Evidence map›Paper›PMID 32511526›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Differential Effects of Intervention Timing on COVID-19 Spread in the United States.

Sen Pei, Sasikiran Kandula, Jeffrey Shaman

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sen PeiDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University.
Sasikiran KandulaDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University.
Jeffrey ShamanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University.

Funding

Development and Dissemination of Operational Real-Time Respiratory Virus ForecastU01GM110748 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2018
$2.6M
NIGMS NIH HHS U01 GM110748
6 · The paper itself

Abstract

Assessing the effects of early non-pharmaceutical interventions1-5 on COVID-19 spread in the United States is crucial for understanding and planning future control measures to combat the ongoing pandemic6-10. Here we use county-level observations of reported infections and deaths11, in conjunction with human mobility data12 and a metapopulation transmission model13,14, to quantify changes of disease transmission rates in US counties from March 15, 2020 to May 3, 2020. We find significant reductions of the basic reproductive numbers in major metropolitan areas in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same control measures been implemented just 1-2 weeks earlier, a substantial number of cases and deaths could have been averted. Specifically, nationwide, 61.6% [95% CI: 54.6%-67.7%] of reported infections and 55.0% [95% CI: 46.1%-62.2%] of reported deaths as of May 3, 2020 could have been avoided if the same control measures had been implemented just one week earlier. We also examine the effects of delays in re-implementing social distancing following a relaxation of control measures. A longer response time results in a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive response in controlling the COVID-19 pandemic.

Identifiers

PMID32511526
PMCPMC7273294

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.