Evidence map›Paper›PMID 40303721›Full record

ArticleTransboundary and emerging diseases2023

A Maximum Entropy Model of the Distribution of Dengue Serotype in Mexico.

Esther Annan, Jailos Lubinda, Jesús Treviño, William Messer, Dina Fonseca, Penghua Wang, Jurgen Pilz, Benjamin Lintner, Aracely Angulo-Molina, Ana L Gallego-Hernández and 1 more

Abstract read
In one paragraph

Article in Transboundary and emerging diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Esther AnnanCenter for Health and Wellbeing, School of Public and International Affairs, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0000-0001-9816-0958
Jailos LubindaMalaria Atlas Project, Telethon Kids Institute, 6009, Nedlands, WA, Australia.ORCID https://orcid.org/0000-0001-9570-9036
Jesús TreviñoDepartment of Urban Affairs at the School of Architecture, Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Nuevo Léon 66455, Mexico.ORCID https://orcid.org/0000-0002-0211-2140
William MesserDepartment of Molecular Microbiology and Immunology, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0002-4381-6347
Dina FonsecaCenter for Vector Biology, Rutgers University, New Brunswick, NJ, USA.ORCID https://orcid.org/0000-0003-4726-7100
Penghua WangDepartment of Immunology, School of Medicine, U Conn Health, Farmington, CT 06030, USA.ORCID https://orcid.org/0000-0002-7332-1871
Jurgen PilzDepartment of Statistics, University of Klagenfurt, Klagenfurt, Austria.ORCID https://orcid.org/0000-0001-9365-4916
Benjamin LintnerDepartment of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.ORCID https://orcid.org/0000-0002-9694-5337
Aracely Angulo-MolinaDepartamento de Ciencias Químico-Biológicas, Universidad of Sonora, Hermosillo 83000, Mexico.ORCID https://orcid.org/0000-0002-8586-3387
Ana L Gallego-HernándezDepartamento de Ciencias Químico-Biológicas, Universidad of Sonora, Hermosillo 83000, Mexico.ORCID https://orcid.org/0000-0001-7818-2244
Ubydul HaqueRutgers Global Health Institute, New Brunswick, NJ, USA.ORCID https://orcid.org/0000-0002-7413-1017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus (DENV) serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling. We fit climatic variables to municipality presence records from 2012 to 2020 in Mexico. Bioclimatic variables were explored for their environmental suitability to different DENV serotypes, and the different distributions were visualized using three cutoff probabilities representing 90%, 95%, and 99% sensitivity. Municipality-level results were then mapped in ArcGIS. The overall accuracy for the predictive models was 0.69, 0.68, 0.75, and 0.72 for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Important predictors of all DENV serotypes were the growing degree days for December, January, and February, which are an indicator of higher temperatures and the precipitation of the wettest month. The minimum temperature of the coldest month between -5°C and 20°C was found to be suitable for DENV-1 and DENV-2 serotypes. Respectively, above 700-900 mm of rainfall, the suitability for DENV-1 and DENV-2 begins to decline, while higher humidity still favors DENV-3 and DENV-4. The sensitivity concerning the suitability map was developed for Mexico. DENV-1, DENV-2, DENV-3, and DENV-4 serotypes will be found more commonly in the municipalities classified as suitable based on their respective sensitivity of 91%, 90%, 89%, and 85% in Mexico. As the microclimates continue to change, specific bioclimatic indices may be used to monitor potential changes in DENV serotype distribution. The suitability for DENV-1 and DENV-2 is expected to increase in areas with lower minimum temperature ranges, while DENV-3 and DENV-4 will likely increase in areas that experience higher humidity. Ongoing surveillance of municipalities with predicted suitability of 89% and 85% should be expanded to account for the accurate DENV serotype prevalence and association between bioclimatic parameters.

Indexed as

DengueDengue VirusClimateEntropyHumansMexicoSerogroup

Identifiers

PMID40303721
PMCPMC12016891

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.