Digital health in smart cities: Rethinking the remote health monitoring architecture on combining edge, fog, and cloud.

Purpose: Smart cities that support the execution of health services are more and more in evidence today. Here, it is mainstream to use IoT-based vital sign data to serve a multi-tier architecture. The state-of-the-art proposes the combination of edge, fog, and cloud computing to support critical health applications efficiently. However, to the best of our knowledge, initiatives typically present the architectures, not bringing adaptation and execution optimizations to address health demands fully. Methods: This article introduces the VitalSense model, which provides a hierarchical multi-tier remote health monitoring architecture in smart cities by combining edge, fog, and cloud computing. Results: Although using a traditional composition, our contributions appear in handling each infrastructure level. We explore adaptive data compression and homomorphic encryption at the edge, a multi-tier notification mechanism, low latency health traceability with data sharding, a Serverless execution engine to support multiple fog layers, and an offloading mechanism based on service and person computing priorities. Conclusions: This article details the rationale behind these topics, describing VitalSense use cases for disruptive healthcare services and preliminary insights regarding prototype evaluation.

NT5E DNA methylation in papillary thyroid cancer: Novel opportunities for precision oncology.

The ectoenzyme CD73, encoded by the NT5E gene, has emerged as a potential prognostic and therapeutic marker for papillary thyroid carcinoma (PTC), which has increased in incidence in recent decades. Here, from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) database, we extracted and combined clinical features, levels of NT5E mRNA, and DNA methylation of PTC samples and performed multivariate and random forest analyses to evaluate the prognostic relevance and the potential of discriminating between adjacent non-malignant and thyroid tumor samples. As a result, we revealed that lower levels of methylation at the cg23172664 site were independently associated with BRAF-like phenotype (p = 0.002), age over 55 years (p = 0.012), presence of capsule invasion (p = 0.007) and presence of positive lymph node metastasis (LNM) (p = 0.04). The methylation levels of cg27297263 and cg23172664 sites showed significant and inversely correlations with levels of NT5E mRNA expression (r = -0.528 and r = -0.660, respectively), and their combination was able to discriminate between adjacent non-malignant and tumor samples with a precision of 96%-97% and 84%-85%, respectively. These data suggest that combining cg23172664 and cg27297263 sites may bring new insights to reveal new subsets of patients with papillary thyroid carcinoma.

Comparative epidemic expansion of SARS-CoV-2 variants Delta and Omicron in the Brazilian State of Amazonas.

The SARS-CoV-2 variants of concern (VOCs) Delta and Omicron spread globally during mid and late 2021, respectively. In this study, we compare the dissemination dynamics of these VOCs in the Amazonas state, one of Brazil's most heavily affected regions. We sequenced the virus genome from 4128 patients collected in Amazonas between July 1st, 2021, and January 31st, 2022, and investigated the viral dynamics using a phylodynamic approach. The VOCs Delta and Omicron BA.1 displayed similar patterns of phylogeographic spread but different epidemic dynamics. The replacement of Gamma by Delta was gradual and occurred without an upsurge of COVID-19 cases, while the rise of Omicron BA.1 was extremely fast and fueled a sharp increase in cases. Thus, the dissemination dynamics and population-level impact of new SARS-CoV-2 variants introduced in the Amazonian population after mid-2021, a setting with high levels of acquired immunity, greatly vary according to their viral phenotype.

Automatic documentation of professional health interactions: A systematic review.

Electronic systems are increasingly present in the healthcare system and are often related to improved medical care. However, the widespread use of these technologies ended up building a relationship of dependence that can disrupt the doctor-patient relationship. In this context, digital scribes are automated clinical documentation systems that capture the physician-patient conversation and then generate the documentation for the appointment, enabling the physician to engage with the patient entirely. We have performed a systematic literature review on intelligent solutions for automatic speech recognition (ASR) with automatic documentation during a medical interview. The scope included only original research on systems that could detect speech and transcribe it in a natural and structured fashion simultaneously with the doctor-patient interaction, excluding speech-to-text-only technologies. The search resulted in a total of 1995 titles, with eight articles remaining after filtering for the inclusion and exclusion criteria. The intelligent models mainly consisted of an ASR system with natural language processing capability, a medical lexicon, and structured text output. None of the articles had a commercially available product at the time of the publication and reported limited real-life experience. So far, none of the applications has been prospectively validated and tested in large-scale clinical studies. Nonetheless, these first reports suggest that automatic speech recognition may be a valuable tool in the future to facilitate medical registration in a faster and more reliable manner. Improving transparency, accuracy, and empathy could drastically change how patients and doctors experience a medical visit. Unfortunately, clinical data on the usability and benefits of such applications is almost non-existent. We believe that future work in this area is necessary and needed.

Development and Validation of Conversational Agent to Pregnancy Safe-education.

Pregnant women constantly need some information to support nutritional decisions during pregnancy, and many do not receive such assistance at all. This study aims to present a conversational agent to provide reliable information to pregnant women, focusing on nutritional education and evaluating the perception of pregnant women and health professionals about the agent. As a scientific contribution, this article developed and implemented a conversational agent in a real environment capable of generating reliable responses on the basis of a set of health documents. We proposed an intervention study with 25 women and 10 healthcare providers through a survey to measure the perceptions of these groups towards conversational agents. The results show that the intended design could ensure positive support for pregnant women, clarify certain issues for the public, and remove some knowledge barriers. The results showed no significant difference between the groups (p-value = 0.713). Depending on the perception of the pregnant group, the conversational agent model can teach new knowledge during the prenatal period (Mean = 4.56). The model presented for health professionals could already be indicated as a support tool for pregnant women (Mean = 4.7).

A rapid review of machine learning approaches for telemedicine in the scope of COVID-19.

The COVID-19 pandemic has rapidly spread around the world. The rapid transmission of the virus is a threat that hinders the ability to contain the disease propagation. The pandemic forced widespread conversion of in-person to virtual care delivery through telemedicine. Given this gap, this article aims at providing a literature review of machine learning-based telemedicine applications to mitigate COVID-19. A rapid review of the literature was conducted in six electronic databases published from 2015 through 2020. The process of data extraction was documented using a PRISMA flowchart for inclusion and exclusion of studies. As a result, the literature search identified 1.733 articles, from which 16 articles were included in the review. We developed an updated taxonomy and identified challenges, open questions, and current data types. Our taxonomy and discussion contribute with a significant degree of coverage from subjects related to the use of machine learning to improve telemedicine in response to the COVID-19 pandemic. The evidence identified by this rapid review suggests that machine learning, in combination with telemedicine, can provide a strategy to control outbreaks by providing smart triage of patients and remote monitoring. Also, the use of telemedicine during future outbreaks could be further explored and refined.

The HoPE Model Architecture: a Novel Approach to Pregnancy Information Retrieval Based on Conversational Agents.

Conversational agents are used to communicating with humans in a friendly manner. To achieve the highest level of performance, agents need to respond assertively and fastly. Transformer architectures are shown to produce excellent performances on recent tasks; however, for tasks involving conversational agents, they may have a lower speed performance. The main goal of this study is to evaluate and propose a HoPE (Healthcare Obstetric in PrEgnancy) model that is tailored to pregnancy data. We carried out a dataset extraction and construction process based on collections of health documents related to breastfeeding, childcare, pregnant care, nutrition, risks, vaccines, exams, and physical exercises. We evaluated two pre-trained models in the Portuguese language for the conversational agent architecture proposal and chose the one with the best performance to compose the HoPE architecture. The BERTimbau model, which has been trained on data augmentation strategies, proves to be able to retrieve information quickly and most accurately than others. For the fine-tuning process, we achieved a Spearman correlation of 95.55 on BERTimbau augmented with a few pairs (1.500 pairs). The HoPE model architecture achieved an F1-Score of 0.89, outperforming other combinations tested in this study. We will evaluate this approach for clinical studies in future studies.

Semantic interoperability in health records standards: a systematic literature review.

The integration and exchange of information among health organizations and system providers are currently regarded as a challenge. Each organization usually has an internal ecosystem and a proprietary way to store electronic health records of the patient's history. Recent research explores the advantages of an integrated ecosystem by exchanging information between the different inpatient care actors. Many efforts seek quality in health care, economy, and sustainability in process management. Some examples are reducing medical errors, disease control and monitoring, individualized patient care, and avoiding duplicate and fragmented entries in the electronic medical record. Likewise, some studies showed technologies to achieve this goal effectively and efficiently, with the ability to interoperate data, allowing the interpretation and use of health information. To that end, semantic interoperability aims to share data among all the sectors in the organization, clinicians, nurses, lab, the entire hospital. Therefore, avoiding data silos and keep data regardless of vendors, to exchange the information across organizational boundaries. This study presents a comprehensive systematic literature review of semantic interoperability in electronic health records. We searched seven databases of articles published between 2010 to September 2020. We showed the most chosen scenarios, technologies, and tools employed to solve interoperability problems, and we propose a taxonomy around semantic interoperability in health records. Also, we presented the main approaches to solve the exchange problem of legacy and heterogeneous data across healthcare organizations.

Strengthening therapeutic adherence and pharmacovigilance to antimalarial treatment in Manaus, Brazil: a multicomponent strategy using mHealth.

BACKGROUND: Public health initiatives for improving adherence to primaquine based regimens and enhancing effective pharmacovigilance are needed to support the efforts for malaria elimination in real world conditions. METHODS: A multicomponent patient-oriented strategy using a Smart Safety Surveillance (3S) approach including: (1) educational materials for treatment counselling and identification of warning symptoms of haemolytic anaemia; (2) an mHealth component using Short Message Service (SMS) treatment reminders and (3) development and implementation of follow-up phone surveys three days after treatment completion, using a web-based platform linked to the local information system of malaria. Adherence was measured using the Morisky Medication Adherence Scale. Self-reported events were registered using a structured questionnaire and communicated to the Brazilian Health Regulatory Agency. RESULTS: Educational materials were disseminated to 5594 patients, of whom 1512 voluntarily entered the mHealth component through the local information system; 7323 SMS were sent, and 1062 participants completed a follow-up survey after treatment. The mean age of patients was 37.36 years (SD 13.65), 61.24% were male, 98.54% were infected with. Plasmodium vivax and 95.90% received a short regimen of chloroquine plus primaquine (CQ + PQ 7 days), as per malaria case management guidelines in Brazil. From the 1062 surveyed participants 93.31% were considered adherent to the treatment. Most of the patients (95.20%) reported at least one adverse event. Headache, lack of appetite and nausea/vomiting were the most frequently reported adverse events by 77.31%, 70.90% and 56.78% of the patients respectively. A quarter of the patients reported anxiety or depression symptoms; 57 (5.37%) patients reported 5 to 6 warning symptoms of haemolytic anaemia including jaundice and dark urine in 44 (4.14%). Overall, three patients presenting symptoms of haemolytic anaemia attended a hospital and were diagnosed with G6PD deficiency, and one had haemolysis. All of them recovered. CONCLUSIONS: Under real world conditions, a multicomponent patient-oriented strategy using information and communication technologies allowed health care providers to reinforce treatment adherence and enhance safety surveillance of adverse events associated with regimens using primaquine. Active monitoring through phone surveys also reduced under-reporting of ADRs. This approach is low-cost, scalable and able to support prioritized activities of the national malaria programme.

SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses.

On 24th November 2021, the sequence of a new SARS-CoV-2 viral isolate Omicron-B.1.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titers of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic Alpha, Beta, Gamma, or Delta are substantially reduced, or the sera failed to neutralize. Titers against Omicron are boosted by third vaccine doses and are high in both vaccinated individuals and those infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of the large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses and uses mutations that confer tight binding to ACE2 to unleash evolution driven by immune escape. This leads to a large number of mutations in the ACE2 binding site and rebalances receptor affinity to that of earlier pandemic viruses.

First and second COVID-19 waves in Brazil: A cross-sectional study of patients' characteristics related to hospitalization and in-hospital mortality.

BACKGROUND: Background The second wave of the COVID-19 pandemic was more aggressive in Brazil compared to other countries around the globe. Considering the Brazilian peculiarities, we analyze the in-hospital mortality concerning socio-epidemiological characteristics of patients and the health system of all states during the first and second waves of COVID-19. METHODS: We performed a cross-sectional study of hospitalized patients with positive RT-PCR for SARS-CoV-2 in Brazil. Data was obtained from the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) and comprised the period from February 25, 2020, to April 30, 2021, separated in two waves on November 5, 2020. We performed a descriptive study of patients analyzing socio-demographic characteristics, symptoms, comorbidities, and risk factors stratified by age. In addition, we analyzed in-hospital and intensive care unit (ICU) mortality in both waves and how it varies in each Brazilian state. FINDINGS: Between February 25, 2020 and April 30, 2021, 678 235 patients were admitted with a positive RT-PCR for SARS-CoV-2, with 325 903 and 352 332 patients for the first and second wave, respectively. The mean age of patients was 59 · 65 (IQR 48 · 0 - 72 · 0). In total, 379 817 (56 · 00%) patients had a risk factor or comorbidity. In-hospital mortality increased from 34 · 81% in the first to 39 · 30% in the second wave. In the second wave, there were more ICU admissions, use of non-invasive and invasive ventilation, and increased mortality for younger age groups. The southern and southeastern regions of Brazil had the highest hospitalization rates per 100 000 inhabitants. However, the in-hospital mortality rate was higher in the northern and northeastern states of the country. Racial differences were observed in clinical outcomes, with White being the most prevalent hospitalized population, but with Blacks/Browns (Pardos) having higher mortality rates. Younger age groups had more considerable differences in mortality as compared to groups with and without comorbidities in both waves. INTERPRETATION: We observed a more considerable burden on the Brazilian hospital system throughout the second wave. Furthermore, the north and northeast of Brazil, which present lower Human Development Indexes, concentrated the worst in-hospital mortality rates. The highest mortality rates are also shown among vulnerable social groups. Finally, we believe that the results can help to understand the behavior of the COVID-19 pandemic in Brazil, helping to define public policies, allocate resources, and improve strategies for vaccination of priority groups. FUNDING: Coordinating Agency for Advanced Training of Graduate Personnel (CAPES) (C.F. 001), and National Council for Scientific and Technological Development (CNPq) (No. 309537/2020-7).

Functional Coronary Artery Assessment: a Systematic Literature Review.

Cardiovascular diseases represent the number one cause of death in the world, including the most common disorders in the heart's health, namely coronary artery disease (CAD). CAD is mainly caused by fat accumulated in the arteries' internal walls, creating an atherosclerotic plaque that impacts the blood flow functional behavior. Anatomical plaque characteristics are essential but not sufficient for a complete functional assessment of CAD. In fact, plaque analysis and visual inspection alone have proven insufficient to determine the lesion severity and hemodynamic repercussion. Furthermore, the fractional flow reserve (FFR) exam, which is considered the gold standard for stenosis functional impair determination, is invasive and contains several limitations. Such a panorama evidences the need for new techniques applied to image exams to improve CAD functional assessment. In this article, we perform a systematic literature review on emerging methods determining CAD significance, thus delivering a unique base for comparing these methods, qualitatively and quantitatively. Our goal is to guide further studies with evidence from the most promising methods, highlighting the benefits from both areas. We summarize benchmarks, metrics for evaluation, and challenges already faced, thus shedding light on the requirements for a valid, meaningful, and accepted technique for functional assessment evaluation. We create a base of comparison based on quantitative and qualitative indicators and highlight the most relevant geometrical metrics that correlate with lesion significance. Finally, we point out future benchmarks based on recent literature.

Cluster of SARS-CoV-2 Gamma Variant Infections, Parintins, Brazil, March 2021.

High case counts after the Gamma (P. 1) variant of severe acute respiratory syndrome coronavirus 2 emerged in Brazil raised concerns that previously infected persons might become reinfected. Investigation of a cluster of coronavirus disease cases in Parintins, in the Brazilian Amazon, suggested household transmission but did not identify high rates of reinfection.

A Blockchain-Based End-to-End Data Protection Model for Personal Health Records Sharing: A Fully Homomorphic Encryption Approach.

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for processing, storing, and sharing health records. Furthermore, fully homomorphic encryption (FHE) is a set of techniques that allows the calculation of encrypted data, which can help to protect personal privacy in data sharing. In this context, we propose an architectural model that applies a DHT technique called the interplanetary protocol file system and blockchain networks to store and distribute data and metadata separately; two new elements, called data steward and shared data vault, are introduced in this regard. These new modules are responsible for segregating responsibilities from health institutions and promoting end-to-end encryption; therefore, a person can manage data encryption and requests for data sharing in addition to restricting access to data for a predefined period. In addition to supporting calculations on encrypted data, our contribution can be summarized as follows: (i) mitigation of risk to personal privacy by reducing the use of unencrypted data, and (ii) improvement of semantic interoperability among health institutions by using distributed networks for standardized PHR. We evaluated performance and storage occupation using a database with 1.3 million COVID-19 registries, which showed that combining FHE with distributed networks could redefine e-health paradigms.

Malaria absorption peaks acquired through the skin of patients with infrared light can detect patients with varying parasitemia.

To eliminate malaria, scalable tools that are rapid, affordable, and can detect patients with low parasitemia are required. Non-invasive diagnostic tools that are rapid, reagent-free, and affordable would also provide a justifiable platform for testing malaria in asymptomatic patients. However, non-invasive surveillance techniques for malaria remain a diagnostic gap. Here, we show near-infrared Plasmodium absorption peaks acquired non-invasively through the skin using a miniaturized hand-held near-infrared spectrometer. Using spectra from the ear, these absorption peaks and machine learning techniques enabled non-invasive detection of malaria-infected human subjects with varying parasitemia levels in less than 10 s.

Structural analysis of SARS-Cov-2 nonstructural protein 1 polymorphisms found in the Brazilian Amazon.

The coronavirus disease COVID-19 has been the cause of millions of deaths worldwide. Among the SARS-CoV-2 proteins, the non-structural protein 1 (NSP1) has great importance during the virus infection process and is present in both alpha and beta-CoVs. Therefore, monitoring of NSP1 polymorphisms is crucial in order to understand their role during infection and virus-induced pathogenicity. Herein, we analyzed how mutations detected in the circulating SARS-CoV-2 in the population of the city of Manaus, Amazonas state, Brazil could modify the tertiary structure of the NSP1 protein. Three mutations were detected in the SARS-CoV-2 NSP1 gene: deletion of the amino acids KSF from positions 141 to 143 (delKSF), SARS-CoV-2, lineage B.1.195; and two substitutions, R29H and R43C, SARS-CoV-2 lineage B.1.1.28 and B.1.1.33, respectively. The delKSF was found in 47 samples, whereas R29H and R43C were found in two samples, one for each mutation. The NSP1 structures carrying the mutations R43C and R29H on the N-terminal portion (e.g. residues 10 to 127) showed minor backbone divergence compared to the Wuhan model. However, the NSP1 C-terminal region (residues 145 to 180) was severely affected in the delKSF and R29H mutants. The intermediate variable region (residues 144 to 148) leads to changes in the C-terminal region, particularly in the delKSF structure. New investigations must be carried out to analyze how these changes affect NSP1 activity during the infection. Our results reinforce the need for continuous genomic surveillance of SARS-CoV-2 to better understand virus evolution and assess the potential impact of the viral mutations on the approved vaccines and future therapies.

High anti-SARS-CoV-2 antibody seroconversion rates before the second wave in Manaus, Brazil, and the protective effect of social behaviour measures: results from the prospective DETECTCoV-19 cohort.

BACKGROUND: The city of Manaus, Brazil, has seen two collapses of the health system due to the COVID-19 pandemic. We report anti-SARS-CoV-2 nucleocapsid IgG antibody seroconversion rates and associated risk factors in Manaus residents before the second wave of the epidemic in Brazil. METHODS: A convenience sample of adult (aged ≥18 years) residents of Manaus was recruited through online and university website advertising into the DETECTCoV-19 study cohort. The current analysis of seroconversion included a subgroup of DETECTCoV-19 participants who had at least two serum sample collections separated by at least 4 weeks between Aug 19 and Oct 2, 2020 (visit 1), and Oct 19 and Nov 27, 2020 (visit 2). Those who reported (or had no data on) having a COVID-19 diagnosis before visit 1, and who were positive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at visit 1 were excluded. Using an in-house ELISA, the reactivity index (RI; calculated as the optical density ratio of the sample to the negative control) for serum anti-SARS-CoV-2 nucleocapsid IgG antibodies was measured at both visits. We calculated the incidence of seroconversion (defined as RI values ≤1·5 at visit 1 and ≥1·5 at visit 2, and a ratio >2 between the visit 2 and visit 1 RI values) during the study period, as well as incidence rate ratios (IRRs) through cluster-corrected and adjusted Poisson regression models to analyse associations between seroconversion and variables related to sociodemographic characteristics, health access, comorbidities, COVID-19 exposure, protective behaviours, and symptoms. FINDINGS: 2496 DETECTCoV-19 cohort participants returned for a follow-up visit between Oct 19 and Nov 27, 2020, of whom 204 reported having COVID-19 before the first visit and 24 had no data regarding previous disease status. 559 participants were seropositive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at baseline. Of the remaining 1709 participants who were seronegative at baseline, 71 did not meet the criteria for seroconversion and were excluded from the analyses. Among the remaining 1638 participants who were seronegative at baseline, 214 showed seroconversion at visit 2. The seroconversion incidence was 13·06% (95% CI 11·52-14·79) overall and 6·78% (5·61-8·10) for symptomatic seroconversion, over a median follow-up period of 57 days (IQR 54-61). 48·1% of seroconversion events were estimated to be asymptomatic. The sample had higher proportions of affluent and higher-educated people than those reported for the Manaus city population. In the fully adjusted and corrected model, risk factors for seroconversion before visit 2 were having a COVID-19 case in the household (IRR 1·49 [95% CI 1·21-1·83]), not wearing a mask during contact with a person with COVID-19 (1·25 [1·09-1·45]), relaxation of physical distancing (1·31 [1·05-1·64]), and having flu-like symptoms (1·79 [1·23-2·59]) or a COVID-19 diagnosis (3·57 [2·27-5·63]) between the first and second visits, whereas working remotely was associated with lower incidence (0·74 [0·56-0·97]). INTERPRETATION: An intense infection transmission period preceded the second wave of COVID-19 in Manaus. Several modifiable behaviours increased the risk of seroconversion, including non-compliance with non-pharmaceutical interventions measures such as not wearing a mask during contact, relaxation of protective measures, and non-remote working. Increased testing in high-transmission areas is needed to provide timely information about ongoing transmission and aid appropriate implementation of transmission mitigation measures. FUNDING: Ministry of Education, Brazil; Fundação de Amparo à Pesquisa do Estado do Amazonas; Pan American Health Organization (PAHO)/WHO.

The ongoing evolution of variants of concern and interest of SARS-CoV-2 in Brazil revealed by convergent indels in the amino (N)-terminal domain of the spike protein.

Mutations at both the receptor-binding domain (RBD) and the amino (N)-terminal domain (NTD) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Spike (S) glycoprotein can alter its antigenicity and promote immune escape. We identified that SARS-CoV-2 lineages circulating in Brazil with mutations of concern in the RBD independently acquired convergent deletions and insertions in the NTD of the S protein, which altered the NTD antigenic-supersite and other predicted epitopes at this region. Importantly, we detected the community transmission of different P.1 lineages bearing NTD indels ∆69-70 (which can impact several SARS-CoV-2 diagnostic protocols), ∆144 and ins214ANRN, and a new VOI N.10 derived from the B.1.1.33 lineage carrying three NTD deletions (∆141-144, ∆211, and ∆256-258). These findings support that the ongoing widespread transmission of SARS-CoV-2 in Brazil generates new viral lineages that might be more resistant to antibody neutralization than parental variants of concern.

Effectiveness of CoronaVac among healthcare workers in the setting of high SARS-CoV-2 Gamma variant transmission in Manaus, Brazil: A test-negative case-control study.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, Gamma, emerged in the city of Manaus in late 2020 during a large resurgence of coronavirus disease (COVID-19), and has spread throughout Brazil. The effectiveness of vaccines in settings with widespread Gamma variant transmission has not been reported. METHODS: We performed a matched test-negative case-control study to estimate the effectiveness of an inactivated vaccine, CoronaVac, in healthcare workers (HCWs) in Manaus, where the Gamma variant accounted for 86% of genotyped SARS-CoV-2 samples at the peak of its epidemic. We performed an early analysis of effectiveness following administration of at least one vaccine dose and an analysis of effectiveness of the two-dose schedule. The primary outcome was symptomatic SARS-CoV-2 infection. FINDINGS: For the early at-least-one-dose and two-dose analyses the study population was, respectively, 53,176 and 53,153 HCWs residing in Manaus and aged 18 years or older, with complete information on age, residence, and vaccination status. Among 53,153 HCWs eligible for the two-dose analysis, 47,170 (89%) received at least one dose of CoronaVac and 2,656 individuals (5%) underwent RT-PCR testing from 19 January, 2021 to 13 April, 2021. Of 3,195 RT-PCR tests, 885 (28%) were positive. 393 and 418 case-control pairs were selected for the early and two-dose analyses, respectively, matched on calendar time, age, and neighbourhood. Among those who had received both vaccine doses before the RT-PCR sample collection date, the average time from second dose to sample collection date was 14 days (IQR 7-24). In the early analysis, vaccination with at least one dose was associated with a 0.50-fold reduction (adjusted vaccine effectiveness (VE), 49.6%, 95% CI 11.3 to 71.4) in the odds of symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the first dose. However, we estimated low effectiveness (adjusted VE 36.8%, 95% CI -54.9 to 74.2) of the two-dose schedule against symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the second dose. A finding that vaccinated individuals were much more likely to be infected than unvaccinated individuals in the period 0-13 days after first dose (aOR 2.11, 95% CI 1.36-3.27) suggests that unmeasured confounding led to downward bias in the vaccine effectiveness estimate. INTERPRETATION: Evidence from this test-negative study of the effectiveness of CoronaVac was mixed, and likely affected by bias in this setting. Administration of at least one vaccine dose showed effectiveness against symptomatic SARS-CoV-2 infection in the setting of epidemic Gamma variant transmission. However, the low estimated effectiveness of the two-dose schedule underscores the need to maintain non-pharmaceutical interventions while vaccination campaigns with CoronaVac are being implemented. FUNDING: Fundação Oswaldo Cruz (Fiocruz); Municipal Health Secretary of Manaus; Fundação de Vigilância em Saúde do Amazonas.

SARS-CoV-2 seroprevalence and associated factors in Manaus, Brazil: baseline results from the DETECTCoV-19 cohort study.

BACKGROUND: Manaus, located in the Brazilian rainforest, has experienced two health system collapses due to the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about which groups among the general population have been most affected. METHODS: A convenience sampling strategy via online advertising recruited 3046 adults between 19 August 2020 and 2 October 2020. Sociodemographic characteristics, COVID-19-related symptoms, COVID-19 testing, self-medication and prescribed medications were recorded. Serum anti-severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) nucleocapsid immunoglobulin G antibodies were measured with an enzyme-linked immunosorbent assay. Prevalence ratios (PR) were obtained using cluster-corrected and adjusted Poisson's regression models. RESULTS: A crude positivity rate among asymptomatic and symptomatic individuals was estimated at 29.10%, with maximum possible seroprevalence of 44.82% corrected by test characteristics and an antibody decay rate of 32.31%. Regression models demonstrated a strong association towards marginalized low-income and vulnerable residents with limited access to health care. The presence of a COVID-19 case [PR 1.39, 95% confidence interval (CI) 1.24-1.57] or death (PR 2.14, 95% CI 1.74-2.62) in a household greatly increased the risk of other household members acquiring infection. The seroprevalence of SARS-CoV-2 was higher among those who self-medicated to prevent infection (PR 1.36, 95% CI 1.27-1.46). CONCLUSIONS: Disproportionate socio-economic disparity was observed among the study participants. The syndemic nature of COVID-19 in the Amazon region needs differential policies and urgent solutions to control the ongoing pandemic.