Evidence map›Paper›PMID 33199946›Full record

ReviewJournal of the Indian Institute of Science2020

City-Scale Agent-Based Simulators for the Study of Non-pharmaceutical Interventions in the Context of the COVID-19 Epidemic: IISc-TIFR COVID-19 City-Scale Simulation Team.

Shubhada Agrawal, Siddharth Bhandari, Anirban Bhattacharjee, Anand Deo, Narendra M Dixit, Prahladh Harsha, Sandeep Juneja, Poonam Kesarwani, Aditya Krishna Swamy, Preetam Patil and 7 more

Abstract readReview
In one paragraph

Review in Journal of the Indian Institute of Science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Projecting COVID-19 cases and hospital burden in Ohio.Journal of theoretical biology · 2023
    Article
  6. Epidemic dynamics in census-calibrated modular contact network.Network modeling and analysis in health informatics and bioinformatics · 2023
    Article
  7. Article
  8. Modelling the first wave of COVID-19 in India.PLoS computational biology · 2022
    Article
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Review
  14. An Agent-Based Digital Twin for Exploring Localized Non-pharmaceutical Interventions to Control COVID-19 Pandemic.Transactions of the Indian National Academy of Engineering : an international journal of engineering and technology · 2021
    Article
  15. 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

17 authors.

Shubhada AgrawalTIFR, Mumbai, India.
Siddharth BhandariTIFR, Mumbai, India.
Anirban BhattacharjeeTIFR, Mumbai, India.
Anand DeoTIFR, Mumbai, India.
Narendra M DixitIndian Institute of Science, Bangalore, India.
Prahladh HarshaTIFR, Mumbai, India.
Sandeep JunejaTIFR, Mumbai, India.
Poonam KesarwaniTIFR, Mumbai, India.
Aditya Krishna SwamyIndian Institute of Science, Bangalore, India.
Preetam PatilIndian Institute of Science, Bangalore, India.
Nihesh RathodIndian Institute of Science, Bangalore, India.
Ramprasad SaptharishiTIFR, Mumbai, India.
Sharad ShriramIndian Institute of Science, Bangalore, India.
Piyush SrivastavaTIFR, Mumbai, India.
Rajesh SundaresanIndian Institute of Science, Bangalore, India.
Nidhin Koshy VaidhiyanIndian Institute of Science, Bangalore, India.
Sarath YasodharanIndian Institute of Science, Bangalore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We highlight the usefulness of city-scale agent-based simulators in studying various non-pharmaceutical interventions to manage an evolving pandemic. We ground our studies in the context of the COVID-19 pandemic and demonstrate the power of the simulator via several exploratory case studies in two metropolises, Bengaluru and Mumbai. Such tools may in time become a common-place item in the tool kit of the administrative authorities of large cities.

Identifiers

PMID33199946
PMCPMC7657713

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.