Evidence map›Paper›PMID 27687898›Full record

ArticleBMJ open2016

Effect of modelling slum populations on influenza spread in Delhi.

Jiangzhuo Chen, Shuyu Chu, Youngyun Chungbaek, Maleq Khan, Christopher Kuhlman, Achla Marathe, Henning Mortveit, Anil Vullikanti, Dawen Xie

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

16 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. COVID-19 in India: Who are we leaving behind?Progress in disaster science · 2021
    Article
  9. Agent-Based Computational Epidemiological Modeling.Journal of the Indian Institute of Science · 2021
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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

9 authors at 2 institutions in 1 country.

Jiangzhuo ChenNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Shuyu ChuNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Youngyun ChungbaekNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Maleq KhanNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Christopher KuhlmanNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Achla MaratheNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Henning MortveitNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Anil VullikantiNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Dawen XieNetwork Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, USA.
Virginia Tech · USBiocom · US

Funding

Synthetic Information Systems for Better Informing Public Health PolicymakersU01GM070694 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI EUBANK, STEPHEN G, MARATHE, MADHAV VISHNU · 2004 to 2016
$8.6M
Systems Analysis of Social Pathways of Epidemics to Reduce Health DisparitiesR01GM109718 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MARATHE, ACHLA, VULLIKANTI, ANIL · 2014 to 2022
$3.6M
NIGMS NIH HHS R01 GM109718NIGMS NIH HHS U01 GM070694
6 · The paper itself

Abstract

objectivesThis research studies the impact of influenza epidemic in the slum and non-slum areas of Delhi, the National Capital Territory of India, by taking proper account of slum demographics and residents' activities, using a highly resolved social contact network of the 13.8 million residents of Delhi.

methodsAn SEIR model is used to simulate the spread of influenza on two different synthetic social contact networks of Delhi, one where slums and non-slums are treated the same in terms of their demographics and daily sets of activities and the other, where slum and non-slum regions have different attributes.

resultsDifferences between the epidemic outcomes on the two networks are large. Time-to-peak infection is overestimated by several weeks, and the cumulative infection rate and peak infection rate are underestimated by 10-50%, when slum attributes are ignored.

conclusionsSlum populations have a significant effect on influenza transmission in urban areas. Improper specification of slums in large urban regions results in underestimation of infections in the entire population and hence will lead to misguided interventions by policy planners.

Indexed as

INFECTIOUS DISEASES

Identifiers

PMID27687898
PMCPMC5051437
OpenAlexW2524568831

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.