[Development of Markov models for economics evaluation of strategies on hepatitis B vaccination and population-based antiviral treatment in China]

Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model

OBJECTIVE

It aimed to analyze the epidemic situation of new coronary pneumonia (COVID-19) based on the epidemiological Markov model, and to study the clinical risk factors of the patients based on the patient's cardinal data and clinical symptoms.

METHODS

A total of 500 patients with COVID-19 diagnosed by nucleic acid testing in the X hospital from January 2020 to May 2020 were collected. According to the severity of the disease, they were classified into general group (200 cases) and acute critical group (300 cases). Markov model to predict the number of COVID-19 infections was constructed. Patient's general information, clinical characteristics, and prevention methods were analyzed.

RESULTS

According to Markov model statistics, the developmental expected stay time of patients infected with COVID-19 was 14 days. 2. The two groups of patients had statistically considerable differences in complications such as gender, age, hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia (P < 0.05). 3. Logistic multivariate regression analysis showed that the clinical risk factors for patients with COVID-19 mainly included the patient's gender, age, whether they were associated with hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia.

CONCLUSION

Markov model can be utilized to judge the time course of the COVID-19 in various development states. In addition, the COVID-19 spread rapidly and is extremely harmful. Clinically, through active prevention, the treatment effect can be improved, the patient's respiratory function, and the quality of life can also be improved.

Cost-effectiveness of couple-based immunization strategy to prevent mother-to-child transmission of hepatitis B virus in China: A decision-analytic Markov model

BACKGROUND

Mother-to-child transmission (MTCT) is the major route of HBV transmission in many parts of the world. We designed couple-based immunization strategy and aimed to assess the cost-effectiveness of this strategy in China.

METHODS

We constructed a decision-analytic Markov model to compared current immunization strategy consisting of hepatitis B vaccination (HepB) for all infants and extra hepatitis B immunoglobulin for infants with HBsAg-positive mothers versus couple-based immunization strategy including additional HBV screening for pre-pregnant couples and HepB for high-risk wives. Costs were assessed from a healthcare system perspective. Number of infants with perinatal HBV infection, life-years (LYs), quality-adjusted life-years (QALYs), and disability-adjusted life-years (DALYs) were used to access effects. We calculated incremental cost-effectiveness ratios (ICERs) and performed sensitivity analysis.

FINDINGS

Based on the birth cohort of 17,578,815 livebirths in China in 2017, couple-based immunization strategy reduced perinatal HBV infection by 18% (9194/51,365) with cost increase of ¥ 41 million, saved 49,986 LYs (ICER: ¥819 per LY saved), gained 48,879 QALYs (ICER: ¥837 per QALY gained) and averted 63,362 DALYs (¥646 per DALY averted) compared with current immunization strategy. These ICERs were below willingness-to-pay levels of China's once GDP per capita (¥59,660), remaining robust in sensitivity analysis.

INTERPRETATION

Under the intermediate endemic of HBV infection in China, implementation of couple-based immunization strategy can improve the efficiency of preventing MTCT of HBV, and is highly cost-effective. This strategy can be a new immunization strategy choice to achieve the target of eliminating hepatitis B by 2030.

FUNDING

National Natural Science Foundation of China.