Evidence map›Paper›PMID 41473504›Full record

ArticleIJID regions2025

Correlation and epidemiologic distribution of emerging coinfections of

Jack Ogony, Judith Mangeni, George Ayodo, Diana Menya, Ivy Akinyi, Ben Oyugi, Arthy Yongo, Fordrane Okumu, Charles Lwanga, Fredrick Oluoch and 1 more

Abstract read
In one paragraph

Article in IJID regions, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jack OgonyDepartment of Environmental Health and Disease Control, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.
Judith MangeniDepartment of Epidemiology and Biomedical Statistics, Moi University, Eldoret, Kenya.
George AyodoDepartment of Public Health and Community Health, Jaramogi Oginga Odinga University of Science and Technology, Kisumu, Kenya.
Diana MenyaDepartment of Epidemiology and Biomedical Statistics, Moi University, Eldoret, Kenya.
Ivy AkinyiDepartment of Public Health and Community Health, Jaramogi Oginga Odinga University of Science and Technology, Kisumu, Kenya.
Ben OyugiDepartment of Public Health and Community Health, Jaramogi Oginga Odinga University of Science and Technology, Kisumu, Kenya.
Arthy YongoDepartment of Public Health and Community Health, Jaramogi Oginga Odinga University of Science and Technology, Kisumu, Kenya.
Fordrane OkumuAdaptive Model for Research and Empowerment in Communities (AMREC), Kisumu, Kenya.
Charles LwangaAdaptive Model for Research and Empowerment in Communities (AMREC), Kisumu, Kenya.
Fredrick OluochDepartment of Health and Sanitation, Ministry of Health, Kisumu, Kenya.
Simon KaranjaDepartment of Environmental Health and Disease Control, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To determine correlation and epidemiological distribution of emerging coinfections of Methods: Prospective cohort study. This study was conducted in Kisumu and Busia Counties in western Kenya. Kisumu County is an urban setting, whereas Busia has peri-urban and rural settings. All the level 2-4 public health facilities in Kisumu central subcounty and Bunyala subcounty in Busia were included. The number of participants recruited per facility was based on the facility level proportions. From each facility level, 18 and 19 participants were recruited in Kisumu and Busia, respectively. A total of 380 febrile children aged below 5 years who screened positive for malaria and/or dengue virus and whose parents/guardians gave consent to participate were recruited. Demographic parameters were simultaneously analyzed. Statistical analysis was performed using the chi-square test. Results: Of the 1004 participants screened, 380 turned seropositive for either malaria or dengue or coinfected. The overall disease burden was 37.8% (380 of 1004). The prevalence of Conclusion: This study finding is suggestive of an active spread of dengue virus infections, leading to coinfections in this geographical region where malaria is endemic. The high temperatures, precipitation, and humidity experienced around Lake Victoria is favoring mosquito vector multiplication, hence the sustained mosquito transmitted disease burden. It is also important to educate clinicians on the differential diagnoses for appropriate case management because the disease patterns vary meaningfully between the two study sites.

Indexed as

CoinfectionCorrelationDengue feverFebrile illnessP. falciparumVector-borne

Identifiers

PMID41473504
PMCPMC12746085

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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.