COVID-19 Modeling To Support Decision Making In Brazil: A Scoping Review

IntroductionIn the context of the COVID-19 pandemic, which required urgent responses from health systems, and ongoing decision making in a context of limited and evolving evidence, modeling played a significant role in supporting public policy making. Nonetheless, particularly in low and middle-income countries, modeling groups are scarce, and usually not routinely involved in supporting public health policy making. We aimed to appraise COVID-19 modeling work in Brazil during the pandemic.MethodsWe performed a scoping review following PRISMA guidelines to identify groups conducting COVID-19 modeling to support health decision-making in Brazil. Search strategies were applied to MEDLINE, LILACS, Embase, ArXiv, and also included National data repositories and gray literature. We excluded reports of models without modeling results. Titles, s, data repository descriptions and full-text articles identified were read and selected by two reviewers. Data extracted included modeling questions, model characteristics (structure, type, and programming), epidemiologic data sources, main outcomes reported, and parameters. To further identify modeling groups that might have not yet published results, snowball sampling was performed, and a short survey was sent electronically. Investigators and policymakers were invited to an online interview, to obtain further information on how they interacted, communicated, and used modeling results.ResultsWe retrieved 1,061 references. After removing duplicates (127), 1,016 s and titles were screened. From an initial selection of 142 s, 133 research groups were identified, of which 67 didn't meet the eligibility criteria. Of these, 66 groups were invited for an interview, of which 24 were available, including 18 modeling groups from academic institutions, and four groups from State Health departments. Most models assessed the impact of mitigation measures in cases/hospitalization/deaths and healthcare service demand. Interaction and communication with decision-makers were not well established in most groups.ConclusionsDespite a large number of modeling groups in Brazil, we observed a significant gap in modeling demand and communicating its results to support the decision-making process during the COVID-19 pandemic.

Brazilian Collaborative Network For COVID-19 Modeling: Successful Experience Of Using Real-Time Science To Support Evidence-Based Decision-Making

IntroductionModeling is important for guiding policy during epidemics. The objective of this work was to describe the experience of structuring a multidisciplinary collaborative network in Brazil for modeling coronavirus disease 2019 (COVID-19) to support decision-making throughout the pandemic.MethodsResponding to a national call in June 2020 for proposals on COVID-19 mitigation projects, we established a team of investigators from public universities located in various regions throughout Brazil. The team's main objective was to model severe acute respiratory syndrome coronavirus 2 transmission dynamics in various demographic and epidemiologic settings in Brazil using different types of models and mitigation interventions. The modeling results aimed to provide information to support policy making. This descriptive study outlines the processes, products, challenges, and lessons learned from this innovative experience.ResultsThe network included 18 researchers (epidemiologists, infectious diseases experts, statisticians, and modelers) from various backgrounds, including ecology, geography, physics, and mathematics. The criteria for joining the network were having a communication channel with public health decision-makers and being involved in generating evidence for public policy. During a 24-month period, the following sub-projects were established: (i) development of a susceptible-exposed-infected-recovered-like, individual-based meta-population and Markov chain model;(ii) projection of COVID-19 transmission and impact over time with respect to cases, hospitalizations, and deaths;(iii) assessment of the impact of non-pharmacological interventions for COVID-19;(iv) evaluation of the impact of reopening schools;and (v) determining optimal strategies for COVID-19 vaccination. In addition, we mapped existing COVID-19 modeling groups nationwide and conducted a systematic review of relevant published research literature from Brazil.ConclusionsInfectious disease modeling for guiding public health policy requires interaction between epidemiologists, public health specialists, and modelers. Communicating modeling results in a non-academic format is an additional challenge, so close interaction with policy makers is essential to ensure that the information is useful. Establishing a network of modeling groups will be useful for future disease outbreaks.

Modeling the impact of child vaccination (5-11 y) on overall COVID-19 related hospitalizations and mortality in a context of omicron variant predominance and different vaccination coverage paces in Brazil.

Background: Developing countries have experienced significant COVID-19 disease burden. With the emergence of new variants, particularly omicron, the disease burden in children has increased. When the first COVID-19 vaccine was approved for use in children aged 5-11 years of age, very few countries recommended vaccination due to limited risk-benefit evidence for vaccination of this population. In Brazil, ranking second in the global COVID-19 death toll, the childhood COVID-19 disease burden increased significantly in early 2022. This prompted a risk-benefit assessment of the introduction and scaling-up of COVID-19 vaccination of children. Methods: To estimate the potential impact of vaccinating children aged 5-11 years with mRNA-based COVID-19 vaccine in the context of omicron dominance, we developed a discrete-time SEIR-like model stratified in age groups, considering a three-month time horizon. We considered three scenarios: No vaccination, slow, and maximum vaccination paces. In each scenario, we estimated the potential reduction in total COVID-19 cases, hospitalizations, deaths, hospitalization costs, and potential years of life lost, considering the absence of vaccination as the base-case scenario. Findings: We estimated that vaccinating at a maximum pace could prevent, between mid-January and April 2022, about 26,000 COVID-19 hospitalizations, and 4200 deaths in all age groups; of which 5400 hospitalizations and 410 deaths in children aged 5-11 years. Continuing vaccination at a slow/current pace would prevent 1450 deaths and 9700 COVID-19 hospitalizations in all age groups in this same time period; of which 180 deaths and 2390 hospitalizations in children only. Interpretation: Maximum vaccination of children results in a significant reduction of COVID-19 hospitalizations and deaths and should be enforced in developing countries with significant disease incidence in children. Funding: This manuscript was funded by the Brazilian Council for Scientific and Technology Development (CNPq - Process # 402834/2020-8).

Modelling optimal vaccination strategies against COVID-19 in a context of Gamma variant predominance in Brazil.

INTRODUCTION: Brazil experienced moments of collapse in its health system throughout 2021, driven by the emergence of variants of concern (VOC) combined with an inefficient initial vaccination strategy against Covid-19. OBJECTIVES: To support decision-makers in formulating COVID-19 immunization policy in the context of limited vaccine availability and evolving variants over time, we evaluate optimal strategies for Covid-19 vaccination in Brazil in 2021, when vaccination was rolled out during Gamma variant predominance. METHODS: Using a discrete-time epidemic model we estimate Covid-19 deaths averted, considering the currently Covid-19 vaccine products and doses available in Brazil; vaccine coverage by target population; and vaccine effectiveness estimates. We evaluated a 5-month time horizon, from early August to the end of December 2021. Optimal vaccination strategies compared the outcomes in terms of averted deaths when varying dose intervals from 8 to 12 weeks, and choosing the minimum coverage levels per age group required prior to expanding vaccination to younger target populations. We also estimated dose availability required over time to allow the implementation of optimal strategies. RESULTS: To maximize the number of averted deaths, vaccine coverage of at least 80 % should be reached in older age groups before starting vaccination into subsequent younger age groups. When evaluating varying dose intervals for AZD1222, reducing the dose interval from 12 to 8 weeks for the primary schedule would result in fewer COVID-19 deaths, but this can only be implemented if accompanied by an increase in vaccine supply of at least 50 % over the coming six-months in Brazil. CONCLUSION: Covid-19 immunization strategies should be tailored to local vaccine product availability and supply over time, circulating variants of concern, and vaccine coverage in target population groups. Modelling can provide valuable and timely evidence to support the implementation of vaccination strategies considering the local context, yet following international and regional technical evidence-based guidance.

Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil.

We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings - school, home, work, and community, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening, and also estimate the number of hospitalization and deaths averted by the implementation of contact tracing. Reopening schools results in a non-linear increase in reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects in reducing the total number of hospitalizations and deaths. Policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. While contact tracing strategies prevent new infections within school environments, they alone are not sufficient to avoid significant impacts on community transmission.

Frequency, signs and symptoms, and criteria adopted for long COVID-19: A systematic review.

AIMS: To identify, systematically evaluate and summarise the best available evidence on the frequency of long COVID-19 (post-acute COVID-19 syndrome), its clinical manifestations, and the criteria used for diagnosis. METHODS: Systematic review conducted with a comprehensive search including formal databases, COVID-19 or SARS-CoV-2 data sources, grey literature, and manual search. We considered for inclusion clinical trials, observational longitudinal comparative and non-comparative studies, cross-sectional, before-and-after, and case series. We assessed the methodological quality by specific tools based on the study designs. We presented the results as a narrative synthesis regarding the frequency and duration of long COVID-19, signs and symptoms, criteria used for diagnosis, and potential risk factors. RESULTS: We included 25 observational studies with moderate to high methodological quality, considering 5440 participants. The frequency of long COVID-19 ranged from 4.7% to 80%, and the most prevalent signs/symptoms were chest pain (up to 89%), fatigue (up to 65%), dyspnea (up to 61%), and cough and sputum production (up to 59%). Temporal criteria used to define long COVID-19 varied from 3 to 24 weeks after acute phase or hospital discharge. Potentially associated risk factors were old age, female sex, severe clinical status, a high number of comorbidities, hospital admission, and oxygen supplementation at the acute phase. However, limitations related to study designs added uncertainty to this finding. None of the studies assessed the duration of signs/symptoms. CONCLUSION: The frequency of long COVID-19 reached up to 80% over the studies included and occurred between 3 and 24 weeks after acute phase or hospital discharge. Chest pain, fatigue, dyspnea, and cough were the most reported clinical manifestations attributed to the condition. Based on these systematic review findings, there is an urgent need to understand this emerging, complex and challenging medical condition. Proposals for diagnostic criteria and standard terminology are welcome.

Delays and Disruptions in Cancer Health Care Due to COVID-19 Pandemic: Systematic Review.

PURPOSE: There has been noteworthy concern about the impact of COVID-19 pandemic on health services including the management of cancer. In addition to being considered at higher risk for worse outcomes from COVID-19, people with cancer may also experience disruptions or delays in health services. This systematic review aimed to identify the delays and disruptions to cancer services globally. METHODS: This is a systematic review with a comprehensive search including specific and general databases. We considered any observational longitudinal and cross-sectional study design. The selection, data extraction, and methodological assessment were performed by two independent reviewers. The methodological quality of the studies was assessed by specific tools. The delays and disruptions identified were categorized, and their frequency was presented. RESULTS: Among the 62 studies identified, none exhibited high methodological quality. The most frequent determinants for disruptions were provider- or system-related, mainly because of the reduction in service availability. The studies identified 38 different categories of delays and disruptions with impact on treatment, diagnosis, or general health service. Delays or disruptions most investigated included reduction in routine activity of cancer services and number of cancer surgeries; delay in radiotherapy; and delay, reschedule, or cancellation of outpatient visits. Interruptions and disruptions largely affected facilities (up to 77.5%), supply chain (up to 79%), and personnel availability (up to 60%). CONCLUSION: The remarkable frequency of delays and disruptions in health care mostly related to the reduction of the COVID-19 burden unintentionally posed a major risk on cancer care worldwide. Strategies can be proposed not only to mitigate the main delays and disruptions but also to standardize their measurement and reporting. As a high number of publications continuously are being published, it is critical to harmonize the upcoming reports and constantly update this review.

Diretrizes para o tratamento farmacológico da COVID-19. Consenso da Associação de Medicina Intensiva Brasileira, da Sociedade Brasileira de Infectologia e da Sociedade Brasileira de Pneumologia e Tisiologia

INTRODUCTION: Different therapies are currently used, considered, or proposed for the treatment of COVID-19;for many of those therapies, no appropriate assessment of effectiveness and safety was performed. This document aims to provide scientifically available evidence-based information in a transparent interpretation, to subsidize decisions related to the pharmacological therapy of COVID-19 in Brazil. METHODS: A group of 27 experts and methodologists integrated a task-force formed by professionals from the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB), the Brazilian Society of Infectious Diseases (Sociedad Brasileira de Infectologia - SBI) and the Brazilian Society of Pulmonology and Tisiology (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT). Rapid systematic reviews, updated on April 28, 2020, were conducted. The assessment of the quality of evidence and the development of recommendations followed the GRADE system. The recommendations were written on May 5, 8, and 13, 2020. RESULTS: Eleven recommendations were issued based on low or very-low level evidence. We do not recommend the routine use of hydroxychloroquine, chloroquine, azithromycin, lopinavir/ritonavir, corticosteroids, or tocilizumab for the treatment of COVID-19. Prophylactic heparin should be used in hospitalized patients, however, no anticoagulation should be provided for patients without a specific clinical indication. Antibiotics and oseltamivir should only be considered for patients with suspected bacterial or influenza coinfection, respectively. CONCLUSION: So far no pharmacological intervention was proven effective and safe to warrant its use in the routine treatment of COVID-19 patients;therefore such patients should ideally be treated in the context of clinical trials. The recommendations herein provided will be revised continuously aiming to capture newly generated evidence.

Guidelines for the pharmacological treatment of COVID-19. The task-force/consensus guideline of the Brazilian Association of Intensive Care Medicine, the Brazilian Society of Infectious Diseases and the Brazilian Society of Pulmonology and Tisiology. / Diretrizes para o tratamento farmacológico da COVID-19. Consenso da Associação de Medicina Intensiva Brasileira, da Sociedade Brasileira de Infectologia e da Sociedade Brasileira de Pneumologia e Tisiologia.

INTRODUCTION: Different therapies are currently used, considered, or proposed for the treatment of COVID-19; for many of those therapies, no appropriate assessment of effectiveness and safety was performed. This document aims to provide scientifically available evidence-based information in a transparent interpretation, to subsidize decisions related to the pharmacological therapy of COVID-19 in Brazil. METHODS: A group of 27 experts and methodologists integrated a task-force formed by professionals from the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB), the Brazilian Society of Infectious Diseases (Sociedad Brasileira de Infectologia - SBI) and the Brazilian Society of Pulmonology and Tisiology (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT). Rapid systematic reviews, updated on April 28, 2020, were conducted. The assessment of the quality of evidence and the development of recommendations followed the GRADE system. The recommendations were written on May 5, 8, and 13, 2020. RESULTS: Eleven recommendations were issued based on low or very-low level evidence. We do not recommend the routine use of hydroxychloroquine, chloroquine, azithromycin, lopinavir/ritonavir, corticosteroids, or tocilizumab for the treatment of COVID-19. Prophylactic heparin should be used in hospitalized patients, however, no anticoagulation should be provided for patients without a specific clinical indication. Antibiotics and oseltamivir should only be considered for patients with suspected bacterial or influenza coinfection, respectively. CONCLUSION: So far no pharmacological intervention was proven effective and safe to warrant its use in the routine treatment of COVID-19 patients; therefore such patients should ideally be treated in the context of clinical trials. The recommendations herein provided will be revised continuously aiming to capture newly generated evidence.