Evidence map›Paper›PMID 39155944›Full record

ArticleIDCases2024

Understanding dengue outbreaks in Rajshahi district, Bangladesh: A comprehensive case study.

Md Mehedi Hasan Sumon, Mohammad Jubair, Selim Reza Tony, Md Johorul Islam, Dipak Kumar Paul, Md Al Shaharia, Khandker Md Faisal Alam, Mustafizur Rahman, Sudhangshu Kumar Biswas

Abstract readCase Reports
In one paragraph

Article in IDCases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

9 authors.

Md Mehedi Hasan SumonBacteriophage Biology and Genomics Lab, Department of Biotechnology & Genetic Engineering, Islamic University, 7003, Bangladesh.
Mohammad JubairGenome Centre, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
Selim Reza TonyVirology Laboratory, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
Md Johorul IslamBacteriophage Biology and Genomics Lab, Department of Biotechnology & Genetic Engineering, Islamic University, 7003, Bangladesh.
Dipak Kumar PaulDepartment of Applied Nutrition and Food Technology, Islamic University, Kushtia 7003, Bangladesh.
Md Al ShahariaUrban and Rural Planning Discipline, Khulna University, Bangladesh.
Khandker Md Faisal AlamDepartment of Microbiology, Rajshahi Medical College, Rajshahi 6100, Bangladesh.
Mustafizur RahmanGenome Centre, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
Sudhangshu Kumar BiswasBacteriophage Biology and Genomics Lab, Department of Biotechnology & Genetic Engineering, Islamic University, 7003, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: The 2023 dengue outbreak in Bangladesh marked an unprecedented increase in fatalities, particularly in Dhaka, and demonstrated extensive prevalence nationwide, including Rajshahi district. Dengue fever remains a significant public health challenge in Southeast Asia, with complex epidemiological patterns. Previous research has mainly focused on den serotypes in Dhaka. Therefore, this study aims to identify serotypes in the Rajshahi district under endemic conditions. Methods: Blood samples from suspected dengue patients were collected at Rajshahi Medical College Hospital. Initial rapid detection of dengue-positive cases was performed using (Nonstructural Protein 1 L) NS1, (Immunoglobulin G) IgG, and (Immunoglobulin M) IgM tests. Upon confirmation of dengue positivity, viral RNA was extracted for molecular testing. The dengue serotype was identified using real-time reverse transcription-polymerase chain reaction (rRT-PCR). Results: The study revealed that 93.3 % of the patient were infected with (Dengue virus type 2) DENV2 and rest 6.7 % of the patient were (Dengue virus type 3) DENV3 among 30 dengue positive patients. Demographic observations show the distribution of dengue over nine upazilas. In Paba upazila, we found two DENV3 alongside DENV2. Conclusion: The study concludes that the 2023 dengue outbreak in Rajshahi district, Bangladesh, predominantly involved the DENV2 serotype. Geospatial analysis underscores the importance of understanding regional distribution patterns to enhance targeted interventions against dengue fever in endemic areas.

Indexed as

BangladeshCase-studyDengueDENV2DENV3Serotype

Identifiers

PMID39155944
PMCPMC11326899

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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.