ArticleScientific reports2024
Spatio-temporal analysis of COVID-19 lockdown effect to survive in the US counties using ANN.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- The Real-Time Estimation of Respiratory Flow and Mask Leakage in a PAPR Using a Single Differential-Pressure Sensor and Microcontroller-Based Smartphone Interface in the Development of a Public-Oriented Powered Air-Purifying Respirator as an Alternative to Lockdown Measures.Sensors (Basel, Switzerland) · 2025Article
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
This study aims to quantify the effectiveness of lockdown as a non-pharmacological solution for managing the COVID-19 pandemic. Daily COVID-19 death counts were collected for four states: California, Georgia, New Jersey, and South Carolina. The effectiveness of the lockdown was studied and the number of people saved during 7 days was evaluated. Five neural network models (MLP, FFNN, CFNN, ENN, and NARX) were implemented, and the results indicate that FFNN is the best prediction model. Based on this model, the total number of survivors over a 7-day period is 211, 270, 989, and 60 in California, Georgia, New Jersey, and South Carolina, respectively. The coefficients and weights of the FFNN for each state differ due to various factors, including socio-demographic conditions and the behavior of citizens towards lockdown laws. New Jersey and South Carolina have the most lockdowns and the least.
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Registered trials
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.