Vaccine Efficacy Rates Research Articles

The Effects of Numerical Evidence and Message Framing in Communicating Vaccine Efficacy

To examine the effects of numerical evidence and message framing in communicating vaccine efficacy information about infectious diseases, an online experiment presented to U.S. adults different versions of a vaccination promotional message that vary by numerical vaccine efficacy evidence: (low efficacy rate: 60% vs. high efficacy rate: 95%), outcome framing (preventing disease-related infection vs. preventing disease-related severe illness), and gain vs. loss framing, using a factorial between-subjects design. While there was no significant interaction between numerical vaccine efficacy evidence and message framing, findings showed that a higher vaccine efficacy rate increased positive beliefs about vaccination and outcome framing emphasizing infection prevention increased message processing fluency. Given that infectious diseases pose higher risks for severe illness among older adults, follow-up analyses by age showed that only younger adults were sensitive to message framing where outcome framing emphasizing infection prevention increased processing fluency.

Mathematical model for understanding the relationship between diabetes and novel coronavirus

A new model is proposed to explore interactions between diabetes and novel coronavirus. The model accounted for both the omicron variant and variants varying from omicron. The model investigated compartments such as hospitalization, diabetes, co-infection, omicron variant, and quarantine. Additionally, the impact of different vaccination doses is assessed. Sensitivity analysis is carried out to determine disease prevalence and control options, emphasizing the significance of knowing epidemics and their characteristics. The model is validated using actual data from Japan. The parameters are fitted with the help of ”Least Square Curve Fitting” method to describe the dynamic behavior of the proposed model. Simulation results and theoretical findings demonstrate the dynamic behavior of novel coronavirus and diabetes mellitus (DM). Biological illustrations that illustrate impact of model parameters are evaluated. Furthermore, effect of vaccine efficacy and vaccination rates for the vaccine’s first, second, and booster doses is conducted. The impact of various preventive measures, such as hospitalization rate, quarantine or self-isolation rate, vaccine dose-1, dose-2, and booster dose, is considered for diabetic individuals in contact with symptomatic or asymptomatic COVID-19 infectious people in the proposed model. The findings demonstrate the significance of vaccine doses on people with diabetes and individuals infectious with omicron variant. The proposed work helps with subsequent prevention efforts and the design of a vaccination policy to mitigate the effect of the novel coronavirus.

Modeling the effects of vaccine efficacy and rate of vaccination on the transmission of pulmonary tuberculosis

Numerous prevention intervention strategies have been developed to curtail the spread of pulmonary tuberculosis to susceptible populations. However, pulmonary tuberculosis continues to claim many lives worldwide. In this paper, a deterministic mathematical model incorporating an asymptomatic infectious population, considering vaccine efficacy, and vaccination rate, has been formulated. The model includes asymptomatic infectious individuals since they spread infections incessantly to susceptible populations without being noticed, thus contributing to the high transmission rate. Sensitivity and numerical analysis have been conducted to investigate the impact of varying vaccine efficacy and vaccination rates on the transmission of pulmonary tuberculosis infections from the asymptomatic infectious population. The sensitivity and numerical results show that an increase in vaccine efficacy reduces the asymptomatic infectious population and subsequently lowers the transmission rate of infections. Moreover, an increase in vaccine efficacy was shown to reduce the control reproduction number due to asymptomatic infectious individuals, thereby decreasing the transmission of pulmonary tuberculosis to susceptible populations. Further results indicate that an increase in vaccination rate reduces the control reproduction number due to asymptomatic infectious individuals, consequently lowering the rate of infection transmission. These findings emphasize the need to develop a vaccine of higher efficacy to reduce infection transmission to susceptible populations by the asymptomatic infectious individuals. Additionally, the results underscore the importance of increasing vaccination rates to eradicate pulmonary tuberculosis from the population.

A Dynamic Model of Information‐Vaccination‐Disease That Accounts for Emerging Viral Variants: Model Development and a Case Study for COVID‐19 in Iceland

Pathogens mutate as diseases spread, and variants that become epidemic or pandemic strains have higher transmission rates and a greater capacity to escape vaccine protection. Considering different vaccine efficacy and vaccination rates is of great significance for the prevention and control of infectious diseases. The spread of vaccination information and the level of trust in vaccinations determine whether people will choose to be vaccinated. To analyze these factors, we developed mean‐field equations for system dynamics to model the complex system of vaccine information dissemination and vaccination, calculated the basic reproduction rate number, and used the Icelandic COVID‐19 outbreak (Omicron variant) as a case study. We found that in the face of emerging variants, increasing vaccine efficacy is more effective than increasing vaccination rates. If vaccine efficacy increases from 40% to 90%, infections can be decreased by 98.5%. However, even a 100% vaccination rate cannot stop the spread of a mutated virus if vaccine efficacy falls below a certain level. High vaccination rates decrease the virus transmission rate. If the efficacy of the vaccine diminishes, the infection will spread rapidly, leading to a greater number of individuals becoming infected with the infectious disease. Due to the high vaccine efficacy against major illnesses and fatalities, improving vaccination rates can lower deaths. Iceland could decrease deaths by 44.8% by raising the vaccination rate from 75.9% to 95.0%. To combat emerging virus variants, it is therefore necessary to both create more effective vaccines and raise awareness of the benefits of vaccination to increase vaccination rates.

The performance of government subsidy schemes in a competitive vaccine market considering consumers' free-riding behavior

Vaccination is acknowledged as the most cost-effective means of combating epidemics. However, the free-riding behavior frequently results in vaccination rates falling below the socially optimal level. To address this issue, governments frequently offer subsidies to either vaccine suppliers or consumers. This paper develops a game-theoretic model that incorporates two vaccine suppliers with different efficacy rates and prices. We propose two subsidy schemes, one based on vaccine price and the other based on vaccine efficacy rate, with the aim of improving vaccination rates. Our results demonstrate that the price-based subsidy scheme (PSS) leads to a higher vaccine price compared to the efficacy-based subsidy scheme (ESS). Moreover, the ESS proves more effective in increasing the equilibrium vaccination rate when the efficacy rate is low, while the PSS is more effective when the efficacy rate is high. However, if the government’s budget is limited, the ESS is more likely to improve the equilibrium vaccination rate compared to the PSS.

A non-linear differential equation model of COVID-19 and seasonal influenza co-infection dynamics under vaccination strategy and immunity waning

This study presents a mathematical model of the transmission dynamics of COVID-19 and influenza co-infection. The potential impacts of the influenza vaccine only on the co-infection dynamics and the potential impacts of both vaccines on the co-infection dynamics are thoroughly studied. The basic reproduction number for the two diseases using the next-generation matrix approach and the stability of the sub-model is examined. The model assessed the scenario whereby both diseases’ waning immunity occurs concurrently to check the epidemic peaks. The numerical simulation results show that the diseases would continue to be endemic in the population if the immunity waning rates increase. The epidemic peak can be reduced by increasing vaccination and vaccine efficacy rates. The results show that the COVID-19 contact rate significantly increases the epidemic level more than the co-infection contact rate. A similar result was obtained when it was observed that the COVID-19 post-recovery waning rate has more significant effects on the epidemic peak than the co-infection post-recovery waning rate. A possible reason for this counter-intuitive occurrence is that two infections cannot have the same viral load nor the same within-host competitiveness. This means an infectious co-infected person will transmit the infection with the highest within-host competitiveness. Here, it is suspected that COVID-19 has a within-host competitive advantage over influenza in the co-dynamics.

Prevalence of symptoms, comorbidities, and reinfections in individuals infected with Wild-Type SARS-CoV-2, Delta, or Omicron variants: a comparative study in western Mexico.

The variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been classified into variants of interest (VOIs) or concern (VOCs) to prioritize global monitoring and research on variants with potential risks to public health. The SARS-CoV-2 high-rate mutation can directly impact the clinical disease progression, epidemiological behavior, immune evasion, vaccine efficacy, and transmission rates. Therefore, epidemiological surveillance is crucial for controlling the COVID-19 pandemic. In the present study, we aimed to describe the prevalence of wild-type (WT) SARS-CoV-2 and Delta and Omicron variants in Jalisco State, Mexico, from 2021 to 2022, and evaluate the possible association of these variants with clinical manifestations of COVID-19. Four thousand and ninety-eight patients diagnosed with COVID-19 by real-time PCR (COVIFLU, Genes2Life, Mexico) from nasopharyngeal samples from January 2021 to January 2022 were included. Variant identification was performed by the RT-qPCR Master Mut Kit (Genes2Life, Mexico). A study population follow-up was performed to identify patients who had experienced reinfection after being vaccinated. Samples were grouped into variants according to the identified mutations: 46.3% were Omicron, 27.9% were Delta, and 25.8% were WT. The proportions of dry cough, fatigue, headache, muscle pain, conjunctivitis, fast breathing, diarrhea, anosmia, and dysgeusia were significantly different among the abovementioned groups (p < 0.001). Anosmia and dysgeusia were mainly found in WT-infected patients, while rhinorrhea and sore throat were more prevalent in patients infected with the Omicron variant. For the reinfection follow-up, 836 patients answered, from which 85 cases of reinfection were identified (9.6%); Omicron was the VOC that caused all reported reinfection cases. In this study, we demonstrate that the Omicron variant caused the biggest outbreak in Jalisco during the pandemic from late December 2021 to mid-February 2022 but with a less severe form than the one demonstrated by Delta and WT. The co-analysis of mutations and clinical outcomes is a public health strategy with the potential to infer mutations or variants that could increase disease severity and even be an indicator of long-term sequelae of COVID-19.

Stability and Threshold Dynamics in a Seasonal Mathematical Model for Measles Outbreaks with Double-Dose Vaccination

Measles is a highly contagious viral disease that can lead to serious complications, including death, particularly in young children. In this study, we developed a mathematical model that incorporates a seasonal transmission parameter to examine the measles transmission dynamics. We define the basic reproduction number (R0) and show its utility as a threshold parameter for global dynamics and the existence of periodic solutions. The model was applied to the measles outbreak that occurred in Pakistan from 2019 to 2021 and provided a good fit to the observed data. Our estimate of the basic reproduction number was found to be greater than one, indicating that the disease will persist in the population. The findings highlight the need to increase vaccination coverage and efficacy to mitigate the impact of the epidemic. The model also shows the long-term behavior of the disease, which becomes endemic and recurs annually. Our simulations demonstrate that a shorter incubation period accelerates the spread of the disease, while a higher vaccination coverage rate reduces its impact. The importance of the second dose of the measles vaccine is emphasized, and a higher vaccine efficacy rate can also help bring R0 below one. Our study provides valuable information for the development and implementation of effective measles control strategies. To prevent future outbreaks, increasing vaccination coverage among the population is the most effective way to reduce the transmission of measles.

Sources of bias in observational studies of covid-19 vaccine effectiveness.

Sources of bias in observational studies of covid-19 vaccine effectiveness.

Booster Dose Vaccination and Dynamics of COVID-19 Pandemic in the Fifth Wave: An Efficient and Simple Mathematical Model for Disease Progression

Mathematical studies exploring the impact of booster vaccine doses on the recent COVID-19 waves are scarce, leading to ambiguity regarding the significance of booster doses. A mathematical model with seven compartments was used to determine the basic and effective reproduction numbers and the proportion of infected people during the fifth wave of COVID-19. Using the next-generation matrix, we computed the effective reproduction parameter, Rt. During the fifth COVID-19 wave, the basic reproductive number in Thailand was calculated to be R0= 1.018691. Analytical analysis of the model revealed both local and global stability of the disease-free equilibrium and the presence of an endemic equilibrium. A dose-dependent decrease in the percentage of infected individuals was observed in the vaccinated population. The simulation results matched the real-world data of the infected patients, establishing the suitability of the model. Furthermore, our analysis suggested that people who had received vaccinations had a better recovery rate and that the death rate was the lowest among those who received the booster dose. The booster dose reduced the effective reproduction number over time, suggesting a vaccine efficacy rate of 0.92. Our study employed a rigorous analytical approach to accurately describe the dynamics of the COVID-19 fifth wave in Thailand. Our findings demonstrated that administering a booster dose can significantly increase the vaccine efficacy rate, resulting in a lower effective reproduction number and a reduction in the number of infected individuals. These results have important implications for public health policymaking, as they provide useful information for the more effective forecasting of the pandemic and improving the efficiency of public health interventions. Moreover, our study contributes to the ongoing discourse on the effectiveness of booster doses in mitigating the impact of the COVID-19 pandemic. Essentially, our study suggests that administering a booster dose can substantially reduce the spread of the virus, supporting the case for widespread booster dose campaigns.

The Effects of Vaccine Efficacy Information on Vaccination Intentions Through Perceived Response Efficacy and Hope

Response efficacy information indicating the effectiveness of a recommended behavior in risk reduction is an important component of health communication. For example, many messages regarding COVID-19 vaccines featured numerical vaccine efficacy rates in preventing infections, hospitalizations, and deaths. While the relationship between disease risk perceptions and fear has been well established, we know less about the psychological factors involved in communicating vaccine efficacy information, such as response efficacy perceptions and hope. This study examines the effects of numerical vaccine efficacy information and message framing on vaccination intentions and their relationship to perceived response efficacy and hope, using a fictitious infectious disease similar to COVID-19. Findings suggest that communicating a high efficacy rate of the vaccine in preventing severe illness increased perceived response efficacy, which in turn boosted vaccination intention directly and indirectly through increasing hope. Also, fear about the virus was positively associated with hope about the vaccine. Implications of using response efficacy information and hope appeals in health communication and vaccination promotion are discussed.

An Optimal Vaccine Allocation Model Considering Vaccine Hesitancy and Efficacy Rates Among Populations

Vaccines need to be urgently allocated in pandemics like the ongoing COVID-19 pandemic. In the literature, vaccines are optimally allocated using various mathematical models, including the extensively used Susceptible-Infected-Recovered epidemic model. However, these models do not account for the time duration concerning multi-dose vaccines, time duration from infection to recovery or death, the vaccine hesitancy (i.e., delay in acceptance or refusal of vaccination), and vaccine efficacy (i.e., the time-varying protection capability of the vaccine). To make the vaccine allocation model more applicable to reality, this paper presents an optimal model considering the above mentioned time duration concerning multi-dose vaccination, time duration from infection to recovery or death, hesitancy rates, efficacy levels, and also breakthrough rates—the rates at which individuals get infected after vaccination. This vaccine allocation model is constructed using a revised Susceptible-Infected-Recovered model. The concept of people*week infections is introduced to measure the number of infected people within a certain time duration, and in this paper, the amount of people*week infections is minimized by the proposed vaccine allocation model. Our case study of the New York State 2021 population of 19,840,000 shows that this optimal allocation method can avoid 0.05%~2.75% people*week infections than the baseline allocation method when 2 to 11 million vaccines are optimally allocated. In conclusion, the obtained optimal allocation method can effectively reduce people*week infections and avoid vaccine waste when more vaccines are available.

Dynamic changes in peripheral lymphocytes and antibody response following a third dose of SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients

The aim of this study was to evaluate the association of circulating lymphocytes profiling with antibody response in cancer patients receiving the third dose of COVID-19 mRNA-BNT162b2 vaccine. Immunophenotyping of peripheral blood was used to determine absolute counts of lymphocyte subsets, alongside detection of IgG antibodies against receptor-binding-domain (RBD) of the SARS-CoV-2 Spike protein (S1) before booster dosing (timepoint-1) and four weeks afterward (timepoint-2). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response. An IgG titer ≥ 4446 AU/mL was assumed as a correlate of 50% vaccine efficacy against symptomatic infections. A total of 258 patients on active treatment within the previous six months were enrolled between September 23 and October 7, 2021. The third dose resulted in an exponential increase in median anti-RBD-S1 IgG titer (P < 0.001), seroconversion rates (P < 0.001), and 50% vaccine efficacy rates (P < 0.001). According to ROC curve analysis, T helper and B cells were significantly associated with seroconversion responses at timepoint-1, whereas only B cells were relevant to 50% vaccine efficacy rates at timepoint-2. A positive linear correlation was shown between anti-RBD-S1 IgG titers and these lymphocyte subset counts. Multivariate analysis ruled out a potential role of T helper cells but confirmed a significant interaction between higher B cell levels and improved antibody response. These findings suggest that peripheral counts of B cells correlate with humoral response to the third dose of mRNA-BNT162b2 vaccine in actively treated cancer patients and could provide insights into a more comprehensive assessment of vaccination efficacy.

Living with the Virus: Graduate School Students Evaluation of Stressors Related to the Pandemic

The Coronavirus Disease (COVID-19) becomes a global threat in March of 2020. Several countries were on lockdown. It affects health and results in post-traumatic stress disorder (PTSD). During the quarantine and lockdown, the lack of freedom resulted to psychological consequences. In the Philippines, it was March 15, 2020 when the initial COVID-19 was instituted commonly recalled due to lockdown and canceled classes. Filipinos in general and students in particular were worried of their health information including vaccine availability, efficacy, and infection rates. Mental health is impaired by pandemic risks. UNICEF Philippines, then, advocated alternative and continuing learning. The major purpose of this research is to determine graduate students' levels of stress during the COVID-19 outbreak. The descriptive-correlational design was used for the quantitative investigation. The 150 responders are selected at random from Metro Manila master's degree students in the academic year 2022-2023. The adopted questionnaire consists of seven items that are multidimensional scales with psychometric qualities. Using chi-square, the findings revealed that, among demographic profiles, only age showed a significant relationship with the association of global stress. Thus, it can be stated that age is a crucial factor in assessing the global stress of graduate students. COVID-19 is more contagious in adults, reflecting their anxiety and stress during the epidemic.

Metanalysis of Vaccine Efficacy for Monkeypox According to Clinical Criteria of History Taking, Clinical Features and Laboratory Investigation

Monkeypox virus is DNA virus of Orthopoxvirus. The Monkeypox is zoonosis disease first diagnosed in the Democratic Republic of the Congo in 1970 and originally transmitted from Vertebrate Reservoir. In 1796, Edward Jenner was the first physician achieved vaccine and prove its efficacy through exposing James Phipps to smallpox after immunization. The current study revises the vaccine efficacy and mortality rate of monkeypox. It is mainly transmitted from Squirrels to human and cause mortality rate ranging from 2.7 to 10.1%. Globally, it estimated 4.4% the mortality rate of Monkeypox cases. Based on current review study, the effectiveness of smallpox vaccine in preventing the monkeypox is quite variable due to several selective clinical cases criteria such as history taking and clinical features and laboratory investigation, which modify the statistical result of the vaccine efficacy. The current study clarifies the faults of calculation by eliminating several reasons and estimating the effectiveness of vaccine in the household and find it to be 16.3% whereas total Vaccine efficacy is 0.6%. Using preventive measures are the first line to avoid infection therefore healthcare workers must adhere to infection control precautions. A current study warns scientists to create monkeypox vaccine rather than depending on smallpox vaccine effectiveness due to lacking of current vaccine effectiveness evidence and treatment.

Preferences and willingness of accepting COVID-19 vaccine booster: Results from a middle-income country

The recent wave of COVID-19 cases has led to the potential need for booster doses. We surveyed 6,294 people and found that 87.6% reported willingness to take a booster dose, with vaccine efficacy rate being the most common reason cited to accept booster dose. Differences in acceptance rates were noted among those working in non-health related sectors, different ethnic groups as well as those who had taken viral vector vaccines.

Model-based evaluation of the impact of prophylactic vaccination applied to Ebola epidemics in Sierra Leone and Democratic Republic of Congo

BackgroundProtection by preventive Ebola vaccines has been demonstrated in clinical trials, but a complete picture of real-world effectiveness is lacking. Our previous study modeling the impact of preventively vaccinating healthcare workers (HCW) alone or with a proportion of the general population (GP) estimated significant reductions in incidence and mortality. The model assumed 100% vaccine efficacy, which is unlikely in the real world. We enhanced this model to account for lower vaccine efficacy and to factor in reduced infectiousness and lower case fatality rate in vaccinated individuals with breakthrough infections.MethodsThe previous model was enhanced to still permit a risk, although lower, for vaccinated individuals to become infected. The enhanced model, calibrated with data from epidemics in Sierra Leone (SL) and North Kivu, Democratic Republic of the Congo, helped evaluate the impact of preventive Ebola vaccination in different scenarios based on different vaccine efficacy rates (90% and 30% reductions in infection risk in the base and conservative scenarios, respectively; additionally, both scenarios with 50% reductions in infectiousness and mortality) and vaccination coverage among HCWs (30%, 90%) and GP (0%, 5%, and 10%).ResultsThe base scenario estimated that, depending upon the proportions of vaccinated HCWs and GP, 33–85% of cases and 34–87% of deaths during the 2014 SL epidemic and 42–89% of cases and 41–89% of deaths during the 2018 North Kivu epidemic would be averted versus no vaccination. Corresponding estimates for the conservative scenario were: 23–74% of cases and 23–77% of deaths averted during the SL epidemic and 31–80% of both cases and deaths averted during the North Kivu epidemic.ConclusionsPreventive vaccination targeting HCW alone or with GP may significantly reduce the size and mortality of an EVD outbreak, even with modest efficacy and coverage. Vaccines may also confer additional benefits through reduced infectiousness and mortality in breakthrough cases.

Effect of awareness, quarantine and vaccination as control strategies on COVID-19 with Co-morbidity and Re-infection.

In this paper, a deterministic compartmental model is presented to assess the impact of vaccination and non-pharmaceutical interventions (social distance, awareness, face mask, and quarantine) on the transmission dynamics of COVID-19 with co-morbidity and re-infection. An expression for the basic reproduction number is then derived for this model. Theoretical analysis shows that the model exhibits backward bifurcation phenomenon when the basic reproduction number is less than unity. But for the case of no re-infection, the model has a globally asymptotically stable disease-free equilibrium (DFE) when the basic reproduction number is less than unity. Furthermore, it is shown that in the case of no re-infection, a unique endemic equilibrium point (EEP) of the model exists which is globally asymptotically stable whenever the reproduction number is greater than unity. From the global sensitivity and uncertainty analysis, we have identified mask coverage, mask efficacy, vaccine coverage, vaccine efficacy, and contact rate as the most influential parameters influencing the spread of COVID-19. Numerical simulation results show that the use of effective vaccines with proper implementation of non-pharmaceutical interventions could lead to the elimination of COVID-19 from the community. Numerical simulations also suggest that the control strategy that ensures a continuous and effective mass vaccination program is the most cost-effective control strategy. The study also shows that in the presence of any co-morbidity and with the occurrence of re-infection, the disease burden may increase.

Dynamic Analysis of a VSEIR Model with Vaccination Efficacy and Immune Decline

Vaccination is an effective way to prevent the spread of infectious diseases. In this study, we formulate a VSEIR mathematical model to explore the effects of vaccination rate, vaccine efficacy, and immune decline on the COVID-19 transmission. The existence and stability criteria of equilibrium states were determined by analyzing the model. Model analysis was performed. One of the interesting phenomena involved in this issue is that diseases may or may not die out when the basic reproduction number falls below unity (i.e., a backward bifurcation may exist and cause multistability). The disease eventually becomes endemic in the population when the basic reproduction number exceeds one. By comparing different vaccination rates, vaccine efficacy, and infection rate factors, the diseases can be eliminated, not only by vaccines but also by strict protective measures. In addition, we used the COVID-19 number of reported cases in Xiamen in September 2021 to fit the model, and the model and the reported data were well matched.

Detection of neutralizing antibodies against multiple SARS-CoV-2 strains in dried blood spots using cell-free PCR

An easily implementable serological assay to accurately detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibodies is urgently needed to better track herd immunity, vaccine efficacy and vaccination rates. Herein, we report the Split-Oligonucleotide Neighboring Inhibition Assay (SONIA) which uses real-time qPCR to measure the ability of neutralizing antibodies to block binding between DNA-barcoded viral spike protein subunit 1 and the human angiotensin-converting enzyme 2 receptor protein. The SONIA neutralizing antibody assay using finger-prick dried blood spots displays 91–97% sensitivity and 100% specificity in comparison to the live-virus neutralization assays using matched serum specimens for multiple SARS-CoV-2 variants-of-concern. The multiplex version of this neutralizing antibody assay, using easily collectable finger-prick dried blood spots, can be a valuable tool to help reveal the impact of age, pre-existing health conditions, waning immunity, different vaccination schemes and the emergence of new variants-of-concern.