Modelling of potential risk areas of pertussis cases in the Philippines using bioclimatic envelopes

The findings highlight how climatic factors shape pertussis distribution through anthropogenic means (e.g., higher humidity increases the chances of acquiring respiratory problems), providing a framework for eco-epidemiological risk assessment. This approach enhances targeted intervention planning, resource allocation, and early warning systems, particularly in resource-limited settings like the Philippines. The study underscores the role of Maximum Entropy in addressing re-emerging diseases, contributing to sustainable public health preparedness and mitigation strategies in tropical regions given that there is currently no predictive model for pertussis cases in the Philippines.

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Publication Details

Journal
Tropical Medicine & International Health
Published
2025-04-21
DOI
https://doi.org/10.1111/tmi.14115
Citations
2
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
2.71
Controls
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article

Modelling of potential risk areas of pertussis cases in the Philippines using bioclimatic envelopes

Nikki Heherson A. Dagamac, Allan Miguel G. Tomimbang, Akira T. Komoda
2 citations
Tropical Medicine & International Health
Data-Driven Disease Surveillance
2.71
article

Modelling of potential risk areas of pertussis cases in the Philippines using bioclimatic envelopes

Nikki Heherson A. Dagamac, Allan Miguel G. Tomimbang, Akira T. Komoda
article en
2 citations

Abstract

The findings highlight how climatic factors shape pertussis distribution through anthropogenic means (e.g., higher humidity increases the chances of acquiring respiratory problems), providing a framework for eco-epidemiological risk assessment. This approach enhances targeted intervention planning, resource allocation, and early warning systems, particularly in resource-limited settings like the Philippines. The study underscores the role of Maximum Entropy in addressing re-emerging diseases, contributing to sustainable public health preparedness and mitigation strategies in tropical regions given that there is currently no predictive model for pertussis cases in the Philippines.

Tropical Medicine & International HealthVol. 30(6)
University of Santo Tomas (PH)
Climate action
Openalex Percentile: Top 11%
Data-Driven Disease Surveillance
2.71
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Modelling of potential risk areas of pertussis cases in the Philippines using bioclimatic envelopes — Nikki Heherson A. Dagamac, Allan Miguel G. Tomimbang, et al. · Tropical Medicine & International Health (2025) | TGRS Research Map | TGRS