Economic Burden of COVID-19 Hospitalization in Almaty, Kazakhstan

ClinicoEconomics and Outcomes Research, 2026

Полный текст Открытый доступ: Gold Метаданные (CSL-JSON)
DOI 10.2147/ceor.s569792
Достоверность данных 70 средняя
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Аннотация

Background: The COVID-19 pandemic has caused substantial health and economic impacts worldwide. However, evidence on the economic burden of COVID-19 hospitalizations in Central Asia remains limited. This study aims to estimate the economic burden of COVID-19 hospitalizations in the Almaty metropolitan area from both healthcare system and societal perspectives between 2020 and 2022. Methods: Administrative hospital data were used to analyze all COVID-19 hospitalizations in Almaty during 2020-2022. Direct medical costs were estimated from the healthcare system perspective using standardized reimbursement tariffs from Kazakhstan's Mandatory Social Health Insurance system. Indirect costs were estimated from a societal perspective using the human capital approach to quantify productivity losses due to hospitalization, recovery, and premature mortality. Sensitivity analyzes the effects of variations in wage levels, discount rates, and medical costs. Results: Older adults (≥65 years) experienced the highest burden of severe outcomes, accounting for the largest share of ICU admissions and deaths. The number of hospitalized patients increased sharply in 2021, accompanied by longer hospital stays and higher healthcare resource utilization. The total economic burden peaked in 2021 at $258.0 million, driven by increased hospitalizations, ICU utilization, and productivity losses associated with hospitalization, recovery, and premature mortality. Sensitivity analysis showed that overall cost estimates were robust to variations in discount rates, while wage assumptions moderately influenced indirect cost estimates. Conclusion: COVID-19 hospitalizations impose a substantial economic burden on both the healthcare system and society in Almaty, particularly during the 2021 pandemic peak. Strengthening early public health interventions and improving real-time health data systems may help optimize resource allocation and enhance preparedness for future health crises.