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagati...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-08-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1008121 |
id |
doaj-85d1d77eb49946958afb7597bc66c59e |
---|---|
record_format |
Article |
spelling |
doaj-85d1d77eb49946958afb7597bc66c59e2021-04-21T15:16:48ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-08-01168e100812110.1371/journal.pcbi.1008121Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination.Prashanth SelvarajEdward A WengerDaniel BridenbeckerNikolai WindbichlerJonathan R RussellJaline GerardinCaitlin A BeverMilen NikolovVector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed.https://doi.org/10.1371/journal.pcbi.1008121 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Prashanth Selvaraj Edward A Wenger Daniel Bridenbecker Nikolai Windbichler Jonathan R Russell Jaline Gerardin Caitlin A Bever Milen Nikolov |
spellingShingle |
Prashanth Selvaraj Edward A Wenger Daniel Bridenbecker Nikolai Windbichler Jonathan R Russell Jaline Gerardin Caitlin A Bever Milen Nikolov Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. PLoS Computational Biology |
author_facet |
Prashanth Selvaraj Edward A Wenger Daniel Bridenbecker Nikolai Windbichler Jonathan R Russell Jaline Gerardin Caitlin A Bever Milen Nikolov |
author_sort |
Prashanth Selvaraj |
title |
Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. |
title_short |
Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. |
title_full |
Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. |
title_fullStr |
Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. |
title_full_unstemmed |
Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination. |
title_sort |
vector genetics, insecticide resistance and gene drives: an agent-based modeling approach to evaluate malaria transmission and elimination. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2020-08-01 |
description |
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed. |
url |
https://doi.org/10.1371/journal.pcbi.1008121 |
work_keys_str_mv |
AT prashanthselvaraj vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT edwardawenger vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT danielbridenbecker vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT nikolaiwindbichler vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT jonathanrrussell vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT jalinegerardin vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT caitlinabever vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination AT milennikolov vectorgeneticsinsecticideresistanceandgenedrivesanagentbasedmodelingapproachtoevaluatemalariatransmissionandelimination |
_version_ |
1714667534771290112 |