To analyze the demand creation strategies for Covid-19 testing and to describe surveillance indicators for testing, quarantine, contact tracing, and telemonitoring in primary health care services.

This cross-sectional study used data from the Covid-19 Testing, Isolation, Quarantine, and Telemonitoring (TQT Covid-19) study, conducted from July 2022 to July 2023. Primary healthcare service units in Rio de Janeiro and Salvador were selected to apply an intervention to develop demand creation strategies for testing uptake. Demand creation strategies were grouped into online strategies, traditional means, primary health care service units, community, and active search. Logistic regression was performed to determine the characteristics of the population reached by each strategy. The following Covid-19 surveillance indicators were estimated for testing and prevention (testing rate, positivity rate, monthly incidence, and full vaccination rate); for telemonitoring (monitoring rate, severity, referrals, and mortality); for quarantine (quarantine conditions); and for contact tracing (proportion of contacts traced and refusals of testing).

The intervention reached 12,401 individuals, and 11,843 tests were performed. Demand creation strategies that reached more individuals for testing were primary health care service units (37.0%) and active search (25.9%). The positivity rate during the study period was 27.2% in Salvador and 11.5% in Rio de Janeiro. A total of 14.1% of cases were monitored, and most were asymptomatic (42.5%) or mild (52.3%). No deaths were reported among monitored cases. The proportion of fully vaccinated individuals was 91.8%. Contact tracing identified 25.1% of reported contacts, and 41.5% declined testing.

The intervention facilitated expanded testing. Primary health care service units and active search were the strategies that reached more individuals for testing. Telemonitoring and contact tracing were the most challenging components to implement in primary health care services units and, given their importance, should be strengthened for future pandemics. These findings underscore the relevance of surveillance for assessing public health measures, identifying gaps, and supporting data-driven decision-making to improve epidemic management.

To analyze the perceptions of Primary Health Care (PHC) professionals regarding Covid-19 testing in basic health units (BHUs).

This qualitative study, part of a formative research project, involved 22 semi-structured interviews and 4 focus groups with professionals working in PHC in a Brazilian capital city. Among other criteria, the professional most directly involved in pandemic response measures in each BHU was selected. Content analysis was performed using a deductive analytical approach, in which the findings were organized into categories defined based on the components of the health system (population; infrastructure; organization of services; service delivery or care model; and management).

Reports commonly referred, in the population component, to the challenges arising from the limitations of PHC coverage; in the infrastructure component, the insufficiency of human resources and physical infrastructure was highlighted, which in turn required changes in the organization and provision of services, with repercussions on the care model. The contributions also revealed that at some points during the pandemic there was a disruption of the work process, especially in family health teams. In the management component, weaknesses in communication flows between the health secretariat and the BHU were identified, although this was less frequently mentioned.

The perception that expanding and decentralizing testing in BHUs was necessary was confirmed. The findings point to the importance of coordinating the pandemic response and effectively decentralizing the actions adopted, of preparedness plans and strengthening PHC and its professionals, as well as investments in infrastructure and team training, and advances in actions aimed at occupational health. The pandemic revealed the importance of advancing the health economic-industrial complex and, fundamentally, strengthening and defending the Brazilian Unified Health System.

To investigate factors associated with self-reported capacity to comply with home isolation after Covid-19 diagnosis in vulnerable communities in two Brazilian cities.

Cross-sectional study, with data from a study on the implementation of an intervention based on strategies of testing, isolation, quarantine, and telemonitoring (TQT) of Covid-19 in Primary Health Care in vulnerable neighborhoods (TQT Covid-19 Study). Demographic, socioeconomic, and behavioral data were used to perform descriptive and logistic regression analyses, aiming to evaluate the factors associated with home isolation capacity.

The sample consisted of 324 participants, most of them women (72.5%) and who self-reported to be Black or mixed-race (85.2%). Regarding level of education, 20.1% had up to elementary school degree; 42% had high school degree; and 37.9% had higher education or graduate degree. The density of people per room was high in 57.1% of households. In the multivariate analysis, high household density (≥ 0.5 residents/room) was significantly associated with reduced isolation capacity (ORa = 0.41; 95%CI 0.20-0.82). Other sociodemographic and behavioral variables, including age, sex, race/skin color, level of education, history of Covid-19 infection, access to health services, and preventive behaviors, did not present a statistically significant association.

According to the study, housing conditions, especially high household density, can be a determinant for adherence to home isolation. Thus, innovative prevention strategies should combine educational and structural actions that consider the household context of vulnerable families.

To explore factors associated with the use of chloroquine, hydroxychloroquine, and ivermectin for Covid-19 prevention in socioeconomically vulnerable populations in Brazil.

A cross-sectional study was conducted using data from the project "Expansion of testing, quarantine, digital health, and telemonitoring strategies to tackle the Covid-19 pandemic in Brazil." Participants were users of 19 primary healthcare units in Salvador (Bahia, BA) and Rio de Janeiro (Rio de Janeiro, RJ) from July 2022 to July 2023. Data were collected via a socioeconomic questionnaire and analyzed using logistic regression to assess factors associated with the use of chloroquine, hydroxychloroquine, or ivermectin for Covid-19 prevention. Multicollinearity was assessed using the generalized variance inflation factor (GVIF), with GVIF^(1/(2*df)) > 5 indicating potential collinearity. Sensitivity analyses were performed using the same backward selection procedure as the main model: excluding "sometimes" responses and stratifying analyses by city (Rio de Janeiro and Salvador).

Among 7,505 participants, 11.7% reported using chloroquine, hydroxychloroquine, or ivermectin for Covid-19 prevention. Use was more frequent among people who identified themselves as Brown (ORa = 1.38; 95%CI 1.10-1.75), aged 35-44 (ORa = 1.34; 95%CI 1.03-1.75) or 44-59 (ORa = 1.36; 95%CI 1.06-1.77), evangelical (ORa = 1.32; 95%CI 1.14-1.53), and with comorbidities (ORa = 1.25; 95%CI 1.07-1.47). Having up to two doses of Covid-19 vaccine (ORa = 1.30; 95%CI 1.06-1.59) and being unvaccinated while living with someone with comorbidities (ORa = 10.34; 95%CI 2.27-53.48) also increased the odds of use. GVIF values were low except for city (8.79), due to its interaction with income; the variable was retained for conceptual reasons. Sensitivity analyses yielded results consistent with the main model.

The use of ineffective medications for Covid-19 prevention was higher among specific demographic groups, reflecting inequalities in access to information and the influence of religious factors. Scientific communication and community engagement strategies remain essential to combat misinformation.

To describe the prevalence of adoption of Covid-19 preventive behaviors and to evaluate associated factors among users of health units in Salvador and Rio de Janeiro.

Cross-sectional study conducted between July 2022 and July 2023. Adoption of preventive behaviors was assessed based on eight behaviors, grouped into the following outcomes: social distancing; respiratory etiquette; mask use; hand hygiene; sociodemographic, housing, structural characteristics, and individual perceptions. All analyses were stratified by study site. Bivariate and multivariate analyses were performed using Poisson regression with robust variance.

A total of 5,476 participants from Salvador and 1,940 from Rio de Janeiro were evaluated. The most prevalent preventive behaviors were respiratory etiquette (82.7 and 84.3%) and hand hygiene (84.9 and 79.1%), respectively. In Salvador, age remained associated with all behaviors assessed. In Rio de Janeiro, adoption of preventive behaviors increased among those who received a Covid-19 vaccine booster. In both cities, individuals aged 40-59 years, ≥ 60 years, and those not employed showed higher adherence to social distancing. Respiratory etiquette was more prevalent among women, individuals with complete high school education, and those who received a Covid-19 booster. Mask use and hand hygiene were associated with female sex, older age, and vaccine booster in both locations. Mask use was also more frequent among those vaccinated against influenza, while hand hygiene was associated with higher education.

These findings reinforce the importance of public policies that promote maintenance of preventive behaviors and awareness of epidemic prevention, particularly among men, younger individuals, those with lower education, and those who do not receive recommended vaccines or booster doses.

To identify factors associated with the acceptability of Covid-19 self-testing among socioeconomically vulnerable populations.

Cross-sectional study using data from the "TQT Covid-19" project, which involved users from 19 primary health care (PHC) units located in socioeconomically vulnerable areas in Salvador (BA) and Rio de Janeiro (RJ), Brazil. Data were collected between July 2022 and July 2023. Descriptive analysis of Covid-19 self-test acceptability was performed, and logistic regression models were used to estimate factors associated with acceptability, with respective 95% confidence intervals (95%CI).

Among 7,939 study participants, 45.8% (95%CI 44.75-46.95) reported willingness to use a Covid-19 self-test. In the analysis of associated factors, regarding sociodemographic profile, non-Black individuals (ORa = 1.17; 95%CI 1.02-1.34), cisgender men (ORa = 1.23; 95%CI 1.12-1.37), and participants with higher educational levels (ORa = 1.60; 95%CI 1.43-1.79) were more likely to accept the self-test. Those with prior knowledge of the self-test (ORa = 2.33; 95%CI 2.11-2.58) and those previously diagnosed with Covid-19 (ORa = 1.17; 95%CI 1.05-1.28) also reported higher acceptance.

Provision of Covid-19 self-testing should be considered as a complement to testing within the public health system, especially due to its acceptance among vulnerable populations and the difficulties in accessing testing in many Brazilian regions. During periods of increased Covid-19 incidence, self-testing may serve as an important strategy for mass case detection, provided that access and knowledge are expanded so communities can play an active role in SARS-CoV-2 epidemiological surveillance.

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, with frequent exacerbations of COPD (ECOPD) significantly impacting patient health and health care systems. Predicting ECOPD early would increase patients' quality of life and decrease the economic burden. The advancement of wearable technologies and Internet of Things (IoT) sensors has enabled continuous remote monitoring (RM), offering new opportunities for early ECOPD prediction. However, effectively leveraging wearable data requires robust artificial intelligence (AI) frameworks capable of processing heterogeneous physiological and environmental information.

This systematic review aims to provide a comprehensive overview of both hardware and software solutions for predicting ECOPD using RM. From the reviewed literature, we first focus on key physiological and environmental variables essential for COPD monitoring that can be extracted from wearables and IoT sensors. Second, we describe the wearable and IoT devices currently deployed in COPD management. Finally, we review machine learning, including deep learning models, used for ECOPD prediction, discussing limitations for real-world implementation. By bridging AI-driven data processing with real-world sensor applications, this review aims to outline the current landscape, existing challenges, and future directions for developing effective RM solutions for ECOPD predictions.

A comprehensive search was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies using AI or machine learning techniques for predicting ECOPD in in-home contexts.

This review identified 26 studies that met the inclusion criteria. Twenty studies aimed at predicting or detecting exacerbations at the onset. The variables tracked most frequently were heart rate (n=9), peripheral oxygen saturation (n=9), and symptoms (n=8). Daily or weekly sampling was most common (n=14). Most studies (n=13) applied machine learning models-primarily random forest (n=5), CatBoost (n=2), decision trees (n=2), and support vector machines (n=2). Deep learning was used in 3 papers, while the remaining applied rule-based logics and probabilistic models. Wearables and IoT were used in only 6 out of 20 studies. Six papers analyzed changes in vital parameters during prodromal phases, defined as the period shortly before the onset of an exacerbation. Three studies collected data continuously, 2 daily, and 1 compared once-daily versus overnight monitoring; 4 of these 6 used wearable devices.

Overall, current evidence highlights the potential of continuous monitoring of physiological and environmental variables for early ECOPD prediction, offering advantages over questionnaires or once-daily measurements. While wearables and IoT devices show promise, their use remains limited. Many studies rely on balanced datasets that do not mirror real-world exacerbation patterns and lack external validation across diverse populations. Future research should emphasize large-scale validation, integration of multimodal data, and translation of AI models into clinically feasible tools to enable timely intervention and improve COPD management.

The rise of social media has significantly impacted public health programs, with platforms such as YouTube, Facebook, X (formerly known as Twitter), Instagram, and, more recently, TikTok being used to promote health information, raise awareness about disease outbreaks, and support disease prevention programs. However, the diverse and often unverified nature of the content on social media can make it challenging to discern accurate information, contributing to user uncertainty, which may in turn contribute to low vaccination rates in some regions. This is especially true in Louisiana as its COVID-19 vaccination rates were among the lowest in the country in 2022. Therefore, understanding public sentiment on social media and developing targeted campaigns to counter unverified information is essential for advancing public health campaigns.

The goal was to gain insights into the underlying factors that contribute to Louisiana's low vaccination rates for routine immunizations by (1) performing social media listening to develop an infodemic management plan and (2) promoting accurate information via a social media campaign.

Social media listening was conducted using Meltwater, a media monitoring and social media listening platform, supplemented by Google Alerts and Google News to identify if vaccine-related stories or sentiments were attracting unusual attention. Additionally, a social media campaign aimed at educating Louisiana residents about disease manifestation, symptoms, vaccines available for disease prevention, and potential side effects was developed. Posts were published 2 to 3 times a week and boosted for 7 days.

From November 13, 2023, to June 11, 2024, social media listening identified at least 15 unique, noteworthy stories that signified sentiment spikes. These conversations were predominantly related to vaccine hesitancy, with users expressing opposition to vaccines or reluctance to engaging with vaccine-related information. Sentiment spikes included themes related to mistrust of vaccines and concerns about their safety and efficacy. The social media campaign received 69,600 impressions, reached 43,429 users, and received 652 reactions and likes, 62 shares, and 105 comments. Most of the audience was female, with higher engagement from older users on Facebook and younger users on Instagram. Finally, posts related to hepatitis B, rotavirus, and measles, mumps, and rubella vaccines received the most attention.

Social media has become a key tool for digital health, helping to implement disease prevention programs and promoting advances in medicine. However, unverified information remains a major reason for the aversion to vaccination despite the dissemination of information from reputable public health organizations, health professionals, hospitals, and medical centers. To address this, information that is accessible, understandable, and culturally competent must be circulated to mitigate disinformation and improve attitudes toward vaccination. More research is needed to evaluate the effectiveness of social media campaigns in reducing vaccine hesitancy and improving willingness to adopt public health recommendations to increase vaccination rates.

The COVID-19 pandemic disrupted healthcare utilization and access for many, with persons living with pre-existing pulmonary conditions like cystic fibrosis (pwCF) having been the most impacted. PwCF appeared to have improvements in lung function and reduction in pulmonary exacerbations during the pandemic. However, it is not clear if general healthcare utilization beyond CF centers were also reduced and whether there existed any sex-based differences in health outcomes during the pandemic. Our objective was to use population-level administrative data to gain a comprehensive understanding of healthcare utilization and outcomes for pwCF pre- compared to post-COVID.

A retrospective provincial-level analysis was conducted using linked administrative datasets from a single-payer health jurisdiction in Alberta, Canada. We measured hospitalization, emergency department and outpatient visits in pwCF 18 months before and after March 12, 2020. Subgroup analysis was undertaken to differences between sexes.

Acute care encounters (including general emergency department [ED] visits and hospitalizations) for pwCF declined during the pandemic. There was a trend towards an increase in outpatient primary care and specialist clinics (both virtual and in-person) in the post-COVID period. Mortality rate was largely unchanged during the pandemic. CF females and males experienced the same relative change in healthcare utilization during the pandemic with a greater reduction in ED visits by CF females.

PwCF accessed acute care resources less but females experienced a greater drop in ED visits despite similar hospitalization rates as males, raising the possibility that females with CF experienced a disproportionate barrier to accessing acute care.

Acute rhinosinusitis (ARS) affects approximately 15% of adults annually. It accounts for nearly 30 million outpatient visits and one in five antibiotic prescriptions, and contributes to over $11 billion in direct healthcare costs in the United States. Because routine clinical evaluation cannot reliably distinguish viral from bacterial ARS, antibiotics are frequently prescribed for infections that are likely viral. Non-antibiotic therapies such as intranasal corticosteroids (INCS) and saline nasal irrigation may provide symptom relief, but their comparative effectiveness in ARS has not been rigorously evaluated.

This protocol describes the design and methodology of a large, multi-center, pragmatic randomized controlled trial to evaluate antibiotic and non-antibiotic treatment strategies for ARS. The trial will compare supportive care, and clinical and laboratory indicators that may identify subgroups most likely to benefit from specific therapies.

This placebo-controlled trial is underway in primary care and urgent care settings in six regions across the U.S. Adults aged 18-75 years with ARS initially receive clinician-directed care. Participants who do not improve after 9 days of symptoms will be randomized into one of four groups: antibiotics alone; placebo-antibiotics plus INCS; antibiotics plus INCS; or placebo-antibiotics alone. All participants receive educational materials and kits for saline nasal irrigation. The trial will enroll 3,720 participants, with approximately 60% expected to enter the randomized phase. Primary outcomes include symptom severity prior to and 3 days post-randomization, as measured by the modified Sino-Nasal Outcome Test-16).

This trial will generate high-quality evidence to inform targeted treatment of ARS, identify subgroups most likely to benefit from antibiotics or non-antibiotic therapies, and support more judicious antibiotic stewardship in routine clinical practice.