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BACKGROUND: In Hungary, although six types of vaccines were widely available, the percentage of people receiving the primary series of COVID-19 vaccination remained below the EU average. This paper investigates the reasons for Hungary's lower vaccination coverage by exploring changing attitudes towards vaccination, socio-demographic determinants, and individual reasons for non-acceptance during the 3rd - 5th pandemic waves of COVID-19. METHODS: The study's empirical analysis is based on representative surveys conducted in Hungary between February 19, 2021, and June 30, 2022. The study used a total of 17 surveys, each with a sample size of at least 1000 respondents. Binomial logistic regression models were used to investigate which socio-demographic characteristics are most likely to influence vaccine hesitancy in Hungary. The study analysed 2506 open-ended responses to identify reasons for vaccine non-acceptance. The responses were categorised into four main categories and 13 sub-categories. RESULTS: Between the third and fifth wave of the pandemic, attitudes towards COVID-19 vaccination have significantly changed. Although the proportion of vaccinated individuals has increased steadily, the percentage of individuals who reported not accepting the vaccine has remained almost unchanged. Socio-demographic characteristics were an important determinant of the observed vaccine hesitancy, although they remained relatively stable over time. Individuals in younger age groups and those with lower socioeconomic status were more likely to decline vaccination, while those living in the capital city were the least likely. A significant reason behind vaccine refusal can undoubtedly be identified as lack of trust (specifically distrust in science), facing an information barrier and the perception of low personal risk. CONCLUSION: Although compulsory childhood vaccination coverage is particularly high in Hungary, voluntary adult vaccines, such as the influenza and COVID-19 vaccines, are less well accepted. Vaccine acceptance is heavily affected by the social-demographic characteristics of people. Mistrust and hesitancy about COVID-19 vaccines, if not well managed, can easily affect people's opinion and acceptance of other vaccines as well. Identifying and understanding the complexity of how vaccine hesitancy evolved during the pandemic can help to understand and halt the decline in both COVID-19 and general vaccine confidence by developing targeted public health programs to address these issues.
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Vacinas contra COVID-19 , COVID-19 , Fatores Socioeconômicos , Hesitação Vacinal , Humanos , Hungria , COVID-19/prevenção & controle , COVID-19/epidemiologia , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Hesitação Vacinal/psicologia , Hesitação Vacinal/estatística & dados numéricos , Vacinas contra COVID-19/administração & dosagem , Adulto Jovem , Adolescente , Idoso , Inquéritos e Questionários , Pandemias/prevenção & controle , Vacinação/estatística & dados numéricos , Vacinação/psicologia , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Aceitação pelo Paciente de Cuidados de Saúde/psicologiaRESUMO
Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution of PanSim allows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.
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COVID-19/terapia , Modelos Teóricos , Adolescente , Adulto , Idoso , Algoritmos , COVID-19/epidemiologia , COVID-19/virologia , Criança , Humanos , Pessoa de Meia-Idade , Pandemias , Quarentena , SARS-CoV-2/isolamento & purificação , Adulto JovemRESUMO
Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the treatment. Due to chemotherapeutic agents, resistance can emerge by Darwinian evolution. Besides this, acquired drug resistance may arise via changes in gene expression. A recent discovery in cancer research uncovered a third possibility, indicating that this phenotype conversion can occur through the transfer of microvesicles from resistant to sensitive cells, a mechanism resembling the spread of an infectious agent. We present a model describing the evolution of sensitive and resistant tumour cells considering Darwinian selection, Lamarckian induction and microvesicle transfer. We identify three threshold parameters which determine the existence and stability of the three possible equilibria. Using a simple Dulac function, we give a complete description of the dynamics of the model depending on the three threshold parameters. We also establish an agent based model as a spatial version of the ODE model and compare the outputs of the two models. We find that although the ODE model does not provide spatial information about the structure of the tumour, it is capable to determine the outcome in terms of tumour size and distribution of cell types. We demonstrate the possible effects of increasing drug concentration, and characterize the possible bifurcation sequences. Our results show that the presence of microvesicle transfer cannot ruin a therapy that otherwise leads to extinction, however it may doom a partially successful therapy to failure.
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Antineoplásicos , Neoplasias , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Resistencia a Medicamentos Antineoplásicos/genética , Humanos , Neoplasias/tratamento farmacológico , Fenótipo , Seleção GenéticaRESUMO
Immunity following natural infection or immunization may wane, increasing susceptibility to infection with time since infection or vaccination. Symptoms, and concomitantly infectiousness, depend on residual immunity. We quantify these phenomena in a model population composed of individuals whose susceptibility, infectiousness, and symptoms all vary with immune status. We also model age, which affects contact, vaccination and possibly waning rates. The resurgences of pertussis that have been observed wherever effective vaccination programs have reduced typical disease among young children follow from these processes. As one example, we compare simulations with the experience of Sweden following resumption of pertussis vaccination after the hiatus from 1979 to 1996, reproducing the observations leading health authorities to introduce booster doses among school-aged children and adolescents in 2007 and 2014, respectively. Because pertussis comprises a spectrum of symptoms, only the most severe of which are medically attended, accurate models are needed to design optimal vaccination programs where surveillance is less effective.
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Coqueluche , Adolescente , Criança , Pré-Escolar , Humanos , Imunização , Programas de Imunização , Imunização Secundária , Vacinação , Coqueluche/epidemiologia , Coqueluche/prevenção & controleRESUMO
The management of COVID-19 appears to be a long-term challenge, even in countries that have managed to suppress the epidemic after their initial outbreak. In this paper, we propose a model predictive approach for the constrained control of a nonlinear compartmental model that captures the key dynamical properties of COVID-19. The control design uses the discrete-time version of the epidemic model, and it is able to handle complex, possibly time-dependent constraints, logical relations between model variables and multiple predefined discrete levels of interventions. A state observer is also constructed for the computation of non-measured variables from the number of hospitalized patients. Five control scenarios with different cost functions and constraints are studied through numerical simulations, including an output feedback configuration with uncertain parameters. It is visible from the results that, depending on the cost function associated with different policy aims, the obtained controls correspond to mitigation and suppression strategies, and the constructed control inputs are similar to real-life government responses. The results also clearly show the key importance of early intervention, the continuous tracking of the susceptible population and that of future work in determining the true costs of restrictive control measures and their quantitative effects.
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The use of multiple vaccine doses has proven to be essential in providing high levels of protection against a number of vaccine-preventable diseases at the individual level. However, the effectiveness of vaccination at the population level depends on several key factors, including the dose-dependent protection efficacy of vaccine, coverage of primary and booster doses, and in particular, the timing of a booster dose. For vaccines that provide transient protection, the optimal scheduling of a booster dose remains an important component of immunization programs and could significantly affect the long-term disease dynamics. In this study, we developed a vaccination model as a system of delay differential equations to investigate the effect of booster schedule using a control parameter represented by a fixed time-delay. By exploring the stability analysis of the model based on its reproduction number, we show the disease persistence in scenarios where the booster dose is sub-optimally scheduled. The findings indicate that, depending on the protection efficacy of primary vaccine series and the coverage of booster vaccination, the time-delay in a booster schedule can be a determining factor in disease persistence or elimination. We present model results with simulations for a vaccine-preventable bacterial disease, Heamophilus influenzae serotype b, using parameter estimates from the previous literature. Our study highlights the importance of timelines for multiple-dose vaccination in order to enhance the population-wide benefits of herd immunity.
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Infecções por Haemophilus/prevenção & controle , Vacinas Anti-Haemophilus/administração & dosagem , Imunização Secundária/estatística & dados numéricos , Vacinação em Massa/estatística & dados numéricos , Modelos Estatísticos , Erradicação de Doenças/organização & administração , Infecções por Haemophilus/epidemiologia , Infecções por Haemophilus/microbiologia , Haemophilus influenzae/imunologia , Humanos , Esquemas de Imunização , Vacinação em Massa/organização & administração , Fatores de Tempo , Cobertura Vacinal/organização & administração , Cobertura Vacinal/estatística & dados numéricosRESUMO
The Mackey-Glass equation is the representative example of delay induced chaotic behavior. Here, we propose various control mechanisms so that otherwise erratic solutions are forced to converge to the positive equilibrium or to a periodic orbit oscillating around that equilibrium. We take advantage of some recent results of the delay differential literature, when a sufficiently large domain of the phase space has been shown to be attractive and invariant, where the system is governed by monotone delayed feedback and chaos is not possible due to some Poincaré-Bendixson type results. We systematically investigate what control mechanisms are suitable to drive the system into such a situation and prove that constant perturbation, proportional feedback control, Pyragas control, and state dependent delay control can all be efficient to control Mackey-Glass chaos with properly chosen control parameters.
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Identifying the steady states of a population is a key issue in theoretical ecology, that includes the study of spatially heterogeneous populations. There are several examples of real ecosystems in patchy environments where the habitats are heterogeneous in their local density dependence. We investigate a multi-patch model of a single species with spatial dispersal, where the growth of the local population is logistic in some localities (negative density dependence) while other patches exhibit a strong Allee effect (positive density dependence). When the local dynamics is logistic in each patch and the habitats are interconnected by dispersal then the total population has only the extinction steady state and a componentwise positive equilibrium, corresponding to persistence in each patch. We show that animal populations in patchy environments can have a large number of steady states if local density dependence varies over the locations. It is demonstrated that, depending on the network topology of migration routes between the patches, the interaction of spatial dispersal and local density dependence can create a variety of coexisting stable positive equilibria. We give a detailed description of the multiple ways dispersal can rescue local populations from extinction.
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Ecossistema , Modelos Biológicos , Dinâmica Populacional , Animais , Ecologia , Densidade Demográfica , Crescimento DemográficoRESUMO
Many observational studies suggest that seasonal migratory birds play an important role in spreading Ixodes scapularis, a vector of Lyme disease, along their migratory flyways, and they are believed to be responsible for geographic range expansion of I. scapularis in Canada. However, the interplay between the dynamics of I. scapularis on land and migratory birds in the air is not well understood. In this study, we develop a periodic delay meta-population model which takes into consideration the local landscape for tick reproduction within patches and the times needed for ticks to be transported by birds between patches. Assuming that the tick population is endemic in the source region, we find that bird migration may boost an already established tick population at the subsequent region and thus increase the risk to humans, or bird migration may help ticks to establish in a region where the local landscape is not appropriate for ticks to survive in the absence of bird migration, imposing risks to public health. This theoretical study reveals that bird migration plays an important role in the geographic range expansion of I. scapularis, and therefore our findings may suggest some strategies for Lyme disease prevention and control.
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Migração Animal , Aves/parasitologia , Ixodes/patogenicidade , Animais , Vetores Aracnídeos , Canadá , Simulação por Computador , Humanos , Ixodes/microbiologia , Doença de Lyme/transmissão , Conceitos Matemáticos , Modelos Biológicos , Dinâmica Populacional , Estações do AnoRESUMO
In this Letter, a generalization of pairwise models to non-Markovian epidemics on networks is presented. For the case of infectious periods of fixed length, the resulting pairwise model is a system of delay differential equations, which shows excellent agreement with results based on stochastic simulations. Furthermore, we analytically compute a new R_{0}-like threshold quantity and an analytical relation between this and the final epidemic size. Additionally, we show that the pairwise model and the analytic results can be generalized to an arbitrary distribution of the infectious times, using integro-differential equations, and this leads to a general expression for the final epidemic size. By showing the rigorous link between non-Markovian dynamics and pairwise delay differential equations, we provide the framework for a more systematic understanding of non-Markovian dynamics.
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We formulate an epidemic model for the spread of an infectious disease along with population dispersal over an arbitrary number of distinct regions. Structuring the population by the time elapsed since the start of travel, we describe the infectious disease dynamics during transportation as well as in the regions. As a result, we obtain a system of delay differential equations. We define the basic reproduction number R(0) as the spectral radius of a next generation matrix. For multi-regional systems with strongly connected transportation networks, we prove that if R(0) ≤ 1 then the disease will be eradicated from each region, while if R(0) > 1 there is a globally asymptotically stable equilibrium, which is endemic in every region. If the transportation network is not strongly connected, then the model analysis shows that numerous endemic patterns can exist by admitting a globally asymptotically stable equilibrium, which may be disease free in some regions while endemic in other regions. We provide a procedure to detect the disease free and the endemic regions according to the network topology and local reproduction numbers. The main ingredients of the mathematical proofs are the inductive applications of the theory of asymptotically autonomous semiflows and cooperative dynamical systems. We visualise stability boundaries of equilibria in a parameter plane to illustrate the influence of the transportation network on the disease dynamics. For a system consisting of two regions, we find that due to spatial heterogeneity characterised by different local reproduction numbers, R(0) may depend non-monotonically on the dispersal rates, thus travel restrictions are not always beneficial.
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Doenças Transmissíveis/transmissão , Modelos Biológicos , Meios de Transporte , Número Básico de Reprodução/estatística & dados numéricos , Doenças Transmissíveis/epidemiologia , Epidemias/estatística & dados numéricos , Saúde Global/estatística & dados numéricos , Humanos , Conceitos Matemáticos , Dinâmica Populacional/estatística & dados numéricos , Meios de Transporte/estatística & dados numéricos , Viagem/estatística & dados numéricosRESUMO
Optimizing vaccination impact during an emerging disease becomes crucial when vaccine supply is limited, and robust protection requires multiple doses. Facing this challenge during the early stages of the COVID-19 vaccine deployment, a pivotal policy question arose: whether to administer a single dose to a larger proportion of the population by deferring the second dose, or to prioritize stronger protection for a smaller subset of the population with the established dosing interval from clinical trials. Using a delay-differential model and considering waning immunity and distribution capacity, we compared these strategies. We found that the efficacy of the first dose significantly influences the impact of delaying the second dose. Even for a relatively low efficacy of the first dose, a delayed strategy may outperform vaccination with the recommended dosing interval in reducing short-term hospitalizations and deaths despite increase in infections. The optimal delay, however, depends on the specific outcome measured and timelines within which the vaccination strategy is evaluated. We found transition lines for the relative reduction of infection, hospitalization and death below which vaccination with the recommended schedule is the preferred strategy. In a realistic parameter space, our results highlight scenarios in which the conclusions of previous studies are invalid.
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BACKGROUND: Two prefusion F protein-based vaccines, Arexvy and Abrysvo, have been approved by Health Canada for protecting older adults against respiratory syncytial virus (RSV)-associated lower respiratory tract disease. We estimated the health benefits and cost-effectiveness of these vaccines under a publicly funded single-dose vaccination program in Ontario that targets residents of long-term care homes (LTCHs). Additionally, we evaluated an extended program that broadens vaccination to include community-dwelling older adults. METHODS: A discrete-event simulation model was parameterised with the burden of RSV disease including outpatient care, hospitalisation, and death among adults aged 60 years or older in Ontario, Canada. Accounting for direct and indirect costs (in 2023 Canadian dollars) associated with RSV-related outcomes, we calculated the net monetary benefit using quality-adjusted life-year (QALY) gained, and determined the range of price-per-dose (PPD) for vaccination programs to be cost-effective from both healthcare and societal perspectives over two RSV seasons. The incremental cost-effectiveness ratio (ICER) was calculated to estimate the additional costs required to gain one QALY. RESULTS: Using a willingness-to-pay of $50,000 per QALY gained, we found that vaccinating 90% of residents in LTCHs with Arexvy would be cost-effective from a societal perspective for a PPD up to $163, producing a mean ICER value of $49,984 (95% CI: $47,539 to $52,704) per QALY gained with a two-year budget impact of $463,468 per 100,000 older adults. The reduction of hospitalizations was estimated at 7.0% compared to the no-vaccination scenario. Extending the program to include community-dwelling older adults with a 74% coverage akin to influenza vaccination, Arexvy remains cost-effective for a PPD up to $139, with a mean ICER value of $49,698 (95% CI: 48,022 to 51,388) per QALY gained and a two-year budget impact of $8.63 million. Compared to the no-vaccination scenario, the extended program resulted in a 57.3% reduction in RSV-related hospitalisations. CONCLUSIONS: Vaccinating residents of LTCHs against RSV disease would be cost-effective depending on PPD; extending the program to community-dwelling older adults would provide substantial health benefits, averting significant direct healthcare costs and productivity losses.
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Doenças Transmissíveis , Infecções por Vírus Respiratório Sincicial , Vacinas contra Vírus Sincicial Respiratório , Vírus Sincicial Respiratório Humano , Vacinas , Vacinas Virais , Humanos , Idoso , Análise Custo-Benefício , Ontário , Infecções por Vírus Respiratório Sincicial/prevenção & controle , Vacinação , Anos de Vida Ajustados por Qualidade de VidaRESUMO
COVID-19, caused by SARS-CoV-2, manifests with differing severity across distinct patient subgroups, with outcomes influenced by underlying comorbidities such as cancer, which may cause functional and compositional alterations of the immune system during tumor progression. We aimed to investigate the association of SARS-CoV-2 infection and its complications with cancer in a large autopsy series and the role of COVID-19 in the fatal sequence leading to death. A total of 2641 adult autopsies were investigated, 539 of these were positive for SARS-CoV-2. Among the total number of patients analyzed, 829 had active cancer. Overall, the cohort included 100 patients who simultaneously had cancer and SARS-CoV-2 infection. The course of COVID-19 was less severe in cancer patients, including a significantly lower incidence of viral and bacterial pneumonia, occurring more frequently as a contributory disease or coexisting morbidity, or as SARS-CoV-2 positivity without viral disease. SARS-CoV-2 positivity was more frequent among non-metastatic than metastatic cancer cases, and in specific tumor types including hematologic malignancies. COVID-19 was more frequently found to be directly involved in the fatal sequence in patients undergoing active anticancer therapy, but less frequently in perioperative status, suggesting that the underlying malignancy and consequent surgery are more important factors leading to death perioperatively than viral disease. The course of COVID-19 in cancer patients was milder and balanced during the pandemic. This may be due to relative immunosuppressed status, and the fact that even early/mild viral infections can easily upset their condition, leading to death from their underlying cancer or its complications.
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Monitoring the effective reproduction number [Formula: see text] of a rapidly unfolding pandemic in real-time is key to successful mitigation and prevention strategies. However, existing methods based on case numbers, hospital admissions or fatalities suffer from multiple measurement biases and temporal lags due to high test positivity rates or delays in symptom development or administrative reporting. Alternative methods such as web search and social media tracking are less directly indicating epidemic prevalence over time. We instead record age-stratified anonymous contact matrices at a daily resolution using a longitudinal online-offline survey in Hungary during the first two waves of the COVID-19 pandemic. This approach is innovative, cheap, and provides information in near real-time for estimating [Formula: see text] at a daily resolution. Moreover, it allows to complement traditional surveillance systems by signaling periods when official monitoring infrastructures are unreliable due to observational biases.
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COVID-19 , Humanos , COVID-19/epidemiologia , Pandemias , Número Básico de Reprodução , Hospitalização , HungriaRESUMO
Various measures have been implemented around the world to prevent the spread of SARS-CoV-2. A potential tool to reduce disease transmission is regular mass testing of a high percentage of the population, possibly with pooling (testing a compound of several samples with one single test). We develop a compartmental model to study the applicability of this method and compare different pooling strategies: regular and Dorfman pooling. The model includes isolated compartments as well, from where individuals rejoin the active population after some time delay. We develop a method to optimize Dorfman pooling depending on disease prevalence and establish an adaptive strategy to select variable pool sizes during the course of the epidemic. It is shown that optimizing the pool size can avert a significant number of infections. The adaptive strategy is much more efficient, and may prevent an epidemic outbreak even in situations when a fixed pool size strategy can not.
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COVID-19 , COVID-19/epidemiologia , Surtos de Doenças , Modelos Epidemiológicos , Humanos , Prevalência , SARS-CoV-2RESUMO
The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices, usually stratified by age, summarise interaction motifs efficiently, but their collection relies on conventional representative survey techniques, which are expensive and slow to obtain. Here we report a data collection effort involving over [Formula: see text] of the Hungarian population to simultaneously record contact matrices through a longitudinal online and sequence of representative phone surveys. To correct non-representative biases characterising the online data, by using census data and the representative samples we develop a reconstruction method to provide a scalable, cheap, and flexible way to dynamically obtain closer-to-representative contact matrices. Our results demonstrate that although some conventional socio-demographic characters correlate significantly with the change of contact numbers, the strongest predictors can be collected only via surveys techniques and combined with census data for the best reconstruction performance. We demonstrate the potential of combined online-offline data collections to understand the changing behavioural responses determining the future evolution of the outbreak, and to inform epidemic models with crucial data.
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COVID-19 , Pandemias , COVID-19/epidemiologia , Censos , Surtos de Doenças , Humanos , Inquéritos e QuestionáriosRESUMO
SIRS models capture transmission dynamics of infectious diseases for which immunity is not lifelong. Extending these models by a W compartment for individuals with waning immunity, the boosting of the immune system upon repeated exposure may be incorporated. Previous analyses assumed identical waning rates from R to W and from W to S. This implicitly assumes equal length for the period of full immunity and of waned immunity. We relax this restriction, and allow an asymmetric partitioning of the total immune period. Stability switches of the endemic equilibrium are investigated with a combination of analytic and numerical tools. Then, continuation methods are applied to track bifurcations along the equilibrium branch. We find rich dynamics: Hopf bifurcations, endemic double bubbles, and regions of bistability. Our results highlight that the length of the period in which waning immunity can be boosted is a crucial parameter significantly influencing long term epidemiological dynamics.
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Doenças Transmissíveis , Modelos Biológicos , Doenças Transmissíveis/epidemiologia , Humanos , Sistema ImunitárioRESUMO
Paxlovid is a promising, orally bioavailable novel drug for SARS-CoV-2 with excellent safety profiles. Our main goal here is to explore the pharmacometric features of this new antiviral. To provide a detailed assessment of Paxlovid, we propose a hybrid multiscale mathematical approach. We demonstrate that the results of the present in silico evaluation match the clinical expectations remarkably well: on the one hand, our computations successfully replicate the outcome of an actual in vitro experiment; on the other hand, we verify both the sufficiency and the necessity of Paxlovid's two main components (nirmatrelvir and ritonavir) for a simplified in vivo case. Moreover, in the simulated context of our computational framework, we visualize the importance of early interventions and identify the time window where a unit-length delay causes the highest level of tissue damage. Finally, the results' sensitivity to the diffusion coefficient of the virus is explored in detail.
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Tratamento Farmacológico da COVID-19 , SARS-CoV-2 , Antivirais/farmacologia , Combinação de Medicamentos , Humanos , Lactamas , Leucina , Nitrilas , Prolina , Ritonavir/farmacologiaRESUMO
Several studies have reported the waning effectiveness of COVID-19 vaccines. This study aims to demonstrate the applicability of the screening method for estimating vaccine effectiveness (VE) in a pandemic. We report VE in Hungary, estimated with the screening method, in 2021, covering a period of Alpha and the Delta variant, including the booster dose roll-out. Hungary is in a unique position to use six different vaccines in the same population. All vaccines provided a high level of protection initially, which declined over time. While the picture is different in each age group, the waning of immunity is apparent for all vaccines, especially in the younger age groups and the Sinopharm, Sputnik-V, and AstraZeneca vaccines, which performed similarly. This is clearly reversed by booster doses, more prominent for those three vaccines, where the decline in protection is more evident. Overall, two vaccines, Pfizer/BioNTech and Moderna, tend to produce the best results in all age groups, even with waning immunity considered. Using the screening method in future pandemic waves is worthwhile, especially in countries struggling with a lack of resources or when there is a need to deliver VE results within a short timeframe due to urgent decision-making.