Evidence map›Paper›PMID 40814009›Full record

ArticleTropical medicine and health2025

Pre- and post-COVID-19 pandemic identification of dengue hotspots and exploration of population and environmental determinants of dengue in Quezon City, Philippines.

John Robert Carabeo Medina, Shin'ya Kawamura, Rie Takeuchi, Rolando V Cruz, Johnedel Mendoza, Paul Michael R Hernandez, Fernando B Garcia, Ernesto R Gregorio, Jun Kobayashi

Abstract read
In one paragraph

Article in Tropical medicine and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

John Robert Carabeo MedinaInstitute of Clinical Epidemiology, National Institutes of Health, University of the Philippines Manila, 623 Pedro Gil St, Ermita, Manila, 1000, Metro Manila, Philippines. jcmedina1@up.edu.ph.
Shin'ya KawamuraNational Institute of Technology, Matsue College, 14-4 Nishi-Ikumacho, Matsue, Shimane, 690-8518, Japan.
Rie TakeuchiGraduate School of Public Health, International University of Health and Welfare, 4-3, Kodunomori, Narita, Chiba, 286-8686, Japan.
Rolando V CruzQuezon City Epidemiology and Surveillance Division, Quezon City Health Department, Local Government of Quezon City, Quezon City, Philippines.
Johnedel MendozaQuezon City Epidemiology and Surveillance Division, Quezon City Health Department, Local Government of Quezon City, Quezon City, Philippines.
Paul Michael R HernandezDepartment of Environmental and Occupational Health, College of Public Health, University of the Philippines Manila, 625 Pedro Gil St, Ermita, Manila, 1000, Metro Manila, Philippines.
Fernando B GarciaDepartment of Health Policy and Administration, College of Public Health, University of the Philippines Manila, 625 Pedro Gil St, Ermita, Manila, 1000, Metro Manila, Philippines.
Ernesto R GregorioDepartment of Health Promotion and Education, College of Public Health, University of the Philippines Manila, 625 Pedro Gil St, Ermita, Manila, 1000, Metro Manila, Philippines.
Jun KobayashiDepartment of Global Health, Graduate School of Health Sciences, University of the Ryukyus, 207 Uehara, Nishihara-cho, Nakagami-gun, Okinawa, 903-0215, Japan.

Funding

JSPS KAKENHI JP20KK0223
6 · The paper itself

Abstract

In 2020, there were decreasing trends in reported dengue cases in several countries in the Western Pacific Region, including the Philippines, amid the COVID-19 pandemic. In this study, the spatial distribution of dengue incidence and the hotspots were described quarterly in Quezon City from 2019 to 2022, with the unit of analysis being the 142 barangays (small territorial and administrative villages) in Quezon City. The influence of selected environmental and demographic factors on the persistence of dengue was also explored. Surveillance data from the Quezon City Epidemiology and Surveillance Division, Normalized Difference Vegetation Index (NDVI), and satellite images of built environments, such as buildings, facilities, and transportation network hubs were processed and analyzed. The local Moran's I statistics performed with 95% confidence level was employed in the identification of local dengue hotspots. Dengue hotspot maps and maps of greenness, surrounding greenness, small building ratios, and the number of transportation network hubs in each barangay (village) of Quezon City were developed. The association of dengue cases with greenness, surrounding greenness, transportation network hubs, small building ratios, and population density was determined through a generalized linear model (GLM). Results revealed that incidence rates of dengue across barangays were spatially heterogeneous, and the dengue hotspots were unstable as they varied quarterly each year. Proximity to surrounding greenness (NDVI 1 km), small building ratio, and presence of transportation network hubs were found to be significantly associated with dengue hotspots. Dengue prevention strategies, such as search-and-destroy activities for breeding sites, are suggested to be implemented regularly in such areas. The study also recommends considering the anticipated increase in dengue hotspots and the significant environmental factors in the development of health promotion and education campaigns.

Indexed as

COVID-19DengueDisease hotspotGeographic information systemGISPhilippinesQuezon City

Identifiers

PMID40814009
PMCPMC12351799

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LicenceCC BY
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Registered trials

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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.