Cost-Effectiveness Analysis of COVID-19 Vaccine Booster Dose in the Thai Setting during the Period of Omicron Variant Predominance.

The Thai government implemented COVID-19 booster vaccines to prevent morbidity and mortality during the spreading of the Omicron variant. However, little is known about which types of vaccine should be invested in as the booster dose for the Thai population. This study aims to investigate the most cost-effective COVID-19 vaccine for a booster shot as empirical evidence for Thai policymakers. This study applied a stochastic simulation based on a compartmental susceptible-exposed-infectious-recovered model and included system dynamics in the model. We evaluated three scenarios: (1) No booster, (2) A viral vector vaccine as the booster dose, (3) An mRNA vaccine as the booster dose. The incremental cost-effectiveness ratio (ICER) was calculated based on provider perspectives. We found the number of cases in scenarios with viral vector and mRNA booster doses to be lower than in the non-booster group. Likewise, the number of deaths in the viral vector and the mRNA booster scenarios was threefold lower than in the no-booster scenario. Moreover, the estimated grand cost for the no-booster scenario was over 100 billion baht, while viral vector and mRNA scenario costs were 70 and 64.7 billion baht, respectively. ICER shows that viral vector and mRNA scenarios are more cost-effective than the no-booster scenario. Viral vector booster shot appeared to be slightly more cost-effective than mRNA booster shot in terms of death aversion. However, being boosted by an mRNA vaccine seemed slightly more cost-effective than a viral vector vaccine concerning case aversion. In conclusion, policies to promote COVID-19 booster shots in the Thai population by either mRNA or viral vector vaccines are likely to be worthwhile for both economic and public health reasons.

Real-World Effectiveness of COVID-19 Vaccines against Severe Outcomes during the Period of Omicron Predominance in Thailand: A Test-Negative Nationwide Case-Control Study.

Due to the widespread Omicron variant of SARS-CoV-2 in Thailand, the effectiveness of COVID-19 vaccines has become a major issue. The primary objective of this study is to examine the real-world effectiveness of COVID-19 vaccines based on secondary data acquired under normal circumstances in a real-world setting, to protect against treatment with invasive ventilation of pneumonia during January to April 2022, a period when Omicron was predominant. We conducted a nationwide test-negative case-control study. The case and control were matched with a ratio of 1:4 in terms of age, date of specimen collection, and hospital collection specimen and the odds ratio was calculated using conditional logistic regression. Overall, there was neither a distinction between mix-and-match regimens and homologous mRNA regimens against severe symptoms, nor was there a decline of the protective effect over the study period. The third and fourth dose boosters with ChAdOx1 nCoV-19 or mRNA vaccines provided high levels of protection against severe outcomes, approximately 87% to 100%, whereas two doses provided a moderate degree (70%). Thus, this study concludes that current national vaccine strategies provide favourable protective benefits against the Omicron variant. All Thais should receive at least two doses, while high-risk or vulnerable groups should be administered at least three doses.

Real-World Effectiveness of Mix-and-Match Vaccine Regimens against SARS-CoV-2 Delta Variant in Thailand: A Nationwide Test-Negative Matched Case-Control Study.

The objective of this study is to explore the real-world effectiveness of various vaccine regimens to tackle the epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant in Thailand during September-December 2021. We applied a test-negative case control study, using nationwide records of people tested for SARS-CoV-2. Each case was matched with two controls with respect to age, detection date, and specimen collection site. A conditional logistic regression was performed. Results were presented in the form vaccine effectiveness (VE) and 95% confidence interval. A total of 1,460,458 observations were analyzed. Overall, the two-dose heterologous prime-boost, ChAdOx1 + BNT162b2 and CoronaVac + BNT162b2, manifested the largest protection level (79.9% (74.0-84.5%) and 74.7% (62.8-82.8%)) and remained stable over the whole study course. The three-dose schedules (CoronaVac + CoronaVac + ChAdOx1, and CoronaVac + CoronaVac + BNT162b2) expressed very high degree of VE estimate (above 80.0% at any time interval). Concerning severe infection, almost all regimens displayed very high VE estimate. For the two-dose schedules, heterologous prime-boost regimens seemed to have slightly better protection for severe infection relative to homologous regimens. Campaigns to expedite the rollout of third-dose booster shot should be carried out. Heterologous prime-boost regimens should be considered as an option to enhance protection for the entire population.

Forecasted Trends of the New COVID-19 Epidemic Due to the Omicron Variant in Thailand, 2022.

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.

Rapid method through routine data to evaluate real-world vaccine effectiveness against coronavirus disease 2019 (COVID-19) infection: lessons from Thailand.

The objective of this article is to draw lessons from the Thai experience in estimating vaccine effectiveness (VE) for coronavirus disease 2019 (COVID-19) based on routine service data. We found that a matched case-control design, using probability-based controls representing the varying vaccine coverage across the population over time, yielded a valid result for VE assessment. The proposed design has an advantage in its applicability drawing from the routine data monitoring system. Future studies that exercise other designs, such as test-negative and cohort studies, are recommended in order to compare and contrast the findings across different designs. To implement a continuous monitoring system on VE, the integration of data from different sources is needed. This requires long-term investment in the data monitoring system for the entire healthcare system.

Predicted Impact of Vaccination and Active Case Finding Measures to Control Epidemic of Coronavirus Disease 2019 in a Migrant-Populated Area in Thailand.

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.

Public health policies and health-care workers' response to the COVID-19 pandemic, Thailand.

Since January 2020, the coronavirus disease 2019 (COVID-19) pandemic has had a far-reaching impact on global morbidity and mortality. The effects of varying degrees of implementation of public health and social measures between countries is evident in terms of widely differing disease burdens and levels of disruption to public health systems. Despite Thailand being the first country outside China to report a positive case of COVID-19, the subsequent number of cases and deaths has been much lower than in many other countries. As of 7 January 2021, the number of confirmed COVID-19-positive cases in Thailand was 9636 (138 per million population) and the number of deaths was 67 (1 per million population). We describe the nature of the health workforce and function that facilitated the capacity to respond to this pandemic. We also describe the public health policies (laboratory testing, test-and-trace system and mandatory 14-day quarantine of cases) and social interventions (daily briefings, restriction of mobility and social gatherings, and wearing of face masks) that allowed the virus to be successfully contained. To enhance the capacity of health-care workers to respond to the pandemic, the government (i) mobilized staff to meet the required surge capacity; (ii) developed and implemented policies to protect occupational safety; and (iii) initiated packages to support morale and well-being. The results of the policies that we describe are evident in the data: of the 66 countries with more than 100 COVID-19-positive cases in health-care workers as at 8 May 2020, Thailand ranked 65th.

Depuis janvier 2020, la pandémie de maladie à coronavirus (COVID-19) a eu un impact considérable sur la morbidité et la mortalité à l'échelle globale. Les degrés de mise en œuvre des mesures sociales et sanitaires, qui varient d'un pays à l'autre, ont des conséquences évidentes, notamment sur les différences de charge que représente la maladie et sur l'ampleur des perturbations touchant les systèmes de santé publique. Même si la Thaïlande est, après la Chine, la première nation à avoir signalé un cas positif de COVID-19, le nombre de cas et de décès qui ont suivi a été nettement moins élevé que dans de nombreux autres pays. Au 7 janvier 2021, la Thaïlande comptait 9636 cas positifs confirmés de COVID-19 (138 par million d'habitants) et 67 décès (1,0 par million d'habitants). Dans le présent document, nous décrivons la nature des professionnels de santé et des fonctions qui ont renforcé les capacités de réaction face à cette pandémie. Nous détaillons également les politiques de santé publique (tests en laboratoire, système de dépistage et de suivi, quarantaine obligatoire de 14 jours pour les cas détectés) et les interventions sociales (séances d'information quotidiennes, restriction des déplacements et des rassemblements, port du masque) qui ont permis de contenir le virus avec succès. Afin d'aider les soignants à lutter contre la pandémie, le gouvernement (i) a mobilisé du personnel pour fournir les capacités d'intervention requises; (ii) a développé et appliqué des mesures de protection pour garantir la sécurité au travail; et enfin, (iii) a proposé des programmes de soutien au moral et au bien-être. Les politiques que nous évoquons se traduisent par des résultats sans équivoque: sur les 66 pays dépassant les 100 cas positifs de COVID-19 chez les professionnels de santé au 8 mai 2020, la Thaïlande se classait à la 65e place.

Desde enero de 2020, la pandemia de la enfermedad por coronavirus (COVID-19) ha tenido un impacto de gran alcance en la morbilidad y la mortalidad mundial. Los efectos de los diferentes grados de aplicación de las medidas sociales y de salud pública entre los países son evidentes en términos de cargas virales muy diferentes y niveles de perturbación de los sistemas de salud pública. A pesar de que Tailandia fue el primer país fuera de China en notificar un caso positivo de COVID-19, el número posterior de casos y muertes ha sido mucho menor que en muchos otros países. Hasta el 7 de enero de 2021, el número de casos positivos confirmados de COVID-19 en Tailandia era de 9.636 (138 por millón de población) y el número de muertes era de 67 (1,0 por millón de población). Describimos la naturaleza del personal sanitario y la función que facilitó la capacidad de respuesta a esta pandemia. También describimos las políticas de salud pública (pruebas de laboratorio, sistema de prueba y rastreo y cuarentena obligatoria de 14 días), así como las intervenciones sociales (sesiones informativas diarias, restricción de la movilidad y de las reuniones sociales, uso de mascarillas, etc.) que permitieron contener el virus con éxito. Para mejorar la capacidad de los trabajadores sanitarios para responder a la pandemia, el gobierno (i) movilizó al personal para satisfacer la capacidad de respuesta requerida; (ii) desarrolló y aplicó políticas para proteger la seguridad laboral; y (iii) puso en marcha paquetes para apoyar la moral y el bienestar de la población. Los resultados de las políticas que describimos son evidentes en los datos: de los 66 países con más de 100 casos positivos de COVID-19 en trabajadores sanitarios a 8 de mayo de 2020, Tailandia ocupaba el puesto 65.