Evidence map›Paper›PMID 31506136›Full record

ArticleEpidemiology and infection2019

Incorporating calendar effects to predict influenza seasonality in Milwaukee, Wisconsin.

Ryan B Simpson, Tania M Alarcon Falconi, Aishwarya Venkat, Kenneth H H Chui, Jose Navidad, Yuri N Naumov, Jack Gorski, Sanjib Bhattacharyya, Elena N Naumova

Open access · hybridAbstract read
In one paragraph

Article in Epidemiology and infection, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Signatures of Cholera Outbreak during the Yemeni Civil War, 2016-2019.International journal of environmental research and public health · 2021
    Article
  9. Article
  10. Effects of Data Aggregation on Time Series Analysis of Seasonal Infections.International journal of environmental research and public health · 2020
    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 3 institutions in 1 country.

Ryan B SimpsonFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Tania M Alarcon FalconiFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Aishwarya VenkatFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Kenneth H H ChuiFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Jose NavidadCity of Milwaukee Health Department Laboratory (MHDL), Milwaukee, WI, USA.
Yuri N NaumovVersiti Wisconsin, Blood Research Institute, Milwaukee, WI, USA.
Jack GorskiVersiti Wisconsin, Blood Research Institute, Milwaukee, WI, USA.
Sanjib BhattacharyyaCity of Milwaukee Health Department Laboratory (MHDL), Milwaukee, WI, USA.
Elena N NaumovaFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.ORCID 0000-0002-9562-4734
Tufts University · USMilwaukee Health Department · USVersiti Blood Center of Wisconsin · US

Funding

Viral Vector CoreU19AI062627 · NIAID · VERSITI WISCONSIN, INC. · PI ECKELS, DAVID D · 2004 to 2008
$11.6M
NIAID NIH HHS U19 AI062627
6 · The paper itself

Abstract

Social outings can trigger influenza transmission, especially in children and elderly. In contrast, school closures are associated with reduced influenza incidence in school-aged children. While influenza surveillance modelling studies typically account for holidays and mass gatherings, age-specific effects of school breaks, sporting events and commonly celebrated observances are not fully explored. We examined the impact of school holidays, social events and religious observances for six age groups (all ages, ⩽4, 5-24, 25-44, 45-64, ⩾65 years) on four influenza outcomes (tests, positives, influenza A and influenza B) as reported by the City of Milwaukee Health Department Laboratory, Milwaukee, Wisconsin from 2004 to 2009. We characterised holiday effects by analysing average weekly counts in negative binomial regression models controlling for weather and seasonal incidence fluctuations. We estimated age-specific annual peak timing and compared influenza outcomes before, during and after school breaks. During the 118 university holiday weeks, average weekly tests were lower than in 140 school term weeks (5.93 vs. 11.99 cases/week, P < 0.005). The dampening of tests during Winter Break was evident in all ages and in those 5-24 years (RR = 0.31; 95% CI 0.22-0.41 vs. RR = 0.14; 95% CI 0.09-0.22, respectively). A significant increase in tests was observed during Spring Break in 45-64 years old adults (RR = 2.12; 95% CI 1.14-3.96). Milwaukee Public Schools holiday breaks showed similar amplification and dampening effects. Overall, calendar effects depend on the proximity and alignment of an individual holiday to age-specific and influenza outcome-specific peak timing. Better quantification of individual holiday effects, tailored to specific age groups, should improve influenza prevention measures.

Indexed as

Disease Transmission, InfectiousHolidaysSocial ParticipationAdolescentAdultAgedAged, 80 and overChildChild, PreschoolHumansIncidenceInfantInfant, NewbornInfluenza, HumanMiddle AgedModels, StatisticalAgecalendar effectsinfluenzaschool holidayssurveillance

Identifiers

PMID31506136
PMCPMC6805754
OpenAlexW2972704620

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.