Evidence map›Paper›PMID 38962557›Full record

ArticleMethods in ecology and evolution2024

bistro: An R package for vector bloodmeal identification by short tandem repeat overlap.

Zena Lapp, Lucy Abel, Judith Mangeni, Andrew A Obala, Wendy P O'Meara, Steve M Taylor, Christine F Markwalter

Abstract read
In one paragraph

Article in Methods in ecology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Sickle Trait Hemoglobin Does Not Influence Anopheles Biting Rates.The American journal of tropical medicine and hygiene · 2026
    Article
  2. Sickle-trait hemoglobin does not influencemedRxiv : the preprint server for health sciences · 2025
    Article
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Zena LappDuke Global Health Institute, Duke University, Durham, NC, USA.
Lucy AbelAcademic Model Providing Access to Healthcare (AMPATH), Eldoret, Kenya.
Judith MangeniDepartment of Epidemiology and Medical Statistics, School of Public Health, Moi University, Eldoret, Kenya.
Andrew A ObalaSchool of Medicine, College of Health Sciences, Moi University, Eldoret, Kenya.
Wendy P O'MearaDuke Global Health Institute, Duke University, Durham, NC, USA.
Steve M TaylorDuke Global Health Institute, Duke University, Durham, NC, USA.
Christine F MarkwalterDuke Global Health Institute, Duke University, Durham, NC, USA.

Funding

Once Bitten: Acquisition of Malaria Adaptive Immunity (OBAMA - Immunity)R01AI179141 · NIAID · DUKE UNIVERSITY · PI Wendy PrudhommeOMeara, Steve Myer Taylor · 2023 to 2026
$4.4M
Once bitten: A longitudinal, observational study of successful malaria parasite transmission events between humans and mosquitosR01AI146849 · NIAID · DUKE UNIVERSITY · PI PRUDHOMMEOMEARA, WENDY, TAYLOR, STEVE MYER · 2019 to 2023
$3.0M
Synthesizing immunoinformatics and genetic epidemiology to identify signatures of natural functional immunity to malaria parasitesK01AI175527 · NIAID · DUKE UNIVERSITY · PI Christine Markwalter · 2023 to 2026
$486k
Antibody biomarker discovery for current and recent asymptomatic malaria exposureF32AI149950 · NIAID · DUKE UNIVERSITY · PI MARKWALTER, CHRISTINE · 2021 to 2022
$142k
NIAID NIH HHS F32 AI149950NIAID NIH HHS K01 AI175527NIAID NIH HHS R01 AI146849NIAID NIH HHS R01 AI179141
6 · The paper itself

Abstract

Measuring vector-human contact in a natural setting can inform precise targeting of interventions to interrupt transmission of vector-borne diseases. One approach is to directly match human DNA in vector bloodmeals to the individuals who were bitten using genotype panels of discriminative short tandem repeats (STRs). Existing methods for matching STR profiles in bloodmeals to the people bitten preclude the ability to match most incomplete profiles and multi-source bloodmeals to bitten individuals.We developed bistro, an R package that implements 3 preexisting STR matching methods as well as the package's namesake, bistro, a new algorithm described here. bistro employs forensic analysis methods to calculate likelihood ratios and match human STR profiles in bloodmeals to people using a dynamic threshold. We evaluated the algorithm's accuracy and compared it to existing matching approaches using a publicly-available panel of 188 single-source and 100 multi-source samples containing DNA from 50 known human sources. Then we applied it to match 777 newly field-collected mosquito bloodmeals to a database of 645 people.The R package implements four STR matching algorithms in user-friendly functions with clear documentation. bistro correctly matched 99% (187/188) of profiles in single-source samples, and 62% (224/359) of profiles from multi-source samples, resulting in a sensitivity of 0.75 (vs < 0.51 for other algorithms). The specificity of bistro was 0.9998 (vs. 1 for other algorithms). Furthermore, bistro identified 79% (720/906) of all possible matches for field-derived mosquitoes, yielding 1.4x more matches than existing algorithms.bistro identifies more correct bloodmeal-human matches than existing approaches, enabling more accurate and robust analyses of vector-human contact in natural settings. The bistro R package and corresponding documentation allow for straightforward uptake of this algorithm by others.

Indexed as

bloodmealbloodmeal matchingDNA matchingmalariamatchshort tandem repeatstrvector-borne disease

Identifiers

PMID38962557
PMCPMC11218906

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.