Evidence map›Paper›PMID 38035255›Full record

ArticleEnvironmental health insights2023

Effective Preventative Measures are Essential to Lower Disease Burden From Dengue and COVID-19 Co-infection in Bangladesh.

Proma Rani Das, Sakif Ahamed Khan, Jannatul Mabia Rahman, Syed Masudur Rahman Dewan

Open access · goldAbstract read
In one paragraph

Article in Environmental health insights, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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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

4 authors at 1 institution in 1 country.

Proma Rani DasDepartment of Pharmacy, School of Medicine, University of Asia Pacific, Dhaka, Bangladesh.
Sakif Ahamed KhanDepartment of Pharmacy, School of Medicine, University of Asia Pacific, Dhaka, Bangladesh.ORCID https://orcid.org/0009-0008-9397-4299
Jannatul Mabia RahmanDepartment of Electrical and Electronic Engineering, University of Asia Pacific, Dhaka, Bangladesh.
Syed Masudur Rahman DewanDepartment of Pharmacy, School of Medicine, University of Asia Pacific, Dhaka, Bangladesh.ORCID https://orcid.org/0000-0003-1443-7150
University of Asia Pacific · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bangladesh is widely recognized as one of the dengue prone nations, and empirical evidence has consistently demonstrated an upward trend in the severity of the disease over time. With the persistent occurrence of dengue in Bangladesh and the ongoing presence of COVID-19, which has not been fully eradicated and may persist for an uncertain period of time, there is a high probability of co-infection between these 2 illnesses. Given the circumstances, the concurrent occurrence of the COVID-19 and dengue epidemics, along with the potential co-infection, may pose an overwhelming burden on healthcare systems that are already grappling with challenges in meeting the existing demand. Due to a lack of awareness, an inadequate health infrastructure, and ineffective disease prevention initiatives, the country is now more susceptible to the threat posed by a co-infection that has been found to be associated with more severe outcomes, marked by significant morbidity and mortality. The objective of this opinion piece is to explore the gravity of co-infection in Bangladesh, as well as the potential challenges to overcome and the preventative measures that need to be implemented to address the severity. This opinion piece proposes a set of modern preventative strategies that, when integrated with conventional methods, have the potential to mitigate disease severity, avert the occurrence of co-infection between COVID-19 and dengue, and halt the co-epidemics of COVID-19 and dengue.

Indexed as

artificial intelligencebiopesticideco-infectionCorona virusDengue

Identifiers

PMID38035255
PMCPMC10685758
OpenAlexW4389144821

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.