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Reporting Summary, Last Updated Feb 6, 2026 — Nature Portfolio

Summary

A Nature Portfolio Reporting Summary form completed by the corresponding author of a study on the impact of unemployment insurance on COVID-19 outcomes, last updated February 6, 2026. The form describes a quantitative study of state-week panel data, drawing on state-level data from CDC, BRFSS, DoL, BLS, CUSP and state government websites and individual-level data from IPUMS-CPS and IPUMS-USA. It lists the timing as 2021-2025, states that 6 states were excluded because of inconsistent or ambiguous policies, and says Stata 19 was used to process data. It states that all data are publicly available, that no human participants were analyzed, and that the policy studied was not randomly assigned. The form selects the behavioural and social sciences reporting track.

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Corresponding author(s): JohnS. Earle

Last updated by author(s): Feb 6, 2026

Reporting Summary

Nature Portfolio wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency
in reporting. For further information on Nature Portfolio policies, see our Editorial Policies and the Editorial Policy Checklist.

Statistics

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.

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bX] The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement
A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly

The statistical test(s) used AND whether they are one- or two-sided
Only common tests should be described solely by name; describe more complex techniques in the Methods section.

A description of all covariates tested

xXx xX x

A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons

A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient)
AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)

For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted
Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes

Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated

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Our web collection on statistics for biologists contains articles on many of the points above

Software and code

Policy information about availability of computer code

Data collection Data collected using Chrome browser from publicly accessible websites, as fully described in the supplementary material.

Data analysis Stata 19 was used to process data.

For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and
reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Portfolio guidelines for submitting code & software for further information.

Data

Policy information about availability of data
All manuscripts must include a data availability statement. This statement should provide the following information, where applicable:

- Accession codes, unique identifiers, or web links for publicly available datasets
- A description of any restrictions on data availability
- For clinical datasets or third party data, please ensure that the statement adheres to our policy

All data used in this article are publicly available. The supplementary materials to the manuscript contains full details about the sources, including URLs used to
access the raw data. All data, raw and processed, will be deposited in a publicly accessible archive prior to publication.

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Research involving human participants, their data, or biological material

Policy information about studies with human participants or human data. See also policy information about sex, gender (identity/presentation),
and sexual orientation and race, ethnicity and racism.

Reporting on sex and gender No human participants analyzed. Only publicly available data from CDC and Census Bureau.

Reporting on race, ethnicity, or | Please specify the socially constructed or socially relevant categorization variable(s) used in your manuscript and explain why
other socially relevant they were used. Please note that such variables should not be used as proxies for other socially constructed/relevant variables
; (for example, race or ethnicity should not be used as a proxy for socioeconomic status).
groupings a .
Provide clear definitions of the relevant terms used, how they were provided (by the participants/respondents, the
researchers, or third parties), and the method(s) used to classify people into the different categories (e.g. self-report, census or
administrative data, social media data, etc.)
Please provide details about how you controlled for confounding variables in your analyses.

Population characteristics Describe the covariate-relevant population characteristics of the human research participants (e.g. age, genotypic
information, past and current diagnosis and treatment categories). If you filled out the behavioural & social sciences study
design questions and have nothing to add here, write "See above."

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Recruitment Describe how participants were recruited. Outline any potential self-selection bias or other biases that may be present and
how these are likely to impact results.

Ethics oversight Identify the organization(s) that approved the study protocol.

Note that full information on the approval of the study protocol must also be provided in the manuscript.

Field-specific reporting

Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

[| Life sciences x Behavioural & social sciences [| Ecological, evolutionary & environmental sciences

For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Behavioural & social sciences study design

All studies must disclose on these points even when the disclosure is negative.

Study description Quantitative study of state-week panel data on the impact of unemployment insurance on COVID-19 outcomes.

Research sample State-level data from CDC, BRFSS, DoL, BLS, CUSP, and state government websites; individual-level data from IPUMS-CPS and IPUMS-
USA (ACS).

Sampling strategy All states meeting criterion of clear UI policy regime; Current Population Survey sample (Census Bureau stratified random sample).

Data collection All data were downloaded from publicly accessible websites.

Timing 2021-2025

Data exclusions 6 states were excluded because of inconsistent or ambiguous policies.

Non-participation All states provided data; CPS sampling (including replacement of nonrespondents and weighting for representativeness) follows

Census Bureau procedures.

Randomization Policy studied was not randomly assigned; causal inference is based on identification strategy.

Reporting for specific materials, systems and methods

We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material,
system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.

Materials & experimental systems Methods

Involved in the study n/a | Involved in the study
Antibodies x | ChIP-seq
Eukaryotic cell lines x | Flow cytometry
Palaeontology and archaeology x | MRI-based neuroimaging

Animals and other organisms
Clinical data

Dual use research of concern

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Seed stocks n/a

Novel plant genotypes Describe the methods by which all novel plant genotypes were produced. This includes those generated by transgenic approaches,
gene editing, chemical/radiation-based mutagenesis and hybridization. For transgenic lines, describe the transformation method, the
number of independent lines analyzed and the generation upon which experiments were performed. For gene-edited lines, describe
the editor used, the endogenous sequence targeted for editing, the targeting guide RNA sequence (if applicable) and how the editor

Authentication Bescribe-any authentication procedures foreach seed stock-used-_or-novel genotype-generated.Describe-any-experiments-used-to
assess the effect of a mutation and, where applicable, how potential secondary effects (e.g. second site T-DNA insertions, mosiacism,
off-target gene editing) were examined.

File and source

File
premature-termination-of-unemployment-benefits-increased-covid-19-transmission-and-deaths-in-the-usa.pdf
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1,793,769 bytes
SHA-256
562404c9a31ede95de6a25f4fd9ea8b77251aa7e40ff28b1de0a095684b52c22
Our copy
premature-termination-of-unemployment-benefits-increased-covid-19-transmission-and-deaths-in-the-usa.pdf
Original
doi.org
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