Estimating snakebite incidence from mathematical models: A test in Costa Rica.
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 pro...
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ftdoajarticles:oai:doaj.org/article:a8ab33b0f76241298a90b3f2328ec1d8 2023-05-15T15:16:18+02:00 Estimating snakebite incidence from mathematical models: A test in Costa Rica. Carlos A Bravo-Vega Juan M Cordovez Camila Renjifo-Ibáñez Mauricio Santos-Vega Mahmood Sasa 2019-12-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0007914 https://doaj.org/article/a8ab33b0f76241298a90b3f2328ec1d8 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0007914 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007914 https://doaj.org/article/a8ab33b0f76241298a90b3f2328ec1d8 PLoS Neglected Tropical Diseases, Vol 13, Iss 12, p e0007914 (2019) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2019 ftdoajarticles https://doi.org/10.1371/journal.pntd.0007914 2022-12-31T07:48:36Z 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 < 0.01) between our estimation and the reported incidence, suggesting the model has a good performance in estimating snakebite incidence. Conclusions Our model underscores the importance of the synergistic effect of exposed population size and snake abundance on snakebite incidence. By combining information from venomous snakes' natural history with census data from rural populations, we were able to estimate snakebite incidence in Costa Rica. The model was able to fit the incidence data at fine administrative scale (district level), which is fundamental for the implementation and planning of management strategies oriented to reduce snakebite burden. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 13 12 e0007914 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Carlos A Bravo-Vega Juan M Cordovez Camila Renjifo-Ibáñez Mauricio Santos-Vega Mahmood Sasa Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
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 < 0.01) between our estimation and the reported incidence, suggesting the model has a good performance in estimating snakebite incidence. Conclusions Our model underscores the importance of the synergistic effect of exposed population size and snake abundance on snakebite incidence. By combining information from venomous snakes' natural history with census data from rural populations, we were able to estimate snakebite incidence in Costa Rica. The model was able to fit the incidence data at fine administrative scale (district level), which is fundamental for the implementation and planning of management strategies oriented to reduce snakebite burden. |
format |
Article in Journal/Newspaper |
author |
Carlos A Bravo-Vega Juan M Cordovez Camila Renjifo-Ibáñez Mauricio Santos-Vega Mahmood Sasa |
author_facet |
Carlos A Bravo-Vega Juan M Cordovez Camila Renjifo-Ibáñez Mauricio Santos-Vega Mahmood Sasa |
author_sort |
Carlos A Bravo-Vega |
title |
Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
title_short |
Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
title_full |
Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
title_fullStr |
Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
title_full_unstemmed |
Estimating snakebite incidence from mathematical models: A test in Costa Rica. |
title_sort |
estimating snakebite incidence from mathematical models: a test in costa rica. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2019 |
url |
https://doi.org/10.1371/journal.pntd.0007914 https://doaj.org/article/a8ab33b0f76241298a90b3f2328ec1d8 |
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Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 13, Iss 12, p e0007914 (2019) |
op_relation |
https://doi.org/10.1371/journal.pntd.0007914 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007914 https://doaj.org/article/a8ab33b0f76241298a90b3f2328ec1d8 |
op_doi |
https://doi.org/10.1371/journal.pntd.0007914 |
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PLOS Neglected Tropical Diseases |
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13 |
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12 |
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e0007914 |
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