Vaccination strategies and transmission of COVID-19: Evidence across advanced countries

Impact of the pandemic on traffic injuries in Macao: an analysis of interrupted time-series data

OBJECTIVE

With social restrictions serving as a mitigating factor against the severe consequences of public health emergencies, this study investigates the impact of episodic travel restrictions on road traffic injuries (TIs) in Macao during the pandemic, employing Interrupted Time Series Analysis (ITSA) models.

METHODS

We used ITSA models, including Bayesian Structured Time Series and Seasonal Autoregressive Integrated Moving Average models, to assess traffic outcomes, particularly focusing on total road traffic crashes (RTCs) and TIs. Predictive models were developed for traffic fatalities, fatal RTCs, RTCs involving injuries and vehicles sustaining damage.

RESULTS

From 2014 to 2020, Macao recorded a total of 99 541 RTCs. Over the study period, there were 32 562 reported injuries. After the outbreak of the epidemic, traffic volume decreased by 53.03%, leading to a 25.54% reduction in RTCs. The severity of crashes also declined, with TIs decreasing by 20.35% compared with the same period in 2019, and fatalities and damaged vehicles decreasing by 37.50% and 26.62%, respectively. Analysis of the interrupted time-series data revealed that the actual number of RTCs after COVID-19 in 2020 was 20% (95% CI: 14% to 26%) lower than expected, and TIs were reduced by 11% (95% CI: 3% to 19%).

CONCLUSION

This study demonstrates that the implementation of episodic travel restrictions significantly reduced TIs and crashes in Macao, providing crucial insights for traffic management and resource allocation during pandemics. These findings contribute to understanding the dynamic relationship between travel restrictions and road traffic outcomes.

Burden of acute and long-term COVID-19: a nationwide study in Bahrain

Background

Coronavirus disease 2019 (COVID-19) may lead to long-term sequelae. This study aimed to understand the acute and post-acute burden of SARS-CoV-2 infection and to identify high-risk groups for post-COVID-19 conditions (PCC).

Methods

A retrospective observational study of the Bahraini population was conducted between 1 May 2021 and 30 April 2023, utilizing the national administrative database. PCC cases were defined according to WHO guidelines. All COVID-19 cases were confirmed using real-time polymerase chain reaction (PCR).

Results

Of 13,067 COVID-19 cases, 12,022 of them experienced acute COVID-19, and 1,045 of them developed PCC. Individuals with PCC tended to be older women with risk factors and instances of SARS-CoV-2 reinfection. The incidence rates per 100,000 individuals during the Alpha pandemic surge (2020), Delta pandemic surge (2021), and Omicron pandemic surge (2022) were 2.2, 137.2, and 222.5 for acute COVID-19, and 0.27, 10.5, and 19.3, respectively, for PCC cases. The death rates per 100,000 individuals during the Alpha, Delta, and Omicron pandemic surges were 3, 112, and 76, respectively, for acute COVID-19 and 1, 10, and 8, respectively, for PCC. The death rate was highest among those aged 65 and older during the Delta pandemic surge.

Conclusion

These findings suggest the need for a timely national vaccination program prior to new COVID-19 surges to prevent complications related to SARS-CoV-2 infection, particularly in the older adult and in non-older adult individuals with risk factors.

To give or not to give? Pandemic vaccine donation policy

OBJECTIVES

The purpose of this work is to characterize scenarios under which it may be in a donor country's own public health interests to donate vaccine doses to another country before its own population has been fully vaccinated. In these scenarios, vaccinating other countries can delay the evolution of new variants of the virus, decrease total deaths, and, in some cases, decrease deaths in the donor countries.

STUDY DESIGN

We simulate the effects of different vaccine donation policies using an epidemiological model employing COVID-19 transmission parameters.

METHODS

We use the epidemiological model of Holleran et al. that incorporates virus mutation to simulate epidemic progression and estimate numbers of deaths arising from several vaccine allocation policies (donor-first, non-donor-first, and vaccine sharing) across a number of scenarios. We analyze the results in light of herd immunity limits derived in Holleran et al.

RESULTS

We identify realistic scenarios under which a donor country prefers to donate vaccines before distributing them locally in order to minimize local deaths during a pandemic. We demonstrate that a non-donor-first vaccination policy can delay, sometimes dramatically, the emergence of more-contagious variants. Even more surprising, donating all vaccines is sometimes better for the donor country than a sharing policy in which half of the vaccines are donated, and half are retained because of the impact donation can have on delaying the emergence of a more contagious virus. Non-donor-first vaccine allocation is optimal in scenarios in which the local health impact of the vaccine is limited or when delaying the emergence of a variant is especially valuable.

CONCLUSION

In all cases, we find that vaccine distribution is not a zero-sum game between donor and non-donor countries, illustrating the general moral reasons to donate vaccines. In some cases, donor nations can also realize local health benefits from donating vaccines. The insights yielded by this framework can be used to guide equitable vaccine distribution in future pandemics.

Impact of the first year of COVID-19 vaccination strategy in Brazil: an ecological study

OBJECTIVES

No consensus exists about the best COVID-19 vaccination strategy to be adopted by low-income and middle-income countries. Brazil adopted an age-based calendar strategy to reduce mortality and the burden on the healthcare system. This study evaluates the impact of the vaccination campaign in Brazil on the progression of the reported COVID-19 deaths.

METHODS

This ecological study analyses the dynamic of vaccination coverage and COVID-19 deaths in hospitalised adults (≥20 years) during the first year of the COVID-19 vaccination roll-out (January to December 2021) using nationwide data (DATASUS). We stratified the adult population into 20-49, 50-59, 60-69 and 70+ years. The dynamic effect of the vaccination campaign on mortality rates was estimated by applying a negative binomial regression. The prevented and possible preventable deaths (observed deaths higher than expected) and potential years of life lost (PYLL) for each age group were obtained in a counterfactual analysis.

RESULTS

During the first year of COVID-19 vaccination, 266 153 517 doses were administered, achieving 91% first-dose coverage. A total of 380 594 deaths were reported, 154 091 (40%) in 70+ years and 136 804 (36%) from 50-59 or 20-49 years. The mortality rates of 70+ decreased by 52% (rate ratio [95% CI]: 0.48 [0.43-0.53]) in 6 months, whereas rates for 20-49 were still increasing due to low coverage (52%). The vaccination roll-out strategy prevented 59 618 deaths, 53 088 (89%) from those aged 70+ years. However, the strategy did not prevent 54 797 deaths, 85% from those under 60 years, being 26 344 (45%) only in 20-49, corresponding to 1 589 271 PYLL, being 1 080 104 PYLL (68%) from those aged 20-49 years.

CONCLUSION

The adopted aged-based calendar vaccination strategy initially reduced mortality in the oldest but did not prevent the deaths of the youngest as effectively as compared with the older age group. Countries with a high burden, limited vaccine supply and young populations should consider other factors beyond the age to prioritise who should be vaccinated first.

Consequences of a shortage and rationing: Evidence from a pediatric vaccine

Shortages and rationing are common in health care, yet we know little about the consequences. We examine an 18-month shortage of the pediatric Haemophilus Influenzae Type B (Hib) vaccine. Using insurance claims data and variation in shortage exposure across birth cohorts, we find that the shortage reduced uptake of high-value primary doses by 4 percentage points and low-value booster doses by 26 percentage points. This suggests providers largely complied with rationing recommendations. In the long-run, catch-up vaccination occurred but was incomplete: shortage-exposed cohorts were 4 percentage points less likely to have received the ir booster dose years later. We also find that the shortage and rationing caused provider switches, extra provider visits, and negative spillovers to other care.

The impact of Covid-19 on demographic components in Spain, 2020-31: A scenario approach

While considerable attention has been paid to the impact of Covid-19 on mortality and fertility, few studies have attempted to evaluate the pandemic's effect on international migration. We analyse the impact of Covid-19 on births, deaths, and international migration in Spain during 2020, comparing observed data with estimated values assuming there had been no pandemic. We also assess the consequences of three post-pandemic scenarios on the size and structure of the population to 2031. Results show that in 2020, excess mortality equalled 16.2 per cent and births were 6.5 per cent lower than expected. Immigration was the most affected component, at 36.0 per cent lower than expected, while emigration was reduced by 23.8 per cent. If net migration values recover to pre-pandemic levels in 2022, the size and structure of the population in 2031 will be barely affected. Conversely, if levels do not recover until 2025, there will be important changes to Spain's age structure.

Impact of the COVID-19 vaccine booster strategy on vaccine protection: a pilot study of a military hospital in Taiwan

Purpose

The global fight against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has led to widespread vaccination efforts, yet the optimal dosing schedule for SARS-CoV-2 vaccines remains a subject of ongoing research. This study aims to investigate the effectiveness of administering two booster doses as the third and fourth doses at different intervals to enhance vaccine protection.

Materials and Methods

This study was conducted at a military regional hospital operated by the Ministry of National Defense in Taiwan. A cohort of vaccinated individuals was selected, and their vaccine potency was assessed at various time intervals following their initial vaccine administration. The study participants received booster doses as the third and fourth doses, with differing time intervals between them. The study monitored neutralizing antibody titers and other relevant parameters to assess vaccine efficacy.

Results

Our findings revealed that the potency of the SARS-CoV-2 vaccine exhibited a significant decline 80 days after the initial vaccine administration. However, a longer interval of 175 days between booster injections resulted in significantly higher neutralizing antibody titers. The individuals who received the extended interval boosters exhibited a more robust immune response, suggesting that a vaccine schedule with a 175-day interval between injections may provide superior protection against SARS-CoV-2.

Conclusion

This study underscores the importance of optimizing vaccine booster dosing schedules to maximize protection against SARS-CoV-2. The results indicate that a longer interval of 175 days between the third and fourth doses of the vaccine can significantly enhance the neutralizing antibody response, potentially offering improved protection against the virus. These findings have important implications for vaccine distribution and administration strategies in the ongoing battle against the SARS-CoV-2 pandemic. Further research and large-scale trials are needed to confirm and extend these findings for broader public health implications.

Risk of Testing Positive for COVID-19 among Healthcare and Healthcare-Related Workers

Understanding the risk factors associated with COVID-19 infection among healthcare workers is crucial for infection prevention and control. The aim of this study was to examine the risk of testing positive for COVID-19 among a multicenter cohort of workers, taking into account their occupational roles (medical professionals, staff in operational and administrative roles, or laboratory personnel) in healthcare settings. The data analyzed in this study included 2163 individuals with suggestive COVID-19 symptoms who underwent laboratory testing. The incidence rate in the study sample was calculated to be 15.3 cases per 10,000 person-days. The results from the multiple regression model indicated that job roles were not significantly associated with the risk of testing positive. However, age and the duration of the pandemic were identified as significant risk factors, with increasing age and longer pandemic duration being associated with a higher risk of testing positive. Additionally, vaccination was found to reduce the risk of testing positive. These findings provide valuable insights into COVID-19 transmission among indoor healthcare workers, highlighting the influence of age, pandemic duration, and vaccination on infection risk. Further research is needed to develop evidence-based strategies aimed at protecting healthcare workers and preventing virus spread in healthcare settings.

How to reduce vaccination hesitancy? The relevance of evidence and its communicator

Even though the immediate urgency of the COVID-19 pandemic seems to have passed, many countries did not reach the vaccination rates they initially aimed for. The stagnation in vaccine uptake during the height of the pandemic presented policy makers with a challenge that remains unresolved and is paramount for future pandemics and other crises: How to convince the (often not insubstantial) unvaccinated proportion of the population of the benefits of a vaccination? Designing more successful communication strategies, both in retrospect and looking ahead, requires a differentiated understanding of the concerns of those that remain unvaccinated. Guided by the elaboration likelihood model, this paper has two objectives: First, it explores by means of a latent class analysis how unvaccinated individuals might be characterized by their attitudes towards COVID-19 vaccination. Second, we investigate to what extent (i) varying types of evidence (none/anecdotal/statistical) can be employed by (ii) different types of communicators (scientists/politicians) to improve vaccination intentions across these subgroups. To address these questions, we conducted an original online survey experiment among 2145 unvaccinated respondents from Germany where a substantial population share remains unvaccinated. The results suggest three different subgroups, which differ regarding their openness towards a COVID-19 vaccination: Vaccination opponents (N = 1184), sceptics (N = 572) and those in principle receptive (N = 389) to be vaccinated. On average, neither the provision of statistical nor anecdotal evidence increased the persuasiveness of information regarding the efficacy of a COVID-19 vaccine. However, scientists were, on average, more persuasive than politicians (relatively increase vaccination intentions by 0.184 standard deviations). With respect to heterogeneous treatment effects among the three subgroups, vaccination opponents seem largely unreachable, while sceptics value information by scientists, particularly if supported by anecdotal evidence (relatively increases intentions by 0.45 standard deviations). Receptives seem much more responsive to statistical evidence from politicians (relatively increases intentions by 0.38 standard deviations).

School-age vaccination, school openings and Covid-19 diffusion

This article investigates the relationship between school openings and Covid-19 diffusion when school-age vaccination becomes available. The analysis relies on a unique geo-referenced high frequency database on age of vaccination, Covid-19 cases and hospitalization indicators from the Italian region of Sicily. The study focuses on the change of Covid-19 diffusion after school opening in a homogeneous geographical territory (i.e., with the same control measures and surveillance systems, centrally coordinated by the Regional Government). The identification of causal effects derives from a comparison of the change in cases before and after school opening in the school year 2020/21, when vaccination was not available, and in 2021/22, when the vaccination campaign targeted individuals of age 12-19 and above 19. Results indicate that, while school opening determined an increase in the growth rate of Covid-19 cases in 2020/2021, this effect has been substantially reduced by school-age vaccination in 2021/2022. In particular, we find that an increase of approximately 10% in the vaccination rate of school-age population reduces the growth rate of Covid-19 cases after school opening by approximately 1%.

Adoption of Digital Vaccination Services: It Is the Click Flow, Not the Value—An Empirical Analysis of the Vaccination Management of the COVID-19 Pandemic in Germany

This research paper examines the adoption of digital services for the vaccination during the COVID-19 pandemic in Germany. Based on a survey in Germany’s federal state with the highest vaccination rate, which used digital vaccination services, its platform configuration and adoption barriers are analyzed to understand existing and future levers for optimizing vaccination success. Though technological adoption and resistance models have been originally developed for consumer-goods markets, this study gives empirical evidence especially for the applicability of an adjusted model explaining platform adoption for vaccination services and for digital health services in general. In this model, the configuration areas of personalization, communication, and data management have a remarkable effect to lower adoption barriers, but only functional and psychological factors affect the adoption intention. Above all, the usability barrier stands out with the strongest effect, while the often-cited value barrier is not significant at all. Personalization is found to be the most important factor for managing the usability barrier and thus for addressing the needs, preferences, situation, and, ultimately, the adoption of the citizens as users. Implications are given for policy makers and managers in such a pandemic crisis to focus on the click flow and server-to-human interaction rather than emphasizing value messages or touching traditional factors.

Vaccine selection for COVID-19 by AHP and novel VIKOR hybrid approach with interval type-2 fuzzy sets

Decisions in the health industry have a significant impact on human lives. With the COVID-19 pandemic, a global war is being waged. Vaccination is a critical component in this fight. The governments are attempting to offer their citizens the best vaccine for the public based on limitations. However, due to the unique characterizations of countries and the people who live in the country, the definition of "the ideal vaccination" is indefinite. Fuzzy set theory has been an ideal tool to cope with problems involving imprecise information such as the meaning of "ideal" in this case. In this study Interval Type-2 Fuzzy Sets (IT2FSs) will be used to describe uncertainty. This IT2FS structure will be the framework of the AHP (Analytic Hierarchy Process), to determine the criteria weights, and the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), to generate a set of optimal choices. The main objective of this study is to sustain the necessary effect of uncertainty of fuzzy sets via the Interval Type-2 Fuzzy (IT2F) metric to the VIKOR method and thus propose an extended VIKOR. The presented new approach will be applied to the problem of vaccine selection for COVID-19. Hence, for the first time in the literature, an application with a multilevel hierarchy will be used in IT2FAHP-VIKOR. Also, obtained optimal solution set with this hybrid framework will be compared with fuzzy AHP-VIKOR and the rankings evaluated with the IT2FTOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and sensitivity analysis will be performed.

Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study

BACKGROUND

The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England.

METHODS

We used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions.

FINDINGS

In the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021.

INTERPRETATION

England's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall.

FUNDING

UK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.

Understanding Covid-19 Mobility Through Human Capital: A Unified Causal Framework

This paper seeks to identify the causal impact of educational human capital on social distancing behavior at workplace in Turkey using district-level data for the period of April 2020 - February 2021. We adopt a unified causal framework, predicated on domain knowledge, theory-justified constraints anda data-driven causal structure discovery using causal graphs. We answer our causal query by employing machine learning prediction algorithms; instrumental variables in the presence of latent confounding and Heckman's model in the presence of selection bias. Results show that educated regions are able to distance-work and educational human capital is a key factor in reducing workplace mobility, possibly through its impact on employment. This pattern leads to higher workplace mobility for less educated regions and translates into higher Covid-19 infection rates. The future of the pandemic lies in less educated segments of developing countries and calls for public health action to decrease its unequal and pervasive impact.

Effects of strict containment policies on COVID-19 pandemic crisis: lessons to cope with next pandemic impacts

The goal of the study here is to analyze and assess whether strict containment policies to cope with Coronavirus Disease 2019 (COVID-19) pandemic crisis are effective interventions to reduce high numbers of infections and deaths. A homogenous sample of 31 countries is categorized in two sets: countries with high or low strictness of public policy to cope with COVID-19 pandemic crisis. The findings here suggest that countries with a low intensity of strictness have average confirmed cases and fatality rates related to COVID-19 lower than countries with high strictness in containment policies (confirmed cases are 24.69% vs. 26.06% and fatality rates are 74.33% vs. 76.38%, respectively, in countries with low and high strictness of COVID-19 public policies of containment). What this study adds is that high levels of strict restriction policies may not be useful measures of control in containing the spread and negative impact of pandemics similar to COVID-19 and additionally a high strictness in containment policies generates substantial social and economic costs. These findings can be explained with manifold socioeconomic and environmental factors that support transmission dynamics and circulation of COVID-19 pandemic. Hence, high levels of strictness in public policy (and also a high share of administering new vaccines) seem to have low effectiveness to stop pandemics similar to COVID-19 driven by mutant viral agents. These results here suggest that the design of effective health policies for prevention and preparedness of future pandemics should be underpinned in a good governance of countries and adoption of new technology, rather than strict and generalized health polices having ambiguous effects of containment in society.

COVID-19 Vaccination is not a Sufficient Public Policy to face Crisis Management of next Pandemic Threats

This study reveals that a vast vaccination campaign is a necessary but not sufficient public policy to reduce the negative impact of Coronavirus Disease 2019 (COVID-19) pandemic crisis because manifold factors guide the spread of this new infectious disease and related mortality in society. Statistical evidence here, based on a worldwide sample of countries, shows a positive correlation between people fully vaccinated and COVID-19 mortality (r = + 0.65, p-value < 0.01). Multivariate regression, controlling income per capita, confirms this finding. Results suggest that the increasing share of people vaccinated against COVID-19 seems to be a necessary but not sufficient health policy to reduce mortality of COVID-19. The findings here can be explained with the role of Peltzman effect, new variants, environmental and socioeconomic factors that affect the diffusion and negative impact of COVID-19 pandemic in society. This study extends the knowledge in this research field to design effective public policies of crisis management for facing next pandemic threats.