Evidence map›Paper›PMID 34662353›Full record

ArticlePloS one2021

Timely surveillance and temporal calibration of disease response against human infectious diseases.

Kamran Najeebullah, Jessica Liebig, Jonathan Darbro, Raja Jurdak, Dean Paini

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% 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, 6 citations in OpenAlex.

  1. Timeliness in canine rabies outbreak report and response.medRxiv : the preprint server for health sciences · 2025
    Article
  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

5 authors at 3 institutions in 1 country.

Kamran NajeebullahData61, Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Australia.ORCID 0000-0003-1884-356X
Jessica LiebigHealth & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Australia.ORCID 0000-0002-9706-9420
Jonathan DarbroMetro North Public Health Unit, Queensland Health, Brisbane, Queensland, Australia.
Raja JurdakDepartment of Computer Science, Queensland University of Technology, Brisbane, Australia.ORCID 0000-0001-7517-0782
Dean PainiHealth & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Australia.
Commonwealth Scientific and Industrial Research Organisation · AUQueensland Health · AUQueensland University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisease surveillance and response are critical components of epidemic preparedness. The disease response, in most cases, is a set of reactive measures that follow the outcomes of the disease surveillance. Hence, timely surveillance is a prerequisite for an effective response. METHODOLOGY/PRINCIPAL

findingsWe apply epidemiological soundness criteria in combination with the Latent Influence Point Process and time-to-event models to construct a disease spread network. The network implicitly quantifies the fertility (whether a case leads to secondary cases) and reproduction (number of secondary cases per infectious case) of the cases as well as the size and generations (of the infection chain) of the outbreaks. We test our approach by applying it to historic dengue case data from Australia. Using the data, we empirically confirm that high morbidity relates positively with delay in disease response. Moreover, we identify what constitutes timely surveillance by applying various thresholds of disease response delay to the network and report their impact on case fertility, reproduction, number of generations and ultimately, outbreak size. We observe that enforcing a response delay threshold of 5 days leads to a large average reduction across all parameters (occurrence 87%, reproduction 83%, outbreak size 80% and outbreak generations 47%), whereas extending the threshold to 10 days, in comparison, significantly limits the effectiveness of the response actions. Lastly, we identify the components of the disease surveillance system that can be calibrated to achieve the identified thresholds.

conclusionWe identify practically achievable, timely surveillance thresholds (on temporal scale) that lead to an effective response and identify how they can be satisfied. Our approach can be utilized to provide guidelines on spatially and demographically targeted resource allocation for public awareness campaigns as well as to improve diagnostic abilities and turn-around times for the doctors and laboratories involved.

Indexed as

AustraliaCalibrationCommunicable DiseasesDengueEpidemiological MonitoringGeographyHumansTime Factors

Identifiers

PMID34662353
PMCPMC8523075
OpenAlexW3205156360

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.