IDEAS home Printed from https://ideas.repec.org/a/plo/pntd00/0007914.html
   My bibliography  Save this article

Estimating snakebite incidence from mathematical models: A test in Costa Rica

Author

Listed:
  • Carlos A Bravo-Vega
  • Juan M Cordovez
  • Camila Renjifo-Ibáñez
  • Mauricio Santos-Vega
  • Mahmood Sasa

Abstract

Background: Snakebite envenoming is a neglected public health challenge that affects mostly economically deprived communities who inhabit tropical regions. In these regions, snakebite incidence data is not always reliable, and access to health care is scare and heterogeneous. Thus, addressing the problem of snakebite effectively requires an understanding of how spatial heterogeneity in snakebite is associated with human demographics and snakes’ distribution. Here, we use a mathematical model to address the determinants of spatial heterogeneity in snakebite and we estimate snakebite incidence in a tropical country such as Costa Rica. Methods and findings: We combined a mathematical model that follows the law of mass action, where the incidence is proportional to the exposed human population and the venomous snake population, with a spatiotemporal dataset of snakebite incidence (Data from year 1990 to 2007 for 193 districts) in Costa Rica. This country harbors one of the most dangerous venomous snakes, which is the Terciopelo (Bothrops asper, Garman, 1884). We estimated B. asper distribution using a maximum entropy algorithm, and its abundance was estimated based on field data. Then, the model was adjusted to the data using a lineal regression with the reported incidence. We found a significant positive correlation (R2 = 0.66, p-value

Suggested Citation

  • Carlos A Bravo-Vega & Juan M Cordovez & Camila Renjifo-Ibáñez & Mauricio Santos-Vega & Mahmood Sasa, 2019. "Estimating snakebite incidence from mathematical models: A test in Costa Rica," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 13(12), pages 1-16, December.
    • Handle: RePEc:plo:pntd00:0007914
    DOI: 10.1371/journal.pntd.0007914
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0007914
    Download Restriction: no
    File URL: https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0007914&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pntd.0007914?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Erik Hansson & Steven Cuadra & Anna Oudin & Kim de Jong & Emilie Stroh & Kjell Torén & Maria Albin, 2010. "Mapping Snakebite Epidemiology in Nicaragua – Pitfalls and Possible Solutions," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 4(11), pages 1-9, November.
    2. Paula M Luz & Claudio J Struchiner & Alison P Galvani, 2010. "Modeling Transmission Dynamics and Control of Vector-Borne Neglected Tropical Diseases," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 4(10), pages 1-6, October.
    3. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    4. Vanessa Racloz & Rebecca Ramsey & Shilu Tong & Wenbiao Hu, 2012. "Surveillance of Dengue Fever Virus: A Review of Epidemiological Models and Early Warning Systems," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 6(5), pages 1-9, May.
    5. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    6. Robert A Harrison & Adam Hargreaves & Simon C Wagstaff & Brian Faragher & David G Lalloo, 2009. "Snake Envenoming: A Disease of Poverty," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 3(12), pages 1-6, December.
    7. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Zacarias & Rafael Loyola, 2019. "Climate change impacts on the distribution of venomous snakes and snakebite risk in Mozambique," Climatic Change, Springer, vol. 152(1), pages 195-207, January.
    2. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    3. Carlos Yañez-Arenas & A Townsend Peterson & Pierre Mokondoko & Octavio Rojas-Soto & Enrique Martínez-Meyer, 2014. "The Use of Ecological Niche Modeling to Infer Potential Risk Areas of Snakebite in the Mexican State of Veracruz," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
    4. Ioana Gutu & Daniela Tatiana Agheorghiesei & Alexandru Tugui, 2023. "Assessment of a Workforce Sustainability Tool through Leadership and Digitalization," IJERPH, MDPI, vol. 20(2), pages 1-30, January.
    5. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    6. S. A. Abu Bakar & Saralees Nadarajah & Z. A. Absl Kamarul Adzhar, 2018. "Loss modeling using Burr mixtures," Empirical Economics, Springer, vol. 54(4), pages 1503-1516, June.
    7. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    8. Herbert Hoijtink & Meinte Vollema, 2003. "Contemporary Extensions of the Rasch Model," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 263-276, August.
    9. Jaewoong Yun, 2023. "Strategies for Improving the Sustainability of Fare-Free Policy for the Elderly through Preferences by Travel Modes," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    10. Malerba, Martino E. & Connolly, Sean R. & Heimann, Kirsten, 2015. "An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake," Ecological Modelling, Elsevier, vol. 317(C), pages 30-40.
    11. Aline Riboli Marasca & Maurício Scopel Hoffmann & Anelise Reis Gaya & Denise Ruschel Bandeira, 2021. "Subjective Well-Being and Psychopathology Symptoms: Mental Health Profiles and their Relations with Academic Achievement in Brazilian Children," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1121-1137, June.
    12. Friederike Paetz, 2016. "Persönlichkeitsmerkmale als Segmentierungsvariablen: Eine empirische Studie [Personality traits for market segmentation: An empirical study]," Schmalenbach Journal of Business Research, Springer, vol. 68(3), pages 279-306, August.
    13. Emre Demirkaya & Yang Feng & Pallavi Basu & Jinchi Lv, 2022. "Large-scale model selection in misspecified generalized linear models [Information theory and an extension of the maximum likelihood principle]," Biometrika, Biometrika Trust, vol. 109(1), pages 123-136.
    14. Kraisak Kesorn & Phatsavee Ongruk & Jakkrawarn Chompoosri & Atchara Phumee & Usavadee Thavara & Apiwat Tawatsin & Padet Siriyasatien, 2015. "Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    15. Rosbergen, Edward & Wedel, Michel & Pieters, Rik, 1997. "Analyzing visual attention tot repeated print advertising using scanpath theory," Research Report 97B32, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    16. Eduardo Correia & Rodrigo Calili & José Francisco Pessanha & Maria Fatima Almeida, 2023. "Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions," Energies, MDPI, vol. 16(6), pages 1-22, March.
    17. Thiago L. Jucá & Leonardo R. Oliveira Normando & Abdulrazak B. Ibrahim & Alex Chapeaurouge & Ana Cristina de Oliveira Monteiro‐Moreira & Stephen P. Mackessy, 2021. "Drought, desertification and poverty: A geospatial analysis of snakebite envenoming in the Caatinga biome of Brazil," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(5), pages 1685-1696, September.
    18. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.
    19. Golob, Thomas F. & Regan, A C, 2002. "Trucking Industry Preferences for Driver Traveler Information Using Wireless Internet-enabled Devices," University of California Transportation Center, Working Papers qt40q8h6sf, University of California Transportation Center.
    20. Golob, Thomas F. & Regan, A C, 2003. "Traffic Congestion and Trucking Managers' Use of Automated Routing and Scheduling," University of California Transportation Center, Working Papers qt74z234n4, University of California Transportation Center.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pntd00:0007914. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosntds (email available below). General contact details of provider: https://journals.plos.org/plosntds/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.