Evidence map›Paper›PMID 32959625›Full record

ArticleJournal of epidemiology and global health2020

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases.

F Baldassi, O Cenciarelli, A Malizia, P Gaudio

Abstract read
In one paragraph

Article in Journal of epidemiology and global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. 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.

F BaldassiDepartment of Industrial Engineering, University of Rome Tor Vergata, Rome, Italy.ORCID 0000-0001-8991-2476
O CenciarelliInternational CBRNe Master Courses, University of Rome Tor Vergata, Rome, Italy.
A MaliziaDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
P GaudioDepartment of Industrial Engineering, University of Rome Tor Vergata, Rome, Italy.ORCID 0000-0003-0861-558X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid detection of ongoing outbreak - and the identification of causative pathogen - is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors - such as population density, travel, and trade - and ecological factors - like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB

Indexed as

Communicable DiseasesDisease OutbreaksPublic Health SurveillanceSoftwareChinaDemocratic Republic of the CongoFemaleHemorrhagic Fever, EbolaHumansMadagascarMalePlagueSevere Acute Respiratory SyndromeepidemiologyInfectious diseasesmodellingoutbreakspathogens

Identifiers

PMID32959625
PMCPMC7758858

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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.