Proceedings from the Fourth Mesoamerican Symposium “Dr. Roberto Navarro López” on Emerging Zoonotic Disease and Arboviruses: Commenting Insights and Research Findings
Bibliographic record
Abstract
Nadia A Fernández-Santos,1,2,* Mario A Rodríguez-Pérez,1,* Sofía Segovia-Mancillas,1,3,* Luis L Rodríguez,4 Sarah A Hamer,5 Gabriel L Hamer,2 Fabián Correa-Morales,6 Susano Medina-Jaramillo,7 Maria Gabriela Palacios-Mendoza,8 Epigmenio Cruz-Aldán,9 Gabriela del Carmen Rodriguez-Dominguez,10 Carlos H Gomez-Hernandez,10 Arturo Larraga-Guillén,11 Irene López González,11 Luis M Rodríguez-Martínez,12 Aldo I Ortega-Morales,13 Ma Isabel Salazar,14 Héctor Enrique Valdez-Gómez,11 Miguel A Márquez Ruiz,15 Maria J Perteguer,16 Benjamín Gastón Gómez-Gordillo,17 Jesús A Aguilar-Durán,1 Ingeborg D Becker Fauser,18 Scott C Weaver,19 Michael J Turell,20 Laura D Kramer,21,* Jose Guillermo Estrada-Franco1,* 1Instituto Politécnico Nacional, Centro de Biotecnología Genómica, Reynosa, Tamaulipas, Mexico; 2Department of Entomology, Texas A&M University, College Station, TX, USA; 3Facultad de Medicina, Universidad México Americana del Norte, Reynosa, Tamaulipas, Mexico; 4Foreign Animal Disease Research Unit, USDA/ARS Plum Island Animal Disease Center, Greenport, NY, USA; 5Department of Veterinary Integrative Biosciences, College Station, TX, USA; 6Centro Nacional de Programas Preventivos y Control de Enfermedades, Secretaría de Salud, Ciudad de México, Mexico; 7Academia Veterinaria Mexicana, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Ciudad de México, Mexico; 8Zoologico Miguel Alvarez del Toro (ZOOMAT), Tuxtla Gutierrez, Chiapas, Mexico; 9Programas Ambientales Grupo Libera, Merida, Yucatán, Mexico; 10Laboratorio Estatal de Salud, Secretaria de Salud de Chiapas, Tuxtla Gutierrez, Chiapas, Mexico; 11CPA-SENASICA, Comisión México-Estados Unidos para la Prevención de la Fiebre Aftosa y otras Enfermedades Exóticas de los Animales, Ciudad de México, Mexico; 12Centro de Estudios e Investigaciones Interdisciplinarios, Universidad Autónoma de Coahuila, Saltillo, Coahuila, Mexico; 13Universidad Autónoma Agraria Antonio Narro Unidad Laguna, Torreón, Coahuila, Mexico; 14Laboratorio Nacional de Vacunología y Virus Tropicales, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Ciudad de México, Mexico; 15Departamento de Postgrado en Medicina Aviar, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Ciudad de México, Mexico; 16Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain; 17Comisión Nacional de Áreas Naturales Protegidas (CONANP), Palacio Federal 3er. Piso, Segunda Oriente-Norte, Tuxtla Gutiérrez, Chiapas, C.P. 29000, Mexico; 18Universidad Nacional Autónoma de México, Facultad de Medicina, Departamento de Medicina Experimental, Hospital General de México, Ciudad de México, Mexico; 19World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; 20VectorID LLC, Frederick, MD, USA; 21School of Public Health, University of the State of New York at Albany, Albany, NY, USA*These authors contributed equally to this workCorrespondence: Jose Guillermo Estrada-Franco, Instituto Politécnico Nacional, Centro de Biotecnología Genómica, Reynosa, Tamaulipas, Mexico, Tel +525534535428, Email jestradaf@ipn.mx Laura D Kramer, School of Public Health, University of the State of New York at Albany, Albany, NY, USA, Tel +15183222706, Email ldkculex@gmail.comAbstract: Zoonotic pathogens such as arboviruses, arenaviruses, filoviruses, coronaviruses, highly pathogenic Avian Influenza A (H5N1) viruses, vesiculoviruses, and many others are emerging and reemerging worldwide, jeopardizing global veterinary and public health. Parasitic diseases such as visceral and cutaneous leishmaniasis, trypanosomiasis (Trypanosoma cruzi), myiasis, and river blindness (Onchocerca volvulus) are also paramount for public health in the Americas and elsewhere. In the fall 2024, a group of experts convened in Chiapas, Mexico, for the Fourth Mesoamerican Symposium “Dr. Roberto Navarro López” on Arboviruses and Emerging Zoonotic Diseases. Here, we highlight the importance of some zoonotic pathogens and parasites affecting human health that are being impacted by anthropogenic activities. In this context, there are drivers such as changes in climate and landscape transformations, unsound agricultural practices, and wildlife niche replacement delivering numerous opportunities for zoonotic pathogens to emerge and threaten human health and food security.Keywords: zoonosis, arboviruses, emerging diseases, re-emerging diseases, symposium, training course
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".