“…(D) Pandemic related COVID-19 interventions: per capita expenditure of COVID-19 pandemic budget in USD ( Ministerio de Economia de Finanzas del Peru, 2021 ); and number of COVID-19 tests (PCR molecular tests, serological tests, and antigen rapid tests) per 100,000 population ( Presidencia de Consejo de Ministros del Peru, 2021 ). (E) Exposure and susceptibility factors: percentage of people with comorbidities, defined as the percentage of people living with diabetes (physician-diagnosed or diagnosed through fasting glucose test), or hypertension (systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg), or obesity (Body mass index ≥30 kg/m 2 )) ( Instituto Nacional de Estadistica e Informatica, 2020 ); percentage of people currently smoking, defined as current tobacco use among persons aged 15 years and older as a percentage of the total persons aged 15 years and older ( Instituto Nacional de EstadisticaInformatica, 2020 , Instituto Nacional de EstadisticaInformatica, 2021c ); and (F) Covid-19 infections: COVID-19 incidence, defined as the number of COVID-19 confirmed cases per 100,000 population based on PCR molecular tests, serological tests, or antigen rapid tests ( Presidencia de Consejo de Ministros del Peru, 2021 ); and excess death rate defined as the number of excess deaths per 100,000 population ( Feyman et al., 2022 ; Henry et al., 2022 ; Islam et al., 2021 ; Iuliano et al., 2021 ; Kontis et al., 2020 ; Kontopantelis et al., 2021 ; Lewnard et al., 2021 ; Moghadas and Galvani, 2021 ; Sempé et al., 2021 ). Figure 1 Conceptual framework for COVID-19 and drivers of excess death rate in Peru.…”
Section: Methodsmentioning
confidence: 99%
“…However, when considering the excess death rate as an indicator, Peru has been one of the worst hit countries worldwide ( Financial Times, 2021 ). The excess death rate has been proposed as a better tool than COVID-19 deaths to assess the direct and indirect effects of COVID-19 on mortality ( Feyman et al., 2022 ; Henry et al., 2022 ; Islam et al., 2021 ; Iuliano et al., 2021 ; Kontis et al., 2020 ; Kontopantelis et al., 2021 ; Lewnard et al., 2021 ; Moghadas and Galvani, 2021 ; Sempé et al., 2021 ).…”
“…(D) Pandemic related COVID-19 interventions: per capita expenditure of COVID-19 pandemic budget in USD ( Ministerio de Economia de Finanzas del Peru, 2021 ); and number of COVID-19 tests (PCR molecular tests, serological tests, and antigen rapid tests) per 100,000 population ( Presidencia de Consejo de Ministros del Peru, 2021 ). (E) Exposure and susceptibility factors: percentage of people with comorbidities, defined as the percentage of people living with diabetes (physician-diagnosed or diagnosed through fasting glucose test), or hypertension (systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg), or obesity (Body mass index ≥30 kg/m 2 )) ( Instituto Nacional de Estadistica e Informatica, 2020 ); percentage of people currently smoking, defined as current tobacco use among persons aged 15 years and older as a percentage of the total persons aged 15 years and older ( Instituto Nacional de EstadisticaInformatica, 2020 , Instituto Nacional de EstadisticaInformatica, 2021c ); and (F) Covid-19 infections: COVID-19 incidence, defined as the number of COVID-19 confirmed cases per 100,000 population based on PCR molecular tests, serological tests, or antigen rapid tests ( Presidencia de Consejo de Ministros del Peru, 2021 ); and excess death rate defined as the number of excess deaths per 100,000 population ( Feyman et al., 2022 ; Henry et al., 2022 ; Islam et al., 2021 ; Iuliano et al., 2021 ; Kontis et al., 2020 ; Kontopantelis et al., 2021 ; Lewnard et al., 2021 ; Moghadas and Galvani, 2021 ; Sempé et al., 2021 ). Figure 1 Conceptual framework for COVID-19 and drivers of excess death rate in Peru.…”
Section: Methodsmentioning
confidence: 99%
“…However, when considering the excess death rate as an indicator, Peru has been one of the worst hit countries worldwide ( Financial Times, 2021 ). The excess death rate has been proposed as a better tool than COVID-19 deaths to assess the direct and indirect effects of COVID-19 on mortality ( Feyman et al., 2022 ; Henry et al., 2022 ; Islam et al., 2021 ; Iuliano et al., 2021 ; Kontis et al., 2020 ; Kontopantelis et al., 2021 ; Lewnard et al., 2021 ; Moghadas and Galvani, 2021 ; Sempé et al., 2021 ).…”
“…5 Yet, a recent study discovered that despite being more likely to have risk factors of severe COVID-19 infections, Veterans exhibited lower excess COVID-19 mortality rate compared to the general population. 6 Therefore, while risk factors of severe COVID-19 infections have been extensively studied among the general population, 3 , 4 it remains unclear whether the same risk factors are applicable to this population. Thus, this unique community merits special attention in the literature.…”
Introduction
While risk factors for severe COVID-19 infections have been well explored among the public, population-specific studies for the U.S. Veteran community are limited in the literature. By performing a comprehensive analysis of the demographics, comorbidities, and symptomatology of a population of COVID-19 positive Veterans Affairs (VA) patients, we aim to uncover predictors of death, survival, need for intubation, and need for nasal cannula oxygen support among this understudied community.
Materials and Methods
A retrospective review was conducted of 124 COVID-19 Veteran patients who were admitted from March to October 2020 to the VA Greater Los Angeles Healthcare System (IRB#2020-000272). Chi-square and Fisher’s exact tests were employed to assess differences in baseline demographic and clinical variables between Veterans who survived COVID-19 versus those who succumbed to COVID-19 illness. Multivariate logistic regression and Cox regression analyses were employed to assess predictors of outcome variables, including death, survival, need for intubation, and need for oxygen support (via nasal cannula). Covariates included a wide range of demographic, comorbidity-related, symptom-related, and summary index variables.
Results
Our study population consisted of primarily senior (average age was 73) Caucasian and African American (52.5% and 40.7%, respectively) Veterans. Bivariate analyses indicated that need for intubation was significantly associated with mortality (P = 0.002). Multivariate analyses revealed that age (P < 0.001, adjusted odds ratio (OR) = 1.16), dyspnea (P = 0.015, OR = 7.73), anorexia (P = 0.022, OR = 16.55), initial disease severity as classified by WHO (P = 0.031, OR = 4.55), and having more than one of the three most common comorbidities (hypertension, diabetes, and cardiac disease) and symptoms (cough, fever, and dyspnea) among our sample (P = 0.009; OR = 19.07) were independent predictors of death. Furthermore, age (P < 0.001, hazard ratio (HR) = 1.14), cerebrovascular disease (P = 0.022, HR = 3.76), dyspnea (P < 0.001, HR = 7.71), anorexia (P < 0.001, HR = 16.75), and initial disease severity as classified by WHO (P = 0.025, HR = 3.30) were independent predictors of poor survival. Finally, dyspnea reliably predicted need for intubation (P = 0.019; OR = 29.65).
Conclusions
Several independent predictors of death, survival, and need for intubation were identified. These risk factors may provide guidelines for risk-stratifying Veterans upon admission to VA hospitals. Additional investigations of COVID-19 prognosis should be conducted on the larger U.S. Veteran population to confirm our findings and add to the current body of literature.
“…Previous reports show that death rates among those who typically received care in the VA system were less affected than the general US population during the COVID-19 pandemic, despite higher rates of comorbidities [5–7]. However, Veterans enrolled in VA care also differ from the general US population in age, sex, racial/ethnic composition, and geographic distribution, and each of these factors has been associated with mortality rates in general and deaths rates due to COVID-19 specifically [8–10].…”
Importance The COVID-19 pandemic had a substantial impact on the overall rate of death in the United States during the first year. It is unclear whether access to comprehensive medical care, such as through the VA healthcare system, altered death rates compared to the US population.
Objective: Quantify the increase in death rates during the first year of the COVID-19 pandemic in the general US population and among individuals who receive comprehensive medical care through the Department of Veterans Affairs (VA).
Design: Analysis of changes in all-cause death rates by quarter, stratified by age, sex race/ethnicity, and region, based on individual-level data. Hierarchical regression models were fit in a Bayesian setting. Standardized rates were used for comparison between populations.
Setting and participants: General population of the United States, enrollees in the VA, and active users of VA healthcare.
Exposure and main outcome: Changes in rates of death from any cause during the COVID-19 pandemic in 2020 compared to previous years.
Results Sharp increases were apparent across all of the adult age groups (25 years and older) in both the general US population and the VA populations. Across all of 2020, the relative increase in death rates was similar in the general US population (RR: 1.20 (95% CI: 1.17, 1.22)), VA enrollees (RR: 1.20 (95% CI: 1.14, 1.29)), and VA active users (RR: 1.19 (95% CI: 1.14, 1.26)). Because the pre-pandemic standardized mortality rates were higher in the VA populations prior to the pandemic, the absolute rates of excess mortality were higher in the VA populations.
Conclusions and Relevance: Despite access to comprehensive medical care, active users of the VA had similar relative mortality increases from all causes compared with the general US population. Factors that influenced baseline rates of death and that mitigated viral transmission in the community are more likely to have influenced the impact of the pandemic.
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