Financial Burden and Catastrophic Health Expenditure Associated with COVID-19 Hospitalizations in Kerala, South India

Comparative analysis of financial toxicity between SARS-CoV-2 infection and common comorbidities

Financial toxicity is common in individuals with COVID-19 and Long COVID. However, the extent of financial toxicity experienced, in comparison to other common comorbidities, is uncertain. Contributing factors exacerbating financial challenges in Long COVID are also unclear. These knowledge gaps are addressed via a cross-sectional analysis utilizing data from the 2022 National Health Interview Survey (NHIS), a representative sample drawn from the United States. COVID-19 cases were identified through self-reported positive testing or physician diagnoses. Long COVID was defined as experiencing COVID-19-related symptoms for more than three months. Comorbidity was assessed based on self-reported diagnoses of ten doctor-diagnosed conditions (Yes/No). Financial toxicity was defined as having difficulty paying medical bills, cost-related medication nonadherence, delaying healthcare due to cost, and/or not obtained healthcare due to cost. A total of 27,492 NHIS 2022 respondents were included in our analysis, representing 253 million U.S. adults. In multivariable logistic regression models, adults with Long COVID (excluding respondents with COVID-19 but not Long COVID), showed increased financial toxicity compared to those with other comorbidities, such as epilepsy (OR [95% CI]: 1.69 [1.22, 2.33]), dementia (1.51 [1.01, 2.25]), cancer (1.43 [1.19, 1.71]) or respiratory/cardiovascular conditions (1.18 [1.00, 1.40]/1.23 [1.02, 1.47]). Long COVID-related financial toxicity was associated with female sex, age <65 years, lack of medical insurance, current paid employment, residence region, food insecurity, fatigue, mild to severe depression symptoms experienced during the survey completion, visits to hospital emergency rooms, presence of arthritis, cardiovascular or respiratory conditions, and social activity limitations. In conclusion, American adults with Long COVID, but not those who had prior COVID-19 infection without Long COVID, exhibited a higher prevalence of financial toxicity compared to individuals with common comorbidities. Vulnerable populations were at greater risk for financial toxicity. These findings emphasize the importance of evaluating strategies to reduce economic burden and increase awareness of the effect of Long COVID-related financial toxicity on patient's healthcare and health status.

Magnitude of Septic Shock and its Associated Factors Among Critically Ill COVID-19 Patients at Addis Ababa COVID-19 Care Centers, Ethiopia

Background

The coronavirus disease (COVID-19) pandemic imposed a major public health impact. Septic shock is one of the frequent complications encountered among critically ill COVID-19 patients, leading to poor healthcare outcomes. This study aimed at assessing the magnitude of septic shock and its associated factors.

Methods and materials

An institution-based cross-sectional study was conducted retrospectively on 242 randomly selected COVID-19 patients admitted to three Addis Ababa COVID-19 care centers from September 2020 to October 2021. Septic shock was defined as a Sequential Organ Failure Assessment (SOFA) score ≥2 points and persisting hypotension requiring vasopressors to maintain a mean arterial pressure of ≥65 mmHg despite adequate volume resuscitation. Variables in the bivariate analysis were fitted to multiple regression analysis to eliminate confounders and determine independent risk factors for septic shock. In the multivariable analysis, statistical significance was declared at P < .05.

Results

The prevalence of septic shock was found to be 39.3% (95% confidence interval [CI]: 33.1, 45.7). Advanced age (≥60 years) [AOR = 7.9; 95% CI: 2.3, 26.8], intensive care unit stay above 7 days [AOR = 6.2; 95%CI: 2.1, 18.7], invasive ventilation [AOR = 10; 95% CI: 3, 37], and chronic obstructive pulmonary disease (COPD) [AOR = 18; 95% CI: 7, 45] were significantly associated with increased septic shock among COVID-19 patients. Meanwhile, diabetes [AOR = 0.24; 95% CI: 0.08, 0.71] and cardiovascular diseases [AOR = 0.17; 95% CI: 0.07, 0.44] were associated with a decrease risk of septic shock.

Conclusion

The prevalence of septic shock in critically ill COVID-19 patients was high and a major concern in this study, and it is independently associated with advanced age, prolonged stay in the intensive care unit, and COPD. Based on these findings, healthcare professionals should closely monitor and manage patients with COVID-19 who have a history of COPD, are older, or prolonged intensive care unit (ICU) stays to prevent septic shock and improve patient outcomes.

A Scoping Review and Taxonomy of Epidemiological-Macroeconomic Models of COVID-19

OBJECTIVES

The COVID-19 pandemic placed significant strain on many health systems and economies. Mitigation policies decreased health impacts but had major macroeconomic impact. This article reviews models combining epidemiological and macroeconomic projections to enable policy makers to consider both macroeconomic and health objectives.

METHODS

A scoping review of epidemiological-macroeconomic models of COVID-19 was conducted, covering preprints, working articles, and journal publications. We assessed model methodologies, scope, and application to empirical data.

RESULTS

We found 80 articles modeling both the epidemiological and macroeconomic outcomes of COVID-19. Model scope is often limited to the impact of lockdown on health and total gross domestic product or aggregate consumption and to high-income countries. Just 14% of models assess disparities or poverty. Most models fall under 4 categories: compartmental-utility-maximization models, epidemiological models with stylized macroeconomic projections, epidemiological models linked to computable general equilibrium or input-output models, and epidemiological-economic agent-based models. We propose a taxonomy comparing these approaches to guide future model development.

CONCLUSIONS

The epidemiological-macroeconomic models of COVID-19 identified have varying complexity and meet different modeling needs. Priorities for future modeling include increasing developing country applications, assessing disparities and poverty, and estimating of long-run impacts. This may require better integration between epidemiologists and economists.

Household catastrophic health expenditure for COVID-19 during March-August 2021, in South India: a cross-sectional study

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic increased the utilisation of healthcare services. Such utilization could lead to higher out-of-pocket expenditure (OOPE) and catastrophic health expenditures (CHE). We estimated OOPE and the proportion of households that experienced CHE by conducting a cross-sectional survey of 1200 randomly selected confirmed COVID-19 cases.

METHODS

A cross-sectional survey was conducted by telephonic interviews of 1200 randomly selected COVID-19 patients who tested positive between 1 March and 31 August 2021. We collected household-level information on demographics, income, expenditure, insurance coverage, direct medical and non-medical costs incurred toward COVID-19 management. We estimated the proportion of CHE with a 95% confidence interval. We examined the association of household characteristics; COVID-19 cases, severity, and hospitalisation status with CHE. A multivariable logistic regression analysis was conducted to ascertain the effects of variables of interest on the likelihood that households face CHE due to COVID-19.

RESULTS

The mean (95%CI) OOPE per household was INR 122,221 (92,744-1,51,698) [US$1,643 (1,247-2,040)]. Among households, 61.7% faced OOPE, and 25.8% experienced CHE due to COVID-19. The odds of facing CHE were high among the households; with a family member over 65 years [OR = 2.89 (2.03-4.12)], with a comorbid individual [OR = 3.38 (2.41-4.75)], in the lowest income quintile [OR = 1.82 (1.12-2.95)], any member visited private hospital [OR = 11.85 (7.68-18.27)]. The odds of having CHE in a household who have received insurance claims [OR = 5.8 (2.81- 11.97)] were high. Households with one and more than one severe COVID-19 increased the risk of CHE by more than two-times and three-times respectively [AOR = 2.67 (1.27-5.58); AOR = 3.18 (1.49-6.81)].

CONCLUSION

COVID-19 severity increases household OOPE and CHE. Strengthening the public healthcare and health insurance with higher health financing is indispensable for financial risk protection of households with severe COVID-19 from CHE.