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Record W4386403455 · doi:10.18103/mra.v11i8.4299

COVID-19 Mortality Is Attenuated at High Tropical and Subtropical Altitude: An Observational Study of a Database Covering Five Latin American Countries

2023· article· en· W4386403455 on OpenAlexaff
Natalia Zubieta DeUrioste, Christian Reyes, Lida Sanchez, Nestor Subieta, Alfredo Merino‐Luna, Iván Solarte, Raffo Escalante-Kanashiro, José Suazo, E Poma, R.D. Aguilar, José Manuel Calle Aracena, Alberto Lopez Bascope, Roberto Vera Alvarez, Rafaela DeUrioste, Ninoska Rossel, Yeshua Lilio, Gary Quilla, Luis León‐Mateos, Santiago Salazar, Francisco Córdova, Fausto Vinicio Maldonado Coronel, Elisabeth Deindl, Ricki Sheldon, Roberto A. Accinelli, Edith M. Schneider Gasser, Jorge Soliz, Gustavo Calleja

Bibliographic record

VenueMedical Research Archives · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsAltitude (triangle)SubtropicsGeographyPandemicLatin AmericansPopulationTemperate climateDemographyEffects of high altitude on humansTropical climateTropicsCoronavirus disease 2019 (COVID-19)Transmission (telecommunications)Mortality rateSocioeconomicsEnvironmental healthMedicineBiologyEcologyMeteorologyDiseasePathologyPolitical science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic, caused by the SARS-COV-2 virus, has had devastating consequences worldwide. Remarkably, the incidence, virus transmission capacity, and severity of COVID-19 have been reported to be significantly decreased in high-altitude human populations. The clinical significance of these findings is enormous, as they suggest that permanent inhabitants of high altitudes have developed adaptive protective changes against certain pathologies. However, these observations have been overshadowed by contradictory reports on the COVID-19 mortality rate at high altitude, ascribed to low population densities. These interpretations, however, fail to consider that the environmental conditions of high-altitude regions of the temperate and tropical geographical zones are radically different from each other. Contrary to common thought, the conditions of high-altitude areas of countries within the tropical zone are so benign that they have favored the growth and development of densely populated cities. In this work, we use data from a COVID-19 database covering five Latin American countries in the tropical and subtropical geographic zone that corresponded to the period between the start of the pandemic and the end of 2020, when no vaccine was yet available. Our results reveal that residing above 1,000 m in tropical countries was a protective factor against COVID-19 mortality. Interestingly, this protective effect was independent of population size. The findings presented here, and those from other similar studies, substantiate the need for more research to reveal the secrets of the physiology of permanent high-altitude residents. In conclusion, our findings clearly demonstrate that the high-altitude environment in tropical and subtropical geographic zones significantly contributes to the decreased mortality impact of the SARS-COV-2 virus in high-altitude-exposed populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.339
GPT teacher head0.552
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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