Effectiveness Of Vaccination Strategies Research Articles

Mathematical modeling to investigate the influence of vaccination and booster doses on the spread of Omicron

The emergence of new variants, such as Omicron, has raised concerns regarding the transmission dynamics of COVID-19 and the effectiveness of vaccination strategies. This paper proposes a mathematical model to investigate the impact of vaccination and booster doses on Omicron transmission dynamics, considering various infection compartments. The model incorporates multiple compartments representing different stages of infection, including susceptible individuals, vaccinated individuals, boosted individuals, and those infected with Omicron. The infection dynamics are captured by parameters such as vaccine efficacy, vaccination with booster received efficacy, and infection rate. Using mathematical analysis and numerical simulations, we explore how different vaccination and booster strategies affect the spread of Omicron. The normalized sensitivity analysis method of R0 is investigated to understand the importance of parameters in disease transmission. Furthermore, we assess the influence of infection compartments, such as asymptomatic and symptomatic cases, on overall transmission dynamics.

Impact of COVID-19 Pandemic Waves on Outcomes of Patients with Previously Untreated Advanced Follicular Lymphoma Enrolled in the Urban Ambispective Study in Italy

Introduction. URBAN [NCT04034056] is a non-interventional, retrospective/prospective study evaluating effectiveness and safety of obinutuzumab-based treatment in the standard clinical care of patients (pts) with previously untreated advanced Follicular Lymphoma (FL). The study is ongoing at 46 sites in Italy. The objective of this analysis was to evaluate the effects of COVID-19 pandemic in terms of infection rates and severity, outcomes, and effectiveness of vaccination strategies in the study population. The observation period encompasses the obinutuzumab-chemotherapy induction phase, the maintenance phase with bimonthly single-agent obinutuzumab, and 1-year follow-up period afterward. Methods. Data on COVID-19 vaccination, COVID-19 infections and outcomes (hospitalizations and deaths) were collected up to the cut-off date (CCOD) of 31-Jan-2022 and were analyzed overall, according to vaccination status, COVID-19 pandemic wave, and period. The following periods were considered: 25-Feb-2020 - 01-Mar-2021 (from the outbreak of pandemic up to the start of vaccination campaign for hematological patients), 01-Mar-2021 - 01-Nov-2021 (predominant delta variant of SARS-CoV-2), and 01-Nov-2021 - 31-Jan-2022 (predominant omicron variant). Comparisons of categorical variables were obtained by Chi-square or Fisher exact test. Results. Information on vaccination status was available for 270 of the 283 enrolled pts who had access to COVID-19 vaccines (BNT162b2, mRNA-1273 or ChAdOx1-S) during the study; 245 (90.7%) of them had received at least one dose of vaccine at CCOD (13.5%, 1 dose; 31.4%, 2 doses; 55.1%, 3 doses). Most of the doses (503/568, 88.6%) were given during obinutuzumab maintenance, since 207 pts had already initiated this phase in March 2021. Fifty-three pts (21.6% of those vaccinated) had at least one cycle delay due to vaccination and all cycle delays occurred during maintenance; no treatment delays were reported during induction. Median observation time for pts in the "unvaccinated" status (i.e. before vaccination or not vaccinated at all [pre/no-vax]) was 13.3 (8.7-23.2) months, while for pts in the "vaccinated" status (post-vax) was 7.9 (0-10.5) months. Overall, 48 COVID-19 infections were detected by swab in 45 pts, without any statistically significant correlation with age, ECOG PS, comorbidity, type of chemotherapy (CHOP, CVP or Bendamustine) or more recent tumor response. Among the 48 COVID-19 infections, 23 occurred in 22 unvaccinated pts and 18 in 17 vaccinated pts (time relationship with vaccination was not available for 7 infections). Overall, a fatal outcome was reported in 10 cases (22.2% of infected pts), including 9 cases (39.1%) among unvaccinated pts, and a single case (5.6%) in those vaccinated (p<0.001). Hospitalization due to COVID-19 was required for 22 infections (45.8%), 14 (60.9%) in pre/no-vax pts, and 5 (27.8%) in post-vax ones (p=0.073). Interestingly, no differences in COVID-19 infection rates have been observed between pts who were receiving obinutuzumab maintenance during the pandemic and those who did not (p=1.000). The table summarizes COVID-19 infections and their outcomes according to vaccination status and by pandemic periods. Conclusions. The URBAN retrospective/prospective study offered the unique opportunity to follow the impact of the evolving patterns of COVID-19 pandemic on a population of pts with advanced FL homogeneously treated with frontline obinutuzumab-based immunochemotherapy and maintenance. Specifically, we were able to gather the consequences of emerging SARS-CoV2 variants dynamically, before and after the availability of vaccines. From our results, the circulation of less aggressive COVID-19 variants and the increased vaccination coverage have led to better patients' outcomes, as observed in the healthy population, despite the B-cell lymphodepleting ability of obinutuzumab. Vaccination in FL pts enrolled in the study showed a protective effect in terms of rate of COVID-19-related risks for hospitalization and death. These findings should be interpreted with caution due to the variable concurrence of external factors, including different policies of contact restrictions, availability of diagnostic tests, and access to post-infection treatments across URBAN Centers during the analyzed periods. More data are currently being collected and will be presented at the conference. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Optimization of COVID-19 vaccination and the role of individuals with a high number of contacts: A model based approach.

We report strong evidence of the importance of contact hubs (or superspreaders) in mitigating the current COVID-19 pandemic. Contact hubs have a much larger number of contacts than the average in the population, and play a key role on the effectiveness of vaccination strategies. By using an age-structures compartmental SEIAHRV (Susceptible, Exposed, Infected symptomatic, Asymptomatic, Hospitalized, Recovered, Vaccinated) model, calibrated from available demographic and COVID-19 incidence, and considering separately those individuals with a much greater number of contacts than the average in the population, we show that carefully choosing who will compose the first group to be vaccinated can impact positively the total death toll and the demand for health services. This is even more relevant in countries with a lack of basic resources for proper vaccination and a significant reduction in social isolation. In order to demonstrate our approach we show the effect of hypothetical vaccination scenarios in two countries of very different scales and mitigation policies, Brazil and Portugal.

Severe Acute Respiratory Infections (SARI) surveillance in over-65-years-old patients: the experience of a University hospital (seasons 2017-2018 and 2018-2019).

Influenza is a relevant public health problem, also due to the risk of complications. The most effective measure to prevent influenza is vaccination; therefore, at present, there is consensus among European countries, regarding the need for routine seasonal influenza vaccination of elderly and individuals at increased risk of severe influenza. At the same time, influenza surveillance is necessary to understand the viruses circulating and effectiveness of vaccination strategies. The present study reports the results of two seasons influenza surveillance (2017/2018 and 2018/2019) conduced in an University Hospital in Rome among hospitalized patients aged ≥65 years. A prospective cohort study. The study consisted of systematic daily screening of all admissions among patients aged ≥65 years meeting a syndromic SARI case definition during two consecutive influenza seasons: 2017/2018 and 2018/2019. Characteristics of patients and their risk factors were collected by a standardized questionnaire and nose-pharyngeal swabs were performed to each patient. Influenza vaccine effectiveness (IVE), rates of vaccinated subjects and case fatality rate were also evaluated. Influenza was laboratory confirmed in 11 (9.9%) of the 111 and 11 (9.6%) of the 115 enrolled patients in seasons 2017/18 and 2018/19, respectively. Adjusted IVE against all influenza type, calculated for each season, was 88.5% (95% CI: 38.9 to 97.8) and 61.7% (95% CI: -59.9 to 90.9) for 2017/2018 and 2018/2019 seasons, respectively. Our analysis shows a Case Fatality Rate of 2.7% and 4.3% for the 2017/18 and 2018/19 seasons, respectively. The surveillance of SARI conduced in one hospital in Rome confirmed that influenza is an important cause of hospital admissions. Routine monitoring of infectious diseases and related aetiology associated with SARI, also at the local-level, is useful for targeting the right preventive measures.

An engineering model of the COVID-19 trajectory to predict the success of isolation initiatives.

Much media and societal attention is today focused on how to best control the spread of coronavirus (COVID-19). Every day brings us new data, and policy makers are implementing different strategies in different countries to manage the impact of COVID-19. To respond to the first 'wave' of infection, several countries, including the UK, opted for isolation/lockdown initiatives, with different degrees of rigour. Data showed that these initiatives have yielded the expected results in terms of containing the rapid trajectory of the virus. When this article was first prepared (April 2020), the affected societies were wondering when the isolation/lockdown initiatives should be lifted. While detailed epidemiological, economic as well as social studies would be required to answer this question completely, here we employ a simple engineering model. Albeit simple, the model is capable of reproducing the main features of the data reported in the literature concerning the COVID-19 trajectory in different countries, including the increase in cases in countries following the initially successful isolation/lockdown initiatives. Keeping in mind the simplicity of the model, we attempt to draw some conclusions, which seem to suggest that a decrease in the number of infected individuals after the initiation of isolation/lockdown initiatives does not necessarily guarantee that the virus trajectory is under control. Within the limit of this model, it would seem that rigid isolation/lockdown initiatives for the medium term would lead to achieving the desired control over the spread of the virus. This observation seems consistent with the 2020 summer months, during which the COVID-19 trajectory seemed to be almost under control across most European countries. Consistent with the results from our simple model, winter 2020 data show that the virus trajectory was again on the rise. Because the optimal solution will achieve control over the spread of the virus while minimising negative societal impacts due to isolation/lockdown, which include but are not limited to economic and mental health aspects, the engineering model presented here is not sufficient to provide the desired answer. However, the model seems to suggest that to keep the COVID-19 trajectory under control, a series of short-to-medium term isolation measures should be put in place until one or more of the following scenarios is achieved: a cure has been developed and has become accessible to the population at large; a vaccine has been developed, tested and distributed to large portions of the population; a sufficiently large portion of the population has developed resistance to the COVID-19 virus; or the virus itself has become less aggressive. It is somewhat remarkable that an engineering model, despite all its approximations, provides suggestions consistent with advanced epidemiological models developed by several experts in the field. The model proposed here is however not expected to be able to capture the emergence of variants of the virus, which seem to be responsible for significant outbreaks, notably in India, in the spring of 2021, it cannot describe the effectiveness of vaccine strategies, as it does not differentiate among different age groups within the population, nor does it allow us to consider the duration of the immunity achieved after infection or vaccination.

Guidelines for analysis of low-frequency antigen-specific T cell results: Dye-based proliferation assay vs 3H-thymidine incorporation

It is generally recognized that dysregulation of the immune system plays a critical role in many diseases, including autoimmune diseases and cancer. T cells play a crucial role in maintaining self-tolerance, while loss of immune tolerance and T cell activation can lead to severe inflammation and tissue damage. T cell responses have a key role in the effectiveness of vaccination strategies and immunomodulating therapies. Immunomonitoring methods have the ability to elucidate immunological processes, monitor the development of disease and assess therapeutic effects. In this respect, it is of particular interest to evaluate antigen (Ag)-specific T cells by determining their frequency, type and functionality in cellular assays. Nevertheless, Ag-specific T cells are detected infrequently in most diseases using current techniques. Many efforts have been made to develop more sensitive, reproducible, and reliable methods for Ag-specific T cell detection. It has been found that analysis of cellular proliferation can be a useful tool to determine the presence and frequency of Ag-specific T cell and to provides insight into modulation of the T cell response by a specific antigen or therapy. However, the selection of a cut-off value for a positive response and therefore a more accurate interpretation of the data, continues to be a major concern. Here, we provide guidelines to select a proper cut-off for monitoring of Ag-specific CD4+ T cell responses.In vitro Ag-stimulation has been assessed with two methods; a dye-based proliferation assay and 3H-thymidine-based assay. Two cut-off approaches are compared; mean and variance of control wells, and the stimulation index. By evaluating the proliferative response to the in vitro Ag-stimulation using these two methods, we demonstrate the importance of taking into consideration the variability of the control wells to distinguish a positive from a false positive response.

Effect of vaccination strategies on the dynamic behavior of epidemic spreading and vaccine coverage

The transmission of infectious, yet vaccine-preventable, diseases is a typical complex social phenomenon, where the increasing level of vaccine update in the population helps to inhibit the epidemic spreading, which in turn, however, discourages more people to participate in vaccination campaigns, due to the “externality effect” raised by vaccination. We herein study the impact of vaccination strategies, pure, continuous (rather than adopt vaccination definitely, the individuals choose to taking vaccine with some probabilities), or continuous with randomly mutation, on the vaccination dynamics with a spatial susceptible-vaccinated-infected-recovered (SVIR) epidemiological model. By means of extensive Monte-Carlo simulations, we show that there is a crossover behavior of the final vaccine coverage between the pure-strategy case and the continuous-strategy case, and remarkably, both the final vaccination level and epidemic size in the continuous-strategy case are less than them in the pure-strategy case when vaccination is cheap. We explain this phenomenon by analyzing the organization process of the individuals in the continuous-strategy case in the equilibrium. Our results are robust to the SVIR dynamics defined on other spatial networks, like the Erdős–Rényi and Barabási–Albert networks.

Impact of uncertainty in foot and mouth disease indirect transmission probability on outbreak duration and number of herds depopulated

The central United States (US) has a large livestock population including cattle, swine, sheep, and goats that are susceptible to foot and mouth disease (FMD). Because FMD is a highly infective foreign animal disease, the only method to assess the impact of an introduction and the effectiveness of control programs is via modeling. We developed simulation scenarios to assess the impact of the introduction of FMD in the central US and the effect of vaccination strategies and variation in biosecurity on FMD outbreaks using the North American Animal Disease Spread Model (NAADSM), a spatially explicit, stochastic infectious disease model.

O10.2 A Community-Randomised Phase IV Human Papillomavirus (HPV) Vaccination Trial of Vaccination Strategy

High-risk human papillomavirus (hrHPV) is the 2nd leading cause of cancer in women Bivalent Cervarix™ vaccine is highly efficacious against hrHPVs and associated precancers. Mathematical models disagree about the best...

SIR-SVS epidemic models with continuous and impulsive vaccination strategies

Vaccination is important for the control of some infectious diseases. This paper considers two SIR-SVS epidemic models with vaccination, where it is assumed that the vaccination for the newborns is continuous in the two models, and that the vaccination for the susceptible individuals is continuous and impulsive, respectively. The basic reproduction numbers of two models, determining whether the disease dies out or persists eventually, are all obtained. For the model with continuous vaccination for the susceptibles, the global stability is proved by using the Lyapunov function. Especially for the endemic equilibrium, to prove the negative definiteness of the derivative of the Lyapunov function for all the feasible values of parameters, it is expressed in three different forms for all the feasible values of parameters. For the model with pulse vaccination for the susceptibles, the global stability of the disease free periodic solution is proved by the comparison theorem of impulsive differential equations. At last, the effect of vaccination strategies on the control of the disease transmission is discussed, and two types of vaccination strategies for the susceptible individuals are also compared.

Vaccination strategies for solid tumors--fundamentals, limitations, and recent results

Recent studies clearly prove the existence of cancer immunosurveillance and justify renewed hope for the development of effective vaccination therapies for solid tumors. The identification of tumor-associated antigens has provided researchers with promising targets for T cell-based immunotherapies. New monitoring techniques will facilitate the correlation of immunological effectiveness of vaccination strategies with clinical results. In order to acchieve greater immunological effectiveness, a tumor vaccine should incorporate both CD4+ and CD8+ epitopes. Adjuvants should be systematically tested for their potential to break immunological tolerance and mechanisms that enable cancer cells to escape from immunosurveillance should be further investigated. This approach will open new perspectives in the development of tumor vaccines for solid tumors. At the same time, future vaccination studies should include patients in earlier stages of their disease or in the adjuvant setting in order to avoid on overwhelming effect of mechanisms that help tumors to evade immunosurveillance.

Simulation model of rubella––the effects of vaccination strategies

The paper presents the construction of a deterministic multistage simulation model with age and sex structure. The model is based on the natural history of rubella. The dynamics of rubella is described by a system of non-linear differential equations. The model was validated by simulating the course of rubella in Trešnjevka, Zagreb, from 1961 to 1991. For the purposes of simulations, the epidemiological parameters commonly accepted to apply to the rubella were used; epidemiological classes, coefficients of transfer among the classes, and durations of stay in the classes; only the force of infection was estimated by iterative simulation until the average observed incidence in non-epidemic and epidemic years was reproduced within computational error. The force of infection was age and sex dependent. The effects of three different vaccination strategies were simulated.

Simulation studies of African horse sickness in Spain.

Factors affecting epidemics of African horse sickness in Spain were studied using a mathematical model. The model examined the likelihood of an epidemic after the introduction of the virus, and the effectiveness of vaccination strategies. Two host species (horses and donkeys) and one vector species (the biting midge Culicoides imicola) were included. A stratified random sampling method (Latin hypercube sampling) was used for sensitivity analysis of the likelihood of an epidemic. Systematic variation of vaccination parameters was used to consider alternative control strategies. In general, when an epidemic occurred most potential hosts became infected. The peak prevalence in C. imicola was low, and never exceeded 3%. The most significant factors in the likelihood of an epidemic were vector population size, the recovery rate in horses and the time of year when the virus was introduced. The lag between virus introduction and protection, the proportion of hosts vaccinated, and including donkeys in vaccination programmes where the factors that most strongly affected the success of different vaccination strategies. These factors should be priorities for empirical research, and should be considered in the design of control strategies in areas at risk of virus introduction.