Evidence map›Paper›PMID 24516519›Full record

ArticlePloS one2014

Effect of the one-child policy on influenza transmission in China: a stochastic transmission model.

Fengchen Liu, Wayne T A Enanoria, Kathryn J Ray, Megan P Coffee, Aubree Gordon, Tomás J Aragón, Guowei Yu, Benjamin J Cowling, Travis C Porco

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 29% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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 4 institutions in 3 countries.

Fengchen LiuF.I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America ; Center for Infectious Diseases and Emergency Readiness, School of Public Health, University of California, Berkeley, California, United States of America.
Wayne T A EnanoriaF.I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America ; Center for Infectious Diseases and Emergency Readiness, School of Public Health, University of California, Berkeley, California, United States of America ; Division of Epidemiology, School of Public Health, University of California, Berkeley, California, United States of America.
Kathryn J RayF.I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America.
Megan P CoffeeF.I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America ; Center for Infectious Diseases and Emergency Readiness, School of Public Health, University of California, Berkeley, California, United States of America.
Aubree GordonDivision of Epidemiology, School of Public Health, University of California, Berkeley, California, United States of America.
Tomás J AragónCenter for Infectious Diseases and Emergency Readiness, School of Public Health, University of California, Berkeley, California, United States of America ; Division of Epidemiology, School of Public Health, University of California, Berkeley, California, United States of America.
Guowei YuWest of China Institute of Environmental Health, Northwest University for Nationalities, Lanzhou, Gansu, China.
Benjamin J CowlingSchool of Public Health, The University of Hong Kong, Hong Kong, China.
Travis C PorcoF.I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America ; Center for Infectious Diseases and Emergency Readiness, School of Public Health, University of California, Berkeley, California, United States of America ; Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, United States of America.
University of California, Berkeley · USUniversity of California, San Francisco · USNorthwest Minzu University · CNUniversity of Hong Kong · HK

Funding

"Modeling contact investigation and rapid response"U01GM087728 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PORCO, TRAVIS CHRISTIAN · 2011 to 2015
$2.2M
NIGMS NIH HHS 1-U01-GM087728-01NIGMS NIH HHS U01 GM087728
6 · The paper itself

Abstract

backgroundChina's one-child-per-couple policy, introduced in 1979, led to profound demographic changes for nearly a quarter of the world's population. Several decades later, the consequences include decreased fertility rates, population aging, decreased household sizes, changes in family structure, and imbalanced sex ratios. The epidemiology of communicable diseases may have been affected by these changes since the transmission dynamics of infectious diseases depend on demographic characteristics of the population. Of particular interest is influenza because China and Southeast Asia lie at the center of a global transmission network of influenza. Moreover, changes in household structure may affect influenza transmission. Is it possible that the pronounced demographic changes that have occurred in China have affected influenza transmission? METHODS AND

findingsTo address this question, we developed a continuous-time, stochastic, individual-based simulation model for influenza transmission. With this model, we simulated 30 years of influenza transmission and compared influenza transmission rates in populations with and without the one-child policy control. We found that the average annual attack rate is reduced by 6.08% (SD 2.21%) in the presence of the one-child policy compared to a population in which no demographic changes occurred. There was no discernible difference in the secondary attack rate, -0.15% (SD 1.85%), between the populations with and without a one-child policy. We also forecasted influenza transmission over a ten-year time period in a population with a two-child policy under a hypothesis that a two-child-per-couple policy will be carried out in 2015, and found a negligible difference in the average annual attack rate compared to the population with the one-child policy.

conclusionsThis study found that the average annual attack rate is slightly lowered in a population with a one-child policy, which may have resulted from a decrease in household size and the proportion of children in the population.

Indexed as

Family Planning PolicyModels, BiologicalAdolescentChildChinaComputer SimulationDemographyFemaleHumansInfluenza, HumanMaleStochastic Processes

Identifiers

PMID24516519
PMCPMC3916292
OpenAlexW2056490157

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.