Evidence map›Paper›PMID 36223673›Full record

ArticleEpidemics2022

Insight into Delta variant dominated second wave of COVID-19 in Nepal.

Khagendra Adhikari, Ramesh Gautam, Anjana Pokharel, Meghnath Dhimal, Kedar Nath Uprety, Naveen K Vaidya

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Khagendra AdhikariAmrit Campus, Tribhuvan University, Kathmandu, Nepal.
Ramesh GautamRatna Rajya Laxmi Campus, Tribhuvan University, Kathmandu, Nepal.
Anjana PokharelPadma Kanya Multiple Campus, Tribhuvan University, Kathmandu, Nepal.
Meghnath DhimalNepal Health Research Council, Kathmandu, Nepal; Global Institute for Interdisciplinary Studies, Lalitpur, Nepal.
Kedar Nath UpretyCentral Department of Mathematics, Tribhuvan University, Kathmandu, Nepal.
Naveen K VaidyaDepartment of Mathematics and Statistics, San Diego State University, San Diego, CA, USA; Computational Science Research Center, San Diego State University, San Diego, CA, USA; Viral Information Institute, San Diego State University, San Diego, CA, USA. Electronic address: nvaidya@sdsu.edu.
Tribhuvan University · NPNepal Development Research Institute · NPSan Diego State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo study the spreading nature of Delta variant (B.1.617.2) dominated COVID-19 in Nepal to help the policymakers assess and manage health care facilities and vaccination programs.

methodsDeterministic mathematical models in the form of systems of ordinary differential equations were developed to describe the COVID-19 transmission in the high- and the low-risk regions of Nepal. The models were validated using the multiple data sets containing daily new cases in the whole country, the high-risk region, the low-risk region, and cases needing medical care, ICU, and ventilator.

resultsWe found the reproduction number of R

conclusionsThe data-driven mathematical models are useful to assess control programs in resource-limited countries. The appropriate combination of vaccination and social distancing are necessary to keep the pandemic under-control and manage the medical care facilities in Nepal.

Indexed as

COVID-19HumansPhysical DistancingSARS-CoV-2Seroepidemiologic StudiesCOVID-19Delta variantHospitalizationNepalVaccination

Identifiers

PMID36223673
PMCPMC9535929
OpenAlexW4302363793

What OpenQuestion holds

Textmetadata
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.