---
title: "Canine rabies network reconstruction: DCSBM outperforms synthetic graph generators"
id: "biorxiv-2-contact-heterogeneity-in-network-reconstruction-evaluating-synthetic-graph"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-2-contact-heterogeneity-in-network-reconstruction-evaluating-synthetic-graph"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1?rss=1"
published_at: "2026-10-22T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Canine rabies network reconstruction: DCSBM outperforms synthetic graph generators
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-2-contact-heterogeneity-in-network-reconstruction-evaluating-synthetic-graph
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1?rss=1)
- **Published At:** 2026-10-22T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The study compared five synthetic **graph generators** against five empirical free-roaming dog contact networks collected in Chad, Indonesia, and Guatemala, evaluating both network topology and outbreak dynamics. - Investigators simulated transmission using both **SEIR** and **SIS** frameworks across a range of infectious-period lengths to probe pathogen-dependent sensitivity of reconstruction choice. - The degree-corrected stochastic block model (**DCSBM**) most consistently matched empirical networks, returning a Mahalanobis distance of 17.6 to the empirical Chad network; other generators produced distances spanning 21.0 to 220.7. - For short infectious windows—relevant to **canine rabies**—outbreak dynamics diverged more between generators; DCSBM reproduced empirical outbreak outcomes most faithfully under these conditions. - As infectious-period length increased, the simulated outbreak measures from most generators converged: by a nine-day infectious window, four of five generators produced outbreak outcomes within two percentage points of the empirical reference. - The findings indicate that both degree heterogeneity and community structure are key features to capture when reconstructing contact networks for short-window pathogens; for long-window pathogens, simpler generators may suffice. - The paper used five empirical datasets and multiple simulated transmission scenarios; the authors reported no competing interests and provided no additional methodological details beyond those in the preprint.
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Inez Derkx 1 Swiss TPH: Schweizerisches Tropen- und Public Health-Institut; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Inez%2BDerkx%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Derkx%20I&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AInez%2BDerkx%2B) * [ORCID record for Inez Derkx](http://orcid.org/0000-0002-6889-494X "Open in new tab") * For correspondence: inez.derkx@swisstph.ch James Mac Hyman 2 Tulane University; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=James%2B%2BMac%2BHyman%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Hyman%20J&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AJames%2B%2BMac%2BHyman%2B) * [ORCID record for James Mac Hyman](http://orcid.org/0000-0001-5247-5794 "Open in new tab") Fatima Abdelrazak Zakaria 3 Institut de Recherche en Elevage pour le Développement, N’Djamena, Chad; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Fatima%2BAbdelrazak%2BZakaria%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Abdelrazak%20Zakaria%20F&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AFatima%2BAbdelrazak%2BZakaria%2B) Mahamat Fayiz Abakar 3 Institut de Recherche en Elevage pour le Développement, N’Djamena, Chad; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Mahamat%2B%2BFayiz%2BAbakar%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Abakar%20M&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AMahamat%2B%2BFayiz%2BAbakar%2B) Salome Dürr 4 Universität Bern Veterinary Public Health Institute; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Salome%2BD%C3%BCrr%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=D%C3%BCrr%20S&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ASalome%2BD%25C3%25BCrr%2B) Nakul Chitnis 5 Swiss TPH * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Nakul%2BChitnis%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Chitnis%20N&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ANakul%2BChitnis%2B) * [Abstract](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5893711/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5893711/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5893711/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5893711/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## Abstract Canine rabies remains endemic across much of Africa and Asia, causing approximately 59,000 global deaths yearly. Network-based models that reconstruct contact patterns are central to predicting canine rabies transmission and to designing targeted interventions, but the choice of network generator algorithm may alter network structure and outbreak predictions. We therefore compared five network generators using five empirical free-roaming dog contact networks from Chad, Indonesia, and Guatemala in network topology and outbreak dynamics under susceptible-exposed-infectious-removed (SEIR) and susceptible-infectious-susceptible (SIS) transmission across a range of infectious-period lengths. We found that the degree-corrected stochastic block model (DCSBM) most consistently reproduces both empirical topology and outbreak dynamics, achieving a Mahalanobis distance of 17.6 to the empirical Chad network compared to a range of 21.0 to 220.7 across the other generators and yielding similar results for the other four locations. Moreover, the SIS and SEIR outbreak dynamics reveal that the DCSBM overall best reproduces the simulated empirical outbreak dynamics, but that the consequences of generator choice are not uniform: network reconstruction matters most precisely for short-infectious-window pathogens like canine rabies and progressively less for long-infectious-window pathogens. By an infectious window of nine days, the outbreak dynamics across four of five generators converge to within two percentage points of the empirical reference, even when their underlying topologies differ substantially. This pathogen-dependent sensitivity offers a principled criterion for when generator selection is consequential and when it is not. This work reiterates the importance of both degree heterogeneity and community structure for faithful contact-network reconstruction in canine rabies modeling, particularly for short-window infectious diseases where contact heterogeneity drives transmission. For longer-window pathogens, simpler generators are likely adequate. ### Competing Interest Statement The authors have declared no competing interest. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY 4.0 International license](http://creativecommons.org/licenses/by/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. 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[ Download PDF](https://www.biorxiv.org/content/10.64898/2026.10.16.759544v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/10/22/2026.10.16.759544.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) Contact heterogeneity in network reconstruction: evaluating synthetic graph generators for rabies transmission modeling Inez Derkx, James Mac Hyman, Fatima Abdelrazak Zakaria, Mahamat Fayiz Abakar, Salome Dürr, Nakul Chitnis bioRxiv 2026.10.16.759544; doi: https://doi.org/10.64898/2026.10.16.759544 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. 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