Evidence map›Paper›PMID 37708121›Full record

ArticlePLoS neglected tropical diseases2023

Reporting delays of chikungunya cases during the 2017 outbreak in Lazio region, Italy.

Mattia Manica, Giovanni Marini, Angelo Solimini, Giorgio Guzzetta, Piero Poletti, Paola Scognamiglio, Chiara Virgillito, Alessandra Della Torre, Stefano Merler, Roberto Rosà and 2 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2023. 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
–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

10 citing papers in PubMed.

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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

12 authors.

Mattia ManicaCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.ORCID 0000-0003-3709-1199
Giovanni MariniResearch and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN), Italy.
Angelo SoliminiDepartment of Public Health and Infectious Diseases, Università di Roma SAPIENZA, Rome, Italy.
Giorgio GuzzettaCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Piero PolettiCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Paola ScognamiglioRegional Service for Surveillance and Control of Infectious Diseases (SERESMI)-Lazio Region, National Institute for Infectious Diseases "Lazzaro Spallanzani"; IRCCS, Rome, Italy.
Chiara VirgillitoDepartment of Public Health and Infectious Diseases, Università di Roma SAPIENZA, Rome, Italy.
Alessandra Della TorreDepartment of Public Health and Infectious Diseases, Università di Roma SAPIENZA, Rome, Italy.
Stefano MerlerCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Roberto RosàResearch and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN), Italy.
Francesco VairoRegional Service for Surveillance and Control of Infectious Diseases (SERESMI)-Lazio Region, National Institute for Infectious Diseases "Lazzaro Spallanzani"; IRCCS, Rome, Italy.
Beniamino CaputoDepartment of Public Health and Infectious Diseases, Università di Roma SAPIENZA, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission. METHODOLOGY/PRINCIPAL

findingsUsing descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak. CONCLUSIONS/SIGNIFICANCE: These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.

Indexed as

Chikungunya FeverDisease OutbreaksEuropeHumansItalyPublic Health

Identifiers

PMID37708121
PMCPMC10501639

What OpenQuestion holds

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Registered trials

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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.