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Estimating Active Cases of COVID-19

Alvarez, J.; Baquero, C.; Cabana, E.; Prakash Champati, J.; Fernandez Anta, A.; Frey, D.; Garcia-Agundez Garcia, A.; Georgiou, C.; Goessens, M.; Hernandez, H.; Lillo, R.; Menezes, R.; Moreno, R.; Nicolaou, N.; Ojo, O.; Ortega, A.; Rausell, E.; Rufino, J.; Stavrakis, E.; Jeevan, G.; Glorioso, C.

2021-12-10 health informatics
10.1101/2021.12.09.21267355 medRxiv
Show abstract

Having accurate and timely data on active COVID-19 cases is challenging, since it depends on the availability of an appropriate infrastructure to perform tests and aggregate their results. In this paper, we consider a case to be active if it is infectious, and we propose methods to estimate the number of active infectious cases of COVID-19 from the official data (of confirmed cases and fatalities) and from public survey data. We show that the latter is a viable option in countries with reduced testing capacity or infrastructures.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 10%
18.7%
Similar papers in this journal
2
Journal of Medical Internet Research
◐ 87 papers in training set
Top 0.1%
12.0%
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3
Scientific Reports
○ 3612 papers in training set
Top 4%
9.7%
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4
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 0.1%
6.3%
Similar papers in this journal
5
Journal of Biomedical Informatics
○ 47 papers in training set
Top 0.4%
4.4%
Similar papers in this journal
50% of probability mass above
6
JAMIA Open
◐ 42 papers in training set
Top 0.6%
3.3%
7
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
● 15 papers in training set
Top 0.1%
2.8%
8
Epidemiology and Infection
◐ 89 papers in training set
Top 0.7%
2.5%
9
BMC Medical Informatics and Decision Making
○ 43 papers in training set
Top 0.8%
2.4%
10
Frontiers in Public Health
○ 148 papers in training set
Top 3%
2.1%
11
Patterns
○ 78 papers in training set
Top 1.0%
2.1%
12
Mathematical Biosciences and Engineering
● 23 papers in training set
Top 0.4%
2.1%
13
Viruses
○ 332 papers in training set
Top 3%
1.7%
14
PLOS Digital Health
● 106 papers in training set
Top 3%
1.7%
15
BMC Medical Research Methodology
○ 47 papers in training set
Top 0.7%
1.5%
16
Royal Society Open Science
● 214 papers in training set
Top 4%
1.5%
17
Mathematics
○ 11 papers in training set
Top 0.1%
1.3%
18
IEEE Journal of Biomedical and Health Informatics
● 37 papers in training set
Top 0.8%
1.1%
19
Philosophical Transactions of the Royal Society B
● 51 papers in training set
Top 0.7%
1.0%
20
PLOS Computational Biology
● 1863 papers in training set
Top 18%
1.0%
21
International Journal of Medical Informatics
○ 26 papers in training set
Top 1%
1.0%
22
Nature Communications
○ 5641 papers in training set
Top 54%
0.9%
23
BMJ Open
● 601 papers in training set
Top 12%
0.9%
24
Mathematical Biosciences
○ 49 papers in training set
Top 1%
0.9%
25
IEEE Access
● 35 papers in training set
Top 1%
0.9%
26
iScience
○ 1154 papers in training set
Top 40%
0.6%
27
Frontiers in Applied Mathematics and Statistics
○ 11 papers in training set
Top 0.5%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.