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The Epidemiology Workbench: a Tool for Communities to Strategize in Response to COVID-19 and other Infectious Diseases

Nunez-Corrales, S.; Jakobsson, E.

2020-07-25 epidemiology
10.1101/2020.07.22.20159798 medRxiv
Show abstract

COVID-19 poses a dramatic challenge to health, community life, and the economy of communities across the world. While the properties of the virus are similar from place to place, the impact has been dramatically different from place to place, due to such factors as population density, mobility, age distribution, etc. Thus, optimum testing and social distancing strategies may also be different from place to place. The Epidemiology Workbench provides access to an agent-based model in which a communitys demographic, geographic, and public health information together with a social distancing and testing strategy may be input, and a range of possible outcomes computed, to inform local authorities on coping strategies. The model is adaptable to other infectious diseases, and to other strains of coronavirus. The tool is illustrated by scenarios for the cities of Urbana and Champaign, Illinois, the home of the University of Illinois at Urbana-Champaign. Our calculations suggest that massive testing is the most effective strategy to combat the likely increase in local cases due to mass ingress of a student population carrying a higher viral load than that currently present in the community.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 12%
15.3%
Similar papers in this journal
2
Epidemics
○ 116 papers in training set
Top 0.1%
12.7%
Similar papers in this journal
3
PLOS Computational Biology
● 1863 papers in training set
Top 3%
9.8%
Similar papers in this journal
4
Scientific Reports
○ 3612 papers in training set
Top 19%
4.9%
Similar papers in this journal
5
Frontiers in Public Health
○ 148 papers in training set
Top 1%
4.1%
Similar papers in this journal
6
Journal of The Royal Society Interface
● 235 papers in training set
Top 1%
3.5%
50% of probability mass above
7
BMC Public Health
○ 158 papers in training set
Top 1%
3.5%
8
Infectious Disease Modelling
○ 54 papers in training set
Top 0.5%
3.3%
9
BMC Infectious Diseases
○ 133 papers in training set
Top 1%
2.8%
10
Annals of Epidemiology
○ 21 papers in training set
Top 0.2%
2.2%
11
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 2%
2.2%
12
Epidemiology and Infection
◐ 89 papers in training set
Top 1.0%
1.9%
13
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 0.6%
1.8%
14
American Journal of Epidemiology
◐ 67 papers in training set
Top 0.7%
1.7%
15
Epidemiology
○ 32 papers in training set
Top 0.3%
1.5%
16
Medical Decision Making
○ 12 papers in training set
Top 0.2%
1.1%
17
Mathematical Biosciences
○ 49 papers in training set
Top 0.9%
1.1%
18
PeerJ
◐ 308 papers in training set
Top 9%
1.1%
19
Viruses
○ 332 papers in training set
Top 4%
1.1%
20
Mathematical Biosciences and Engineering
● 23 papers in training set
Top 0.7%
1.0%
21
Computer Methods in Biomechanics and Biomedical Engineering
○ 10 papers in training set
Top 0.2%
0.9%
22
PLOS Neglected Tropical Diseases
● 466 papers in training set
Top 5%
0.9%
23
Royal Society Open Science
● 214 papers in training set
Top 6%
0.9%
24
PLOS Global Public Health
● 344 papers in training set
Top 8%
0.6%
25
Frontiers in Applied Mathematics and Statistics
○ 11 papers in training set
Top 0.5%
0.6%
26
Physica A: Statistical Mechanics and its Applications
○ 13 papers in training set
Top 0.3%
0.6%
27
JAMIA Open
◐ 42 papers in training set
Top 2%
0.6%
28
Journal of Theoretical Biology
○ 162 papers in training set
Top 2%
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.