METHODS: A modified susceptible-exposed-infectious-recovered compartmental model was developed that included two sequential incubation and infectious periods, with stratification by clinical state. The model was further stratified by age and incorporated population mobility to capture NPIs and micro-distancing (behaviour changes not captured through population mobility). Emerging variants of concern (VoC) were included as an additional strain competing with the existing wild-type strain. Several scenarios that included different vaccination strategies (i.e. vaccines that reduce disease severity and/or prevent infection, vaccination coverage) and mobility restrictions were implemented.
RESULTS: The national model and the regional models all fit well to notification data but underestimated ICU occupancy and deaths in recent weeks, which may be attributable to increased severity of VoC or saturation of case detection. However, the true case detection proportion showed wide credible intervals, highlighting incomplete understanding of the true epidemic size. The scenario projections suggested that under current vaccination rates complete relaxation of all NPIs would trigger a major epidemic. The results emphasise the importance of micro-distancing, maintaining mobility restrictions during vaccination roll-out and accelerating the pace of vaccination for future control. Malaysia is particularly susceptible to a major COVID-19 resurgence resulting from its limited population immunity due to the country's historical success in maintaining control throughout much of 2020.
METHOD: The COVID-19 Vaccination Policy Research and Decision-Support Initiative in Asia (CORESIA) was established to address policy questions related to CVCs. An online cross-sectional survey was conducted from June to October 2021 in nine Asian countries. Multivariable logistical regression analyses were performed to identify potential opposers of CVCs.
RESULTS: Six groups were identified as potential opposers of CVCs: (i) unvaccinated (Odd Ratio (OR): 2.01, 95% Confidence Interval (CI): 1.65-2.46); vaccine hesitant and those without access to COVID-19 vaccines; (ii) those not wanting existing NPIs to continue (OR: 2.97, 95% CI: 2.51-3.53); (iii) those with low level of trust in governments (OR: 1.25, 95% CI: 1.02-2.52); (iv) those without travel plans (OR: 1.58, 95% CI: 1.31-1.90); (v) those expecting no financial gains from CVCs (OR: 2.35, 95% CI: 1.98-2.78); and (vi) those disagreeing to use CVCs for employment, education, events, hospitality, and domestic travel.
CONCLUSIONS: Addressing recurring public health bottlenecks such as vaccine hesitancy and equitable access, adherence to policies, public trust, and changing the narrative from 'societal-benefit' to 'personal-benefit' may be necessary and may help increase wider adoption of CVCs in Asia.
MATERIAL AND METHODS: A systematic review was conducted by examining online databases (Scopus, MEDLINE and Science Direct) to identify health economic evaluation studies of COVID-19 vaccines. Critical appraisal of studies was conducted using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).
RESULTS: A total of nine studies were selected for analysis. Results show two strategies that were cost-effective compared to its comparators: mass vaccination program compared to no vaccination and universal vaccination approach compared to a risk-stratified vaccination approach. Several other strategies were found to increase the cost-consequences in the COVID-19 vaccination program: higher vaccine effectiveness, higher vaccination pace, increased vaccination coverage, and vaccine prioritisation for an at-risk population. The study findings were restricted to analysis based on the current available data.
CONCLUSION: COVID-19 vaccination policies should aim for increased vaccine production as well as a rapid and extensive vaccine delivery system to ensure the maximal value of vaccination strategies. These results can aid policymakers in opting for the most efficient approach to vaccinating the population during this COVID-19 pandemic and future pandemic.
METHODS: We collected 3,489,367 tweets data from January 2020 to August 2021. We analyzed factual and fake news using the string comparison method. The difflib library was used to measure similarity. The user's engagement was analyzed by averaging the engagement metrics of tweets, retweets, favorites, replies, and posts shared with sentiments and opinions regarding COVID-19 and COVID-19 vaccination.
RESULT: Positive sentiments on COVID-19 and COVID-19 vaccination dominated, however, the negative sentiments increased during the beginning of the implementation of restrictions on community activities (PPKM). The tweets were dominated by the importance of health protocols (washing hands, keeping distance, and wearing masks). Several types of vaccines were on top of the word count in the vaccine subtopic. Acceptance of the vaccination increased during the studied period, and the fake news was overweighed by the facts. The tweets were dynamic and showed that the engaged topics were changed from the nature of COVID-19 to the vaccination and virus mutation which peaked in the early and middle terms of 2021. The public sentiment and engagement were shifted from hesitancy to anxiety towards the safety and effectiveness of the vaccines, whilst changed again into wariness on an uprising of the delta variant.
CONCLUSION: Understanding public sentiment and opinion can help policymakers to plan the best strategy to cope with the pandemic. Positive sentiments and fact-based opinions on COVID-19, and COVID-19 vaccination had been shown predominantly. However, sufficient health literacy levels could yet be predicted and sought for further study.