Tropical medicine and infectious disease · 2025
High-Resolution Geospatial Analysis of Dengue Vulnerability in Urban and Rural Areas of San Luis Potosí, Mexico.
СтатьяНазвание и аннотация: Перевод в очереди
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Gaytán Hernández Darío, Sánchez Hernández Daniel, Hernández Ibarra Luis Eduardo, Ibarra Zapata Enrique, Parra Rodríguez Omar, Gallegos García Verónica, Medina de la Cruz Omar, Gallegos García Marisol
Аннотация
OBJECTIVE: The aim was to analyze the temporal evolution and spatial distribution of classic and hemorrhagic dengue in the Mexican state of San Luis Potosí at the basic geostatistical area (BGA) level and to develop multivariate models to estimate the population's degree of vulnerability.
METHODOLOGY: Classic and hemorrhagic dengue cases for 2015-2020 were obtained from the Mexican Ministry of Health, georeferenced at the pixel level, and subsequently grouped by BGA. Environmental, proximity, and social variables were obtained from official sites: IMTA, SMN, USGS, and INEGI. Multivariate logistic regression models were developed using PASW Statistics v. 18 software to estimate the degree of vulnerability, and the receiver operating characteristic curve was used to validate them.
RESULTS: A total of 125, 128, 109, 624, 1580, and 1817 dengue cases were identified for 2015, 2016, 2017, 2018, 2019, and 2020, respectively. The major factors contributing to the vulnerability of classic dengue fever included population, temperature, and distance to agricultural areas. For hemorrhagic dengue, the contributing factors were temperature, population, and mean annual rainfall. Vulnerability prediction was determined by taking the area under the curve values, which were 0.957 for classic dengue fever and 0.930 for hemorrhagic dengue, both indicating a "very good ability" to predict.
CONCLUSIONS: These results can be used to design and implement targeted strategies, particularly for modifiable factors, such as prevention measures directed towards populated areas and the improvement of sewage systems, in addition to non-modifiable factors, such as temperature and rainfall. This method can be replicated as an additional tool to address this public health issue.
METHODOLOGY: Classic and hemorrhagic dengue cases for 2015-2020 were obtained from the Mexican Ministry of Health, georeferenced at the pixel level, and subsequently grouped by BGA. Environmental, proximity, and social variables were obtained from official sites: IMTA, SMN, USGS, and INEGI. Multivariate logistic regression models were developed using PASW Statistics v. 18 software to estimate the degree of vulnerability, and the receiver operating characteristic curve was used to validate them.
RESULTS: A total of 125, 128, 109, 624, 1580, and 1817 dengue cases were identified for 2015, 2016, 2017, 2018, 2019, and 2020, respectively. The major factors contributing to the vulnerability of classic dengue fever included population, temperature, and distance to agricultural areas. For hemorrhagic dengue, the contributing factors were temperature, population, and mean annual rainfall. Vulnerability prediction was determined by taking the area under the curve values, which were 0.957 for classic dengue fever and 0.930 for hemorrhagic dengue, both indicating a "very good ability" to predict.
CONCLUSIONS: These results can be used to design and implement targeted strategies, particularly for modifiable factors, such as prevention measures directed towards populated areas and the improvement of sewage systems, in addition to non-modifiable factors, such as temperature and rainfall. This method can be replicated as an additional tool to address this public health issue.