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BACKGROUNDIn 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent to which non-COVID deaths contributed to excess mortality, its regional characterization, and the association between municipal-and individual-level sociodemographic inequality has not been characterized. METHODSWe conducted a retrospective municipal an individual-level study using death certificate data in Mexico from 2016-2020. We analyzed mortality related to COVID-19 and to non-COVID-19 causes using ICD-10 codes to identify cause-specific mortality. Excess mortality was estimated as the increase in deaths in 2020 compared to the average of 2016-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. We evaluated correlates of non-COVID-19 mortality at the individual level using mixed effects logistic regression and correlates of non-COVID-19 excess mortality in 2020 at the municipal level using negative binomial regression. RESULTSWe identified 1,069,174 deaths in 2020 (833.5 per 100,000 inhabitants), which was 49% higher compared to the 2016-2019 average (557.38 per 100,000 inhabitants). Overall excess mortality (276.11 deaths per 100,000 inhabitants) was attributable in 76.1% to COVID-19; however, non-COVID-19 causes comprised one-fifth of excess deaths. COVID-19 deaths occurred primarily in-hospital, while excess non-COVID-19 deaths decreased in this setting and increased out-of-hospital. Excess non-COVID-19 mortality displayed geographical heterogeneity linked to sociodemographic inequalities with clustering in states in southern Mexico. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization, and social marginalization. At the individual level, lower educational attainment, blue collar workers, and lack of medical care assistance were associated with non-COVID-19 mortality during 2020. CONCLUSIONNon-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual-and municipal-level sociodemographic inequalities. These findings should prompt an urgent call to action to improve healthcare coverage and access to reduce health and sociodemographic inequalities in Mexico to reduce preventable mortality in situations which increase the stress of healthcare systems, including the ongoing COVID-19 pandemic.
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BACKGROUNDVaccination has been effective in ameliorating the impact of COVID-19. However, estimation of vaccine effectiveness (VE) is still unavailable for some widely used vaccines and underrepresented groups. Here, we report on the effectiveness of a nation-wide COVID-19 vaccination program in Mexico. METHODSWe used a test-negative design within a national COVID-19 surveillance system to assess VE of the BNT162b2, mRNA-12732, Gam-COVID-Vac, Ad5-nCoV, Ad26.COV2.S, ChAdOx1 and CoronaVac vaccines, against SARS-CoV-2 infection, COVID-19 related hospitalization and death for adults [≥]18 years in Mexico. VE was estimated using Cox proportional hazard models considering time-varying vaccination status in partial and fully vaccinated individuals compared to unvaccinated adults, adjusted by age, sex, comorbidities and municipality. We also estimated VE for adults [≥]60 years, for cases with diabetes and comparing periods with predominance of variants B.1.1.519 and B.1.617.2. RESULTSWe assessed 793,487 vaccinated compared to 4,792,338 unvaccinated adults between December 24th, 2020, and September 27th, 2021. VE against SARS-CoV-2 infection was highest for fully vaccinated individuals with mRNA-12732 (91.5%, 95%CI 90.3-92.4) and Ad26.COV2.S (82.2%, 95%CI 81.4-82.9), whereas for COVID-19 related hospitalization were BNT162b2 (84.3%, 95%CI 83.6-84.9) and Gam-COVID-Vac (81.4% 95%CI 79.5-83.1) and for mortality BNT162b2 (89.8%, 95%CI 89.2-90.2) and mRNA-12732 (93.5%, 95%CI 86.0-97.0). VE for all evaluated vaccines was reduced for adults [≥]60 years, people with diabetes, and in periods of Delta variant predominance. CONCLUSIONSAll evaluated vaccines were effective against SARS-CoV-2 infection and COVID-19 related hospitalization and death. Mass vaccination campaigns with multiple vaccine products are feasible and effective to maximize vaccination coverage.
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BackgroundPost-acute COVID-19 syndrome (PACS) is a multi-system disease comprising persistent symptomatology after the acute phase of infection. Long-term PACS effects significantly impact patient outcomes, but their incidence remains uncharacterized due to high heterogeneity between studies. Therefore, we aimed to summarize published data on PACS, characterizing the clinical presentation, prevalence, and modifiers of prevalence estimates. MethodIn this systematic review and meta-analysis, we research MEDLINE for original studies published from January 1st, 2020, to January 31st, 2021, that reported proportions of PACS manifestations. Studies were eligible for inclusion if they included patients aged [≥]18 years with confirmed COVID-19 by RT-PCR or antigen testing and a minimum follow-up of 21 days. The prevalence of individual manifestations across studies was pooled using random-effects meta-analysis. For evaluating determinants of heterogeneity, meta-regression analysis was performed. This study was registered in PROSPERO (CRD42019125025). ResultsAfter screening 1,235 studies, we included 29 reports for analysis. Twenty-seven meta-analyses were performed, and 61 long-term manifestations were described. The pooled prevalence of PACS was 56% (95%CI 45-66%), with the most common manifestations being diminished health status, fatigue, asthenia, dyspnea, myalgias, hyposmia and dysgeusia. Most of the included studies presented high heterogeneity. After conducting the meta-regression analysis, we identified that age, gender, number of comorbidities, and reported symptoms significantly modify the prevalence estimation of PACS long-term manifestations. ConclusionPACS is inconsistently reported between studies, and population characteristics influence the prevalence estimates due to high heterogeneity. A systematized approach for the study of PACS is needed to characterize its impact adequately. Fundingnone
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The impact of the COVID-19 pandemic in Mexico City has been sharp, as several social inequalities coexist with chronic comorbidities. Here, we conducted an in-depth evaluation of the impact of social, municipal, and individual factors on the COVID-19 pandemic in working-age population living in Mexico City. To this end, we used data from the National Epidemiological Surveillance System; furthermore, we used a multidimensional metric, the social lag index (DISLI), to evaluate its interaction with mean urban population density (MUPD) and its impact on COVID-19 rates. Influence DISLI and MUPD on the effect of vehicular mobility policies on COVID-19 rates were also tested. Finally, we assessed the influence of MUPD and DISLI on discrepancies of COVID-19 and non-COVID-19 excess mortality compared with death certificates from the General Civil Registry. We detected vulnerable groups who belonged to economically active sectors and who experienced increased risk of adverse COVID-19 outcomes. The impact of social inequalities transcends individuals and has significant effects at a municipality level, with and interaction between DISLI and MUPD. Marginalized municipalities with high population density experienced an accentuated risk for adverse COVID-19 outcomes. Additionally, policies to reduce vehicular mobility had differential impacts across marginalized municipalities. Finally, we report an under-registry of COVID-19 deaths and significant excess mortality associated with non-COVID-19 deaths closely related to MUPD/DISLI in an ambulatory setting, which could be a negative externality of hospital reconversion. In conclusion, social, individual, and municipality-wide factors played a significant role in shaping the course of the COVID-19 pandemic in Mexico City.
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BACKGROUNDSARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico. METHODSWe analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n=6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n=216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality. RESULTSRapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and [≥]7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course. CONCLUSIONSRapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.
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INTRODUCTIONChronological age (CA) is a predictor of adverse COVID-19 outcomes; however, CA alone does not capture individual responses to SARS-CoV-2 infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. METHODSIn this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (ICU admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge/PhenoAccelAge components. RESULTSWe included 1068 subjects of whom 401 presented critical illness and 204 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel>0 had higher risk of death and critical illness compared to those with lower values (log-rank p<0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection: 1) Inflammaging associated with CA, 2) metabolic dysfunction associated with cardio-metabolic comorbidities, 3) unfavorable hematological response, and 4) response associated with favorable outcomes. CONCLUSIONSAdaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.
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ABSTRACT (50 WORDS)We profiled cases with non-respiratory symptoms (NRS) and asymptomatic SARS-CoV-2 assessed within Mexico Citys Epidemiological Surveillance System. We show that initially asymptomatic or NRS cases have decreased risk of adverse COVID-19 outcomes compared to cases with respiratory symptoms. Comorbidity and age influence likelihood of developing symptoms in initially asymptomatic cases.
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BACKGROUNDHealth-care workers (HCWs) have increased risk for SARS-CoV-2 infection. Information about the prevalence and risk factors for adverse outcomes in HCWs is scarce in Mexico. Here, we aimed to explore prevalence of SARS-CoV-2, symptoms, and risk factors associated with adverse outcomes in HCWs in Mexico City. METHODSWe explored data collected by the National Epidemiological Surveillance System in Mexico City. All cases underwent real-time RT-PCR test. We explored outcomes related to severe COVID-19 in HCWs and the diagnostic performance of symptoms to detect SARS-CoV-2 infection in HCWs. RESULTSAs of July 2nd, 2020, 34,263 HCWs were tested for SARS-CoV-2 and 10,925 were confirmed (31.9%). Overall, 4,200 were nurses (38.4%), 3,244 physicians (29.7%), 126 dentists (1.15%) and 3,355 laboratory personnel and other HCWs (30.7%). After follow-up, 992 HCWs required hospitalization (9.08%), 206 developed severe outcomes (1.89%), and 90 required mechanical-ventilatory support (0.82%). Lethality was recorded in 224 (2.05%) cases. Symptoms associated with SARS-CoV-2 positivity were fever, cough, malaise, shivering, myalgias at evaluation but neither had significant predictive value. We also identified 333 asymptomatic SARS-CoV-2 infections (3.05%). Older HCWs with chronic non-communicable diseases, pregnancy, and severe respiratory symptoms were associated with higher risk for adverse outcomes. Physicians had higher risk for hospitalization and for severe outcome compared with nurses and other HCWs. CONCLUSIONSWe report a high prevalence of SARS-CoV-2 in HCWs in Mexico City. No symptomatology can accurately discern HCWs with SARS-CoV-2 infection. Particular attention should focus on HCWs with risk factors to prevent adverse outcomes and reduce infection risk.
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BACKGROUNDCOVID-19 has had a disproportionate impact on older adults. Mexicos population is younger, yet COVID-19s impact on older adults is comparable to countries with older population structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging. METHODSWe analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for improving COVID-19 mortality risk prediction. RESULTSWe analyzed 7,029 confirmed SARS-CoV-2 cases in adults aged [≥]60 years. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization and ICU admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas. CONCLUSIONSStructural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach.
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BACKGROUNDThe SARS-CoV-2 outbreak poses challenge to healthcare systems due to high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity and its role in improving risk prediction. METHODSWe obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19 related lethality. Finally, we built a clinical score to predict COVID-19 lethality. RESULTSAmong 177,133 subjects at May 18th, 2020, we observed 51,633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, COPD, advanced age, hypertension, immunosuppression, and CKD; we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for ICU admission and intubation. Our predictive score for COVID-19 lethality included age [≥]65 years, diabetes, early-onset diabetes, obesity, age <40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (c-statistic=0.823). RESULTSHere, we propose a mechanistic approach to evaluate risk for complications and lethality attributable to COVID-19 considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first contact scenario.
