Evidence map›Paper›PMID 34627201›Full record

ArticleBMC public health2021

Cross-sectional telephone surveys as a tool to study epidemiological factors and monitor seasonal influenza activity in Malta.

V Marmara, D Marmara, P McMenemy, A Kleczkowski

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. 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

4 authors at 4 institutions in 2 countries.

V MarmaraFaculty of Economics, Management & Accountancy, University of Malta, Msida, MSD, 2080, Malta.
D MarmaraFaculty of Health Sciences, Mater Dei Hospital, Block A, Level 1, University of Malta, Msida, MSD, 2090, Malta. attard.danika@gmail.com.
P McMenemyDepartment of Mathematics, University of Stirling, Stirling, FK94LA, Scotland, UK.
A KleczkowskiDepartment of Mathematics and Statistics, University of Strathclyde, Rm. 1001, 26 Richmond Street, Glasgow, G1 1XH, Scotland.
Mater Dei Hospital · MTUniversity of Malta · MTUniversity of Stirling · GBUniversity of Strathclyde · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeasonal influenza has major implications for healthcare services as outbreaks often lead to high activity levels in health systems. Being able to predict when such outbreaks occur is vital. Mathematical models have extensively been used to predict epidemics of infectious diseases such as seasonal influenza and to assess effectiveness of control strategies. Availability of comprehensive and reliable datasets used to parametrize these models is limited. In this paper we combine a unique epidemiological dataset collected in Malta through General Practitioners (GPs) with a novel method using cross-sectional surveys to study seasonal influenza dynamics in Malta in 2014-2016, to include social dynamics and self-perception related to seasonal influenza.

methodsTwo cross-sectional public surveys (n = 406 per survey) were performed by telephone across the Maltese population in 2014-15 and 2015-16 influenza seasons. Survey results were compared with incidence data (diagnosed seasonal influenza cases) collected by GPs in the same period and with Google Trends data for Malta. Information was collected on whether participants recalled their health status in past months, occurrences of influenza symptoms, hospitalisation rates due to seasonal influenza, seeking GP advice, and other medical information.

resultsWe demonstrate that cross-sectional surveys are a reliable alternative data source to medical records. The two surveys gave comparable results, indicating that the level of recollection among the public is high. Based on two seasons of data, the reporting rate in Malta varies between 14 and 22%. The comparison with Google Trends suggests that the online searches peak at about the same time as the maximum extent of the epidemic, but the public interest declines and returns to background level. We also found that the public intensively searched the Internet for influenza-related terms even when number of cases was low.

conclusionsOur research shows that a telephone survey is a viable way to gain deeper insight into a population's self-perception of influenza and its symptoms and to provide another benchmark for medical statistics provided by GPs and Google Trends. The information collected can be used to improve epidemiological modelling of seasonal influenza and other infectious diseases, thus effectively contributing to public health.

Indexed as

Influenza, HumanCross-Sectional StudiesHumansMaltaSeasonsTelephoneCross-sectional surveysEpidemiologyInfluenza symptomsPriorsSeasonal influenzaUnder-reporting

Identifiers

PMID34627201
PMCPMC8502089
OpenAlexW3206708869

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.