Optimized delay of the second COVID-19 vaccine dose reduces ICU admissions.

Slower than anticipated, COVID-19 vaccine production and distribution have impaired efforts to curtail the current pandemic. The standard administration schedule for most COVID-19 vaccines currently approved is two doses administered 3 to 4 wk apart. To increase the number of individuals with partial protection, some governments are considering delaying the second vaccine dose. However, the delay duration must take into account crucial factors, such as the degree of protection conferred by a single dose, the anticipated vaccine supply pipeline, and the potential emergence of more virulent COVID-19 variants. To help guide decision-making, we propose here an optimization model based on extended susceptible, exposed, infectious, and removed (SEIR) dynamics that determines the optimal delay duration between the first and second COVID-19 vaccine doses. The model assumes lenient social distancing and uses intensive care unit (ICU) admission as a key metric while selecting the optimal duration between doses vs. the standard 4-wk delay. While epistemic uncertainties apply to the interpretation of simulation outputs, we found that the delay is dependent on the vaccine mechanism of action and first-dose efficacy. For infection-blocking vaccines with first-dose efficacy ≥50%, the model predicts that the second dose can be delayed by ≥8 wk (half of the maximal delay), whereas for symptom-alleviating vaccines, the same delay is recommended only if the first-dose efficacy is ≥70%. Our model predicts that a 12-wk second-dose delay of an infection-blocking vaccine with a first-dose efficacy ≥70% could reduce ICU admissions by 400 people per million over 200 d.

Modelling the effect of a dengue vaccine on reducing the evolution of resistance against antibiotic due to misuse in dengue cases.

BACKGROUND: This paper intends to check whether and how a hypothetical dengue vaccine could contribute to issue of evolution of bacteria resistance against antibiotics by reducing the number of patients that would inappropriately being treated with antibiotics. METHODS: We use a new mathematical model that combines, in a novel way, two previously published papers, one on the evolution of resistance against antibiotics and one classical Ross-Macdonald model for dengue transmission. RESULTS: The model is simulated numerically and reproduces a real case of evolution of resistance against antibiotics. In addition the model shows that the use of a hypothetical dengue vaccine could help to curb the evolution of resistance against an antibiotic inappropriately used in dengue patients. Both the increase in the proportion of resistant bacteria due to the misuse of antibiotics in dengue cases as a function of the fraction of treated patients and the reduction of that proportion as a function of vaccination coverage occur in a highly non-linear fashion. CONCLUSION: The use of a dengue vaccine is helpful in reducing the rate of evolution of antibiotic resistance in a scenario of misuse of the antibiotics in dengue patients.

Two complementary model-based methods for calculating the risk of international spreading of a novel virus from the outbreak epicentre. The case of COVID-19.

We present two complementary model-based methods for calculating the risk of international spread of the novel coronavirus SARS-CoV-2 from the outbreak epicentre. One model aims to calculate the number of cases that would be exported from an endemic country to disease-free regions by travellers. The second model calculates the probability that an infected traveller will generate at least one secondary autochthonous case in the visited country. Although this paper focuses on the data from China, our methods can be adapted to calculate the risk of importation and subsequent outbreaks. We found an average R0 = 5.31 (ranging from 4.08 to 7.91) and a risk of spreading of 0.75 latent individuals per 1000 travellers. In addition, one infective traveller would be able to generate at least one secondary autochthonous case in the visited country with a probability of 23%.

Influence of pharmacogenetic polymorphisms and demographic variables on metformin pharmacokinetics in an admixed Brazilian cohort.

AIMS: To identify pharmacogenetic and demographic variables that influence the systemic exposure to metformin in an admixed Brazilian cohort. METHODS: The extreme discordant phenotype was used to select 106 data sets from nine metformin bioequivalence trials, comprising 256 healthy adults. Eleven single-nucleotide polymorphisms in SLC22A1, SLC22A2, SLC47A1 SLC47A2 and in transcription factor SP1 were genotyped and a validated panel of ancestry informative markers was used to estimate the individual proportions of biogeographical ancestry. Two-step (univariate followed by multivariate) regression modelling was developed to identify covariates associated with systemic exposure to metformin, accessed by the area under the plasma concentration-time curve, between 0 and 48 h (AUC0-48h ), after single oral doses of metformin (500 or 1000 mg). RESULTS: The individual proportions of African, Amerindian and European ancestry varied widely, as anticipated from the structure of the Brazilian population The dose-adjusted, log-transformed AUC0-48h 's (ng h ml-1  mg-1 ) differed largely in the two groups at the opposite ends of the distribution histogram, namely 0.82, 0.79-0.85 and 1.08, 1.06-1.11 (mean, 95% confidence interval; P = 6.10-26 , t test). Multivariate modelling revealed that metformin AUC0-48h increased with age, food and carriage of rs12208357 in SLC22A1 but was inversely associated with body surface area and individual proportions of African ancestry. CONCLUSIONS: A pharmacogenetic marker in OCT1 (SLC22A1 rs12208357), combined with demographic covariates (age, body surface area and individual proportion of African ancestry) and a food effect explained 29.7% of the variability in metformin AUC0-48h .

The risk of urban yellow fever resurgence in Aedes-infested American cities.

Aedes aegypti, historically known as yellow fever (YF) mosquito, transmits a great number of other viruses such as Dengue, West Nile, Chikungunya, Zika, Mayaro and perhaps Oropouche, among others. Well established in Africa and Asia, Aedes mosquitoes are now increasingly invading large parts of the American continent, and hence the risk of urban YF resurgence in the American cities should because of great concern to public health authorities. Although no new urban cycle of YF was reported in the Americas since the end of an Aedes eradication programme in the late 1950s, the high number of non-vaccinated individuals that visit endemic areas, that is, South American jungles where the sylvatic cycle of YF is transmitted by canopy mosquitoes, and return to Aedes-infested urban areas, increases the risk of resurgence of the urban cycle of YF. We present a method to estimate the risk of urban YF resurgence in dengue-endemic cities. This method consists in (1) to estimate the number of Aedes mosquitoes that explains a given dengue outbreak in a given region; (2) calculate the force of infection caused by the introduction of one infective individual per unit area in the endemic area under study; (3) using the above estimates, calculate the probability of at least one autochthonous YF case per unit area produced by one single viraemic traveller per unit area arriving from a YF endemic or epidemic sylvatic region at the city studied. We demonstrate that, provided the relative vector competence, here defined as the capacity to being infected and disseminate the virus, of Ae. aegypti is greater than 0.7 (with respect to dengue), one infected traveller can introduce urban YF in a dengue endemic area.

Limited sampling strategy for determining metformin area under the plasma concentration-time curve.

AIM: The aim was to develop and validate limited sampling strategy (LSS) models to predict the area under the plasma concentration-time curve (AUC) for metformin. METHODS: Metformin plasma concentrations (n = 627) at 0-24 h after a single 500 mg dose were used for LSS development, based on all subsets linear regression analysis. The LSS-derived AUC(0,24 h) was compared with the parameter 'best estimate' obtained by non-compartmental analysis using all plasma concentration data points. Correlation between the LSS-derived and the best estimated AUC(0,24 h) (r(2) ), bias and precision of the LSS estimates were quantified. The LSS models were validated in independent cohorts. RESULTS: A two-point (3 h and 10 h) regression equation with no intercept estimated accurately the individual AUC(0,24 h) in the development cohort: r(2)  = 0.927, bias (mean, 95% CI) -0.5, -2.7-1.8% and precision 6.3, 4.9-7.7%. The accuracy of the two point LSS model was verified in study cohorts of individuals receiving single 500 or 1000 mg (r(2)  = -0.933-0.934) or seven 1000 mg daily doses (r(2)  = 0.918), as well as using data from 16 published studies covering a wide range of metformin doses, demographics, clinical and experimental conditions (r(2)  = 0.976). The LSS model reproduced previously reported results for effects of polymorphisms in OCT2 and MATE1 genes on AUC(0,24 h) and renal clearance of metformin. CONCLUSIONS: The two point LSS algorithm may be used to assess the systemic exposure to metformin under diverse conditions, with reduced costs of sampling and analysis, and saving time for both subjects and investigators.

The risk of dengue for non-immune foreign visitors to the 2016 summer olympic games in Rio de Janeiro, Brazil.

BACKGROUND: Rio de Janeiro in Brazil will host the Summer Olympic Games in 2016. About 400,000 non-immune foreign tourists are expected to attend the games. As Brazil is the country with the highest number of dengue cases worldwide, concern about the risk of dengue for travelers is justified. METHODS: A mathematical model to calculate the risk of developing dengue for foreign tourists attending the Olympic Games in Rio de Janeiro in 2016 is proposed. A system of differential equation models the spread of dengue amongst the resident population and a stochastic approximation is used to assess the risk to tourists. Historical reported dengue time series in Rio de Janeiro for the years 2000-2015 is used to find out the time dependent force of infection, which is then used to estimate the potential risks to a large tourist cohort. The worst outbreak of dengue occurred in 2012 and this and the other years in the history of Dengue in Rio are used to discuss potential risks to tourists amongst visitors to the forthcoming Rio Olympics. RESULTS: The individual risk to be infected by dengue is very much dependent on the ratio asymptomatic/symptomatic considered but independently of this the worst month of August in the period studied in terms of dengue transmission, occurred in 2007. CONCLUSIONS: If dengue returns in 2016 with the pattern observed in the worst month of August in history (2007), the expected number of symptomatic and asymptomatic dengue cases among tourists will be 23 and 206 cases, respectively. This worst case scenario would have an incidence of 5.75 (symptomatic) and 51.5 (asymptomatic) per 100,000 individuals.

Modeling Importations and Exportations of Infectious Diseases via Travelers.

This paper is an attempt to estimate the risk of infection importation and exportation by travelers. Two countries are considered: one disease-free country and one visited or source country with a running endemic or epidemic infectious disease. Two models are considered. In the first model (disease importation), susceptible individuals travel from their disease-free home country to the endemic country and come back after some weeks. The risk of infection spreading in their home country is then estimated supposing the visitors are submitted to the same force of infection as the local population but do not contribute to it. In the second model (disease exportation), it is calculated the probability that an individual from the endemic (or epidemic) country travels to a disease-free country in the condition of latent infected and eventually introduces the infection there. The input of both models is the force of infection at the visited/source country, assumed known. The models are deterministic, but a preliminary stochastic formulation is presented as an appendix. The models are exemplified with two distinct real situations: the risk of dengue importation from Thailand to Europe and the risk of Ebola exportation from Liberia to the USA.

Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil.

Brazil will host the FIFA World Cup™, the biggest single-event competition in the world, from June 12-July 13 2014 in 12 cities. This event will draw an estimated 600,000 international visitors. Brazil is endemic for dengue. Hence, attendees of the 2014 event are theoretically at risk for dengue. We calculated the risk of dengue acquisition to non-immune international travellers to Brazil, depending on the football match schedules, considering locations and dates of such matches for June and July 2014. We estimated the average per-capita risk and expected number of dengue cases for each host-city and each game schedule chosen based on reported dengue cases to the Brazilian Ministry of Health for the period between 2010-2013. On the average, the expected number of cases among the 600,000 foreigner tourists during the World Cup is 33, varying from 3-59. Such risk estimates will not only benefit individual travellers for adequate pre-travel preparations, but also provide valuable information for public health professionals and policy makers worldwide. Furthermore, estimates of dengue cases in international travellers during the World Cup can help to anticipate the theoretical risk for exportation of dengue into currently non-infected areas.

Pharmacogenomic implications of the differential distribution of CYP3A5 metabolic phenotypes among Latin American populations.

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.

Analysing vaccine efficacy evaluated in phase 3 clinical trials carried out during outbreaks.

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.

Immune response stability to the SARS-CoV-2 mRNA vaccine booster is influenced by differential splicing of HLA genes.

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.

THE OPTIMUM LEVEL OF MELD TO MINIMIZE THE MORTALITY ON LIVER TRANSPLANTATION WAITING LIST, AND LIVER TRANSPLANTED PATIENT IN SÃO PAULO STATE, BRAZIL.

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.

Theoretical models: necessary reflections. / Modelos teóricos: reflexões necessárias.

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.

Estimated COVID-19 severe cases and deaths averted in the first year of the vaccination campaign in Brazil: A retrospective observational study.

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).

The effectiveness of COVID-19 vaccines against severe cases and deaths in Brazil from 2021 to 2022: a registry-based study.

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).

Theoretical report: reflections and considerations for authors, reviewers, and editors.

Epidemiological studies focused on public health have currently shown significant limitations regarding in-depth theoretical reports, overvaluing methodological aspects. The lack of theoretical explanation affects both the quality and reproducibility of studies. This study therefore reflected on the importance of in-depth theoretical reports considering the theoretical foundation used by researchers in the main sections of the manuscript (title, abstract, introduction, methodology, results, discussion, and conclusion) based on a review of the scientific literature on the subject. We believe that this article can help understand the importance and the development of in-depth theoretical reports in scientific articles, contributing to assessments, interpretations, and criticisms of reviewers and editors regarding the explanation and reporting of theoretical foundation in manuscripts submitted to scientific journals.

Backdrop to the development of Brazil's national COVID-19 immunization plan. / Contexto de elaboração do Plano de Imunização contra COVID-19 no Brasil.

The process of developing Brazil's COVID-19 immunization plan began belatedly and involved a number of experts, including a technical group responsible for defining priority groups for vaccination. This process was permeated by contradictions between the government and researchers. Finally, on 20 January 2021, the government published an updated version of the plan, which remains limited in scope.

O processo de elaboração do Plano de Imunização contra Covid-19 no Brasil se iniciou tardiamente e contou com a participação de especialistas incluindo o grupo técnico responsável pela definição de grupos prioritários para a vacinação. Este processo foi permeado de indefinições entre o Governo Federal e pesquisadores e, finalmente, no dia 20 de janeiro de 2021 foi divulgada a versão atualizada do Plano ainda incipiente no que tange a sua abrangência.

Vulnerable populations and tuberculosis treatment outcomes in Brazil. / Populações vulneráveis e o desfecho dos casos de tuberculose no Brasil.

This article aims to assess the association between being a prisoner or homeless and treatment failure in cases of tuberculosis diagnosed in Brazil in 2015. We examined cases of tuberculosis in prisoners and the homeless in Brazil in 2015 reported to the national notifiable diseases information system using descriptive analysis and logistic regression. There were 82,056 cases of tuberculosis in 2015. Of these, 7,462 (10.3%) were prisoners and 2,782 (3.9%) were homeless. The rate of treatment success in prisoners was 78.6%, while the rate of failure in the homeless was 63.2%. Being a prisoner was a protective factor against treatment failure (adjusted odds ratio 0.68, 95%CI 0.63-0.73), while being homeless was a risk factor for treatment failure (adjusted odds ratio 2.38, 95%CI 2.17-2.61). Treatment success and failure rates differed between prisoners and the homeless. Our findings reinforce the need for public health policies tailored to the specific needs of these groups implemented in conjunction with social services and public security agencies in order to have a significant impact on TB incidence.

O objetivo deste artigo é avaliar a associação entre estar privado de liberdade ou em situação de rua e o insucesso no desfecho dos casos de tuberculose diagnosticados no Brasil em 2015. Foram estudados casos de tuberculose na população privada de liberdade e em situação de rua do Brasil em 2015, por análise descritiva e regressão logística baseado no Sistema de Informação de Agravos de Notificação. Em 2015 notificou-se 82.056 casos de tuberculose, destes 7.462 (10,3%) estavam privados de liberdade e 2.782 (3,9%) em situação de rua. A proporção de sucesso no desfecho dos casos na população privada de liberdade foi de 78,6%, enquanto na população em situação de rua, a proporção de insucesso foi 63,2%. Estar privado de liberdade mostrou-se protetor para o insucesso no desfecho dos casos (Razão de Chances ajustada 0,68, IC95% 0,63-0,73), enquanto estar em situação de rua mostrou-se um fator de risco para o insucesso (Razão de Chances ajustada 2,38, IC95% 2,17-2,61). O desfecho dos casos de tuberculose se diferencia entre as populações privada de liberdade e em situação de rua, fazendo-se necessário a implantação de políticas públicas de saúde que considerem suas especificidades e seja articulada com órgãos sociais e segurança a fim de que impacte nos indicadores da doença.