Evidence map›Paper›PMID 32637975›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Lockdown measures and relative changes in the age-specific incidence of SARS-CoV-2 in Spain.

De Salazar, Gómez-Barroso D, Pampaka D, Gil Jm, Peñalver B, Fernández-Escobar C, Lipsitch M, Larrauri A, Goldstein E, Hernán Ma

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

De SalazarCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States.
Gómez-Barroso DCentro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.
Pampaka DCentro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.
Gil JmDepartment of Anesthesiology, Santa Creu i Sant Pau Hospital, Barcelona, Spain.
Peñalver BCentro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.
Fernández-Escobar CCentro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.
Lipsitch MCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States.
Larrauri ACentro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.
Goldstein ECenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States.
Hernán MaDepartment of Epidemiology and Department of Biostatistics, Harvard T.H. Chan School of Public Health; Harvard-MIT Division of Health Sciences and Technology, Boston, United States.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

backgroundThe first months of the SARS-CoV-2 epidemic in Spain resulted in high incidence and mortality. A national sero-epidemiological survey suggests higher cumulative incidence of infection in older individuals than in younger individuals. However, little is known about the epidemic dynamics in different age groups, including the relative effect of the lockdown measures introduced on March 15, and strengthened on March 30 to April 14, 2020 when only essential workers continued to work.

methodsWe used data from the National Epidemiological Surveillance Network (RENAVE in Spanish) on the daily number of reported COVID-19 cases (by date of symptom onset) in eleven 5-year age groups: 15-19y through 65-69y. For each age group g, we computed the proportion E(g) of individuals in age group g among all reported cases aged 15-69y during the pre-lockdown period (March 1-10, 2020) and the corresponding proportion L(g) during two lockdown periods (March 25-April 3 and April 8-17, 2020). For each lockdown period, we computed the proportion ratios PR(g)= L(g)/E(g). For each pair of age groups g1,g2, PR(g1)>PR(g2) implies a relative increase in the incidence of detected SARS-CoV-2 infection in the age group g1 compared with g2 for the later vs. early period.

resultsFor the first lockdown period, the highest PR values were in age groups 50-54y (PR=1.21; 95% CI: 1.12,1.30) and 55-59y (PR=1.19; 1.11,1.27). For the second lockdown period, the highest PR values were in age groups 15-19y (PR=1.26; 0.95,1.68) and 50-54y (PR=1.20; 1.09,1.31).

conclusionsOur results suggest that different outbreak control measures led to different changes in the relative incidence by age group. During the first lockdown period, when non-essential work was allowed, individuals aged 40-64y, particularly those aged 50-59y presented with higher COVID-19 relative incidence compared to pre-lockdown period, while younger adults/older adolescents (together with persons aged 50-59y) had increased relative incidence during the later, strengthened lockdown. The role of different age groups during the epidemic should be considered when implementing future mitigation efforts.

Identifiers

PMID32637975
PMCPMC7340201

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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.