Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling

Félix E. Rivera-Mariani; Armando J. Borrero-Aponte; Benjamín Bolaños-Rosero

Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling

Félix E. Rivera-Mariani^*, Armando J. Borrero-Aponte, Benjamín Bolaños-Rosero

^*Corresponding author for this work

Research output: Contribution to conference › Poster

Abstract

This poster presentation, which was a Late-Breaking Abstract, demonstrates that outdoor fungal spore concentrations, unlike pollen, serve as effective short-term environmental predictors for surges in both incidence and mortality of influenza and COVID-19 in Puerto Rico’s San Juan-Metro and Caguas regions, particularly during the fall season. Machine learning and time-series analyses indicate that integrating fungal spore data can enhance respiratory virus surveillance and help guide timely public health interventions.

Original language	American English
State	Published - Aug 18 2025
Event	Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE): Global Environmental Health Equity Across the Lifespan - Hyatt Regency Atlanta, Atlanta, United States Duration: Aug 17 2025 → Aug 20 2025

Conference

Conference	Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE)
Abbreviated title	ISES-ISEE
Country/Territory	United States
City	Atlanta
Period	8/17/25 → 8/20/25

Bibliographical note

Late-Breaking E-poster Presentation

Organization custom fields

Author/co-author with international scholars
Organization is International

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series ModelingFinal published version, 1.19 MB

http://spiral.lynn.edu/facpubs/2107

Cite this

Rivera-Mariani, F. E., Borrero-Aponte, A. J., & Bolaños-Rosero, B. (2025). Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling. Poster session presented at Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE), Atlanta, Georgia, United States. http://spiral.lynn.edu/facpubs/2107

Rivera-Mariani, Félix E. ; Borrero-Aponte, Armando J. ; Bolaños-Rosero, Benjamín. / Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling. Poster session presented at Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE), Atlanta, Georgia, United States.

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title = "Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling",

abstract = "This poster presentation, which was a Late-Breaking Abstract, demonstrates that outdoor fungal spore concentrations, unlike pollen, serve as effective short-term environmental predictors for surges in both incidence and mortality of influenza and COVID-19 in Puerto Rico{\textquoteright}s San Juan-Metro and Caguas regions, particularly during the fall season. Machine learning and time-series analyses indicate that integrating fungal spore data can enhance respiratory virus surveillance and help guide timely public health interventions.",

author = "Rivera-Mariani, \{F{\'e}lix E.\} and Borrero-Aponte, \{Armando J.\} and Benjam{\'i}n Bola{\~n}os-Rosero",

note = "Late-Breaking E-poster Presentation; Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE) : Global Environmental Health Equity Across the Lifespan, ISES-ISEE ; Conference date: 17-08-2025 Through 20-08-2025",

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day = "18",

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}

Rivera-Mariani, FE, Borrero-Aponte, AJ & Bolaños-Rosero, B 2025, 'Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling', Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE), Atlanta, United States, 8/17/25 - 8/20/25. <http://spiral.lynn.edu/facpubs/2107>

Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling. / Rivera-Mariani, Félix E.; Borrero-Aponte, Armando J.; Bolaños-Rosero, Benjamín.
2025. Poster session presented at Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE), Atlanta, Georgia, United States.

Research output: Contribution to conference › Poster

TY - CONF

T1 - Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling

AU - Rivera-Mariani, Félix E.

AU - Borrero-Aponte, Armando J.

AU - Bolaños-Rosero, Benjamín

N1 - Late-Breaking E-poster Presentation

PY - 2025/8/18

Y1 - 2025/8/18

N2 - This poster presentation, which was a Late-Breaking Abstract, demonstrates that outdoor fungal spore concentrations, unlike pollen, serve as effective short-term environmental predictors for surges in both incidence and mortality of influenza and COVID-19 in Puerto Rico’s San Juan-Metro and Caguas regions, particularly during the fall season. Machine learning and time-series analyses indicate that integrating fungal spore data can enhance respiratory virus surveillance and help guide timely public health interventions.

AB - This poster presentation, which was a Late-Breaking Abstract, demonstrates that outdoor fungal spore concentrations, unlike pollen, serve as effective short-term environmental predictors for surges in both incidence and mortality of influenza and COVID-19 in Puerto Rico’s San Juan-Metro and Caguas regions, particularly during the fall season. Machine learning and time-series analyses indicate that integrating fungal spore data can enhance respiratory virus surveillance and help guide timely public health interventions.

M3 - Poster

T2 - Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE)

Y2 - 17 August 2025 through 20 August 2025

ER -

Rivera-Mariani FE, Borrero-Aponte AJ, Bolaños-Rosero B. Ambient Fungal Spores as Short- Term Predictors of Respiratory Virus Incidence and Mortality in Puerto Rico: Evidence from Machine Learning and Time-Series Modeling. 2025. Poster session presented at Joint Annual Meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology (ISES-ISEE), Atlanta, Georgia, United States.