Back

Preventing COVID-19 Fatalities: State versus Federal Policies

Renne, J.-P.; Roussellet, G.; Schwenkler, G.

2020-11-03 health policy
10.1101/2020.10.28.20221952 medRxiv
Show abstract

Are COVID-19 fatalities large when a federal government does not enforce containment policies and instead allow states to implement their own policies? We answer this question by developing a stochastic extension of a SIRD epidemiological model for a country composed of multiple states. Our model allows for interstate mobility. We consider three policies: mask mandates, stay-at-home orders, and interstate travel bans. We fit our model to daily U.S. state-level COVID-19 death counts and exploit our estimates to produce various policy counterfactuals. While the restrictions imposed by some states inhibited a significant number of virus deaths, we find that more than two-thirds of U.S. COVID-19 deaths could have been prevented by late November 2020 had the federal government enforced federal mandates as early as some of the earliest states did. Our results quantify the benefits of early actions by a federal government for the containment of a pandemic.

Matching journals

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

1
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 2%
14.9%
2
PLOS ONE
4510 papers in training set
Top 13%
14.5%
3
PNAS Nexus
147 papers in training set
Top 0.1%
10.2%
4
Scientific Reports
3102 papers in training set
Top 6%
10.2%
5
Science
429 papers in training set
Top 6%
4.9%
50% of probability mass above
6
Epidemics
104 papers in training set
Top 0.4%
3.6%
7
Nature Human Behaviour
85 papers in training set
Top 1%
3.1%
8
Medical Decision Making
10 papers in training set
Top 0.1%
2.9%
9
Nature Medicine
117 papers in training set
Top 1%
2.1%
10
Clinical Infectious Diseases
231 papers in training set
Top 2%
1.9%
11
Emerging Infectious Diseases
103 papers in training set
Top 1%
1.8%
12
Social Science & Medicine
15 papers in training set
Top 0.4%
1.8%
13
BMC Public Health
147 papers in training set
Top 4%
1.5%
14
Royal Society Open Science
193 papers in training set
Top 3%
1.3%
15
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 4%
1.3%
16
Cell Systems
167 papers in training set
Top 8%
1.3%
17
Eurosurveillance
80 papers in training set
Top 1.0%
1.2%
18
Nature
575 papers in training set
Top 14%
0.9%
19
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
0.8%
20
COVID
13 papers in training set
Top 0.3%
0.8%
21
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 7%
0.7%
22
JMIR Public Health and Surveillance
45 papers in training set
Top 4%
0.7%
23
International Journal of Infectious Diseases
126 papers in training set
Top 4%
0.5%
24
Clinical Microbiology and Infection
60 papers in training set
Top 2%
0.5%
25
PLOS Computational Biology
1633 papers in training set
Top 29%
0.5%
26
Biology
43 papers in training set
Top 4%
0.5%
27
Nature Communications
4913 papers in training set
Top 67%
0.5%
28
FACETS
11 papers in training set
Top 0.4%
0.5%