Cost Effectiveness and Budget Impact Analyses of Influenza Vaccination for Prisoners in Thailand: An Application of System Dynamic Modelling

Influenza outbreaks in Thai prisons were increasing in number every year and to address this, the Thai Ministry of Public Health (MOPH) initiated a policy to promote vaccination for prisoners. The objective of this study was to assess the cost effectiveness and budget impact of the influenza vaccination policy for prisoners in Thailand. The study obtained data from the Division of Epidemiology, Department of Disease Control (DDC), MOPH. Deterministic system dynamic modelling was exercised to estimate the financial implication of the vaccination programme in comparison with routine outbreak control. The incremental cost-effectiveness ratio (ICER) was calculated via a DDC perspective. The reproductive number was estimated at 1.4. A total of 143 prisons across the country (375,763 prisoners) were analysed. In non-vaccination circumstances, the total healthcare cost amounted to 174.8 million Baht (US$5.6 million). Should all prisoners be vaccinated, the total healthcare cost would reduce to 90.9 million Baht (US$ 2.9 million), and 46.8 million Baht (US$1.5 million) of this is related to the vaccination. The ICER of vaccination (compared with routine outbreak control) varied between 39,738.0 to 61,688.3 Baht per disability-adjusted life year (DALY) averted (US$ 1281.9–1989.9). Should the vaccination cover 30% of the prisoners, the ICER would be equal to 46,866.8 Baht (US$1511.8) per DALY averted with the budget burden amounted to Baht (US$ 4.8 million). The vaccination programme would become more cost-effective if the routine outbreak control was intensified. In summary, the vaccination programme was a cost-effective measure to halt influenza outbreak amongst prisoners. Further primary studies that aim to assess the actual impact of the programme are recommended

Sensitivity of contact-tracing for Covid-19 in Thailand: a capture-recapture application

BackgroundWe investigate the completeness of contact tracing for COVID-19 during the first wave of the COVID-19 pandemic in Thailand, from early January 2020 to 30 June 2020.MethodsUni-list capture-recapture models were applied to the frequency distributions of index cases to inform two questions: (1) the unobserved number of index cases with contacts, and (2) the unobserved number of index cases with secondary cases among their contacts.ResultsGeneralized linear models (using Poisson and logistic families) did not return any significant predictor (age, sex, nationality, number of contacts per case) on the risk of transmission and hence capture-recapture models did not adjust for observed heterogeneity. Best fitting models, a zero truncated negative binomial for question 1 and zero-truncated Poisson for question 2, returned sensitivity estimates for contact tracing performance of 77.6% (95% CI = 73.75–81.54%) and 67.6% (95% CI = 53.84–81.38%), respectively. A zero-inflated negative binomial model on the distribution of index cases with secondary cases allowed the estimation of the effective reproduction number at 0.14 (95% CI = 0.09–0.22), and the overdispersion parameter at 0.1.ConclusionCompleteness of COVID-19 contact tracing in Thailand during the first wave appeared moderate, with around 67% of infectious transmission chains detected. Overdispersion was present suggesting that most of the index cases did not result in infectious transmission chains and the majority of transmission events stemmed from a small proportion of index cases