A system dynamics modelling simulation based on a cohort of hepatitis B epidemic research in east China community

A system dynamics model of the COVID-19 pandemic considering risk perception: A case study of Iran

The new coronavirus disease 2019 (COVID-19) has become a complex issue around the world. As the disease advancing and death rates are continuously increasing, governments are trying to control the situation by implementing different response policies. In order to implement appropriate policies, we need to consider the behavior of the people. Risk perception (RP) is a critical component in many health behavior change theories studies. People's RP can shape their behavior. This research presents a system dynamics (SD) model of the COVID-19 outbreak considering RP. The proposed model considers effective factors on RP, including different media types, awareness, and public acceptable death rate. In addition, the simplifying assumption of permanent immunity due to infection has been eliminated, and reinfection is considered; thus, different waves of the pandemic have been simulated. Using the presented model, the trend of advancing and death rates due to the COVID-19 pandemic in Iran can be predicted. Some policies are proposed for pandemic management. Policies are categorized as the capacity of hospitals, preventive behaviors, and accepted death rate. The results show that the proposed policies are effective. In this case, reducing the accepted death rate was the most effective policy to manage the pandemics. About 20% reduction in the accepted death rate causes about 23% reduction in cumulative death and delays at epidemic peak. The mean daily error in predicting the death rate is less than 10%.

Evaluation of the effect of enhanced immunization in adults: A cross-sectional study in the southeast city of China

The efficacy of hepatitis B vaccination in adults was evaluated by comparison of the positive seroprotection rates and the hepatitis B surface antibody (anti-HBs) geometric mean titers (GMTs) between intensive intervention areas and non-intensive intervention areas after 8 years post-vaccination in the Zhejiang province. Seven cities (towns) in Zhejiang province were selected as intensive intervention areas, and adults in the demonstration areas receive hepatitis B vaccine voluntarily and for free. Other areas were non-intensive intervention areas. A total of 3587 participants received the full vaccination course (three doses), and blood samples were withdrawn 8 years after the first vaccination comprised the immunized group, and 2000 participants constituted the control group. The anti-HBs positive seroprotection rates of the immunized and control groups were 65.0% and 53.0%, respectively. The anti-HBs GMT of the subjects in the immunized group was 26.30 mIU/mL compared to 9.33 mIU/mL in the control group (P < .001). Significant differences were detected in the 24-35-, 36-45-, and 46-55-year-old subgroups in the positive seroprotection rates and the anti-HBs GMTs (P < .001) between the immunized and control groups. Moreover, significant differences were found in the anti-HBs GMT in the 46-55-year-old subgroup between the two groups (P = .02), while no differences were observed in the positive seroprotection rate (P = .428). In conclusion, adults who did not receive the hepatitis B vaccine in infancy and had negative serological markers of hepatitis B, especially adults <47-years-old, need vaccination.

Cost-Effectiveness of Hepatitis B Mass Screening and Management in High-Prevalent Rural China: A Model Study From 2020 to 2049

BACKGROUND

Chronic hepatitis B (CHB) is highly prevalent among adults in rural China and better management of those populations is of vital importance for viral hepatitis elimination. Adult immunization has been the subject of much controversy in previous studies. This study estimates the cost-effectiveness of population-based hepatitis B screening, treatment, and immunization strategy (comprehensive strategy) in rural areas with high prevalence under the national policy of sharp-drop drug prices.

METHODS

We constructed a Markov model comparing 4 strategies in a 30-year horizon from the healthcare payer perspective: (1) the conventional pattern; (2) screening and treating infected (treatment); (3) screening and immunizing susceptible individuals (immunization); and (4) the comprehensive strategy. Screening intensity ranged from 50% to 100%. Outcomes were measured by costs, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and clinical outcomes.

RESULTS

The costs for the conventional pattern, treatment strategy, immunization strategy, and comprehensive strategy were US$ 341, 351, 318, and 323, respectively. In addition, effects were 17.45, 17.57, 17.46, and 17.58 QALYs, respectively. The ICER of the comprehensive strategy was US$ 35/QALY gained at 50% screening intensity and 420 US$/QALY gained at 100%. The net monetary benefit increased with increasing screening intensity and declined after 90%, with the highest value of US$40 693. All new infections and 52.5% mortality could be avoided from 2020 to 2049 if all patients were properly treated and all susceptible individuals were immunized. The results were stable within a wide range of parameters.

CONCLUSION

It was cost-effective to implement the mass hepatitis B screening, treatment, and immunization strategy in areas of rural China with high prevalence, and the strategy gained the most net monetary benefit at a screening intensity of 90%. Although it was impractical to fulfill 100% coverage, efforts should be made to obtain more people screened.

Population-based screening of newborns: Findings from the newborn screening expansion study (part two)

Rapid advances in genomic technologies to screen, diagnose, and treat newborns will significantly increase the number of conditions in newborn screening (NBS). We previously identified four factors that delay and/or complicate NBS expansion: 1) variability in screening panels persists; 2) the short duration of pilots limits information about interventions and health outcomes; 3) recent recommended uniform screening panel (RUSP) additions are expanding the definition of NBS; and 4) the RUSP nomination and evidence review process has capacity constraints. In this paper, we developed a use case for each factor and suggested how model(s) could be used to evaluate changes and improvements. The literature on models was reviewed from a range of disciplines including system sciences, management, artificial intelligence, and machine learning. The results from our analysis highlighted that there is at least one model which could be applied to each of the four factors that has delayed and/or complicate NBS expansion. In conclusion, our paper supports the use of modeling to address the four challenges in the expansion of NBS.

System dynamic modelling of healthcare associated influenza -a tool for infection control

BACKGROUND

The transmission dynamics of influenza virus within healthcare settings are not fully understood. Capturing the interplay between host, viral and environmental factors is difficult using conventional research methods. Instead, system dynamic modelling may be used to illustrate the complex scenarios including non-linear relationships and multiple interactions which occur within hospitals during a seasonal influenza epidemic. We developed such a model intended as a support for health-care providers in identifying potentially effective control strategies to prevent influenza transmission.

METHODS

By using computer simulation software, we constructed a system dynamic model to illustrate transmission dynamics within a large acute-care hospital. We used local real-world clinical and epidemiological data collected during the season 2016/17, as well as data from the national surveillance programs and relevant publications to form the basic structure of the model. Multiple stepwise simulations were performed to identify the relative effectiveness of various control strategies and to produce estimates of the accumulated number of healthcare-associated influenza cases per season.

RESULTS

Scenarios regarding the number of patients exposed for influenza virus by shared room and the extent of antiviral prophylaxis and treatment were investigated in relation to estimations of influenza vaccine coverage, vaccine effectiveness and inflow of patients with influenza. In total, 680 simulations were performed, of which each one resulted in an estimated number per season. The most effective preventive measure identified by our model was administration of antiviral prophylaxis to exposed patients followed by reducing the number of patients receiving care in shared rooms.

CONCLUSIONS

This study presents an system dynamic model that can be used to capture the complex dynamics of in-hospital transmission of viral infections and identify potentially effective interventions to prevent healthcare-associated influenza infections. Our simulations identified antiviral prophylaxis as the most effective way to control in-hospital influenza transmission.