Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR

Yin Cheong Aden Ip; Luca Montemartini; Jia Jin Marc Chang; Andrea Desiderato; Nicolás D. Franco-Sierra; Christian Geckeler; Mailyn Adriana Gonzalez Herrera; Michele Gregorini; Meret Jucker; Steffen Kirchgeorg; Martina Lüthi; Elvira Mächler; Frederik Bendix Thostrup; Guglielmo Murari; Marina Mura; Paola Pulido-Santacruz; Florencia Sangermano; Tobias Schindler; Claus Melvad; Stefano Mintchev; Kristy Deiner

doi:10.1016/j.onehlt.2025.101167

Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR

Yin Cheong Aden Ip^*, Luca Montemartini, Jia Jin Marc Chang, Andrea Desiderato, Nicolás D. Franco-Sierra, Christian Geckeler, Mailyn Adriana Gonzalez Herrera, Michele Gregorini, Meret Jucker, Steffen Kirchgeorg, Martina Lüthi, Elvira Mächler, Frederik Bendix Thostrup, Guglielmo Murari, Marina Mura, Paola Pulido-Santacruz, Florencia Sangermano, Tobias Schindler, Claus Melvad, Stefano MintchevKristy Deiner

^*Corresponding author for this work

Department of Mechanical and Production Engineering - Mechatronics and Dynamics

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Abstract

Zoonotic malaria risk at human-wildlife-environment interfaces requires surveillance that integrates signals from reservoirs, vectors and the environment. We coupled a drone-based environmental DNA (eDNA) canopy swabbing approach with portable quantitative PCR (qPCR) to detect Plasmodium DNA in situ during a 24-h field exercise in the Amazon rainforest. Drone-lowered sterile swabs into the canopy, which were then extracted and subjected to a multiplex pan-Plasmodium assay targeting five human-infecting Plasmodium species (limit of detection 0.2 parasites μL⁻¹). Of 12 samples (10 canopy swabs, 2 field blanks; 13 total runs including repeats), one canopy swab amplified in duplicate (Ct = 28.7 and 29.23), while positive controls amplified as expected (Ct = 30.82 and 31.11) and all other environmental samples and blanks were negative. Passive acoustics confirmed co-occurring howler monkeys (Alouatta spp.), a known reservoir, whereas Anopheles mosquitoes were not recovered from concurrently deployed insect canopy traps. The end-to-end workflow, from drone deployment to qPCR diagnostic readout, averaged 1.5 h per assay, without requiring cold-chain logistics. This proof-of-concept demonstrates that intracellular parasite DNA can be recovered from canopy surfaces and read out in real-time, providing upstream, landscape-level intelligence to guide targeted vector surveillance in remote settings. Our approach operationalizes One Health by integrating environmental, wildlife, and vector signals within a single technological platform, representing a paradigm shift from reactive, sector-specific surveillance to proactive, integrated pathogen intelligence across the human-animal-environment interface.

Original language	English
Article number	101167
Journal	One Health
Volume	21
DOIs	https://doi.org/10.1016/j.onehlt.2025.101167
Publication status	Published - Dec 2025

Keywords

Amazon rainforest
Environmental DNA
Indigenous communities
Mobile laboratory
One Health
Parasites
Plasmodium
Spillover
Surface swabbing
Zoonosis

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Ip, Y. C. A., Montemartini, L., Chang, J. J. M., Desiderato, A., Franco-Sierra, N. D., Geckeler, C., Herrera, M. A. G., Gregorini, M., Jucker, M., Kirchgeorg, S., Lüthi, M., Mächler, E., Thostrup, F. B., Murari, G., Mura, M., Pulido-Santacruz, P., Sangermano, F., Schindler, T., Melvad, C., ... Deiner, K. (2025). Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR. One Health, 21, Article 101167. https://doi.org/10.1016/j.onehlt.2025.101167

@article{f84d008231ed42448d6f4de85db4a2be,

title = "Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR",

abstract = "Zoonotic malaria risk at human-wildlife-environment interfaces requires surveillance that integrates signals from reservoirs, vectors and the environment. We coupled a drone-based environmental DNA (eDNA) canopy swabbing approach with portable quantitative PCR (qPCR) to detect Plasmodium DNA in situ during a 24-h field exercise in the Amazon rainforest. Drone-lowered sterile swabs into the canopy, which were then extracted and subjected to a multiplex pan-Plasmodium assay targeting five human-infecting Plasmodium species (limit of detection 0.2 parasites μL−1). Of 12 samples (10 canopy swabs, 2 field blanks; 13 total runs including repeats), one canopy swab amplified in duplicate (Ct = 28.7 and 29.23), while positive controls amplified as expected (Ct = 30.82 and 31.11) and all other environmental samples and blanks were negative. Passive acoustics confirmed co-occurring howler monkeys (Alouatta spp.), a known reservoir, whereas Anopheles mosquitoes were not recovered from concurrently deployed insect canopy traps. The end-to-end workflow, from drone deployment to qPCR diagnostic readout, averaged 1.5 h per assay, without requiring cold-chain logistics. This proof-of-concept demonstrates that intracellular parasite DNA can be recovered from canopy surfaces and read out in real-time, providing upstream, landscape-level intelligence to guide targeted vector surveillance in remote settings. Our approach operationalizes One Health by integrating environmental, wildlife, and vector signals within a single technological platform, representing a paradigm shift from reactive, sector-specific surveillance to proactive, integrated pathogen intelligence across the human-animal-environment interface.",

keywords = "Amazon rainforest, Environmental DNA, Indigenous communities, Mobile laboratory, One Health, Parasites, Plasmodium, Spillover, Surface swabbing, Zoonosis",

author = "Ip, \{Yin Cheong Aden\} and Luca Montemartini and Chang, \{Jia Jin Marc\} and Andrea Desiderato and Franco-Sierra, \{Nicol{\'a}s D.\} and Christian Geckeler and Herrera, \{Mailyn Adriana Gonzalez\} and Michele Gregorini and Meret Jucker and Steffen Kirchgeorg and Martina L{\"u}thi and Elvira M{\"a}chler and Thostrup, \{Frederik Bendix\} and Guglielmo Murari and Marina Mura and Paola Pulido-Santacruz and Florencia Sangermano and Tobias Schindler and Claus Melvad and Stefano Mintchev and Kristy Deiner",

note = "Publisher Copyright: {\textcopyright} 2025 The Authors",

year = "2025",

month = dec,

doi = "10.1016/j.onehlt.2025.101167",

language = "English",

volume = "21",

journal = "One Health",

issn = "2352-7714",

publisher = "Elsevier B.V.",

}

Ip, YCA, Montemartini, L, Chang, JJM, Desiderato, A, Franco-Sierra, ND, Geckeler, C, Herrera, MAG, Gregorini, M, Jucker, M, Kirchgeorg, S, Lüthi, M, Mächler, E, Thostrup, FB, Murari, G, Mura, M, Pulido-Santacruz, P, Sangermano, F, Schindler, T, Melvad, C, Mintchev, S & Deiner, K 2025, 'Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR', One Health, vol. 21, 101167. https://doi.org/10.1016/j.onehlt.2025.101167

TY - JOUR

T1 - Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR

AU - Ip, Yin Cheong Aden

AU - Montemartini, Luca

AU - Chang, Jia Jin Marc

AU - Desiderato, Andrea

AU - Franco-Sierra, Nicolás D.

AU - Geckeler, Christian

AU - Herrera, Mailyn Adriana Gonzalez

AU - Gregorini, Michele

AU - Jucker, Meret

AU - Kirchgeorg, Steffen

AU - Lüthi, Martina

AU - Mächler, Elvira

AU - Thostrup, Frederik Bendix

AU - Murari, Guglielmo

AU - Mura, Marina

AU - Pulido-Santacruz, Paola

AU - Sangermano, Florencia

AU - Schindler, Tobias

AU - Melvad, Claus

AU - Mintchev, Stefano

AU - Deiner, Kristy

PY - 2025/12

Y1 - 2025/12

N2 - Zoonotic malaria risk at human-wildlife-environment interfaces requires surveillance that integrates signals from reservoirs, vectors and the environment. We coupled a drone-based environmental DNA (eDNA) canopy swabbing approach with portable quantitative PCR (qPCR) to detect Plasmodium DNA in situ during a 24-h field exercise in the Amazon rainforest. Drone-lowered sterile swabs into the canopy, which were then extracted and subjected to a multiplex pan-Plasmodium assay targeting five human-infecting Plasmodium species (limit of detection 0.2 parasites μL−1). Of 12 samples (10 canopy swabs, 2 field blanks; 13 total runs including repeats), one canopy swab amplified in duplicate (Ct = 28.7 and 29.23), while positive controls amplified as expected (Ct = 30.82 and 31.11) and all other environmental samples and blanks were negative. Passive acoustics confirmed co-occurring howler monkeys (Alouatta spp.), a known reservoir, whereas Anopheles mosquitoes were not recovered from concurrently deployed insect canopy traps. The end-to-end workflow, from drone deployment to qPCR diagnostic readout, averaged 1.5 h per assay, without requiring cold-chain logistics. This proof-of-concept demonstrates that intracellular parasite DNA can be recovered from canopy surfaces and read out in real-time, providing upstream, landscape-level intelligence to guide targeted vector surveillance in remote settings. Our approach operationalizes One Health by integrating environmental, wildlife, and vector signals within a single technological platform, representing a paradigm shift from reactive, sector-specific surveillance to proactive, integrated pathogen intelligence across the human-animal-environment interface.

AB - Zoonotic malaria risk at human-wildlife-environment interfaces requires surveillance that integrates signals from reservoirs, vectors and the environment. We coupled a drone-based environmental DNA (eDNA) canopy swabbing approach with portable quantitative PCR (qPCR) to detect Plasmodium DNA in situ during a 24-h field exercise in the Amazon rainforest. Drone-lowered sterile swabs into the canopy, which were then extracted and subjected to a multiplex pan-Plasmodium assay targeting five human-infecting Plasmodium species (limit of detection 0.2 parasites μL−1). Of 12 samples (10 canopy swabs, 2 field blanks; 13 total runs including repeats), one canopy swab amplified in duplicate (Ct = 28.7 and 29.23), while positive controls amplified as expected (Ct = 30.82 and 31.11) and all other environmental samples and blanks were negative. Passive acoustics confirmed co-occurring howler monkeys (Alouatta spp.), a known reservoir, whereas Anopheles mosquitoes were not recovered from concurrently deployed insect canopy traps. The end-to-end workflow, from drone deployment to qPCR diagnostic readout, averaged 1.5 h per assay, without requiring cold-chain logistics. This proof-of-concept demonstrates that intracellular parasite DNA can be recovered from canopy surfaces and read out in real-time, providing upstream, landscape-level intelligence to guide targeted vector surveillance in remote settings. Our approach operationalizes One Health by integrating environmental, wildlife, and vector signals within a single technological platform, representing a paradigm shift from reactive, sector-specific surveillance to proactive, integrated pathogen intelligence across the human-animal-environment interface.

KW - Amazon rainforest

KW - Environmental DNA

KW - Indigenous communities

KW - Mobile laboratory

KW - One Health

KW - Parasites

KW - Plasmodium

KW - Spillover

KW - Surface swabbing

KW - Zoonosis

UR - https://www.scopus.com/pages/publications/105013883812

U2 - 10.1016/j.onehlt.2025.101167

DO - 10.1016/j.onehlt.2025.101167

M3 - Journal article

C2 - 40894953

AN - SCOPUS:105013883812

SN - 2352-7714

VL - 21

JO - One Health

JF - One Health

M1 - 101167

ER -

Real-time malaria detection in the Amazon rainforest via drone-collected eDNA and portable qPCR

Abstract

Keywords

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