The hearth of mathematical and statistical modelling during the Coronavirus pandemic.

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.

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.

Who cites it

7 citing papers in PubMed.

1. Modeling the epidemic control measures in overcoming COVID-19 outbreaks: A fractional-order derivative approach.Chaos, solitons, and fractals · 2022
   Article
2. Thoracic Surgical Oncology in Lombardy: How to Do It During COVID-19 Time?The Annals of thoracic surgery · 2020
   Article
3. Opening and closing the doors of the lockdown in Italy without forgetting lung cancer patients.Interactive cardiovascular and thoracic surgery · 2020
   Review
4. Reorganization of thoracic surgery activity in a national high-volume comprehensive cancer centre in the Italian epicentre of coronavirus disease 2019.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2020
   Article
5. Model the transmission dynamics of COVID-19 propagation with public health intervention.Results in applied mathematics · 2020
   Article
6. Development of a Multi-Dimensional Parametric Model With Non-Pharmacological Policies for Predicting the COVID-19 Pandemic Casualties.IEEE access : practical innovations, open solutions · 2020
   Article
7. A Novel Parametric Model for the Prediction and Analysis of the COVID-19 Casualties.IEEE access : practical innovations, open solutions · 2020
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

2 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

Indexed as