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Record W4417259304 · doi:10.64898/2025.12.07.25341615

Contact in context: Animal profiles, human activities, and land use histories shape human-animal contacts with implications for zoonotic spillover in the Democratic Republic of Congo

2025· preprint· en· W4417259304 on OpenAlexfundno aff
Romain Duda, Victor Narat, Robert Monfura, Marc Allassonnière‐Tang, Placide Mbala‐Kingebeni, Claude Monghiemo, Tamara Giles‐Vernick

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsnot available
FundersAgence Nationale de la RechercheCanadian Institute for Advanced Research
KeywordsBiodiversityLand useSpillover effectTransectCarnivoreRelative species abundanceAbundance (ecology)Introduced species

Abstract

fetched live from OpenAlex

Abstract Pathogenic spillovers from animals into humans have catalyzed epidemics throughout history. They result from multiple factors. One such factor, human-animal contact, remains poorly understood. Current studies often neglect variability in human-animal engagements across ecological zones and the broader processes bringing people, animals, and pathogens into engagement. We investigated factors and longer-term processes shaping human-animal contacts and risks of zoonotic spillover in a region experiencing landscape fragmentation. We conducted our mixed-methods investigation in three villages along an ecological gradient of forest fragmentation in the Democratic Republic of Congo (DRC), a hotspot of biodiversity and disease emergence. Among 24 village participants, we collected daily activities and contacts with highly diverse animal species to evaluate the types and frequencies of these contacts. We developed a cluster analysis to categorize classes of animals according to type and frequency of contact. We also conducted transects to estimate animal species abundance according to village proximity. We tested the influence of animal species abundance, human activities, gender, and village on human-animal contact frequency. We conducted ethnographic and ethnohistorical interviews and observations to explore changing human-animal relations. Participants had physical and environmental contact with 61 different animal species. We found three classes of animal species with which participants had most frequent physical and environmental contact. Historical processes and human activities, avoidance toward some animal species, and relative abundance of species contribute to shape contemporary human-animal contacts, and more broadly, potential risks of exposures to zoonotic pathogens. Our modeling of gender, village, relative abundance and human activities on animals clustered by contact frequency, however, yielded few predictors of contact frequency. We identify factors and processes associated with human-animal contacts in an ecologically varied zone and its categorization of contact profiles. Future studies should explore a wider array of human-animal contacts and situate them in their historical contexts. Author Summary Pathogenic spillovers from animals into humans have catalyzed epidemics throughout history. These spillovers result from many factors, although one –– human-animal contact –– is poorly understood. The variability of human-animal interactions and historical changes shaping interactions between people, animals, and pathogens are not well addressed. Our mixed-methods study explored factors and longer-term processes affecting human-animal contacts and risks of spillover in a fragmented forest of the Democratic Republic of Congo. We found that participants had physical and environmental contact with 61 different animal species. We identified three classes of animal species with which participants had most frequent physical and environmental contact. These classes were shaped by three major factors: historical changes affecting human activities and ecologies; human preferences to avoid certain species; and relative abundance of animal species. More broadly, these classes reflected potential risks of exposures to zoonotic pathogens. Although our model to predict how gender, village, relative abundance and human activities influenced these animal classes clustered by contact frequency, it yielded few predictors. Our study did, however, identify factors and processes associated with human-animal contacts in an fragmented forest zone. We recommend that future studies explore a wider array of human-animal contacts, situating them in their historical contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.332
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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