Combining Digital and Molecular Approaches Using Health and Alternate Data Sources in a Next-Generation Surveillance System for Anticipating Outbreaks of Pandemic Potential.

Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive and innovative surveillance strategies aiming at early alert and timely containment of emerging and reemerging pathogens are a pressing priority. Shortcomings and delays in current pathogen surveillance practices further disturbed informing responses, interventions, and mitigation of recent pandemics, including H1N1 influenza and SARS-CoV-2. We present the design principles of the architecture for an early-alert surveillance system that leverages the vast available data landscape, including syndromic data from primary health care, drug sales, and rumors from the lay media and social media to identify areas with an increased number of cases of respiratory disease. In these potentially affected areas, an intensive and fast sample collection and advanced high-throughput genome sequencing analyses would inform on circulating known or novel pathogens by metagenomics-enabled pathogen characterization. Concurrently, the integration of bioclimatic and socioeconomic data, as well as transportation and mobility network data, into a data analytics platform, coupled with advanced mathematical modeling using artificial intelligence or machine learning, will enable more accurate estimation of outbreak spread risk. Such an approach aims to readily identify and characterize regions in the early stages of an outbreak development, as well as model risk and patterns of spread, informing targeted mitigation and control measures. A fully operational system must integrate diverse and robust data streams to translate data into actionable intelligence and actions, ultimately paving the way toward constructing next-generation surveillance systems.

Syndromic Surveillance Using Structured Telehealth Data: Case Study of the First Wave of COVID-19 in Brazil.

BACKGROUND: Telehealth has been widely used for new case detection and telemonitoring during the COVID-19 pandemic. It safely provides access to health care services and expands assistance to remote, rural areas and underserved communities in situations of shortage of specialized health professionals. Qualified data are systematically collected by health care workers containing information on suspected cases and can be used as a proxy of disease spread for surveillance purposes. However, the use of this approach for syndromic surveillance has yet to be explored. Besides, the mathematical modeling of epidemics is a well-established field that has been successfully used for tracking the spread of SARS-CoV-2 infection, supporting the decision-making process on diverse aspects of public health response to the COVID-19 pandemic. The response of the current models depends on the quality of input data, particularly the transmission rate, initial conditions, and other parameters present in compartmental models. Telehealth systems may feed numerical models developed to model virus spread in a specific region. OBJECTIVE: Herein, we evaluated whether a high-quality data set obtained from a state-based telehealth service could be used to forecast the geographical spread of new cases of COVID-19 and to feed computational models of disease spread. METHODS: We analyzed structured data obtained from a statewide toll-free telehealth service during 4 months following the first notification of COVID-19 in the Bahia state, Brazil. Structured data were collected during teletriage by a health team of medical students supervised by physicians. Data were registered in a responsive web application for planning and surveillance purposes. The data set was designed to quickly identify users, city, residence neighborhood, date, sex, age, and COVID-19-like symptoms. We performed a temporal-spatial comparison of calls reporting COVID-19-like symptoms and notification of COVID-19 cases. The number of calls was used as a proxy of exposed individuals to feed a mathematical model called "susceptible, exposed, infected, recovered, deceased." RESULTS: For 181 (43%) out of 417 municipalities of Bahia, the first call to the telehealth service reporting COVID-19-like symptoms preceded the first notification of the disease. The calls preceded, on average, 30 days of the notification of COVID-19 in the municipalities of the state of Bahia, Brazil. Additionally, data obtained by the telehealth service were used to effectively reproduce the spread of COVID-19 in Salvador, the capital of the state, using the "susceptible, exposed, infected, recovered, deceased" model to simulate the spatiotemporal spread of the disease. CONCLUSIONS: Data from telehealth services confer high effectiveness in anticipating new waves of COVID-19 and may help understand the epidemic dynamics.

Real-world effectiveness of biological therapy in patients with rheumatoid arthritis: Systematic review and meta-analysis.

Background: The treatment of rheumatoid arthritis (RA), a chronic systemic inflammatory autoimmune disease, is based on disease-modifying anti-rheumatic drugs (DMARDs). Typically, it starts with conventional synthetic DMARDs (csDMARDs), and depending on the patient's response to the treatment and the adverse events experienced, biological DMARDs (bDMARDs) are initiated. bDMARDs are more specific to inflammatory factors than csDMARDs and more efficient in inducing remission and low disease activity. Thus, this study aimed to assess the effectiveness of biological therapy in patients with rheumatoid arthritis in administrative health databases. Methods: PubMed, Embase, Lilacs, Ovid, Scopus, and Web of Science databases were searched from inception to 21 October 2021, to identify observational studies that evaluated the effectiveness of biological therapy in patients with rheumatoid arthritis using administrative databases and real-world data. The methodological quality was assessed by the methodological index for non-randomized studies (MINORS). A fixed or random-effects model estimated risk ratios with 95% confidence intervals. The analysis was divided into four groups: tumor necrosis factor inhibitors (TNFi) versus non-TNFi; TNFi versus TNFi (adalimumab, etanercept, and golimumab versus infliximab); bDMARDs versus Janus kinase inhibitors (JAKi); and bDMARDs monotherapy versus combination therapy (bDMARDs and MTX). Results: Twenty-one records were eligible for inclusion in this systematic review and meta-analysis; seven population-based cohorts, eight prospective, and six retrospective cohort studies. Overall, 182,098 rheumatoid arthritis patients were evaluated. In the meta-analysis, lower effectiveness was observed among TNFi users than in non-TNFi (RR: 0.88; 95% CI: 0.81-0.95; p < 0.01; I2 = 94.0%) and bDMARDs than in JAKi (RR: 0.86; 95% CI: 0.79-0.94; p < 0.01; I2 = 93.0%). Higher effectiveness among adalimumab, etanercept, and golimumab than in infliximab (RR: 1.19; 95% CI: 1.05-1.36; p < 0.01; I2 = 96.0%) was found. No significant differences in the effectiveness of bDMARD monotherapy compared to combination therapy (RR: 0.83; 95% CI: 0.68-1.00; p < 0.01; I2 = 81.0%) was observed. E-value analysis indicated that the estimates were not robust against unmeasured confounding. Conclusion: According to the available real-world data, our results suggest that biological therapy effectively treats patients with rheumatoid arthritis, indicating higher effectiveness with non-TNFi and JAKi than with TNFi. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID#CRD42020190838, identifier CRD42020190838.

Safety of biological therapy in patients with rheumatoid arthritis in administrative health databases: A systematic review and meta-analysis.

Background: Rheumatoid arthritis (RA) is a systemic inflammatory disease that affects the synovial fluid of joints, tendons, and some extra-articular sites. Biologic agents have been highly effective and are comparable in reducing RA symptoms, slowing disease progression, and improving physical function; however, concerns have been raised about the risks of several potential adverse effects. Thus, this study aimed to assess the safety of biological therapy in patients with rheumatoid arthritis in observational studies using administrative health databases. Methods: PubMed, Embase, Lilacs, Ovid, Scopus, and Web of Science were searched from inception to 21 October 2021. The analysis was divided into five groups: tumor necrosis factor inhibitors (TNFi) versus non-TNFi; TNFi versus csDMARDs; bDMARDs versus csDMARDs; abatacept versus bDMARDs; and TNFi versus Janus kinase inhibitors (JAKi). The adverse events were cancer, cardiovascular events, infection, herpes zoster, tuberculosis, and death. The methodological quality of the studies was assessed by the Newcastle-Ottawa Scale. A random-effects model estimated risk ratios with 95% confidence intervals. Results: Thirty-one studies were eligible for inclusion in the present systematic review, published from 2014 to 2021. A total of 1,039,398 RA patients were assessed. The 31 studies evaluated eleven different biological drugs. No significant differences were found regarding safety between TNFi versus non-TNFi (RR 1.08; 95% CI 0.92-1.28; p < 0.01; I2 = 93.0%), TNFi versus csDMARDs (RR 0.91; 95% CI 0.75-1.10; p < 0.01; I2 = 87.0%), bDMARDs versus csDMARDs (RR 0.99; 95% CI 0.82-1.20; p < 0.01; I2 = 93.0%), abatacept versus bDMARDs (RR 0.80; 95% CI 0.54-1.18; p < 0.01; I2 = 90.0%), and TNFi versus JAKi (RR 3.54; 95% CI 0.30-42.09; p = 0.01; I2 = 81.0%). In the subgroup analysis, among studies comparing abatacept to TNFi, a lower risk of cardiovascular events was associated with abatacept (RR 0.37; 95% CI 0.24-0.55). Conclusion: Our results do not suggest an increased risk of adverse events associated with biological therapy in treating RA patients, indicating a lower risk of cardiovascular events with abatacept than TNFi. However, these findings must be interpreted with caution given the limitations of this study and the low/very low certainty of the evidence. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?, identifier [CRD42020190838].

Distribution of Human Immunodeficiency Virus and Human T-Leukemia Virus Co-infection in Bahia, Brazil.

Human Immunodeficiency Virus (HIV) and Human T-Leukemia Virus (HTLV) are retroviruses that share similar routes of transmission. In Brazil, the prevalence of HIV and HTLV varies according to geographic region. The state of Bahia, located in the Northeast region, is considered endemic for both retroviruses. The present study aimed to characterize the frequency of HIV/HTLV coinfection and evaluate the geographic distribution of coinfection throughout the state. This cross-sectional study was conducted at the state's Central Laboratory of Public Health (LACEN-BA) and included all samples from 2004 to 2013 submitted to serological testing for anti-HIV and anti-HTLV-1/2, screened by chemiluminescence/ELISA and confirmed by Western blot. Infection rates are expressed as the number of infected individuals per 100,000 inhabitants from each municipality. A total of 129,158 samples originating from 358/417 (85.8%) municipalities in Bahia were evaluated. HTLV was detected in 2.4% of the HIV-positive samples (n = 42) compared to 0.5% of those with negative HIV serology (n = 677) (OR: 4.65; CI: 3.39-6.37). HIV/HTLV coinfection was more frequent in women (69.0%); the median age of coinfected individuals was 47.2 years [interquartile range (IQR): 41.6-55.4 years]. In the 14/417 (3.4%) municipalities where at least one case of HIV/HTLV coinfection was detected, the overall HTLV coinfection rate in HIV-positive samples was 0.25 (range: 0.17-13.84) per 100,000 inhabitants. Most cases of HIV/HTLV-1 coinfection (21/37, 57%) were concentrated in the municipality of Salvador. Isolated instances (one or two cases) of HIV/HTLV-1 coinfection were distributed across municipalities known to be endemic for HTLV infection.

Seroprevalence and Spatial Distribution of Hepatitis C Virus in Bahia, Brazil.

In Salvador, which is the capital of the Brazilian state of Bahia, it has been estimated that 1.5% of the general population is infected with hepatitis C virus (HCV); however, the circulation of HCV throughout the state remains unknown. The present retrospective study aimed to determine anti-HCV seroprevalence and describe the geographic distribution of hepatitis C in Bahia. Data from HCV serological tests submitted to the Bahia Central Laboratory of Public Health between 2004 and 2013 were analyzed. Serology for HCV was performed using the AxSYM anti-HCV enzymatic microparticle immunoassay and chemiluminescence immunoassay. A subgroup of samples with detectable HCV-RNA was genotyped using the linear array hepatitis C virus genotyping assay. A total of 247,837 samples were analyzed. The median age of the studied population was 31 years (interquartile range, 25-44 years), and the female:male ratio was 3.9:1. The global seroprevalence of HCV in Bahia was estimated to be 1.3% (3,230/247,837), corresponding to an infection rate of 21.2/100,000 inhabitants. The seroprevalence of HCV was higher among males and increased with age. The presence of anti-HCV antibodies was detected throughout all mesoregions of Bahia, and the municipality with the highest infection rate was Ipiaú (112.04 cases/100,000 inhabitants). Genotypes 1 and 3 were found to be the most prevalent, followed by genotypes 2, 4, and 5. Our results provide evidence of the widespread distribution of previous HCV infection throughout the state of Bahia.

Bridging Learning in Medicine and Citizenship During the COVID-19 Pandemic: A Telehealth-Based Case Study.

BACKGROUND: COVID-19 presented great challenges for not only those in the field of health care but also those undergoing medical training. The burden on health care services worldwide has limited the educational opportunities available for medical students due to social distancing requirements. OBJECTIVE: In this paper, we describe a strategy that combines telehealth and medical training to mitigate the adverse effects of the COVID-19 pandemic. METHODS: A toll-free telescreening service, Telecoronavirus, began operations in March 2020. This service was operated remotely by supervised medical students and was offered across all 417 municipalities (14.8 million inhabitants) in the Brazilian state of Bahia. Students recorded clinical and sociodemographic data by using a web-based application that was simultaneously accessed by medical volunteers for supervision purposes, as well as by state health authorities who conducted epidemiological surveillance and health management efforts. In parallel, students received up-to-date scientific information about COVID-19 via short educational videos prepared by professors. A continuously updated triage algorithm was conceived to provide consistent service. RESULTS: The program operated for approximately 4 months, engaging 1396 medical students and 133 physicians. In total, 111,965 individuals residing in 343 municipalities used this service. Almost 70,000 individuals were advised to stay at home, and they received guidance to avoid disease transmission, potentially contributing to localized reductions in the spread of COVID-19. Additionally, the program promoted citizenship education for medical students, who were engaged in a real-life opportunity to fight the pandemic within their own communities. The objectives of the education, organization, and assistance domains of the Telecoronavirus program were successfully achieved according to the results of a web-based post-project survey that assessed physicians' and students' perceptions. CONCLUSIONS: In a prolonged pandemic scenario, a combination of remote tools and medical supervision via telehealth services may constitute a useful strategy for maintaining social distancing measures while preserving some practical aspects of medical education. A low-cost tool such as the Telecoronavirus program could be especially valuable in resource-limited health care scenarios, in addition to offering support for epidemiological surveillance actions.

Distribution of Human T-Lymphotropic Virus (HTLV) and Hepatitis C Co-infection in Bahia, Brazil.

Both Human T-lymphotropic virus type 1 (HTLV-1) and hepatitis C virus (HCV) are endemic in Brazil. In Salvador, the capital of the state of Bahia, 2% and 1.5% of the general population is infected with HTLV-1 or HCV. This study aimed to estimate the prevalence and the distribution of HTLV/HCV coinfection in Bahia. This cross-sectional study was conducted at the Central Laboratory of Public Health for the state of Bahia (LACEN-BA). All samples in the LACEN database submitted to serological testing for anti-HCV (chemiluminescence) and anti-HTLV-1/2 (chemiluminescence/ELISA and Western blot) from 2004 to 2013 were included. Infection rate was expressed as the number of infected individuals per 100,000 inhabitants in a given municipality; municipalities were grouped by microregion for further analysis. A total of 120,192 samples originating from 358 of the 417 municipalities in Bahia (85.8%) were evaluated. The overall HCV coinfection rate in HTLV-positive was 14.31% [2.8 (ranging from 0.4 to 8.0) per 100,000 inhabitants.] Twenty-one (5%) of the municipalities reported at least one case of HTLV/HCV coinfection. Most cases (87%) were concentrated in three microregions (Salvador: 79%, Ilhéus/Itabuna: 5%, Porto Seguro: 3%). Coinfection occurred more frequently in males (51%) with a mean age of 59 [(IQR): 46-59] years. HTLV/HCV coinfection in the state of Bahia was more frequently found among males living in the microregions of Salvador, Ilhéus/Itabuna and Porto Seguro, all of which are known to be endemic for HTLV infection.

Evidence of New Endemic Clusters of Human T-Cell Leukemia Virus (HTLV) Infection in Bahia, Brazil.

BACKGROUND: Salvador, Bahia (northeastern Brazil), has been identified as the epicenter of Human T-cell leukemia virus Human T-cell leukemia virus (HTLV) type 1 infection in the country. This study aims to estimate the rate of HTLV infection and the geographical distribution of this virus in this state. METHODS: All HTLV tests (chemiluminescence/ELISA assays/Western Blotting) performed in the Central Laboratory of Public Health of Bahia (LACEN) from 2004 to 2013 were included. Data was extracted from LACEN's database using high volume extract, transformation and load throughput. Infection rate was expressed as the number of infected individuals per 100,000 inhabitants considering municipalities grouped in microregions and/or mesoregions as the unit of analysis. RESULTS: A total of 233,876 individuals were evaluated. Individuals were from 394 out of 417 municipalities of Bahia (94.5%). HTLV chemiluminescence/ELISA assay was found to be reactive for 3,138 individuals from whom 2,323 had WB results (1,978 positives, 62 negative and 282 indeterminate). Out of 1978 reactive samples, 1,813 (91.7%) were positive for HTLV-1, 58 (2.9%) for HTLV-2 and 107 (5.4%) were for both HTLV-1 and HTLV-2. The cumulative mean rate of HTLV-positive cases in Bahia was 14.4 per 100,000 inhabitants. Three microregions presented rates >20 HTLV-positive cases/100,000 inhabitants: Barreiras (24.83 cases per 100,000 inhabitants), Salvador (22.90 cases per 100,000 inhabitants), and Ilhéus-Itabuna (22.60 cases per 100,000 inhabitants). CONCLUSION: HTLV infection is disseminated in the state of Bahia, with an overall moderate rate of infection. Further studies should be conducted to characterize the epidemiological and clinical profile of HTLV-infected individuals better and to propose effective prevention measures.

Administrative Data Linkage in Brazil: Potentials for Health Technology Assessment.

Health technology assessment (HTA) is the systematic evaluation of the properties and impacts of health technologies and interventions. In this article, we presented a discussion of HTA and its evolution in Brazil, as well as a description of secondary data sources available in Brazil with potential applications to generate evidence for HTA and policy decisions. Furthermore, we highlighted record linkage, ongoing record linkage initiatives in Brazil, and the main linkage tools developed and/or used in Brazilian data. Finally, we discussed the challenges and opportunities of using secondary data for research in the Brazilian context. In conclusion, we emphasized the availability of high quality data and an open, modern attitude toward the use of data for research and policy. This is supported by a rigorous but enabling legal framework that will allow the conduct of large-scale observational studies to evaluate clinical, economical, and social impacts of health technologies and social policies.