Time-dependent vaccine efficacy estimation quantified by a mathematical model.

In this paper we calculate the variation of the estimated vaccine efficacy (VE) due to the time-dependent force of infection resulting from the difference between the moment the Clinical Trial (CT) begins and the peak in the outbreak intensity. Using a simple mathematical model we tested the hypothesis that the time difference between the moment the CT begins and the peak in the outbreak intensity determines substantially different values for VE. We exemplify the method with the case of the VE efficacy estimation for one of the vaccines against the new coronavirus SARS-CoV-2.

Quantifying protocols for safe school activities.

By the peak of COVID-19 restrictions on April 8, 2020, up to 1.5 billion students across 188 countries were affected by the suspension of physical attendance in schools. Schools were among the first services to reopen as vaccination campaigns advanced. With the emergence of new variants and infection waves, the question now is to find safe protocols for the continuation of school activities. We need to understand how reliable these protocols are under different levels of vaccination coverage, as many countries have a meager fraction of their population vaccinated, including Uganda where the coverage is about 8%. We investigate the impact of face-to-face classes under different protocols and quantify the surplus number of infected individuals in a city. Using the infection transmission when schools were closed as a baseline, we assess the impact of physical school attendance in classrooms with poor air circulation. We find that (i) resuming school activities with people only wearing low-quality masks leads to a near fivefold city-wide increase in the number of cases even if all staff is vaccinated, (ii) resuming activities with students wearing good-quality masks and staff wearing N95s leads to about a threefold increase, (iii) combining high-quality masks and active monitoring, activities may be carried out safely even with low vaccination coverage. These results highlight the effectiveness of good mask-wearing. Compared to ICU costs, high-quality masks are inexpensive and can help curb the spreading. Classes can be carried out safely, provided the correct set of measures are implemented.

Big data technology in infectious diseases modeling, simulation, and prediction after the COVID-19 outbreak.

After the outbreak of COVID-19, the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods. Starting from the research purpose and data, researchers improved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems. In terms of modeling methods, the researchers use compartment subdivision, dynamic parameters, agent-based model methods, and artificial intelligence related methods. In terms of factors studied, the researchers studied 6 categories: human mobility, nonpharmaceutical interventions (NPIs), ages, medical resources, human response, and vaccine. The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies. This review started with a research structure of research purpose, factor, data, model, and conclusion. Focusing on the post-COVID-19 infectious disease prediction simulation research, this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.

Prevalence and predictors of anti-SARS-CoV-2 serology in a highly vulnerable population of Rio de Janeiro: A population-based serosurvey.

Background: COVID-19 serosurveys allow for the monitoring of the level of SARS-CoV-2 transmission and support data-driven decisions. We estimated the seroprevalence of anti-SARS-CoV-2 antibodies in a large favela complex in Rio de Janeiro, Brazil. Methods: A population-based panel study was conducted in Complexo de Manguinhos (16 favelas) with a probabilistic sampling of participants aged ≥1 year who were randomly selected from a census of individuals registered in primary health care clinics that serve the area. Participants answered a structured interview and provided blood samples for serology. Multilevel regression models (with random intercepts to account for participants' favela of residence) were used to assess factors associated with having anti-S IgG antibodies. Secondary analyses estimated seroprevalence using an additional anti-N IgG assay. Findings: 4,033 participants were included (from Sep/2020 to Feb/2021, 22 epidemic weeks), the median age was 39·8 years (IQR:21·8-57·7), 61% were female, 41% were mixed-race (Pardo) and 23% Black. Overall prevalence was 49·0% (95%CI:46·8%-51·2%) which varied across favelas (from 68·3% to 31·4%). Lower prevalence estimates were found when using the anti-N IgG assay. Odds of having anti-S IgG antibodies were highest for young adults, and those reporting larger household size, poor adherence to social distancing and use of public transportation. Interpretation: We found a significantly higher prevalence of anti-S IgG antibodies than initially anticipated. Disparities in estimates obtained using different serological assays highlight the need for cautious interpretation of serosurveys estimates given the heterogeneity of exposure in communities, loss of immunological biomarkers, serological antigen target, and variant-specific test affinity. Funding: Fundação Oswaldo Cruz, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), the European Union's Horizon 2020 research and innovation programme, Royal Society, Serrapilheira Institute, and FAPESP.

Population-level seropositivity trend for SARS-Cov-2 in Rio Grande do Sul, Brazil

OBJECTIVE To describe the evolution of seropositivity in the State of Rio Grande do Sul, Brazil, through 10 consecutive surveys conducted between April 2020 and April 2021. METHODS Nine cities covering all regions of the State were studied, 500 households in each city. One resident in each household was randomly selected for testing. In survey rounds 1–8 we used the rapid WONDFO SARS-CoV-2 Antibody Test (Wondfo Biotech Co., Guangzhou, China). In rounds 9–10, we used a direct ELISA test that identifies IgG to the viral S protein (S-UFRJ). In terms of social distancing, individuals were asked three questions, from which we generated an exposure score using principal components analysis. RESULTS Antibody prevalence in early April 2020 was 0.07%, increasing to 10.0% in February 2021, and to 18.2% in April 2021. In round 10, self-reported whites showed the lowest seroprevalence (17.3%), while indigenous individuals presented the highest (44.4%). Seropositivity increased by 40% when comparing the most with the least exposed. CONCLUSIONS The proportion of the population already infected by SARS-Cov-2 in the state is still far from any perspective of herd immunity and the infection affects population groups in very different levels.

Challenges of evaluating and modelling vaccination in emerging infectious diseases.

Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.

Turnover of SARS-CoV-2 Lineages Shaped the Pandemic and Enabled the Emergence of New Variants in the State of Rio de Janeiro, Brazil.

In the present study, we provide a retrospective genomic epidemiology analysis of the SARS-CoV-2 pandemic in the state of Rio de Janeiro, Brazil. We gathered publicly available data from GISAID and sequenced 1927 new genomes sampled periodically from March 2021 to June 2021 from 91 out of the 92 cities of the state. Our results showed that the pandemic was characterized by three different phases driven by a successive replacement of lineages. Interestingly, we noticed that viral supercarriers accounted for the overwhelming majority of the circulating virus (>90%) among symptomatic individuals in the state. Moreover, SARS-CoV-2 genomic surveillance also revealed the emergence and spread of two new variants (P.5 and P.1.2), firstly reported in this study. Our findings provided important lessons learned from the different epidemiological aspects of the SARS-CoV-2 dynamic in Rio de Janeiro. Altogether, this might have a strong potential to shape future decisions aiming to improve public health management and understanding mechanisms underlying virus dispersion.

Smart testing and critical care bed sharing for COVID-19 control.

During the early months of the current COVID-19 pandemic, social distancing measures effectively slowed disease transmission in many countries in Europe and Asia, but the same benefits have not been observed in some developing countries such as Brazil. In part, this is due to a failure to organise systematic testing campaigns at nationwide or even regional levels. To gain effective control of the pandemic, decision-makers in developing countries, particularly those with large populations, must overcome difficulties posed by an unequal distribution of wealth combined with low daily testing capacities. The economic infrastructure of these countries, often concentrated in a few cities, forces workers to travel from commuter cities and rural areas, which induces strong nonlinear effects on disease transmission. In the present study, we develop a smart testing strategy to identify geographic regions where COVID-19 testing could most effectively be deployed to limit further disease transmission. By smart testing we mean the testing protocol that is automatically designed by our optimization platform for a given time period, knowing the available number of tests, the current availability of ICU beds and the initial epidemiological situation. The strategy uses readily available anonymised mobility and demographic data integrated with intensive care unit (ICU) occupancy data and city-specific social distancing measures. Taking into account the heterogeneity of ICU bed occupancy in differing regions and the stages of disease evolution, we use a data-driven study of the Brazilian state of Sao Paulo as an example to show that smart testing strategies can rapidly limit transmission while reducing the need for social distancing measures, even when testing capacity is limited.

Slow Spread of SARS-CoV-2 in Southern Brazil Over a 6-Month Period: Report on 8 Sequential Statewide Serological Surveys Including 35 611 Participants.

Objectives. To evaluate the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) over 6 months in the Brazilian State of Rio Grande do Sul (population 11.3 million), based on 8 serological surveys. Methods. In each survey, 4151 participants in round 1 and 4460 participants in round 2 were randomly sampled from all state regions. We assessed presence of antibodies against SARS-CoV-2 using a validated lateral flow point-of-care test; we adjusted figures for the time-dependent decay of antibodies. Results. The SARS-CoV-2 antibody prevalence increased from 0.03% (95% confidence interval [CI] = 0.00%, 0.34%; 1 in every 3333 individuals) in mid-April to 1.89% (95% CI = 1.36%, 2.54%; 1 in every 53 individuals) in early September. Prevalence was similar across gender and skin color categories. Older adults were less likely to be infected than younger participants. The proportion of the population who reported leaving home daily increased from 21.4% (95% CI = 20.2%, 22.7%) to 33.2% (95% CI = 31.8%, 34.5%). Conclusions. SARS-CoV-2 infection increased slowly during the first 6 months in the state, differently from what was observed in other Brazilian regions. Future survey rounds will continue to document the spread of the pandemic.

SARS-CoV-2 testing disparities across geographical regions from a large metropolitan area in Brazil: Results from a web-based survey among individuals interested in clinical trials for COVID-19 vaccines.

After more than a year since the novel coronavirus (SARS-CoV-2) disease 2019 or COVID-19 has reached the status of a global pandemic, the number of COVID-19 cases continues to rise in Brazil. As no effective treatment been approved yet, only mass vaccination can stop the spread of SARS-CoV-2 and end the COVID-19 pandemic. Multiple COVID-19 vaccine candidates are under development and some are currently in use. This study aims to describe the characteristics of individuals who have registered in an online platform to participate in clinical trials for COVID-19 vaccines. Additionally, participants' characteristics according to age and presence of comorbidities associated with severe COVID-19 and differences of SARS-CoV-2 testing across different geographical areas/neighborhoods are provided. This was a cross-sectional web-based study conducted between September and December/2020, aiming to reach individuals aged ≥18 years who live in Rio de Janeiro metropolitan area, Brazil. Among 21,210 individuals who completed the survey, 20,587 (97.1%) were willing to participate in clinical trials for COVID-19 vaccines. Among those willing to participate, 57.8% individuals were aged 18-59 years and had no comorbidity, 33.7% were aged 18-59 years and had at least one comorbidity, and 8.6% were aged ≥ 60 years regardless the presence of any comorbidity. Almost half (42.6%) reported ever testing for COVID-19, and this proportion was lower among those aged ≥ 60 years (p < 0.001). Prevalence of positive PCR results was 16.0%, higher among those aged 18-59 years (p < 0.009). Prevalence of positive antibody result was 10.0%, with no difference across age and comorbidity groups. Participants from areas/neighborhoods with higher Human Development Index (HDI) reported ever testing for SARS-CoV-2 more frequently than those from lower HDI areas. Interest to participate in clinical trials for COVID-19 vaccines candidates in Rio de Janeiro was significantly high. The online registry successfully reached out a large number of individuals with diverse sociodemographic, economic and clinical backgrounds.

High prevalence of symptoms among Brazilian subjects with antibodies against SARS-CoV-2.

Since the beginning of the pandemic of COVID-19, there has been a widespread assumption that most infected persons are asymptomatic. Using data from the recent wave of the EPICOVID19 study, a nationwide household-based survey including 133 cities from all states of Brazil, we estimated the proportion of people with and without antibodies for SARS-CoV-2 who were asymptomatic, which symptoms were most frequently reported, number of symptoms and the association with socio-demographic characteristics. We tested 33,205 subjects using a rapid antibody test previously validated. Information was collected before participants received the test result. Out of 849 (2.7%) participants positive for SARS-CoV-2 antibodies, only 12.1% (95% CI 10.1-14.5) reported no symptoms, compared to 42.2% (95% CI 41.7-42.8) among those negative. The largest difference between the two groups was observed for changes in smell/taste (56.5% versus 9.1%, a 6.2-fold difference). Changes in smell/taste, fever and body aches were most likely to predict positive tests as suggested by recursive partitioning tree analysis. Among individuals without any of these three symptoms, only 0.8% tested positive, compared to 18.3% of those with both fever and changes in smell or taste. Most subjects with antibodies against SARS-CoV-2 are symptomatic, even though most present only mild symptoms.

Social distancing patterns in nine municipalities of Rio Grande do Sul, Brazil: the Epicovid19/RS study

ABSTRACT OBJECTIVE To describe social distancing practices in nine municipalities of the state of Rio Grande do Sul, Brazil, stratified by gender, age, and educational attainment. METHODS Two sequential cross-sectional studies were conducted in the municipalities of Canoas, Caxias do Sul, Ijuí, Passo Fundo, Pelotas, Porto Alegre, Santa Cruz do Sul, Santa Maria, and Uruguaiana to estimate the population prevalence of COVID-19. The study was designed to be representative of the urban population of these municipalities. A questionnaire including three questions about social distancing was also administered to the participants. Here, we present descriptive analyses of social distancing practices by subgroups and use chi-square tests for comparisons. RESULTS In terms of degree of social distancing, 25.8% of the interviewees reported being essentially isolated and 41.1% reported being quite isolated. 20.1% of respondents reported staying at home all the time, while 44.5% left only for essential activities. More than half of households reported receiving no visits from non-residents. Adults aged 20 to 59 reported the least social distancing, while more than 80% of participants aged 60 years or older reported being essentially isolated or quite isolated. Women reported more stringent distancing than men. Groups with higher educational attainment reported going out for daily activities more frequently. CONCLUSIONS The extremes of age are more protected by social distancing, but some groups remain highly exposed. This can be an important limiting factor in controlling progression of the COVID-19 pandemic. RESUMO OBJETIVO Descrever práticas de distanciamento social em nove municípios do Rio Grande do Sul por sexo, idade, escolaridade e cidade. MÉTODOS Foram realizados dois estudos transversais sequenciais representativos da população urbana nos municípios de Canoas, Caxias do Sul, Ijuí, Passo Fundo, Pelotas, Porto Alegre, Santa Cruz do Sul, Santa Maria e Uruguaiana com o intuito de estimar a prevalência populacional de Covid-19. Foi aplicado questionário contendo três perguntas sobre distanciamento social, cujas práticas foram submetidas a análises descritivas por subgrupos. Os dados foram comparados por testes qui-quadrado. RESULTADOS Em termos de grau de distanciamento social, 25,8% dos entrevistados relataram estar praticamente isolados e 41,1% indicam praticar bastante distanciamento. Relataram ficar em casa o tempo todo 20,1% dos entrevistados, e 44,5% informam que saem apenas para atividades essenciais. Mais da metade dos domicílios não recebe visitas de não moradores. O grupo que relatou menos distanciamento social foi o de adultos entre 20 e 59 anos, enquanto mais de 80% dos entrevistados com 60 anos ou mais relataram estar praticamente isolados ou fazendo bastante distanciamento. As mulheres relataram fazer mais distanciamento que os homens, e os grupos de maior escolaridade foram os que relataram sair diariamente para atividades regulares com mais frequência. CONCLUSÕES Os grupos mais jovens e mais idosos estão mais protegidos pelo distanciamento social, mas há grupos bastante expostos, o que pode ser um limitador importante no controle da progressão da epidemia de Covid-19.

SARS-CoV-2 antibody prevalence in Brazil: results from two successive nationwide serological household surveys.

BACKGROUND: Population-based data on COVID-19 are essential for guiding policies. There are few such studies, particularly from low or middle-income countries. Brazil is currently a hotspot for COVID-19 globally. We aimed to investigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence by city and according to sex, age, ethnicity group, and socioeconomic status, and compare seroprevalence estimates with official statistics on deaths and cases. METHODS: In this repeated cross-sectional study, we did two seroprevalence surveys in 133 sentinel cities in all Brazilian states. We randomly selected households and randomly selected one individual from all household members. We excluded children younger than 1 year. Presence of antibodies against SARS-CoV-2 was assessed using a lateral flow point-of-care test, the WONDFO SARS-CoV-2 Antibody Test (Wondfo Biotech, Guangzhou, China), using two drops of blood from finger prick samples. This lateral-flow assay detects IgG and IgM isotypes that are specific to the SARS-CoV-2 receptor binding domain of the spike protein. Participants also answered short questionnaires on sociodemographic information (sex, age, education, ethnicity, household size, and household assets) and compliance with physical distancing measures. FINDINGS: We included 25 025 participants in the first survey (May 14-21) and 31 165 in the second (June 4-7). For the 83 (62%) cities with sample sizes of more than 200 participants in both surveys, the pooled seroprevalence increased from 1·9% (95% CI 1·7-2·1) to 3·1% (2·8-3·4). City-level prevalence ranged from 0% to 25·4% in both surveys. 11 (69%) of 16 cities with prevalence above 2·0% in the first survey were located in a stretch along a 2000 km of the Amazon river in the northern region. In the second survey, we found 34 cities with prevalence above 2·0%, which included the same 11 Amazon cities plus 14 from the northeast region, where prevalence was increasing rapidly. Prevalence levels were lower in the south and centre-west, and intermediate in the southeast, where the highest level was found in Rio de Janeiro (7·5% [4·2-12·2]). In the second survey, prevalence was similar in men and women, but an increased prevalence was observed in participants aged 20-59 years and those living in crowded conditions (4·4% [3·5-5·6] for those living with households with six or more people). Prevalence among Indigenous people was 6·4% (4·1-9·4) compared with 1·4% (1·2-1·7) among White people. Prevalence in the poorest socioeconomic quintile was 3·7% (3·2-4·3) compared with 1·7% (1·4-2·2) in the wealthiest quintile. INTERPRETATION: Antibody prevalence was highly heterogeneous by country region, with rapid initial escalation in Brazil's north and northeast. Prevalence is strongly associated with Indigenous ancestry and low socioeconomic status. These population subgroups are unlikely to be protected if the policy response to the pandemic by the national government continues to downplay scientific evidence. FUNDING: Brazilian Ministry of Health, Instituto Serrapilheira, Brazilian Collective Health Association, and the JBS Fazer o Bem Faz Bem.

Key questions for modelling COVID-19 exit strategies.

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

Social distancing patterns in nine municipalities of Rio Grande do Sul, Brazil: the Epicovid19/RS study.

OBJECTIVE To describe social distancing practices in nine municipalities of the state of Rio Grande do Sul, Brazil, stratified by gender, age, and educational attainment. METHODS Two sequential cross-sectional studies were conducted in the municipalities of Canoas, Caxias do Sul, Ijuí, Passo Fundo, Pelotas, Porto Alegre, Santa Cruz do Sul, Santa Maria, and Uruguaiana to estimate the population prevalence of COVID-19. The study was designed to be representative of the urban population of these municipalities. A questionnaire including three questions about social distancing was also administered to the participants. Here, we present descriptive analyses of social distancing practices by subgroups and use chi-square tests for comparisons. RESULTS In terms of degree of social distancing, 25.8% of the interviewees reported being essentially isolated and 41.1% reported being quite isolated. 20.1% of respondents reported staying at home all the time, while 44.5% left only for essential activities. More than half of households reported receiving no visits from non-residents. Adults aged 20 to 59 reported the least social distancing, while more than 80% of participants aged 60 years or older reported being essentially isolated or quite isolated. Women reported more stringent distancing than men. Groups with higher educational attainment reported going out for daily activities more frequently. CONCLUSIONS The extremes of age are more protected by social distancing, but some groups remain highly exposed. This can be an important limiting factor in controlling progression of the COVID-19 pandemic.

Population-based surveys of antibodies against SARS-CoV-2 in Southern Brazil.

Population-based data on COVID-19 are urgently needed. We report on three rounds of probability sample household surveys in the state of Rio Grande do Sul (Brazil), carried out in nine large municipalities using the Wondfo lateral flow point-of-care test for immunoglobulin M and G antibodies against SARS-CoV-2 (https://en.wondfo.com.cn/product/wondfo-sars-cov-2-antibody-test-lateral-flow-method-2/). Before survey use, the assay underwent four validation studies with pooled estimates of sensitivity (84.8%; 95% confidence interval (CI) = 81.4-87.8%) and specificity (99.0%; 95% CI = 97.8-99.7%). We calculated that the seroprevalence was 0.048% (2/4,151; 95% CI = 0.006-0.174) on 11-13 April (round 1), 0.135% (6/4,460; 95% CI = 0.049-0.293%) on 25-27 April (round 2) and 0.222% (10/4,500; 95% CI = 0.107-0.408) on 9-11 May (round 3), with a significant upward trend over the course of the surveys. Of 37 family members of positive individuals, 17 (35%) were also positive. The epidemic is at an early stage in the state, and there is high compliance with social distancing, unlike in other parts of Brazil. Periodic survey rounds will continue to monitor trends until at least the end of September, and our population-based data will inform decisions on preventive policies and health system preparedness at the state level.