SARS-CoV-2 BW lineage, a fast-growing Omicron variant from southeast Mexico bearing relevant escape mutations.

PURPOSE: The swift expansion of the BW.1 SARS-CoV-2 variant coincided with a rapid increase of COVID-19 cases occurring in Southeast Mexico in October, 2022, which marked the start of Mexico's sixth epidemiological wave. In Yucatan, up to 92% (58 of 73) of weekly sequenced genomes between epidemiological week 42 and 47 were identified as either BW.1 or its descendant, BW.1.1 in the region, during the last trimester of 2022. In the current study, a comprehensive genomic comparison was carried out to characterize the evolutionary history of the BW lineage, identifying its origins and its most important mutations. METHODS: An alignment of all the genomes of the BW lineage and its parental BA.5.6.2 variant was carried out to identify their mutations. A phylogenetic and ancestral sequence reconstruction analysis with geographical inference, as well as a longitudinal analysis of point mutations, were performed to trace back their origin and contrast them with key RBD mutations in variant BQ.1, one of the fastest-growing lineages to date. RESULTS: Our ancestral reconstruction analysis portrayed Mexico as the most probable origin of the BW.1 and BW.1.1 variants. Two synonymous substitutions, T7666C and C14599T, support their Mexican origin, whereas other two mutations are specific to BW.1: S:N460K and ORF1a:V627I. Two additional substitutions and a deletion are found in its descending subvariant, BW.1.1. Mutations found in the receptor binding domain, S:K444T, S:L452R, S:N460K, and S:F486V in BW.1 have been reported to be relevant for immune escape and are also key mutations in the BQ.1 lineage. CONCLUSIONS: BW.1 appears to have arisen in the Yucatan Peninsula in Southeast Mexico sometime around July 2022 during the fifth COVID-19 wave. Its rapid growth may be in part explained by the relevant escape mutations also found in BQ.1.

Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database.

Identifying risk factors associated with COVID-19 lethality is crucial in combating the ongoing pandemic. In this study, we developed lethality predictive models for each epidemiological wave and for the overall dataset using the Extreme Gradient Boosting technique and analyzed them using Shapley values to determine the contribution levels of various features, including demographics, comorbidities, medical units, and recent medical information from confirmed COVID-19 cases in Mexico between February 23, 2020, and April 15, 2022. The results showed that pneumonia and advanced age were the most important factors predicting patient death in all cohorts. Additionally, the medical unit where the patient received care acted as a risk or protective factor. IMSS medical units were identified as high-risk factors in all cohorts, except in wave four, while SSA medical units generally were moderate protective factors. We also found that intubation was a high-risk factor in the first epidemiological wave and a moderate-risk factor in the following waves. Female gender was a protective factor of moderate-high importance in all cohorts, while being between 18 and 29 years old was a moderate protective factor and being between 50 and 59 years old was a moderate risk factor. Additionally, diabetes (all cohorts), obesity (third wave), and hypertension (fourth wave) were identified as moderate risk factors. Finally, residing in municipalities with the lowest Human Development Index level represented a moderate risk factor. In conclusion, this study identified several significant risk factors associated with COVID-19 lethality in Mexico, which could aid policymakers in developing targeted interventions to reduce mortality rates.

Socioeconomic determinants of health and COVID-19 in Mexico.

INTRODUCTION: The population living in conditions of poorness has a heavier pathological burden than social strata with better economic possibilities. OBJECTIVE: To determine the influence of socioeconomic and demographic factors on COVID-19 morbidity, mortality and lethality in municipalities and states of Mexico. METHODS: Morbidity, mortality and lethality associated with COVID-19 were analyzed according to the human development index and its indicators, and type of population. Descriptive statistical analyses, correlations between developmental variables and morbidity, mortality and lethality, association tests and hierarchical groupings were carried out. RESULTS: Positive correlations were observed between morbidity and mortality and the human development index; COVID-19 fatality increased as the values of said index decreased. There was a significantly higher risk of elevated mortality in localities with moderate and low development, and in those with less than 49,999 inhabitants. The main factors associated with fatality were lack of access to health services, income vulnerability and social deprivation. CONCLUSIONS: The evidence generated should lead to decisions aimed at improving the quality of life of the population with social deprivations and vulnerabilities, which needs to be protected against the consequences of current COVID-19 pandemic.

INTRODUCCIÓN: La población en situación de pobreza presenta una carga patológica mayor que los estratos sociales con mejores posibilidades económicas. OBJETIVO: Determinar la influencia de los factores socioeconómicos y demográficos en la morbilidad, mortalidad y letalidad de COVID-19 en municipios y estados de México. MÉTODOS: Se analizó la morbilidad, mortalidad y letalidad asociadas a COVID-19 conforme el índice de desarrollo humano y sus indicadores, así como el tipo de población. Se realizaron análisis estadísticos descriptivos, de correlación entre variables de desarrollo versus morbilidad, mortalidad y letalidad, pruebas de asociación y agrupaciones jerárquicas. RESULTADOS: Se observaron correlaciones positivas entre la morbilidad y mortalidad y el índice de desarrollo humano; la letalidad por COVID-19 aumentó conforme disminuyó dicho índice. Existió riesgo significativamente superior de alta letalidad en las localidades con moderado y bajo desarrollo, así como en aquellas con menos de 49 999 habitantes. Los principales factores asociados a la letalidad fueron la falta de acceso a los servicios de salud, la vulnerabilidad por ingreso y la carencia social. CONCLUSIONES: La evidencia generada debe llevar a decisiones tendentes al mejoramiento de la calidad de vida de la población con carencias y vulnerabilidades sociales, que necesita ser protegida contra las consecuencias de la actual pandemia de COVID-19.

Covid-19 y el índice de desarrollo humano en México.

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Comparative performance of four single extreme outlier discordancy tests from Monte Carlo simulations.

Using highly precise and accurate Monte Carlo simulations of 20,000,000 replications and 102 independent simulation experiments with extremely low simulation errors and total uncertainties, we evaluated the performance of four single outlier discordancy tests (Grubbs test N2, Dixon test N8, skewness test N14, and kurtosis test N15) for normal samples of sizes 5 to 20. Statistical contaminations of a single observation resulting from parameters called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or ε from ±1.1 up to ±200 for slippage of dispersion, as well as no contamination (δ = 0 and ε = ±1), were simulated. Because of the use of precise and accurate random and normally distributed simulated data, very large replications, and a large number of independent experiments, this paper presents a novel approach for precise and accurate estimations of power functions of four popular discordancy tests and, therefore, should not be considered as a simple simulation exercise unrelated to probability and statistics. From both criteria of the Power of Test proposed by Hayes and Kinsella and the Test Performance Criterion of Barnett and Lewis, Dixon test N8 performs less well than the other three tests. The overall performance of these four tests could be summarized as N2≅N15 > N14 > N8.

Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

Dominance of Three Sublineages of the SARS-CoV-2 Delta Variant in Mexico.

In this study, we analyzed the sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which has completely replaced other previously circulating variants in the country due to its transmission advantage. Among all the Delta sublineages that were detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described herein, and phylogenetic analyses and haplotype networks are used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the main sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variant associated with the third wave of the COVID-19 pandemic in Mexico and highlights the importance of SARS-CoV-2 genomic surveillance for the timely identification of emerging variants that may impact public health.

The Alpha Variant (B.1.1.7) of SARS-CoV-2 Failed to Become Dominant in Mexico.

During the coronavirus disease 2019 (COVID-19) pandemic, the emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in the United Kingdom in September 2020, was well documented in different areas of the world and became a global public health concern because of its increased transmissibility. The B.1.1.7 lineage was first detected in Mexico during December 2020, showing a slow progressive increase in its circulation frequency, which reached its maximum in May 2021 but never became predominant. In this work, we analyzed the patterns of diversity and distribution of this lineage in Mexico using phylogenetic and haplotype network analyses. Despite the reported increase in transmissibility of the B.1.1.7 lineage, in most Mexican states, it did not displace cocirculating lineages, such as B.1.1.519, which dominated the country from February to May 2021. Our results show that the states with the highest prevalence of B.1.1.7 were those at the Mexico-U.S. border. An apparent pattern of dispersion of this lineage from the northern states of Mexico toward the center or the southeast was observed in the largest transmission chains, indicating possible independent introduction events from the United States. However, other entry points cannot be excluded, as shown by multiple introduction events. Local transmission led to a few successful haplotypes with a localized distribution and specific mutations indicating sustained community transmission. IMPORTANCE The emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world were due to its increased transmissibility. However, it did not displace cocirculating lineages in most of Mexico, particularly B.1.1.519, which dominated the country from February to May 2021. In this work, we analyzed the distribution of B.1.1.7 in Mexico using phylogenetic and haplotype network analyses. Our results show that the states with the highest prevalence of B.1.1.7 (around 30%) were those at the Mexico-U.S. border, which also exhibited the highest lineage diversity, indicating possible introduction events from the United States. Also, several haplotypes were identified with a localized distribution and specific mutations, indicating that sustained community transmission occurred in the country.

Determinantes socioeconómicos de salud y COVID-19 en México / Socioeconomic determinants of health and COVID-19 in Mexico

Resumen Introducción: La población en situación de pobreza presenta una carga patológica mayor que los estratos sociales con mejores posibilidades económicas. Objetivo: Determinar la influencia de los factores socioeconómicos y demográficos en la morbilidad, mortalidad y letalidad de COVID-19 en municipios y estados de México. Métodos: Se analizó la morbilidad, mortalidad y letalidad asociadas a COVID-19 conforme el índice de desarrollo humano y sus indicadores, así como el tipo de población. Se realizaron análisis estadísticos descriptivos, de correlación entre variables de desarrollo versus morbilidad, mortalidad y letalidad, pruebas de asociación y agrupaciones jerárquicas. Resultados: Se observaron correlaciones positivas entre la morbilidad y mortalidad y el índice de desarrollo humano; la letalidad por COVID-19 aumentó conforme disminuyó dicho índice. Existió riesgo significativamente superior de alta letalidad en las localidades con moderado y bajo desarrollo, así como en aquellas con menos de 49 999 habitantes. Los principales factores asociados a la letalidad fueron la falta de acceso a los servicios de salud, la vulnerabilidad por ingreso y la carencia social. Conclusiones: La evidencia generada debe llevar a decisiones tendentes al mejoramiento de la calidad de vida de la población con carencias y vulnerabilidades sociales, que necesita ser protegida contra las consecuencias de la actual pandemia de COVID-19.

Abstract Introduction: The population living in conditions of poorness has a heavier pathological burden than social strata with better economic possibilities. Objective: To determine the influence of socioeconomic and demographic factors on COVID-19 morbidity, mortality and lethality in municipalities and states of Mexico. Methods: Morbidity, mortality and lethality associated with COVID-19 were analyzed according to the human development index and its indicators, and type of population. Descriptive statistical analyses, correlations between developmental variables and morbidity, mortality and lethality, association tests and hierarchical groupings were conducted. Results: Positive correlations were observed between morbidity and mortality and the human development index; COVID-19 fatality increased as the values of said index decreased. There was a significantly higher risk of elevated mortality in localities with moderate and low development, and in those with less than 49,999 inhabitants. The main factors associated with fatality were lack of access to health services, income vulnerability and social deprivation. Conclusions: The evidence generated should lead to decisions aimed at improving the quality of life of the population with social deprivations and vulnerabilities, which needs to be protected against the consequences of current COVID-19 pandemic.