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In this paper we examine several definitions of vaccine efficacy (VE) that we found in the literature, for diseases that express themselves in outbreaks, that is, when the force of infection grows in time, reaches a maximum and then vanishes. The fact that the disease occurs in outbreaks results in several problems that we analyse. We propose a mathematical model that allows the calculation of VE for several scenarios. Vaccine trials usually needs a large number of volunteers that must be enrolled. Ideally, all volunteers should be enrolled in approximately the same time, but this is generally impossible for logistic reasons and they are enrolled in a fashion that can be replaced by a continuous density function (for example, a Gaussian function). The outbreak can also be replaced by a continuous density function, and the use of these density functions simplifies the calculations. Assuming, for example Gaussian functions, one of the problems one can immediately notice is that the peak of the two curves do not occur at the same time. The model allows us to conclude: First, the calculated vaccine efficacy decreases when the force of infection increases; Second, the calculated vaccine efficacy decreases when the gap between the peak in the force of infection and the peak in the enrollment rate increases; Third, different trial protocols can be simulated with this model; different vaccine efficacy definitions can be calculated and in our simulations, all result are approximately the same. The final, and perhaps most important conclusion of our model, is that vaccine efficacy calculated during outbreaks must be carefully examined and the best way we can suggest to overcome this problem is to stratify the enrolled volunteer's in a cohort-by-cohort basis and do the survival analysis for each cohort, or apply the Cox proportional hazards model for each cohort.

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Many molecular mechanisms that lead to the host antibody response to COVID-19 vaccines remain largely unknown. In this study, we used serum antibody detection combined with whole blood RNA-based transcriptome analysis to investigate variability in vaccine response in healthy recipients of a booster (third) dose schedule of the mRNA BNT162b2 vaccine against COVID-19. The cohort was divided into two groups: (1) low-stable individuals, with antibody concentration anti-SARS-CoV IgG S1 below 0.4 percentile at 180 days after boosting vaccination; and (2) high-stable individuals, with antibody values greater than 0.6 percentile of the range in the same period (median 9525 [185-80,000] AU/mL). Differential gene expression, expressed single nucleotide variants and insertions/deletions, differential splicing events, and allelic imbalance were explored to broaden our understanding of the immune response sustenance. Our analysis revealed a differential expression of genes with immunological functions in individuals with low antibody titers, compared to those with higher antibody titers, underscoring the fundamental importance of the innate immune response for boosting immunity. Our findings also provide new insights into the determinants of the immune response variability to the SARS-CoV-2 mRNA vaccine booster, highlighting the significance of differential splicing regulatory mechanisms, mainly concerning HLA alleles, in delineating vaccine immunogenicity.

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This study shows that the distribution of CYP3A5 alleles (*1, *3, *6 and *7) and genotype-predicted CYP3A5 phenotypes vary significantly across Latin American cohorts (Brazilians and the One Thousand Genomes Admixed American superpopulation), as well as among subcohorts comprising individuals with the highest proportions of Native, European or sub-Saharan African ancestry. Differences in biogeographical ancestry across the study groups are the likely explanation for these results. The differential distribution of CYP3A5 phenotypes has major pharmacogenomic implications, affecting the proportion of individuals carrying high risk CYP3A5 phenotypes for the immunosuppressant tacrolimus and the number of patients that would need to be genotyped to prevent acute rejection in kidney transplant recipients under tacrolimus treatment.

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BACKGROUND: After validation in multiple types of liver disease patients, the MELD score was adopted as a standard by which liver transplant candidates with end-stage liver disease were prioritized for organ allocation in the United States since 2002, and in Brazil, since 2006. AIMS: To analyze the mortality profile of patients on the liver transplant waiting list correlated to MELD score at the moment of transplantation. METHODS: This study used the data from the Secretary of Health of the São Paulo State, Brazil, which listed 22,522 patients, from 2006 (when MELD score was introduced in Brazil) until June 2009. Patients with acute hepatic failure and tumors were included as well. We also considered the mortality of both non-transplanted and transplanted patients as a function of the MELD score at presentation. RESULTS: Our model showed that the best MELD score for patients on the liver transplant waiting list associated to better results after liver transplantation was 26. CONCLUSIONS: We found that the best score for applying to liver transplant waiting list in the State of São Paulo was 26. This is the score that minimizes the mortality in both non-transplanted and liver transplanted patients.

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OBJECTIVE: To present theoretical-methodological reflections on the elaboration, types, and functions of theoretical models as well as their conceptual and analytic frameworks. METHODS: This is an essay, whose material collection was carried out in a non-systematic way, by electing studies exclusively based on the line of argument and reflection that the authors intend to submit to appreciation and public debate. RESULTS: We present reflections on the types and functions of theoretical models, theoretical foundations in research, and reflections on the importance of theoretical models for public health research and their relation with the process of elaboration, development, and reporting in scientific studies. In addition, we describe types of theoretical models referring to the conceptual and empirical levels and the important elaboration and description of their combination for scientific practice. CONCLUSION: With this article, our intention is to stimulate discussions and reflections on current methods that permeate scientific practice and encourage the use of Theoretical Models as a basis for scientific research in its elaboration, development, and reporting process.

OBJETIVO: Apresentar reflexões teórico-metodológicas sobre elaboraçõo, tipos e funções dos modelos teóricos, bem como suas estruturas conceituais e de análise. MÉTODOS: Trata-se de um ensaio cujo processo de coleta do material foi realizado de forma não sistemática, eleito exclusivamente e baseado na linha de argumentaçõo e reflexão que os autores pretendem submeter à apreciaçõo e ao debate público. RESULTADOS: Este trabalho apresenta reflexões sobre tipos e funções dos modelos teóricos, fundamentaçõo teórica nas pesquisas e reflexões sobre a importância dos modelos teóricos para as pesquisas em saúde pública e sua relaçõo com o processo de elaboraçõo, desenvolvimento e relato nos estudos científicos. Além disso, são descritos tipos de modelos teóricos referentes aos planos conceitual e empírico, e a importante elaboraçõo e descriçõo da junçõo de ambos para o fazer científico. CONCLUSÃO: Espera-se que este artigo levante discussões e reflexões sobre os métodos atuais que permeiam o fazer científico e fomentem a utilizaçõo dos modelos teóricos como base das pesquisas científicas em seu processo de elaboraçõo, desenvolvimento e relato.

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Background: Brazil started the COVID-19 mass vaccination in January 2021 with CoronaVac and ChAdOx1, followed by BNT162b2 and Ad26.COV2.S vaccines. By the end of 2021, more than 317 million vaccine doses were administered in the adult population. This study aimed at estimating the effectiveness of the primary series of COVID-19 vaccination and booster shots in protecting against severe cases and deaths in Brazil during the first year of vaccination. Methods: A cohort dataset of over 158 million vaccination and severe cases records linked from official national registries was analyzed via a mixed-effects Poisson model, adjusted for age, state of residence, time after immunization, and calendar time to estimate the absolute vaccine effectiveness of the primary series of vaccination and the relative effectiveness of the booster. The method permitted analysis of effectiveness against hospitalizations and deaths, including in the periods of variant dominance. Findings: Vaccine effectiveness against severe cases and deaths remained over 25% and 50%, respectively, after 19 weeks from primary vaccination of BNT162b2, ChAdOx1, or CoronaVac vaccines. The boosters conferred greater protection than the primary series of vaccination, with heterologous boosters providing marginally greater protection than homologous. The effectiveness against hospitalization during the Omicron dominance in the 60+ years old population started at 61.7% (95% CI, 26.1-86.2) for ChAdOx1, 95.6% (95% CI, 82.4-99.9) for CoronaVac, and 72.3% (95% CI, 51.4-87.4) for the BNT162b2 vaccine. Interpretation: This study provides real-world evidence of the effectiveness of COVID-19 vaccination in Brazil, including during the Omicron wave, demonstrating protection even after waning effectiveness. Comparisons of the effectiveness among different vaccines require caution due to potential bias effects related to age groups, periods in the pandemic, and eventual behavioural changes. Funding: Fundação Oswaldo Cruz (FIOCRUZ), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), Pan American Health Organization (PAHO), Departamento de Ciência e Tecnologia da Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos em Saúde do Ministério da Saúde do Brasil (DECIT/SCTIE/MS).

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Background: A nationwide Severe Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) vaccination campaign was initiated in Brazil in January 2021 with CoronaVac (Sinovac Biotech) and ChAdOx1 nCoV-19 (AstraZeneca) followed by BNT162b2 mRNA (Pfizer-BioNTech) and Ad26.COV2.S (Johnson & Johnson-Janssen) vaccines. Here we provide estimates of the number of severe cases and deaths due to coronavirus disease (COVID-19) averted during the first year of the mass vaccination campaign in Brazil. Methods: Data on COVID-19 vaccination and COVID-19-related illness and death were obtained from the Brazilian Ministry of Health and used to estimate the direct effects of the vaccination campaign on the number of severe cases and deaths due to COVID-19 occurring between January 17, 2021 and January 31, 2022. To this end, we compared the daily age-specific rates between the unvaccinated population and the "at least partly vaccinated" population (received at least one dose of a two-dose vaccine), as well as other two vaccination subgroups, "fully vaccinated" (completed the one- or two-dose vaccine schedule), and "boosted-vaccinated" (fully vaccinated and recipients of booster dose) populations. Findings: We estimated that 74% (n = 875,846; 95% confidence interval, CI 843,383-915,709) of total expected cases of severe COVID-19 and 82% (n = 303,129; 95% CI 284,019-321,681) of total expected deaths due to COVID-19 were averted in the first year of the national vaccination campaign. The averted burden was heterogeneous between age groups and higher in the more populous states. However, outcome rate differences between vaccinated and unvaccinated groups were higher in the less populated states. Interpretation: The first year of the COVID-19 vaccination program in Brazil saved the lives of at least 303,129 adults. The results highlight the need for future vaccination campaigns, including those required in the current pandemic, to rapidly achieve high uptake, particularly among the elderly and residents of the least populous regions. Funding: Ministry of Health (Brazil).

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ABSTRACT BACKGROUND: After validation in multiple types of liver disease patients, the MELD score was adopted as a standard by which liver transplant candidates with end-stage liver disease were prioritized for organ allocation in the United States since 2002, and in Brazil, since 2006. AIMS: To analyze the mortality profile of patients on the liver transplant waiting list correlated to MELD score at the moment of transplantation. METHODS: This study used the data from the Secretary of Health of the São Paulo State, Brazil, which listed 22,522 patients, from 2006 (when MELD score was introduced in Brazil) until June 2009. Patients with acute hepatic failure and tumors were included as well. We also considered the mortality of both non-transplanted and transplanted patients as a function of the MELD score at presentation. RESULTS: Our model showed that the best MELD score for patients on the liver transplant waiting list associated to better results after liver transplantation was 26. CONCLUSIONS: We found that the best score for applying to liver transplant waiting list in the State of São Paulo was 26. This is the score that minimizes the mortality in both non-transplanted and liver transplanted patients.

RESUMO RACIONAL: Desde 2002, após validação em múltiplos tipos de hepatopatias, o escore MELD foi adotado como padrão pelo qual os candidatos a transplante de fígado com doença hepática terminal têm sido priorizados para alocação de órgãos nos Estados Unidos, e em 2006 no Brasil. OBJETIVOS: Analisar a mortalidade de pacientes em lista de espera para transplante de fígado correlacionando com o MELD, no momento do transplante. MÉTODOS: Foram utilizados os dados da Secretaria de Saúde do Estado de São Paulo, Brasil, onde foram listados 22.522 pacientes, desde 2006 (quando o escore MELD foi introduzido no Brasil) até junho de 2009. Foram incluídos pacientes com falência hepática e tumores. A mortalidade de pacientes não transplantados e transplantados também foi considerada em função do escore MELD. RESULTADOS: Nosso modelo mostrou que o melhor valor do MELD, em pacientes em lista de espera para transplante e com melhores resultados, foi de 26. Este valor minimiza mortalidade em pacientes não transplantados bem comem pacientes na lista de espera para transplante de fígado. CONCLUSÕES: O escore MELD ótimo para entrar na lista de espera para transplante de fígado, no estado de São Paulo, é em torno de 26. Esse é o valor que minimiza a mortalidade tanto dos pacientes não transplantados em lista de espera, quanto dos submetidos à transplante de fígado.