Pard Teekasap

The COVID-19 booster immunization policy is cost-effective, but evidence on additional booster doses and appropriate strategies is scarce. This research compared the cost-effectiveness of annual, twice-a-year, and biennial booster dose policies. We performed stochastic modeling using compartmental susceptible-exposed-infectious-recovered models and a system dynamic model. We evaluated four policy scenarios: (1) hypothetical no-booster immunization policy; (2) twice-a-year vaccination policy; (3) annual vaccination policy; and (4) biennial vaccination policy. In addition, we conducted a one-way sensitivity analysis by adjusting R0 from 1.8 to 3.0 in all scenarios (epidemic stage) and by decreasing the vaccination cost by 50% at the end of the first year to reflect the current policy direction to enhance domestic vaccine production. Compared to non-booster policies, all three booster strategies reduced the number of cases, hospital admissions, and severe infections remarkably. Without a booster, total cases would reach 16,220,615 (95% confidence interval [CI] 6,726,550–29,661,112) by day 1,460, whereas, with a twice-a-year booster, the total cases would reach 597,901 (95% CI 526,230–694,458) in the same period. Even though the no booster scenario exhibited the lowest cost by approximately the first 500 days, by day 1,460 the biennial booster scenario demonstrated the lowest cost at 72.0 billion baht (95% CI 68.6–79.4 billion). The most cost-saving policy was the biennial booster scenario. The annual booster scenario also stood as a cost-effective option for most outcomes. In the epidemic stage and in an assumption where the vaccination costs dropped, all booster policies became more cost-effective or cost-saving compared with the main assumption. This study underscores the significance of the COVID-19 vaccine booster policy. Implementing policies should take into consideration cost-effectiveness, feasibility, and public communication.

Economic development must occur alongside environmental sustainability. The circular economy (CE) in an industrial context is a critical area that has been widely studied. However, the scope of the CE is broad and involves the development of various fields, ranging from energy and production to digitalization. The areas targeted for CE development also vary according to the stage of economic development. This study focuses on identifying the potential for CE development from the perspective of developing economies by using patent and bibliometric analyses.

Thailand is among many countries severely affected by COVID-19 since the beginning of the global pandemic. Thus, a deliberate planning of health care resource allocation against health care demand in light of the new SARS-CoV-2 variant, Omicron, is crucial. This study aims to forecast the trends in COVID-19 cases and deaths from the Omicron variant in Thailand. We used a compartmental susceptible-exposed-infectious-recovered model combined with a system dynamics model. We developed four scenarios with differing values of the reproduction number (R) and vaccination rates. In the most pessimistic scenario (R = 7.5 and base vaccination rate), the number of incident cases reached a peak of 49,523 (95% CI: 20,599 to 99,362) by day 73, and the peak daily deaths grew to 270 by day 50. The predicted cumulative cases and deaths at the end of the wave were approximately 3.7 million and 22,000, respectively. In the most optimistic assumption (R = 4.5 and speedy vaccination rate), the peak incident cases was about one third the cases in the pessimistic assumption (15,650, 95% CI: 12,688 to 17,603). In the coming months, Thailand may face a new wave of the COVID-19 epidemic due to the Omicron variant. The case toll due to the Omicron wave is likely to outnumber the earlier Delta wave, but the death toll is proportionately lower. Vaccination campaigns for the booster dose should be expedited to prevent severe illnesses and deaths in the population.

Background The introduction of the Omicron variant is of significant concern to the Thai Government due to the possibility of a new wave of the COVID-19 epidemic, which may cause a huge strain to the country’s health system. This study aims to forecast the trends of COVID-19 cases and deaths given the advent of the Omicron variant in Thailand. Methods We used a compartmental susceptible-exposed-infectious-recovered model in combination with a system dynamics model. We developed four scenarios according to differing values of the production number (R) and varying vaccination rates. Results The findings indicated that in the most pessimistic scenario (R = 7.5 and base vaccination rate), the number of incident cases reached a peak of 49,523 (95% CI: 20,599 to 99,362) by day 73 and the peak daily deaths enlarged to 270 by day 50 (95% CI: 124 to 520). The predicted cumulative cases and deaths at the end of the wave (day 120) were approximately 3.7 million and 22,000 respectively. In the most optimistic assumption (with R = 4.5 and a speedy vaccination rate [tripled the base rate]), the peak of the incident cases was about one third of the most pessimistic assumption (15,650, 95% CI: 12,688 to 17,603). The corresponding daily fatalities were 72 (95% CI: 54 to 84) and the prevalent intubated cases numbered 572 (95% CI: 429 to 675). Conclusions In the coming months, Thailand may face a new wave of the COVID-19 epidemic due to the Omicron variant. The case toll due to the Omicron wave is likely to outnumber the earlier Delta wave, but the death toll is proportionately lower. Despite the immune-escape characteristic of the Omicron variant, the vaccination campaign for the booster dose should be expedited as an effective way of preventing severe illness and death.

Background: Thailand experienced the first wave of Coronavirus Disease 2019 (COVID-19) during March–May 2020 and has been facing the second wave since December 2020. The area facing the greatest impact was Samut Sakhon, a main migrant-receiving province in the country. The Department of Disease Control (DDC) of the Thai Ministry of Public Health (MOPH) considered initiating a vaccination strategy in combination with active case finding (ACF) in the epidemic area. The DDC commissioned a research team to predict the impact of various vaccination and ACF policy scenarios in terms of case reduction and deaths averted, which is the objective of this study. Methods: The design of this study was a secondary analysis of quantitative data. Most of the data were obtained from the DDC, MOPH. Deterministic system dynamics and compartmental models were exercised. A basic reproductive number (R₀) was estimated at 3 from the beginning. Vaccine efficacy against disease transmission was assumed to be 50%. A total of 10,000 people were estimated as an initial population size. Results: The findings showed that the greater the vaccination coverage, the smaller the size of incident and cumulative cases. Compared with a no-vaccination and no-ACF scenario, the 90%-vaccination coverage combined with 90%-ACF coverage contributed to a reduction of cumulative cases by 33%. The case reduction benefit would be greater when R₀ was smaller (∼ 53% and ∼ 51% when R₀ equated 2 and 1.5, respectively). Conclusion: This study reaffirmed the idea that a combination of vaccination and ACF measures contributed to favourable results in reducing the number of COVID-19 cases and deaths, relative to the implementation of only a single measure. The greater the vaccination and ACF coverage, the greater the volume of cases saved. Though we demonstrated the benefit of vaccination strategies in this setting, actual implementation should consider many more policy angles, such as social acceptability, cost-effectiveness and operational feasibility. Further studies that address these topics based on empirical evidence are of great value.

Thailand has become a popular destination for international migrant workers, particularly from Cambodia, Lao PDR, and Myanmar. However, only a fraction of these migrant workers were insured by public health insurance. The objective of this study was to apply systems thinking to explore contextual factors affecting access to public health insurance among cross-border migrants in Thailand. A group model building approach was applied. Participants (n = 20) were encouraged to share ideas about underlying drivers and barriers of migrants’ access to health insurance. The causal loop diagram and stock and flow diagram were synthesised to identify the dynamics of access to migrant health insurance. Results showed that nationality verification is an important mechanism to deal with the precarious citizenship status of undocumented migrants. However, some migrants are still left uninsured. The likely explanations are the semi-voluntary nature of the Health Insurance Card Scheme, administrative delay of the enrollment process, and resistance of some employers to hiring migrants. As a result, findings suggest that effective communication is required to raise acceptance towards insurance among migrants and their employers. A participatory public policy process is needed to create a good balance of migrant policies among diverse authorities.

The economic benefits of the circular economy policy are understudied. This paper shed light on the economic benefits of a circular economy in countries without resource scarcity problem. System dynamics method was used to overcome the data limitation problem. The results show that, although the investment cost is significant, countries will gain economic benefits in term of lower raw material costs in a long run. Because of that, products are accessible by a larger group which results in a higher sale volume.

There is a long debate whether the IT investment can stimulate firm performance. This paper aims to shed more light on this issue by developing a mathematical simulation model that is based on the reasons from different schools of thought. The results show that both schools of though are correct in different situation. In an early era, superior IT infrastructure can create a better firm performance because it can differentiate the IT leaders from others. However, in a long run, other firms are aware of benefits from IT investment so they invest more on IT projects. IT outsourcers and consultants also gain more experience from working in multiple projects which make the IT cost lower. Therefore, in a long run, IT investment does not drive a firm performance.

This paper studies the relationship between technology spillover from foreign direct investment (FDI) and productivity growth through the development of a dynamic model. The model has been developed based on the feedback numerical simulation approach. The variables included in the model are productivity, gross domestic product (GDP), GDP per capita, FDI, employment and gross fixed capital formation (GFCF). The model has been applied to the Thailand context as a case study. The results show that increase in technology spillover can gradually increase the productivity of the country and the GDP per capita. Higher GDP per capita will attract more FDI into the country but with a significant delay. When the unemployment rate is low, reducing technology spillover can increase the unemployment rate but more technology spillover does not reduce the unemployment rate.