Hospitalization Costs of COVID-19 Cases and Their Associated Factors in Guangdong, China: A Cross-Sectional Study

Cost of illness studies in COVID-19: a scoping review

BACKGROUND

Human communities suffered a vast socioeconomic burden in dealing with the pandemic of coronavirus disease 2019 (COVID-19) globally. Real-word data about these burdens can inform governments about evidence-based resource allocation and prioritization. The aim of this scoping review was to map the cost-of-illness (CoI) studies associated with COVID-19.

METHODS

This scoping review was conducted from January 2019 to December 2021. We searched cost-of-illness papers published in English within Web of Sciences, PubMed, Google Scholar, Scopus, Science Direct and ProQuest. For each eligible study, extracted data included country, publication year, study period, study design, epidemiological approach, costing method, cost type, cost identification, sensitivity analysis, estimated unit cost and national burden. All of the analyses were applied in Excel software.

RESULTS

2352 records were found after the search strategy application, finally 28 articles met the inclusion criteria and were included in the review. Most of the studies were done in the United States, Turkey, and China. The prevalence-based approach was the most common in the studies, and most of studies also used Hospital Information System data (HIS). There were noticeable differences in the costing methods and the cost identification. The average cost of hospitalization per patient per day ranged from 101$ in Turkey to 2,364$ in the United States. Among the studies, 82.1% estimated particularly direct medical costs, 3.6% only indirect costs, and 14.3% both direct and indirect costs.

CONCLUSION

The economic burden of COVID-19 varies from country to country. The majority of CoI studies estimated direct medical costs associated with COVID-19 and there is a paucity of evidence for direct non-medical, indirect, and intangible costs, which we recommend for future studies. To create homogeneity in CoI studies, we suggest researchers follow a conceptual framework and critical appraisal checklist of cost-of-illness (CoI) studies.

Assessment of hospitalisation costs and their determinants among Covid-19 patients in South Central Ethiopia

BACKGROUND

The coronavirus disease 2019 (Covid-19) pandemic is a global public health problem. The Covid-19 pandemic has had a substantial impact on the economy of developing countries, including Ethiopia.This study aimed to determine the hospitalisation costs of Covid-19 and the factors associated with the high cost of hospitalisation in South Central Ethiopia.

METHODS

A retrospective cost analysis of Covid-19 patients hospitalised between July 2020 and July 2021 at Bokoji Hospital Covid-19 Treatment Centre was conducted using both the micro-costing and top-down approaches from the health system perspective. This analysis used cost data obtained from administrative reports, the financial reports of the treatment centre, procurement invoices and the Covid-19 standard treatment guidelines. The Student's t-test, Mann-Whitney U test or Kruskal-Wallis test was employed to test the difference between sociodemographic and clinical factors when appropriate.To identify the determinants of cost drivers in the study population, a generalised linear model with gamma distribution and log link with a stepwise algorithm were used.

RESULTS

A total of 692 Covid-19 patients were included in the costing analysis. In this study, the mean cost of Covid-19-infected patients with no symptoms was US$1,073.86, with mild symptoms US$1,100.74, with moderate symptoms US$1,394.74 and in severe-critically ill condition US$1,708.05.The overall mean cost was US$1,382.50(95% CI: 1,360.60-1,404.40) per treated episode.The highest mean cost was observed for personnel, accounting for 64.0% of the overall cost. Older age, pre-existing diseases, advanced disease severity at admission, admission to the intensive care unit, prolonged stay on treatment and intranasal oxygen support were strongly associated with higher costs.

CONCLUSIONS

This study found that the clinical management of Covid-19 patients incurred significant expenses to the health system. Factors such as older age, disease severity, presence of comorbidities, use of inhalation oxygen therapy and prolonged hospital stay were associated with higher hospitalisation costs.Therefore, the government should give priority to the elderly and those with comorbidities in the provision of vaccination to reduce the financial burden on health facilities and health systems in terms of resource utilisation.

An optimal control model for Covid-19 spread with impacts of vaccination and facemask

A non-linear system of differential equations was used to explain the spread of the COVID-19 virus and a SEIQR model was developed and tested to provide insights into the spread of the pandemic. This article, which is related to the aforementioned work as well as other work covering variations of SIR models, Hermite Wavelets Transform, and also the Generalized Compartmental COVID-19 model, we develop a mathematical control model and apply it to represent optimal vaccination strategy against COVID-19 using Pontryagin's Maximum Principle and also factoring in the effect of facemasks on the spread of the virus. As background work, we analyze the mathematical epidemiology model with the facemask effect on both reproduction number and stability, we also analyze the difference between confirmed COVID-19 cases of the Quarantine class and anonymous cases of the Infectious class that is expected to recover. We also apply control theory to mine insights for effective virus spread prevention strategies. Our models are validated using Matlab mathematical model validation tools. Statistical tests against data from Jordan are used to validate our work including the modeling of the relation between the facemask effect and COVID-19 spread. Furthermore, the relation between control measure ξ, cost, and Infected cases is also studied.

Proposing a New Conceptual Syndemic Framework for COVID-19 Vaccine Hesitancy: A Narrative Review

BACKGROUND

Discussions regarding syndemics have dominated research in recent years. Vaccine hesitancy has also been propelled to the forefront. In this narrative review, we aim to frame a novel syndemic framework to understand the interaction between vaccine hesitancy, COVID-19, and negative health outcomes.

METHODS

A non-systematic electronic search was conducted in PubMed and Google Scholar. Search criteria were limited to articles published between November 2019 and June 2022. Articles related to the COVID-19 syndemic and vaccine hesitancy were included.

RESULTS

Our review revealed that the adherence to COVID-19 regulations-although they were effective in preventing COVID-19 transmission, cases, and deaths-created a dynamically unstable 'vicious cycle' between undesirable health, economic, and social outcomes. The "accumulation" of complex stressors decreased individuals' cognitive flexibility and hindered them from making decisions and getting vaccinated. Furthermore, it increased individuals' risk of acquiring COVID-19, losing their employment, increasing poverty, and decreasing healthcare utilization. We illustrated how the amalgamation of sociodemographic and contextual factors associated with COVID-19 might impact people's vaccine decisions, making them more hesitant toward COVID-19 vaccination. Failing to receive vaccinations increases the chances of COVID-19 transmission, hospitalization, and other negative health outcomes.

CONCLUSIONS

Understanding the interaction between these factors is essential to provide policymakers with inspiration to set appropriate interventions for promoting COVID-19 vaccination acceptance to decrease the overall burden of pandemics.

Healthcare resource use and associated costs in a cohort of hospitalized COVID-19 patients in Spain: A retrospective analysis from the first to the third pandemic wave. EPICOV study

OBJECTIVES

Describe healthcare resource use and costs per hospitalized coronavirus disease-2019 (COVID-19) patient during the three main outbreak waves.

METHODS

A retrospective observational study. COVID-19 patient data were collected from a dataset from 17 hospitals in the HM Hospitals Group. Mean total costs per hospitalized patient and per day were estimated in each wave, as defined by the Spanish National Health System perspective. In addition, costs were estimated for both patients admitted and those not admitted to the intensive care unit (ICU) and were stratified by age groups.

RESULTS

A total of 3756 COVID-19 patients were included: 2279 (60.7%) for the first, 740 (19.7%) for the second, and 737 (19.6%) for the and third wave. Most (around 90%) did not require ICU treatment. For those patients, mean ± SD cost per patient ranged from €10 196.1 ± €7237.2 (mean length of stay [LOS] ± SD: 9.7 ± 6.2 days) for the second wave to €9364.5 ± €6321.1 for the third wave (mean 9.0 ± 5.7 days). Mean costs were around €1000 per day for all the waves. For patients admitted to the ICU, cost per patient ranged from €81 332.5 ± €63 725.8 (mean 31.0 ± 26.3 days) for the second wave to €36 952.1 ± €24 809.2 (mean 15.7 ± 8.2 days) for the third wave. Mean costs per day were around €3000 for all the waves. When estimated by age, mean LOS and costs were greater in patients over 80 when not admitted to the ICU and for patients aged 60 to 79 when admitted to the ICU.

CONCLUSIONS

LOS was longer for patients admitted to the ICU (especially in the first two waves) and for older patients in our study cohort; these populations incurred the highest hospitalization costs.

Efficacy and safety of chinese herbal medicine for treating mild or moderate COVID-19: A systematic review and meta-analysis of randomized controlled trials and observational studies

Background: The coronavirus disease 2019 (COVID-19) is still a pandemic globally, about 80% of patients infected with COVID-19 were mild and moderate. Chinese herbal medicine (CHM) has played a positive role in the treatment of COVID-19, with a certain number of primary studies focused on CHM in managing COVID-19 published. This study aims to systematically review the currently published randomized controlled trials (RCTs) and observational studies (OBs), and summarize the effectiveness and safety of CHM in the treatment of mild/moderate COVID-19 patients.

Methods: We searched 9 databases up to 19 March 2022. Pairs of reviewers independently screened literature, extracted data and assessed risk of bias. For overall effect, we calculated the absolute risk difference (ARD) of weighted averages of different estimates, and certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system.

Results: We included 35 RCTs and 24 OBs enrolling 16,580 mild/moderate patients. The certainty of evidence was very low to low. Compared with usual supportive treatments, most effect estimates of CHM treatments were consistent in direction. CHMs presented significant benefits in reducing rate of conversion to severe cases (ARD = 99 less per 1000 patients in RCTs and 131 less per 1000 patients in OBs, baseline risk: 16.52%) and mortality (ARD = 3 less per 1000 patients in RCTs and OBs, baseline risk: 0.40%); shortening time to symptom resolution (3.35 days in RCTs and 2.94 days in OBs), length of hospital stay (2.36 days in RCTs and 2.12 days in OBs) and time to viral clearance (2.64 days in RCTs and 4.46 days in OBs); increasing rate of nucleic acid conversion (ARD = 73 more per 1000 patients in OBs, baseline risk: 16.30%). No serious adverse reactions were found and the differences between CHM and usual supportive care were insignificant.

Conclusion: Encouraging evidence showed that CHMs were beneficial in treating mild or moderate patients. CHMs have been proved to possess a safety profile that is comparable to that of usual supportive treatment alone. More rigorously designed clinical trials and mechanism studies are still warranted to further confirm the present findings.

Determinants of Hospitalization Costs among Moderate Cases of COVID-19

Objective: To estimate demographic predictors of medical expense in hospitalization of moderate COVID-19. Methods: From January to March 2020, a total of 39 patients were treated and recovered from COVID-19 in a tertiary medical center in East China. Detailed cost data were collected and we estimated the demographic predictors of both total hospital expense and daily hospital expense. Results: The mean medical expense for treating hospitalized moderate COVID-19 cases was $1177.81. Every additional year in the patient’s age corresponds to .9% more in total hospital expense (Coef. = 0.009, 95% CI 0.002-0.017, P < 0.01). The difference in daily medical expense between age groups was not statistically significant. Conclusions: Hospitalization cost was significantly elevated among the older patients, and the age effect in cost was mainly driven by the longer length of stay in the hospital. From a cost-saving perspective, the elderly population might deserve priority consideration when COVID-19 vaccination programs are implemented.

COVID-19 in Multimorbid Patients-A Controlled Microcost Description Analysis of Diagnosis Related Group (DRG)-Case Series in Acute Care without Non-Invasive Ventilation

Diagnosis-related cost analyzes are important for health economic planning and decision-making. They form the basis for further developing of remuneration systems for health services. The rapid increase in hospital stays by COVID-19 patients requires a valid and exact calculation of the treatment costs. COVID-19 patients with many accompanying illnesses increase the requirements for a cost calculation. The focus of this work is to carry out a DRG-related micro-cost analysis, considering the age, length of stay and comorbidities of COVID-19 patients. So far, there is little information about treatment costs for multimorbid patients with COVID-19 who have not received invasive ventilation. The method is based on a standardized cost unit calculation for determining the treatment costs in a German hospital. The costs (€) of inpatients treated with COVID-19 were compared with a control group of the same DRGs of patients without COVID-19. The average total costs for inpatient treatment were €2866. The highest share of costs falls on nursing, personnel, and material costs of the non-medical infrastructure. Frequent comorbidities were heart failure, diabetes mellitus, other respiratory diseases, dizziness, and impairment of the musculoskeletal system.