The impact of altitude on hospitalization and hospital mortality from pandemic 2009 influenza A (H1N1) virus pneumonia in Mexico

Araníbar J, Munayco Escate CV. High altitudes, population density, and poverty: Unraveling the complexities of COVID-19 in Peru during the years 2020-2022

Background

Several factors related to hospitalizations, morbidity, and mortality from COVID-19 have been identified. However, limited exploration has been done on geographic and socioeconomic factors that could significantly impact these outcomes.

Objectives

This study aimed to determine whether altitude, population density, and percentage of population in total poverty are associated with COVID-19 incidence per 1000 inhabitants and COVID-19 case-fatality rate in Peru, from 2020 to 2022.

Methods

This study utilized a multiple group ecological design and relied on secondary databases containing daily records of COVID-19 positive cases and deaths due to COVID-19. An epidemiological analysis was performed, subsequently processed using a random effects model.

Results

As of August 2022, Peru had recorded a total of 3,838,028 COVID-19 positive cases and 215,023 deaths due to COVID-19. Our analysis revealed a statistically significant negative association between altitude and COVID-19 incidence (aBETA: -0.004; Standard Error: 0.001; p < 0.05). Moreover, we observed a positive association between population density and incidence (aBETA: 0.006; Standard Error: 0.001; p < 0.05). However, we found no significant association between the percentage of population in total poverty and COVID-19 incidence.

Conclusion

Our study found that an increase in altitude was associated with a decrease in COVID-19 incidence, while an increase in population density was associated with an increase in COVID-19 incidence. High altitude, population density and percentage of population in total poverty does not change case-fatality rate due to COVID-19.

Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19

INTRODUCTION

The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P/F) ≤ 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P/F adjusted for this high altitude.

METHODS

This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogotá, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p <0.25. Then, these variables were automatically selected with a backward stepwise approach with a significance level of 0.1. The interaction terms and fractional polynomials were also examined in the final model. Multiple imputation procedures and bootstraps were used to obtain the coefficients with the best external validation. In addition, total adjustment of the model and logistic regression diagnostics were performed. The same methodology was used to develop a second model with the P/F adjusted for altitude. Finally, the areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves of the two models were compared.

RESULTS

A total of 2,210 subjects were included in the final analysis. The final model included 11 variables without interaction terms or nonlinear functions. The coefficients are presented excluding influential observations. The final equation for the model fit was g(x) = age(0.04819)+weight(0.00653)+height(-0.01856)+haemoglobin(-0.0916)+platelet count(-0.003614)+ creatinine(0.0958)+lactate dehydrogenase(0.001589)+sodium(-0.02298)+potassium(0.1574)+systolic pressure(-0.00308)+if moderate ARDS(0.628)+if severe ARDS(1.379), and the probability of in-hospital death was p (x) = e g (x)/(1+ e g (x)). The AUC of the ROC curve was 0.7601 (95% confidence interval (CI) 0.74-0, 78). The second model with the adjusted P/F presented an AUC of 0.754 (95% CI 0.73-0.77). No statistically significant difference was found between the AUC curves (p value = 0.6795).

CONCLUSION

This study presents a prediction model for patients with C-ARDS at 2,600 masl with easily available admission variables for early stratification of in-hospital mortality risk. Adjusting the P/F for 2,600 masl did not improve the predictive capacity of the model. We do not recommend adjusting the P/F for altitude.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China

Existing studies reported higher altitudes reduce the COVID-19 infection rate in the United States, Colombia, and Peru. However, the underlying reasons for this phenomenon remain unclear. In this study, regression analysis and mediating effect model were used in a combination to explore the altitudes relation with the pattern of transmission under their correlation factors. The preliminary linear regression analysis indicated a negative correlation between altitudes and COVID-19 infection in China. In contrast to environmental factors from low-altitude regions (<1500 m), high-altitude regions (>1500 m) exhibited lower PM2.5, average temperature (AT), and mobility, accompanied by high SO₂ and absolute humidity (AH). Non-linear regression analysis further revealed that COVID-19 confirmed cases had a positive correlation with mobility, AH, and AT, whereas negatively correlated with SO₂, CO, and DTR. Subsequent mediating effect model with altitude-correlated factors, such as mobility, AT, AH, DTR and SO₂, suffice to discriminate the COVID-19 infection rate between low- and high-altitude regions. The mentioned evidence advance our understanding of the altitude-mediated COVID-19 transmission mechanism.

The Association of Latitude and Altitude with COVID-19 Symptoms: A VIRUS: COVID-19 Registry Analysis

Background:

Better delineation of COVID-19 presentations in different climatological conditions might assist with prompt diagnosis and isolation of patients.

Objectives:

To study the association of latitude and altitude with COVID-19 symptomatology.

Methods:

This observational cohort study included 12267 adult COVID-19 patients hospitalized between 03/2020 and 01/2021 at 181 hospitals in 24 countries within the SCCM Discovery VIRUS: COVID-19 Registry. The outcome was symptoms at admission, categorized as respiratory, gastrointestinal, neurological, mucocutaneous, cardiovascular, and constitutional. Other symptoms were grouped as atypical. Multivariable regression modeling was performed, adjusting for baseline characteristics. Models were fitted using generalized estimating equations to account for the clustering.

Results:

The median age was 62 years, with 57% males. The median age and percentage of patients with comorbidities increased with higher latitude. Conversely, patients with comorbidities decreased with elevated altitudes. The most common symptoms were respiratory (80%), followed by constitutional (75%). Presentation with respiratory symptoms was not associated with the location. After adjustment, at lower latitudes (<30º), patients presented less commonly with gastrointestinal symptoms (p<.001, odds ratios for 15º, 25º, and 30º: 0.32, 0.81, and 0.98, respectively). Atypical symptoms were present in 21% of the patients and showed an association with altitude (p=.026, odds ratios for 75, 125, 400, and 600 meters above sea level: 0.44, 0.60, 0.84, and 0.77, respectively).

Conclusions:

We observed geographic variability in symptoms of COVID-19 patients. Respiratory symptoms were most common but were not associated with the location. Gastrointestinal symptoms were less frequent in lower latitudes. Atypical symptoms were associated with higher altitude.

Clinical characteristics and mortality associated with COVID-19 at high altitude: a cohort of 5161 patients in Bogotá, Colombia

Background

There are few data on the clinical outcomes of patients with coronavirus disease 2019 (COVID-19) in cities over 1000 m above sea level (masl).

Objectives

To describe the clinical characteristics and mortality of patients with COVID-19 treated at a high complexity hospital in Bogotá, Colombia, at 2640 masl.

Methods

This was an observational study of a cohort including 5161 patients with confirmed COVID-19 infection from 19 March 2020 to 30 April 2021. Demographic data, laboratory values, comorbidities, oxygenation indices, and clinical outcomes were collected. Data were compared between survivors and nonsurvivors. An independent predictive model was performed for mortality and invasive mechanical ventilation (IMV) using classification and regression trees (CART).

Results

The median cohort age was 66 years (interquartile range (IQR) 53–77), with 1305 patients dying (25%) and 3856 surviving (75%). The intensive care unit (ICU) received 1223 patients (24%). Of 898 patients who received IMV, 613 (68%) of them perished. The ratio of partial pressure arterial oxygen (PaO₂) to fraction inspired oxygen (FiO₂), or the P/F ratio, upon ICU admission was 105 (IQR 77–146) and 137 (IQR 91–199) in the deceased and survivors, respectively. The CART model showed that the need for IMV, age greater than 79 years, ratio of oxygen saturation (SaO₂) to FiO₂, or the S/F ratio, less than 259, and lactate dehydrogenase (LDH) greater than 617 U/L at admission were associated with a greater probability of death.

Conclusion

Among more than 5000 patients with COVID-19 treated in our hospital, mortality at hospital discharge was 25%. Older age, low S/F ratio, and high LDH at admission were predictors of mortality.

Pandemic preparedness and COVID-19: an exploratory analysis of infection and fatality rates, and contextual factors associated with preparedness in 177 countries, from Jan 1, 2020, to Sept 30, 2021

BACKGROUND

National rates of COVID-19 infection and fatality have varied dramatically since the onset of the pandemic. Understanding the conditions associated with this cross-country variation is essential to guiding investment in more effective preparedness and response for future pandemics.

METHODS

Daily SARS-CoV-2 infections and COVID-19 deaths for 177 countries and territories and 181 subnational locations were extracted from the Institute for Health Metrics and Evaluation's modelling database. Cumulative infection rate and infection-fatality ratio (IFR) were estimated and standardised for environmental, demographic, biological, and economic factors. For infections, we included factors associated with environmental seasonality (measured as the relative risk of pneumonia), population density, gross domestic product (GDP) per capita, proportion of the population living below 100 m, and a proxy for previous exposure to other betacoronaviruses. For IFR, factors were age distribution of the population, mean body-mass index (BMI), exposure to air pollution, smoking rates, the proxy for previous exposure to other betacoronaviruses, population density, age-standardised prevalence of chronic obstructive pulmonary disease and cancer, and GDP per capita. These were standardised using indirect age standardisation and multivariate linear models. Standardised national cumulative infection rates and IFRs were tested for associations with 12 pandemic preparedness indices, seven health-care capacity indicators, and ten other demographic, social, and political conditions using linear regression. To investigate pathways by which important factors might affect infections with SARS-CoV-2, we also assessed the relationship between interpersonal and governmental trust and corruption and changes in mobility patterns and COVID-19 vaccination rates.

FINDINGS

The factors that explained the most variation in cumulative rates of SARS-CoV-2 infection between Jan 1, 2020, and Sept 30, 2021, included the proportion of the population living below 100 m (5·4% [4·0-7·9] of variation), GDP per capita (4·2% [1·8-6·6] of variation), and the proportion of infections attributable to seasonality (2·1% [95% uncertainty interval 1·7-2·7] of variation). Most cross-country variation in cumulative infection rates could not be explained. The factors that explained the most variation in COVID-19 IFR over the same period were the age profile of the country (46·7% [18·4-67·6] of variation), GDP per capita (3·1% [0·3-8·6] of variation), and national mean BMI (1·1% [0·2-2·6] of variation). 44·4% (29·2-61·7) of cross-national variation in IFR could not be explained. Pandemic-preparedness indices, which aim to measure health security capacity, were not meaningfully associated with standardised infection rates or IFRs. Measures of trust in the government and interpersonal trust, as well as less government corruption, had larger, statistically significant associations with lower standardised infection rates. High levels of government and interpersonal trust, as well as less government corruption, were also associated with higher COVID-19 vaccine coverage among middle-income and high-income countries where vaccine availability was more widespread, and lower corruption was associated with greater reductions in mobility. If these modelled associations were to be causal, an increase in trust of governments such that all countries had societies that attained at least the amount of trust in government or interpersonal trust measured in Denmark, which is in the 75th percentile across these spectrums, might have reduced global infections by 12·9% (5·7-17·8) for government trust and 40·3% (24·3-51·4) for interpersonal trust. Similarly, if all countries had a national BMI equal to or less than that of the 25th percentile, our analysis suggests global standardised IFR would be reduced by 11·1%.

INTERPRETATION

Efforts to improve pandemic preparedness and response for the next pandemic might benefit from greater investment in risk communication and community engagement strategies to boost the confidence that individuals have in public health guidance. Our results suggest that increasing health promotion for key modifiable risks is associated with a reduction of fatalities in such a scenario.

FUNDING

Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Interplay between hypoxia and inflammation contributes to the progression and severity of respiratory viral diseases

History of pandemics is dominated by viral infections and specifically respiratory viral diseases like influenza and COVID-19. Lower respiratory tract infection is the fourth leading cause of death worldwide. Crosstalk between resultant inflammation and hypoxic microenvironment may impair ventilatory response of lungs. This reduces arterial partial pressure of oxygen, termed as hypoxemia, which is observed in a section of patients with respiratory virus infections including SARS-CoV-2 (COVID-19). In this review, we describe the interplay between inflammation and hypoxic microenvironment in respiratory viral infection and its contribution to disease pathogenesis.

Altitude and COVID-19: Friend or foe? A narrative review

Recent reports suggest that high-altitude residence may be beneficial in the novel coronavirus disease (COVID-19) implicating that traveling to high places or using hypoxic conditioning thus could be favorable as well. Physiological high-altitude characteristics and symptoms of altitude illnesses furthermore seem similar to several pathologies associated with COVID-19. As a consequence, high altitude and hypoxia research and related clinical practices are discussed for potential applications in COVID-19 prevention and treatment. We summarize the currently available evidence on the relationship between altitude/hypoxia conditions and COVID-19 epidemiology and pathophysiology. The potential for treatment strategies used for altitude illnesses is evaluated. Symptomatic overlaps in the pathophysiology of COVID-19 induced ARDS and high altitude illnesses (i.e., hypoxemia, dyspnea…) have been reported but are also common to other pathologies (i.e., heart failure, pulmonary embolism, COPD…). Most treatments of altitude illnesses have limited value and may even be detrimental in COVID-19. Some may be efficient, potentially the corticosteroid dexamethasone. Physiological adaptations to altitude/hypoxia can exert diverse effects, depending on the constitution of the target individual and the hypoxic dose. In healthy individuals, they may optimize oxygen supply and increase mitochondrial, antioxidant, and immune system function. It is highly debated if these physiological responses to hypoxia overlap in many instances with SARS-CoV-2 infection and may exert preventive effects under very specific conditions. The temporal overlap of SARS-CoV-2 infection and exposure to altitude/hypoxia may be detrimental. No evidence-based knowledge is presently available on whether and how altitude/hypoxia may prevent, treat or aggravate COVID-19. The reported lower incidence and mortality of COVID-19 in high-altitude places remain to be confirmed. High-altitude illnesses and COVID-19 pathologies exhibit clear pathophysiological differences. While potentially effective as a prophylactic measure, altitude/hypoxia is likely associated with elevated risks for patients with COVID-19. Altogether, the different points discussed in this review are of possibly some relevance for individuals who aim to reach high-altitude areas. However, due to the ever-changing state of understanding of COVID-19, all points discussed in this review may be out of date at the time of its publication.

Modeling COVID-19 scenarios for the United States

We use COVID-19 case and mortality data from 1 February 2020 to 21 September 2020 and a deterministic SEIR (susceptible, exposed, infectious and recovered) compartmental framework to model possible trajectories of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the effects of non-pharmaceutical interventions in the United States at the state level from 22 September 2020 through 28 February 2021. Using this SEIR model, and projections of critical driving covariates (pneumonia seasonality, mobility, testing rates and mask use per capita), we assessed scenarios of social distancing mandates and levels of mask use. Projections of current non-pharmaceutical intervention strategies by state-with social distancing mandates reinstated when a threshold of 8 deaths per million population is exceeded (reference scenario)-suggest that, cumulatively, 511,373 (469,578-578,347) lives could be lost to COVID-19 across the United States by 28 February 2021. We find that achieving universal mask use (95% mask use in public) could be sufficient to ameliorate the worst effects of epidemic resurgences in many states. Universal mask use could save an additional 129,574 (85,284-170,867) lives from September 22, 2020 through the end of February 2021, or an additional 95,814 (60,731-133,077) lives assuming a lesser adoption of mask wearing (85%), when compared to the reference scenario.

Individual and climate factors associated with acute respiratory infection in Colombian children

The objective of this study was to examine the association between acute respiratory infection recall (ARI-recall) and individual and environmental factors such as climate, precipitation, and altitude above sea level in Colombian children. A secondary analysis of 11,483 Colombian children, whose mothers were interviewed in the 2010 National Demographic and Health Survey, was carried out. The outcome variable was the mother's or caregiver's ARI-recall. The independent variables were expressed at individual, cluster, and municipal levels. At the individual level, we considered health and individual characteristics of the children; at cluster level, we incorporated the altitude above sea level; and at the municipal level, we included precipitation and annual average climate. The association between ARI-recall and independent variables was assessed using a multilevel logistic regression model. ARI-recall was significantly associated with age (OR = 0.61; 95%CI: 0.48-0.79), belonging to an indigenous group (OR = 1.51; 95%CI: 1.16-1.96), and a medium or very poor wealth index (OR = 2.03; 95%CI: 1.25-3.30 and OR = 1.75; 95%CI: 1.08-2.84, respectively). We found interaction between acute child malnutrition and average annual precipitation. Children with acute malnutrition and from municipalities with high annual precipitation had significantly 3.6-fold increased risk of ARI-recall (OR = 3.6; 95%CI: 1.3-10.1). Individual conditions and precipitation are risk factors for ARI-recall in Colombian children. These results could be useful to understand ARI occurrence in children living in tropical countries with similar characteristics.

Generation of switched memory B cells in response to vaccination in Down syndrome children and their siblings

BACKGROUND

Immunodeficiency is an integral aspect of Down syndrome, as demonstrated by the increased susceptibility to infection of affected. Mortality is still higher than in general population, with respiratory infections among the major causes of death. As more people with Down syndrome are living today than ever before, it is indispensable to develop strategies to prevent and cure the associated disorders. Vaccination is the most successful instrument of preventive medicine. Special seasonal influenza and pneumococcal vaccination strategies have been designed for individuals with risk conditions of all ages. Down syndrome individuals are not included in the high-risk categories.

METHODS

We enrolled in our study 15 children with Down syndrome and their siblings, vaccinated for the first time with seasonal influenza vaccine and receiving a booster dose of a glyco-conjugated pneumococcal vaccine. We compared the immunological features and response to vaccination measuring serum antibody titers and frequency of specific memory B cells.

RESULTS

We confirm that a severe reduction of switched memory B cells is always associated to Down syndrome. After primary vaccination Down syndrome children generate significantly less specific switched memory B cells than their siblings. The response to a booster dose of vaccine is instead comparable in both groups. The production of specific antibodies was equally effective in Down syndrome and controls both after primary and secondary immunization.

CONCLUSIONS

Down syndrome individuals should be considered a high risk group, because of their increased susceptibility to infection and reduced number of switched memory B cells. Tailored vaccination protocols are needed in order to reduce their burden of infections throughout life.

Impact of home environment interventions on the risk of influenza-associated ARI in Andean children: observations from a prospective household-based cohort study

Background

The Respiratory Infections in Andean Peruvian Children (RESPIRA-PERU) study enrolled children who participated in a community-cluster randomized trial of improved stoves, solar water disinfection, and kitchen sinks (IHIP trial) and children from additional Andean households. We quantified the burden of influenza-associated acute respiratory illness (ARI) in this household-based cohort.

Methods

From May 2009 to September 2011, we conducted active weekly ARI surveillance in 892 children age <3 years, of whom 272 (30.5%) had participated in the IHIP trial. We collected nasal swabs during ARI, tested for influenza and other respiratory viruses by RT-PCR, and determined influenza incidence and risk factors using mixed-effects regression models.

Results

The overall incidence of influenza-associated ARI was 36.6/100 child-years; incidence of influenza A, B, and C was 20.5, 8.7, and 5.2/100 child-years, respectively. Influenza C was associated with fewer days of subjective fever (median 1 vs. 2) and malaise (median 0 vs. 2) compared to influenza A. Non-influenza ARI also resulted in fewer days of fever and malaise, and fewer healthcare visits than influenza A-associated ARI. Influenza incidence varied by calendar year (80% occurred in the 2010 season) and IHIP trial participation. Among households that participated in the IHIP trial, influenza-associated ARI incidence was significantly lower in intervention than in control households (RR 0.40, 95% CI: 0.20–0.82).

Conclusions

Influenza burden is high among Andean children. ARI associated with influenza A and B had longer symptom duration and higher healthcare utilization than influenza C-associated ARI or non-influenza ARI. Environmental community interventions may reduce influenza morbidity.