Evidence map›Paper›PMID 36288030›Full record

ArticleTropical medicine and infectious disease2022

Infectious Disease Modeling with Socio-Viral Behavioral Aspects-Lessons Learned from the Spread of SARS-CoV-2 in a University.

Nuning Nuraini, Kamal Khairudin Sukandar, Maria Yulita Trida Tahu, Ernawati Arifin Giri-Rachman, Anggraini Barlian, Sri Harjati Suhardi, Udjianna Sekteria Pasaribu, Sonny Yuliar, Diky Mudhakir, Herto Dwi Ariesyady and 3 more

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2022. 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. COVID-19: Current Status and Future Prospects.Tropical medicine and infectious disease · 2023
    Article
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

13 authors.

Nuning NurainiDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Kamal Khairudin SukandarDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung 40132, Indonesia.ORCID 0000-0002-7175-4403
Maria Yulita Trida TahuDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Ernawati Arifin Giri-RachmanSchool of Life Science and Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Anggraini BarlianSchool of Life Science and Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Sri Harjati SuhardiSchool of Life Science and Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Udjianna Sekteria PasaribuDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Sonny YuliarCenter of Public Policy and Governance, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Diky MudhakirSchool of Pharmacy, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Herto Dwi AriesyadyFaculty of Civil and Environmental Engineering, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Dian RosleineSchool of Life Science and Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Iyan SofyanGeneral Administration and Information Bureau, Institut Teknologi Bandung, Bandung 40132, Indonesia.
Widjaja MartokusumoSchool of Architecture, Planning and Policy Development, Institut Teknologi Bandung, Bandung 40132, Indonesia.ORCID 0000-0003-1756-5916

Funding

Bandung Institute of Technology, Indonesia Pending
6 · The paper itself

Abstract

When it comes to understanding the spread of COVID-19, recent studies have shown that pathogens can be transmitted in two ways: direct contact and airborne pathogens. While the former is strongly related to the distancing behavior of people in society, the latter are associated with the length of the period in which the airborne pathogens remain active. Considering those facts, we constructed a compartmental model with a time-dependent transmission rate that incorporates the two sources of infection. This paper provides an analytical and numerical study of the model that validates trivial insights related to disease spread in a responsive society. As a case study, we applied the model to the COVID-19 spread data from a university environment, namely, the Institut Teknologi Bandung, Indonesia, during its early reopening stage, with a constant number of students. The results show a significant fit between the rendered model and the recorded cases of infections. The extrapolated trajectories indicate the resurgence of cases as students' interaction distance approaches its natural level. The assessment of several strategies is undertaken in this study in order to assist with the school reopening process.

Indexed as

interaction distanceschool reopening strategySIR modelsocio-behavioral aspects

Identifiers

PMID36288030
PMCPMC9608982

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.