Evidence map›Paper›PMID 38352906›Full record

ArticleBioinformation2024

Nipah: The looming post-covid pandemic.

Olivia Sekimoto, Francesco Chiappelli

Open access · hybridAbstract readEditorial
In one paragraph

Article in Bioinformation, 2024. 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, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Olivia SekimotoCajulis Pediatric Dentistry, Chula Vista, CA 91914, USA.
Francesco ChiappelliDental Group of Sherman Oaks, Sherman Oaks, CA 91403, USA.
Oklahoma State University Center for Health Sciences · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

First identified as a pathogen in Malaysia and Singapore in 1999, Nipah virus (NiV) caused nearly 300 human cases and over 100 fatalities. It also killed about 1 million pigs. Three years later (2002), it was reported in Pteropus bats in Malaysia, in Cambodia & Thailand, (2005), and as far as Madagascar (2007) and Ghana (2008). India (Kerala) reported its first human NiV-caused fatalities in September 2023. Taken together, these trends emphasize its public health threat. In humans, NiV infection initially leads to fever, headache, body aches and muscle pain, nausea and vomiting. The symptoms rapidly evolve into sore throat, cough and atypical pneumonia leading to severe respiratory distress. The cadre of NiV-induced pathology (Nipah disease, NiD) then includes severe dizziness and drowsiness, progressive alteration in cognition and consciousness, acute encephalitis and seizures. Public health protocols (e.g., mask-wearing, quarantine), essential to contain and control CoViD-19, seem insufficient to contain NiD spread because NiV transmission occurs primarily via direct contacts with body fluids of infected carriers, but presumably not by airborne transmission. As in the case of SARS-C0V2, health care providers (i.e., physicians, dentists, nurses, dental assistants) are greatest risks not only of contracting but of spreading NiV infection. NiV is a high-pathogenicity pathogen, against which, at present, we have no anti-viral medications or preventive vaccine. Taken together, the evidence to date heightens the threat of an upcoming NiD pandemic.

Indexed as

central nervous system - CNSCoViD-19dentistsNipah viral disease - NiDNipah Virus - NiVpublic healthSARS-Cov2

Identifiers

PMID38352906
PMCPMC10859950
OpenAlexW4391648853

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.