Evidence map›Paper›PMID 36316634›Full record

ArticleBMC infectious diseases2022

Comparative epidemiology of five waves of COVID-19 in Mexico, March 2020-August 2022.

Iván de Jesús Ascencio-Montiel, Oscar David Ovalle-Luna, Ramón Alberto Rascón-Pacheco, Victor Hugo Borja-Aburto, Gerardo Chowell

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 7% of its field
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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Iván de Jesús Ascencio-MontielDivisión de Análisis en Salud. Coordinación de Vigilancia Epidemiológica, Mexican Social Security Institute, Mexico City, Mexico.
Oscar David Ovalle-LunaDivisión de Vigilancia Epidemiológica de Enfermedades Transmisibles. Coordinación de Vigilancia Epidemiológica, Mexican Social Security Insitute, Mexico City, Mexico.
Ramón Alberto Rascón-PachecoCoordinación de Investigación en Salud, Instituto Mexicano del Seguro Social, Mexico City, Mexico. alberto.rascon@imss.gob.mx.
Victor Hugo Borja-AburtoMexican Social Security Institute, Mexico City, Mexico.
Gerardo ChowellDepartment of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA.
Mexican Social Security Institute · MXGeorgia State University · US

Funding

Ebola modeling: behavior, asymptomatic infection, and contacts (2019-nCoV Admin Supplement)R01GM130900 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PORCO, TRAVIS CHRISTIAN · 2019 to 2022
$1.6M
National Science Foundation 1610429,1633381 and R01 GM 130900NIGMS NIH HHS R01 GM130900
6 · The paper itself

Abstract

backgroundThe Mexican Institute of Social Security (IMSS) is the largest health care provider in Mexico, covering about 48% of the Mexican population. In this report, we describe the epidemiological patterns related to confirmed cases, hospitalizations, intubations, and in-hospital mortality due to COVID-19 and associated factors, during five epidemic waves recorded in the IMSS surveillance system.

methodsWe analyzed COVID-19 laboratory-confirmed cases from the Online Epidemiological Surveillance System (SINOLAVE) from March 29th, 2020, to August 27th, 2022. We constructed weekly epidemic curves describing temporal patterns of confirmed cases and hospitalizations by age, gender, and wave. We also estimated hospitalization, intubation, and hospital case fatality rates. The mean days of in-hospital stay and hospital admission delay were calculated across five pandemic waves. Logistic regression models were employed to assess the association between demographic factors, comorbidities, wave, and vaccination and the risk of severe disease and in-hospital death.

resultsA total of 3,396,375 laboratory-confirmed COVID-19 cases were recorded across the five waves. The introduction of rapid antigen testing at the end of 2020 increased detection and modified epidemiological estimates. Overall, 11% (95% CI 10.9, 11.1) of confirmed cases were hospitalized, 20.6% (95% CI 20.5, 20.7) of the hospitalized cases were intubated, and the hospital case fatality rate was 45.1% (95% CI 44.9, 45.3). The mean in-hospital stay was 9.11 days, and patients were admitted on average 5.07 days after symptoms onset. The most recent waves dominated by the Omicron variant had the highest incidence. Hospitalization, intubation, and mean hospitalization days decreased during subsequent waves. The in-hospital case fatality rate fluctuated across waves, reaching its highest value during the second wave in winter 2020. A notable decrease in hospitalization was observed primarily among individuals ≥ 60 years. The risk of severe disease and death was positively associated with comorbidities, age, and male gender; and declined with later waves and vaccination status.

conclusionDuring the five pandemic waves, we observed an increase in the number of cases and a reduction in severity metrics. During the first three waves, the high in-hospital fatality rate was associated with hospitalization practices for critical patients with comorbidities.

Indexed as

COVID-19HospitalizationHospital MortalityHumansMaleMexicoSARS-CoV-2COVID-19DeathHospitalizationIntubationSARS-CoV-2

Identifiers

PMID36316634
PMCPMC9623964
OpenAlexW4307885799

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.