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African Swine Fever Transmission Modeling
Research Guide

What is African Swine Fever Transmission Modeling?

African Swine Fever Transmission Modeling develops mechanistic and stochastic models to simulate ASF virus spread among wild boars, domestic pigs, and via fomites, integrating livestock movements and interventions.

Researchers use compartmental SEIR models and agent-based simulations to predict ASF outbreaks. These models incorporate vector roles like Ornithodoros ticks and fomite transmission (Gaudreault et al., 2020, 404 citations). Over 300 papers address ASF epidemiology since 2000, with focus on European incursions since 2014 (Chenais et al., 2019, 316 citations).

Curated Papers

Key Challenges

Why It Matters

ASF modeling informs biosecurity measures and culling strategies, protecting $250B+ global pork industries from outbreaks causing 100% mortality in pigs (Penrith and Vosloo, 2009, 295 citations). Models evaluate trade restrictions and vaccination scenarios, as in European wild boar cycles (Chenais et al., 2019). Plowright et al. (2017, 1176 citations) link such modeling to preventing zoonotic spillovers from wildlife-livestock interfaces, while Gortázar et al. (2007, 459 citations) highlight shared disease risks in Europe.

Key Research Challenges

Wildlife-Livestock Interface Modeling

Capturing bidirectional transmission between wild boars and domestic pigs requires integrating heterogeneous contact networks. Gortázar et al. (2007) document European wildlife-livestock disease sharing, complicating parameter estimation. Stochastic models struggle with sparse field data on boar densities.

Fomite and Vector Transmission

Quantifying indirect spread via contaminated vehicles and Ornithodoros ticks demands multi-pathway models. Gaudreault et al. (2020) identify ASFV as a DNA arbovirus maintained by ticks in sylvatic cycles. Validation remains challenging due to unobserved fomite events (Penrith and Vosloo, 2009).

Intervention Scenario Evaluation

Simulating culling, zoning, and movement bans under uncertainty needs probabilistic frameworks. Chenais et al. (2019) review 2014-2018 European epidemiology, stressing adaptive strategies. Models often overlook human behavior in compliance.

Essential Papers

Pathways to zoonotic spillover

Raina K. Plowright, Colin R. Parrish, Hamish McCallum et al. · 2017 · Nature Reviews Microbiology · 1.2K citations

Prediction and prevention of the next pandemic zoonosis

Stephen S. Morse, Jonna A. K. Mazet, Mark Woolhouse et al. · 2012 · The Lancet · 1.1K citations

An overview of calf diarrhea - infectious etiology, diagnosis, and intervention

Yong-Il Cho, Kyoung‐Jin Yoon · 2014 · Journal of Veterinary Science · 687 citations

Calf diarrhea is a commonly reported disease in young animals, and still a major cause of productivity and economic loss to cattle producers worldwide. In the report of the 2007 National Animal Hea...

Emerging human infectious diseases and the links to global food production

Jason R. Rohr, Christopher B. Barrett, David J. Civitello et al. · 2019 · Nature Sustainability · 678 citations

Infectious diseases are emerging globally at an unprecedented rate while global food demand is projected to increase sharply by 2100. Here, we synthesize the pathways by which projected agricultura...

Diseases shared between wildlife and livestock: a European perspective

Christian Gortázar, E. Ferroglio, Úrsula Höfle et al. · 2007 · European Journal of Wildlife Research · 459 citations

African Swine Fever Virus: An Emerging DNA Arbovirus

Natasha N. Gaudreault, Daniel W. Madden, William C. Wilson et al. · 2020 · Frontiers in Veterinary Science · 404 citations

African swine fever virus (ASFV) is the sole member of the family <i>Asfarviridae</i>, and the only known DNA arbovirus. Since its identification in Kenya in 1921, ASFV has remained endemic in Afri...

Epidemiological considerations on African swine fever in Europe 2014–2018

Erika Chenais, Klaus Depner, Vittorio Gubertì et al. · 2019 · Porcine Health Management · 316 citations

Reading Guide

Foundational Papers

Start with Penrith and Vosloo (2009, 295 citations) for core transmission routes, then Morse et al. (2012, 1067 citations) for zoonotic prevention frameworks, and Gortázar et al. (2007, 459 citations) for wildlife-livestock interfaces.

Recent Advances

Study Chenais et al. (2019, 316 citations) for 2014-2018 Europe data and Gaudreault et al. (2020, 404 citations) for tick vector biology.

Core Methods

SEIR compartments for direct spread, agent-based for spatial boar movements, stochastic simulations for interventions (Chenais et al., 2019). Network models capture fomite paths (Gaudreault et al., 2020).

How PapersFlow Helps You Research African Swine Fever Transmission Modeling

Discover & Search

Research Agent uses searchPapers('African Swine Fever transmission model wild boar') to retrieve 500+ papers, then citationGraph on Chenais et al. (2019) reveals 316-cited clusters on European spread. findSimilarPapers extends to stochastic simulations, while exaSearch uncovers gray literature on fomite risks.

Analyze & Verify

Analysis Agent applies readPaperContent to Gaudreault et al. (2020) for tick vector details, verifyResponse with CoVe cross-checks model parameters against Penrith and Vosloo (2009). runPythonAnalysis simulates SEIR dynamics via NumPy/pandas on outbreak data, with GRADE scoring evidence strength for intervention efficacy.

Synthesize & Write

Synthesis Agent detects gaps in wildlife modeling via contradiction flagging across Gortázar et al. (2007) and Chenais et al. (2019), while Writing Agent uses latexEditText, latexSyncCitations for model equations, and latexCompile for publication-ready reports. exportMermaid visualizes transmission network diagrams.

Use Cases

"Simulate ASF spread in wild boar populations with Python"

Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (NumPy SEIR model on Chenais 2019 data) → matplotlib plot of R0 scenarios.

"Draft LaTeX paper on ASF fomite transmission models"

Synthesis Agent → gap detection → Writing Agent → latexEditText (add equations) → latexSyncCitations (Gaudreault 2020) → latexCompile → PDF with figures.

"Find code for agent-based ASF simulations"

Research Agent → paperExtractUrls → Code Discovery → paperFindGithubRepo → githubRepoInspect → runnable NetLogo model for wild-domestic pig contacts.

Automated Workflows

Deep Research workflow scans 50+ ASF papers via searchPapers → citationGraph → structured report on transmission pathways (Gaudreault et al., 2020). DeepScan's 7-step chain with CoVe verifies model assumptions against Chenais et al. (2019) epidemiology. Theorizer generates hypotheses on tick-fomite synergies from Penrith and Vosloo (2009).

Try Doxa for African Swine Fever Transmission Modeling Research

Frequently Asked Questions

What defines African Swine Fever Transmission Modeling?

Mechanistic models simulate ASFV spread via direct contacts, fomites, and vectors like Ornithodoros ticks among pigs and wild boars (Gaudreault et al., 2020).

What methods are used in ASF modeling?

Stochastic SEIR and agent-based models integrate livestock movements and interventions (Chenais et al., 2019). These extend compartmental frameworks with spatial networks.

What are key papers on ASF transmission?

Gaudreault et al. (2020, 404 citations) detail arbovirus cycles; Chenais et al. (2019, 316 citations) cover European epidemiology; Penrith and Vosloo (2009, 295 citations) review spread mechanisms.

What open problems exist in ASF modeling?

Parameterizing fomite risks and human-mediated spread remains unresolved due to data gaps (Penrith and Vosloo, 2009). Wildlife density estimation hinders accurate simulations (Gortázar et al., 2007).