# Tracking the flow of malaria parasites and drug resistance within the DRC and across its borders

> **NIH NIH R01** · BROWN UNIVERSITY · 2022 · $663,012

## Abstract

ABSTRACT
Malaria​ ​remains​ ​endemic​ ​in​ ​sub-Saharan​ ​Africa​ ​in​ ​large​ ​part​ ​due​ ​to​ ​continued​ ​evolution​ ​and​ ​spread​ ​of​ ​drug
resistance​ ​which​ ​undermines​ ​ongoing​ ​large-scale​ ​control​ ​and​ ​elimination​ ​efforts.​ ​We​ ​will​ ​leverage
high-throughput​ ​genotyping​ ​of​ ​parasites​ ​using​ ​a​ ​state-of-the-art​ ​panel​ ​of​ ​molecular​ ​inversion​ ​probes​ ​(MIPs)​ ​for
targeted​ ​sequencing​ ​of​ ​thousands​ ​of​ ​resistance​ ​and​ ​neutral​ ​loci​ ​across​ ​thousands​ ​of​ ​infections​ ​covering​ ​the
entire​ ​Democratic​ ​Republic​ ​of​ ​Congo​ ​(DRC)​ ​and​ ​select​ ​areas​ ​in​ ​bordering​ ​countries.​ ​This​ ​will​ ​provide​ ​us​ ​a​ ​map
with​ ​an​ ​unprecedented​ ​scale​ ​and​ ​resolution​ ​to​ ​define​ ​the​ ​evolution​ ​and​ ​spread​ ​of​ ​antimalarial​ ​resistance
mutations.​ ​In​ ​this​ ​project,​ ​we​ ​will​ ​first​ ​develop​ ​our​ ​genotyping​ ​panel​ ​which​ ​should​ ​provide​ ​a​ ​high-resolution​ ​tool
for​ ​studying​ ​all​ ​known​ ​drug​ ​resistance​ ​loci​ ​and​ ​general​ ​parasite​ ​population​ ​structure​ ​in​ ​this​ ​and​ ​other​ ​settings.
Applying​ ​this​ ​to​ ​well​ ​annotated​ ​samples​ ​from​ ​across​ ​the​ ​DRC​ ​and​ ​bordering​ ​countries,​ ​we​ ​will​ ​define​ ​the
prevalence​ ​of​ ​drug​ ​resistance​ ​mutations​ ​and​ ​define​ ​them​ ​based​ ​on​ ​their​ ​genetic​ ​haplotypes​ ​which​ ​act​ ​as​ ​a
unique​ ​fingerprints.​ ​We​ ​will​ ​then​ ​map​ ​these​ ​drug​ ​resistance​ ​haplotypes​ ​and​ ​study​ ​their​ ​spread​ ​and​ ​spatial
associations​ ​and​ ​further​ ​examine​ ​their​ ​epidemiologic​ ​associations​ ​and​ ​interactions.​ ​Onto​ ​this​ ​detailed​ ​spatial
map,​ ​we​ ​will​ ​​ ​examine​ ​specific​ ​locales​ ​of​ ​interest​ ​for​ ​temporal​ ​changes.​ ​​ ​These​ ​focal​ ​regions​ ​in​ ​the​ ​DRC
represent​ ​diverse​ ​ecologic​ ​and​ ​demographic​ ​features​ ​that​ ​likely​ ​impact​ ​resistance​ ​spread​ ​and​ ​evolution
including​ ​areas​ ​with​ ​minimal​ ​health​ ​care​ ​infrastructure​ ​and​ ​ongoing​ ​regions​ ​of​ ​conflict.​ ​Our​ ​final​ ​work​ ​will​ ​be​ ​to
apply​ ​more​ ​sophisticated​ ​models​ ​to​ ​the​ ​rich​ ​sequence​ ​data​ ​in​ ​order​ ​to​ ​estimate​ ​the​ ​flow​ ​of​ ​parasites​ ​and
resistance​ ​mutations​ ​within​ ​and​ ​between​ ​the​ ​DRC.​ ​This​ ​includes​ ​the​ ​development​ ​of​ ​new​ ​​ ​population​ ​structure
models​ ​(MALECOT)​ ​incorporating​ ​parasite​ ​infections​ ​that​ ​have​ ​multiple​ ​strains​ ​allowing​ ​for​ ​a​ ​better
understanding​ ​of​ ​the​ ​full​ ​dataset​ ​as​ ​in​ ​polyclonal​ ​infections​ ​are​ ​often​ ​the​ ​majority​ ​in​ ​endemic​ ​African​ ​countries.
This​ ​model​ ​should​ ​be​ ​broadly​ ​applicable​ ​to​ ​other​ ​studies​ ​of​ ​malaria​ ​or​ ​infections​ ​with​ ​mixed​ ​strains.​ ​We​ ​will
also​ ​leverage​ ​​ ​spatially​ ​explicit​ ​models​ ​to​ ​define​ ​general​ ​parasite​ ​flow​ ​in​ ​both​ ​relative​ ​and​ ​absolute​ ​terms
comparing​ ​and​ ​contrasting​ ​to​ ​the​ ​flow​ ​of​ ​resistant​ ​parasites.​ ​This​ ​work​ ​w...

## Key facts

- **NIH application ID:** 10164713
- **Project number:** 5R01AI139520-05
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** JEFFREY A. BAILEY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $663,012
- **Award type:** 5
- **Project period:** 2018-06-21 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10164713

## Citation

> US National Institutes of Health, RePORTER application 10164713, Tracking the flow of malaria parasites and drug resistance within the DRC and across its borders (5R01AI139520-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10164713. Licensed CC0.

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