ABSTRACT: Objective: To describe the methodological characteristics and good research practices of COVID-19 interventional studies developed in Brazil in the first months of the pandemic. Methods: We reviewed the bulletin of the National Research Ethics Committee - Coronavirus Special Edition (Comissão Nacional de Ética em Pesquisa - CONEP-COVID) (May 28, 2020) and the databases of the International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov, and Brazilian Clinical Trials Registry (Registro Brasileiro de Ensaios Clínicos - ReBEC) to identify interventional studies registered in Brazil that assessed drug type, biological therapy, or vaccines. We described their methodological characteristics and calculated their power for different effect magnitudes. Results: A total of 62 studies were included, 55 retrieved from the CONEP website, and 7 from registry databases. The most tested pharmacological interventions in these studies were: chloroquine/hydroxychloroquine, azithromycin, convalescent plasma, tocilizumab, sarilumab, eculizumab, vaccine, corticosteroids, anticoagulants, n-acetylcysteine, nitazoxanide, ivermectin, and lopinavir/ritonavir. Out of 22 protocols published on registry databases until May 2020, 18 (82%) were randomized clinical trials, and 13 (59%) had an appropriate control group. However, 9 (41%) of them were masked, and only 5 (24%) included patients diagnosed with a specific laboratory test (for example, reverse transcription polymerase chain reaction - RT-PCR). Most of these studies had power > 80% only to identify large effect sizes. In the prospective follow-up, 60% of the studies available at CONEP until May 2020 had not been published on any registry platform (ICTRP/ReBEC/ClinicalTrials) by July 21, 2020. Conclusion: The interventions evaluated during the Brazilian research response reflect those of international initiatives, but with a different distribution and a large number of studies assessing hydroxychloroquine/chloroquine. Limitations in methodological design and sample planning represent challenges that could affect the research outreach.

The objective of the study was to assess the safety, tolerability, and potential efficacy of intranasally administered AD17002, a detoxified form of Escherichia coli heat-labile enterotoxin, in treating individuals with mild-to-moderate coronavirus disease of 2019 (COVID-19). In this randomized, double-blinded, and placebo-controlled phase 2a study, a total of 30 adults aged 20–70 years with mild-to-moderate COVID-19 were recruited from three medical centers in Taiwan in 2022–2023. The trial comprised two cohorts, and participants were randomly assigned to receive intranasal administrations of either three doses of AD17002 immunomodulator or a placebo formulation buffer. Outcome analyses were conducted on the intention-to-treat set, and the safety set that included all randomized participants exposed to the AD17002. The proportion of cycle threshold (Ct) ≥30 and time to the recovery of key symptoms were assessed. An exploratory study was conducted to analyze the integrity of the viral genome after treatment. Administering 20 μg of AD17002 three times, either at 1-week or 1-day intervals, proved to be safe and well tolerated in subjects with mild-to-moderate COVID-19. AD17002 demonstrated a rapid and positive outcome in reducing the viral load in patients receiving the treatment. Impact of AD17002 treatment was further supported by the analysis of viral genome integrity following the treatment. The enhancement in clinical recovery by AD17002 within 5 days after symptom onset was observed but did not achieve statistical significance. According to the results, intranasal administration of AD17002 was safe, well-tolerated, and potentially effective for treating mild-to-moderate COVID-19. This study looked at a new treatment called AD17002, which is designed to boost the body’s immune response by increasing the production of special proteins called type I interferons. These proteins help the body fight infections. Previous research in animals showed that AD17002 helped clear the virus faster and reduced lung damage caused by SARS-CoV-2, the virus responsible for COVID-19. It had also been tested in humans as a nasal spray to improve flu vaccines. In this phase 2 clinical trial, AD17002 was given to people with mild-to-moderate COVID-19 caused by the viral variants. The treatment was well-tolerated, with no major side effects, and showed promising results. It helped reduce the amount of virus in the body, which was confirmed by measuring the genetic material of the virus before and after treatment. This suggests that AD17002 could be an effective way to treatCOVID-19. The study supports the idea that AD17002 might help lessen the severity of COVID-19 symptoms and reduce the spread of the virus. This is important because viral variants have become more contagious and better at evading the immune system.

A phase 1/2, open-label clinical trial in individuals, 18 years of age and older, who are in good health, have no known history of Coronavirus Disease 2019 (COVID-19) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, and meet all other eligibility criteria. This clinical trial is designed to assess the safety, reactogenicity and immunogenicity of a delayed (>/=12 weeks) vaccine boost on a range of Emergency Use Authorization (EUA)-dosed COVID-19 vaccines (mRNA-1273, and mRNA-1273.211 manufactured by ModernaTX, Inc.; BNT162b2 manufactured by Pfizer/BioNTech; or Ad26.COV2.S manufactured by Janssen Pharmaceuticals/Johnson & Johnson). This is an adaptive design and may add arms (and increase sample size) as vaccines are awarded EUA and/or variant lineage spike vaccines are manufactured or become available. Enrollment will occur at up to twelve domestic clinical research sites.

This study includes two cohorts. Cohort 1 will include approximately 880 individuals (50 subjects/group; Groups 1E-11E) greater than 18 years of age and older, stratified into two age strata (18-55 years and >/=56 years) who previously received COVID-19 vaccine at Emergency Use Authorization dosing (EUA) (two vaccinations of mRNA-1273 at the 100 mcg dose, two vaccinations of BNT162b2 at the 30 mcg dose, or one vaccination of Ad26.COV2.S at the 5x10^10 vp dose). Groups 15E-17E will enroll 60 subjects, split (approximately evenly) between age strata as able. Those subjects will be offered enrollment into this study >/=12 weeks after they received the last dose of their EUA vaccine. Subjects will receive a single open-label intramuscular (IM) injection of the designated delayed booster vaccine and will be followed through 12 months after vaccination: 1) Group 1E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S at 5x10^10 vp followed by a 100-mcg dose of mRNA-1273, Group 4E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S at 5x10^10 vp followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 7E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S 5x10^10 vp followed by a 30-mcg dose of BNT162b2, Group 10E - previously EUA-dosed vaccination with Janssen - Ad26.COV2-S 5x10^10 vp followed by a 100-mcg dose of mRNA-1273.211; Group 12E - previously EUA-dosed vaccination with Janssen - Ad26.COV2-S 5x10^10 vp followed by a 50-mcg dose of mRNA-1273; Group 15E - previously EUA-dosed vaccination with Janssen (two doses for Group 15E) - Ad26.COV2.S at 5x1010 vp followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV-2 rS vaccine with 50 mcg Matrix-M); 2) Group 2E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 100-mcg dose of mRNA-1273, Group 5E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 8E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 30-mcg dose of BNT162b2, Group 13E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 50-mcg dose of mRNA-1273; Group 16E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV2 rS vaccine with 50 mcg Matrix-M); 3) Group 3E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 100-mcg dose of mRNA-1273. Group 6E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 9E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 30-mcg dose of BNT162b2, Group 11E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 100-mcg dose of mRNA-1273.211. Group 14E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 50-mcg dose of mRNA-1273, Group 17E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV2 rS vaccine with 50 mcg Matrix-M).

A telephone visit will occur one week after each primary EUA vaccination and one week after the booster dose. In person follow-up visits will occur on 14 days following completion of EUA vaccinations and on days 14, and 28 days after the booster dose, as well as 3, 6, and 12 months post the booster vaccination. Additional pools of subjects can be included if needed as additional COVID-19 vaccines are awarded EUA.

The primary objectives of this study are 1) to evaluate the safety and reactogenicity of delayed heterologous or homologous vaccine doses after EUA dosed vaccines, and 2) to evaluate the breadth of the humoral immune responses of heterologous and homologous delayed boost regimens following EUA dosing.

The impact of the COVID-19 pandemic worldwide has led to a desperate search for effective drugs and vaccines. There are still no approved agents for disease prophylaxis. We thus decided to use a drug repositioning strategy to perform a state-of-the-art review of a promising but controversial drug, hydroxychloroquine (HCQ), in an effort to provide an objective, scientific and methodologically correct overview of its potential prophylactic role. The advantage of using known drugs is that their toxicity profile is well known and there are fewer commercial interests (e.g., expired patents), thus allowing the scientific community to be freer of constraints. The main disadvantage is that the economic resources are almost always insufficient to promote large multinational clinical trials. In the present study, we reviewed the literature and available data on the prophylactic use of HCQ. We also took an in-depth look at all the published clinical data on the drug and examined ongoing clinical trials (CTs) from the most important CT repositories to identify a supporting rationale for HCQ prophylactic use. Our search revealed a substantial amount of preclinical data but a lack of clinical data, highlighting the need to further assess the translational impact of in vitro data in a clinical setting. We identified 77 CTs using a multiplicity of HCQ schedules, which clearly indicates that we are still far from reaching a standard of care. The majority of the CTs (92%) are randomized and 53% are being conducted in a phase 3 or 2/3 setting. The comparator is placebo or control in 55 (77%) of the randomized studies. Forty-eight (62%) CTs expect to enroll up to 1,000 subjects and 50 (71%) plan to recruit healthcare workers (HCW). With regard to drug schedules, 45 (58.5%) CTs have planned a loading dose, while 18 (23.4%) have not; the loading dose is 800 mg in 19 trials (42.2%), 400 mg in 19 (42.2%), 600 mg in 4 (8.9%) and 1,200 mg in 1 (2.2%). Forty trials include at least one daily schedule, while 19 have at least one weekly schedule. Forty-one (53.2%) will have a treatment duration of more than 30 days. Awaiting further developments that can only derive from the results of these prospective randomized CTs, the take-home message of our review is that a correct methodological approach is the key to understanding whether prophylactic HCQ can really represent an effective strategy in preventing COVID-19.

While mass vaccination campaigns against COVID-19 have inoculated almost 200 million Americans and billions more worldwide, significant pockets of vaccine hesitancy remain. Research has firmly established that vaccine efficacy is an important driver of public vaccine acceptance and choice. However, current vaccines offer widely varying levels of protection against different adverse health outcomes of COVID-19. This study employs an experiment embedded on a survey of 1,194 US adults in June 2021 to examine how communications about vaccine efficacy affect vaccine choice. The experiment manipulated how vaccine efficacy was defined across four treatments: (1) protection against symptomatic infection; (2) protection against severe illness; (3) protection against hospitalization/death; (4) efficacy data on all three metrics. The control group received no efficacy information. Subjects were asked to choose between a pair of vaccines—a one-dose viral vector vaccine or two-dose mRNA vaccine—whose efficacy data varied across the four experimental treatment groups. Efficacy data for each vaccine on each dimension were adapted from clinical trial data on the Johnson & Johnson/Janssen and Pfizer/BioNTech vaccines. Among all respondents, only modest preference gaps between the two vaccines emerged in the control group and when the two vaccines’ roughly equivalent efficacy data against hospitalization and death were reported. Strong preferences for a two-dose mRNA vaccine emerged in treatments where its higher efficacy against symptomatic or severe illness was reported, as well as in the treatment where data on all three efficacy criteria were reported. Unvaccinated respondents preferred a one-dose viral vector vaccine when only efficacy data against hospitalization or death was presented. Black and Latino respondents were significantly more likely to choose the one-shot viral vector vaccine in the combined efficacy treatment than were whites. Results speak to the importance of understanding how communications about vaccine efficacy affect public preferences in an era of increasing uncertainty about efficacy against variants.

The COVID-19 Citizen Science (CCS) Study was launched early in the pandemic to collect patient-reported information about exposures, risk behaviors and outcomes relevant to the pandemic. The Patient-Centered Outcomes Research Institute (PCORI) funded the research team to expand recruitment into CCS using PCORnet, the National Patient-Centered Clinical Research Network, and to use the resulting data to compare the patient-reported impact of pandemic associated policies. The research team systematically collected pandemic-associated policies enacted by counties across the United States (focusing in areas where there were many CCS participants), and to do so on a weekly basis from the beginning of the pandemic using publicly available sources. Researchers combined data from various sources to answer two primary research questions (RQ): What is the comparative impact of different shelter-in-place/reopening policies, overall and in vulnerable populations, on patient-reported financial insecurity, mental health, and other subjective outcomes important to patients? What is the comparative effectiveness of county-level containment and mitigation strategies at achieving timely access to COVID-19 vaccination, testing, healthcare, information and contact tracing? The research team collected patient-reported data from the CCS study and policy data from the U.S COVID-19 County Policy (UCCP) database. Electronic health record (EHR) data were also available from some participants recruited from health systems located across 7 U.S. states who consented and authorized use of these data for the study. Data for these participants were extracted from the PCORnet Common Data Model (CDM). Additional county-level contextual variables were included in analysis. This collection contains CCS survey data on patient-reported anxiety with county-level policies data (DS1), respondent demographics (DS2), baseline survey results (DS3), daily (DS4) and weekly (DS5) COVID-19 symptoms reports, COVID-19 vaccination surveys repeated monthly (DS6) as well as a one-time vaccination survey (DS7), and pandemic impacts check-in surveys (DS8). CDM datasets include logistic regression model outcomes to predict study enrollment among all invited participants (DS9), codes for immunizations (DS10), laboratory tests (DS11), and procedures (DS12). County-level variables are also available for years 2021 (DS13) and 2023 (DS14).

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.

CDC has three COVID-19 case surveillance datasets:

• COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements)
• COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)
• COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements)

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data cells are suppressed to protect individual privacy.
• The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020, to clarify the interpretation of antigen detection tests and serologic test results within the case classification (Interim-20-ID-02). The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported voluntarily to CDC.

For more information: NNDSS Supports the COVID-19 Response | CDC.

The deidentified data in the “COVID-19 Case Surveillance Public Use Data” include demographic characteristics, any exposure history, disease severity indicators and outcomes, clinical data, laboratory diagnostic test results, and presence of any underlying medical conditions and risk behaviors. All data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.

COVID-19 Case Reports

COVID-19 case reports have been routinely submitted using nationally standardized case reporting forms. On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19 included. Current versions of these case definitions are available here: https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/.

All cases reported on or after were requested to be shared by public health departments to CDC using the standardized case definitions for laboratory-confirmed or probable cases. On May 5, 2020, the standardized case reporting form was revised. Case reporting using this new form is ongoing among U.S. states and territories.

Data are Considered Provisional

• The COVID-19 case surveillance data are dynamic; case reports can be modified at any time by the jurisdictions sharing COVID-19 data with CDC. CDC may update prior cases shared with CDC based on any updated information from jurisdictions. For instance, as new information is gathered about previously reported cases, health departments provide updated data to CDC. As more information and data become available, analyses might find changes in surveillance data and trends during a previously reported time window. Data may also be shared late with CDC due to the volume of COVID-19 cases.
• Annual finalized data: To create the final NNDSS data used in the annual tables, CDC works carefully with the reporting jurisdictions to reconcile the data received during the year until each state or territorial epidemiologist confirms that the data from their area are correct.
• Access Addressing Gaps in Public Health Reporting of Race and Ethnicity for COVID-19, a report from the Council of State and Territorial Epidemiologists, to better understand the challenges in completing race and ethnicity data for COVID-19 and recommendations for improvement.

Data Limitations

To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.

Data Quality Assurance Procedures

CDC’s Case Surveillance Section routinely performs data quality assurance procedures (i.e., ongoing corrections and logic checks to address data errors). To date, the following data cleaning steps have been implemented:

• Questions that have been left unanswered (blank) on the case report form are reclassified to a Missing value, if applicable to the question. For example, in the question “Was the individual hospitalized?” where the possible answer choices include “Yes,” “No,” or “Unknown,” the blank value is recoded to Missing because the case report form did not include a response to the question.
• Logic checks are performed for date data. If an illogical date has been provided, CDC reviews the data with the reporting jurisdiction. For example, if a symptom onset date in the future is reported to CDC, this value is set to null until the reporting jurisdiction updates the date appropriately.
• Additional data quality processing to recode free text data is ongoing. Data on symptoms, race and ethnicity, and healthcare worker status have been prioritized.

Data Suppression

To prevent release of data that could be used to identify people, data cells are suppressed for low frequency (<5) records and indirect identifiers (e.g., date of first positive specimen). Suppression includes rare combinations of demographic characteristics (sex, age group, race/ethnicity). Suppressed values are re-coded to the NA answer option; records with data suppression are never removed.

For questions, please contact Ask SRRG (eocevent394@cdc.gov).

Additional COVID-19 Data

COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths by state and by county. These

ACTT-2 will evaluate the combination of baricitinib and remdesivir compared to remdesivir alone. Subjects will be assessed daily while hospitalized. If the subjects are discharged from the hospital, they will have a study visit at Days 15, 22, and 29. For discharged subjects, it is preferred that the Day 15 and 29 visits are in person to obtain safety laboratory tests and oropharyngeal (OP) swab and blood (serum only) samples for secondary research as well as clinical outcome data. However, infection control or other restrictions may limit the ability of the subject to return to the clinic. In this case, these visits may be conducted by phone, and only clinical data will be obtained. The Day 22 visit does not have laboratory tests or collection of samples and is conducted by phone. The primary outcome is time to recovery by Day 29.

Following the spread of the SARS-CoV-2 coronavirus, an unprecedented burden has been placed on health care systems, with health care workers (HCWs) being most at risk of COVID-19 infection. The effect of the probiotic Loigolactobacillus coryniformis K8 CECT 5711 on frontline HCWs exposed to the virus was studied in a randomized, double-blind, placebo controlled trial. Parameters related to the incidence and severity of COVID-19 as well as the immune response and the side effects of the COVID-19 vaccine were evaluated. For 2 months, a group of 250 front-line HCWs over the age of 20 was randomly allocated to receive either L. coryniformis K8 or a placebo daily. SARS-CoV-2 infection incidence was verified via PCR or antigen test. In those volunteers who were vaccinated during the intervention, serum levels of specific IgG were analyzed at the end of the study. The incidence of COVID-19 infection was very low [IR (SD) = 0.016 (0.011)], and no significant difference was found between the groups [IRR (95% CI): 1.008 (0.140–7.268), p = 0.994]. For immune response analysis, the total sample was divided according to the days between the first dose and the antibody analysis (cutoff points were set at ≤ 56, 57–80 and ≥ 81 days). The specific IgG level decreased over time (p > 0.001). However, in the subgroup of subjects for whom more than 81 days had passed since they received the first dose, the specific IgG levels were significantly higher in the those that took the L. coryniformis K8 [7.12 (0.21)] than in the control group 6.48 (0.19). Interestingly, the subjects who started probiotic consumption before the first dose reported significantly fewer side effects (of any kind) at the 1st dose of the vaccine (OR: 0.524, p = 0.043), specifically less arm pain (OR: 0.467, p = 0.017). In conclusion, the administration of L. coryniformis K8 CECT 5711 to HCWs helps to extend the immune protection generated by the COVID-19 vaccine over time.

Infectious Disease Clinical Trials Market Outlook

In 2023, the infectious disease clinical trials market size was valued at approximately $7.2 billion. Forecasting ahead, with a compound annual growth rate (CAGR) of 6.8%, the market size is expected to reach around $13.4 billion by 2032. This growth is fueled by increasing investments in research and development, rising prevalence of infectious diseases, and an urgent need for new and effective treatments.

The growth of the infectious disease clinical trials market is driven by several key factors. Firstly, the rise in global healthcare expenditure, particularly toward combating infectious diseases, has significantly bolstered the demand for clinical trials. Governments and private sectors around the world are increasingly allocating funds to support the development of vaccines and therapeutics. Additionally, the continual emergence of new infectious pathogens, such as the recent COVID-19 pandemic, underscores the need for innovative treatments and vaccines, thereby driving the market growth.

Secondly, advancements in biotechnology and molecular biology have revolutionized the approach toward infectious disease treatment and prevention. Novel technologies such as CRISPR gene editing and next-generation sequencing are enabling researchers to develop more targeted and effective therapies. These technological advancements not only enhance the efficiency of clinical trials but also reduce the time and cost associated with drug development, making it feasible to bring new treatments to market more quickly.

Thirdly, the increasing collaboration between pharmaceutical companies, biotechnology firms, and academic institutions is fostering a conducive environment for clinical trials. These collaborations often result in the pooling of resources and expertise, which enhances the capacity to undertake extensive clinical studies. This synergistic approach is crucial in addressing the complex challenges posed by infectious diseases, facilitating the rapid development and deployment of new therapeutic solutions.

Regionally, North America holds the largest share in the infectious disease clinical trials market, attributed to robust healthcare infrastructure, significant investment in research and development, and the presence of key market players. The Asia Pacific region is expected to exhibit the highest growth rate, driven by the rising incidence of infectious diseases, increasing healthcare expenditure, and growing focus on clinical research activities. Europe also remains a significant market, with substantial funding from governmental and non-governmental organizations for infectious disease research and a well-established regulatory framework supporting clinical trials.

Phase Analysis

Phase I clinical trials are the first stage of testing in human subjects and usually involve a small group of healthy volunteers. The primary objective is to assess the safety, tolerability, pharmacokinetics, and pharmacodynamics of a drug. The increasing complexity of new therapies and the demand for early-phase testing are driving the growth of Phase I trials. Additionally, the integration of novel biomarkers and adaptive trial designs are enhancing the efficiency and success rates of Phase I trials.

Phase II trials, which involve a larger group of patients, focus on evaluating the efficacy of the drug, identifying its optimal dosing regimen, and further assessing its safety. The high prevalence of infectious diseases such as HIV, hepatitis, and influenza necessitates extensive Phase II trials to determine therapeutic effectiveness. The increasing collaboration between biotechnology companies and academic institutions accelerates the development of effective treatments, thereby driving the growth of Phase II trials.

Phase III trials are pivotal in confirming the effectiveness of the drug, monitoring side effects, and comparing it to commonly used treatments. These trials involve large patient groups and are crucial for the regulatory approval of new therapies. The rising number of infectious disease outbreaks and the urgent need for effective treatments and vaccines are fueling the demand for Phase III trials. Governmental and regulatory bodies are also providing incentives and fast-track approvals to expedite the development of critical therapies, thereby supporting the growth of Phase III trials.

Phase IV trials, conducted after a drug has been approved for market release, aim to monitor the long-term effectiveness and safety of the drug in a broader pati

Rationale: The World Health Organization (WHO) has declared the current coronavirus disease (COVID-19) outbreak, caused by the SARS-CoV-2 virus, to be a pandemic and, therefore, a Public Health Emergency of International Concern. The COVID-19 outbreak has a huge impact on health care, but also on economic and social costs. Track-and-trace programs are important measures to control the virus, but they have their limitations such as delays in the test results (e.g., it takes time to develop symptoms after infection, to access a test, receive the test result, and for close contacts to be traced). Early traceability of the virus may help in the track-and-trace programs to control the virus. It is currently thought that most – but not all – infected individuals develop symptoms, but that the infectious period starts on average two days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for up to half of all transmissions. By detecting infected individuals before they have overt symptoms, the proportion of transmissions by pre-symptomatic individuals could potentially be significantly reduced. Primary Objective: Using laboratory-confirmed SARS-CoV-2 infections (detected via serology, PCR and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data, and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. Study design: Randomized, single-blinded, two-period, two-sequence crossover trial. The study will start with an initial Learning Phase (maximum 3 months), followed by a 3-month Period 1 and a 3-month Period 2. Each subject will undergo the experimental condition (=algorithm uses data from app and bracelet) in one of these periods and the control condition (=algorithm uses data from the app only) in the other period, but the order will be randomly assigned, resulting in Sequence 1 (experimental condition first) and Sequence 2 (control condition first). Study population: A target of 20,000 subjects will be enrolled in this study. Subjects will be recruited from previously studied cohorts as well as via public campaigns. They will be invited to visit the COVID-RED web portal. When they have successfully completed the survey questions in the COVID-RED web portal, are considered eligible and have indicated interest in joining the study, then they will receive the subject information sheet and consent form. Subjects can be enrolled when they comply with the following inclusion and exclusion criteria: Key Inclusion criteria: • Resident of the Netherlands • At least 18 years old • Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, study team should be notified) • Be able to read, understand and write Dutch Key Exclusion criteria • Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests) (self-reported) • Current suspected (e.g., waiting for test result) coronavirus infection or symptoms of a coronavirus infection (self-reported) • Electronic implanted device (such as a pacemaker) • Suffering from cholinergic urticaria Intervention: All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app, wear their Ava bracelet each night and synchronise it with the app each day, during the entire period of study participation. The experimental condition (=algorithm uses app and bracelet data) will be compared to the control condition (=algorithm uses app data only). Main study parameters/endpoints: The primary endpoint for this study for each subject is the daily indication of potential SARS-CoV-2 infection as provided by the algorithm of the Ava COVID-RED app with or without using data from the Ava bracelet. This daily endpoint will be compared with actual SARS-CoV-2 test results (PCR/antigen and/or serology) collected before, during and at the end of study participation. For the primary comparison, this daily endpoint will be summarized over each trial period per subject to determine (1) whether a subject was ever judged to have had a high risk for a potential SARS-Cov-2 infection, and (2) whether a subject was ever confirmed to have had a SARS-CoV-2 infection by PCR/antigen and/or serology testing. For this comparison, parameters such as sensitivity, specificity, positive predictive value, and negative predictive value will be calculated. Nature and extent of the burden and risks associated with participation, benefit and group relatedness: Subjects wearing the Ava bracelet may experience skin irritation or sensitization due to rubbing and friction. Subjects are instructed to only wear the device at night to allow the skin to dry and breath during the day. They will be instructed to discontinue wearing the Ava bracelet and contact the study team in case they experience any signs of allergic reaction, feel soreness, tingling, numbness, burning or stiffness in their hands or wrists while or after wearing the Ava bracelet. Subjects may feel uncomfortable answering health questions in the Ava COVID-RED app, but they have the choice of not responding to the questions in the app. Subjects will be asked to donate fingerprick blood for SARS-CoV-2 antibody testing at up to 4 different timepoints, which may cause minor discomfort. This study will use the existing testing infrastructure in the Netherlands provided by the Municipal Health services (GGD) for SARS-CoV-2 infection, and, only when this is not possible, PCR testing in the central study laboratory will be arranged. Recruitment and follow-up will be completely remote and take place via post, email, phone and electronic web portals. In this way, risk of SARS-CoV-2 infection is minimized as much as possible for those wanting to participate in the trial and for the staff conducting the trial. Another risk for the subject is the potential breach of data security. The study team will implement security measures to prevent loss of data or unauthorised access to the data and we will follow the General Data Protection Regulation (GDPR). Data will be pseudo-anonymized within the platforms where data analysis will be performed. Data transfers will use a trial-specific identifier which is not linked to any external participant identifiers. Overall, the burden for the subjects is assessed as small and is justified given the importance of assessing a potential method in early detection of COVID-19. The expected benefit is large as the algorithms trained on the obtained data recordings from the Ava bracelet are expected to recognize COVID-19 earlier than the presentation of clinical symptoms. The latter would allow for earlier isolation and stratification as well as monitoring of SARS-CoV-2 infected persons preventing further spread and, if applicable, allowing for appropriate healthcare.

Coronavirus disease 2019 (COVID-19) patients sometimes experience long-term symptoms following resolution of acute disease, including fatigue, brain fog, and rashes. Collectively these have become known as long COVID. Our aim was to first determine long COVID prevalence in 185 randomly surveyed COVID-19 patients and, subsequently, to determine if there was an association between occurrence of long COVID symptoms and reactivation of Epstein–Barr virus (EBV) in 68 COVID-19 patients recruited from those surveyed. We found the prevalence of long COVID symptoms to be 30.3% (56/185), which included 4 initially asymptomatic COVID-19 patients who later developed long COVID symptoms. Next, we found that 66.7% (20/30) of long COVID subjects versus 10% (2/20) of control subjects in our primary study group were positive for EBV reactivation based on positive titers for EBV early antigen-diffuse (EA-D) IgG or EBV viral capsid antigen (VCA) IgM. The difference was significant (p < 0.001, Fisher’s exact test). A similar ratio was observed in a secondary group of 18 subjects 21–90 days after testing positive for COVID-19, indicating reactivation may occur soon after or concurrently with COVID-19 infection. These findings suggest that many long COVID symptoms may not be a direct result of the SARS-CoV-2 virus but may be the result of COVID-19 inflammation-induced EBV reactivation.

Methods Study Design. 357 Applicants were screened using a Health Insurance Portability and Accountability Act (HIPAA)-compliant online form under which informed consent was obtained. The HIPAA-compliant form, screening, and study protocol were approved by the ethical review committee of our Institutional Review Board prior to initiation (Integrity IRB Protocol identifier [ID]: 40005). As an assurance of confidentiality, only one investigator performed the recruitment, data collection and validation, kept the patient data in a secure database that was used only in coded form (to remove all patient identifiers) before the analysis of the data by the research team. Thus, all patient records, test data and the identity of the subjects submitting photos of skin manifestations has been kept by a single source.

Patient Recruitment. Subjects were chosen from applicants who responded to online advertisements that we ran seeking recovered COVID-19 patients for this study. Each applicant was required to upload documentation of their COVID-19 medical history. These included copies of COVID-19 test results and hospitalization records, as well as completing an in-depth online survey in which they provided details related to their COVID-19 symptoms and outcomes on the HIPAA-compliant form. Follow-up was done by one investigator to verify that each subject met the study criteria, and to allow subjects demonstrating skin manifestations to provide images of such for the record, and to be kept in blinded files for evaluation by the remaining researchers. Subjects in the study were selected randomly from all who applied and were a match to the criteria for any of the study groups. Applicants were excluded if they were under 21 years of age, over 74 years of age, or if they had any of these health conditions: pregnant, had been given a COVID-19 vaccine, or had long-COVID-like symptoms prior to testing positive for COVID-19. The selection process continued until 68 qualified subjects had been selected. These 68 subjects provided serological samples to be tested for the relevant EBV parameters using a commercial laboratory. The selection of applicants and serological testing was conducted between 11 December 2020 through 11 February 2021. A small stipend to help defray costs associated with providing records and blood samples was available to subjects.

Assessments. All study participants volunteered to provide blood samples through a clinical reference laboratory (Quest Diagnostics). The samples were tested for EBV VCA antibody (IgM), EBV VCA antibody (IgG), EBNA antibody (IgG), and EBV EA-D antibody (IgG). Subjects describing long COVID symptoms who did not test positive for EBV VCA antibody (IgM) or for EBV EA-D antibody (IgG) were also tested for EBV DNA with a quantitative, real-time PCR test with a linear range of 200-2,000,000 copies/mL.

EBV antibodies were measured using a Liaison analyzer system to measure chemiluminescence from a commercially available immunoassay (CLIA) for the qualitative determination of IgG and IgM antibodies in human serum specimens. The method for qualitative determination of specific IgG and IgM antibodies to EBV was a competitive (indirect) CLIA. The principal components of the EBV VCA (IgG) and EBV VCA (IgM) tests were magnetic particles coated with VCA p18 synthetic peptide, BSA, phosphate buffer containing < 0.1% sodium azide. The principal components of the EBNA (IgG) tests were magnetic particles coated with EBNA-1 synthetic peptide, BSA, phosphate buffer containing < 0.1% sodium azide. The principal components of the EBV EA-D (IgG) tests were magnetic particles coated with EA-D polypeptide (obtained in E. coli by recombinant DNA technology), BSA, phosphate buffer containing < 0.1% sodium azide. The EBV DNA, Quantitative, Real-Time PCR test was developed in house, and its analytical performance validated by Quest Diagnostics.

When EBV VCA antibody (IgM) is detectable but EBNA antibody (IgG) is not, this generally indicates primary EBV infection or EBV reactivation. When EBV VCA antibody (IgM) and EBNA antibody (IgG) are both detectable, this generally indicates EBV reactivation. EBV EA-D antibody (IgG) is generally only detectable in patients with primary infection or EBV reactivation. Thus, testing for the presence of EBV VCA antibody (IgM) or EBV EA-D antibody (IgG) has been commonly used to detect EBV reactivation. Some reactivation cases missed by the other tests can be detected through serum testing for the presence of EBV DNA circulating following viral release during recrudescence, by quantitative real-time polymerase chain reaction (PCR) of EBV. In our study, a subject was classified as having EBV reactivation if they exceeded any of these threshold values: EBV VCA antibody (IgM) > 39.99 U/mL, EBV EA-D antibody (IgG) > 9.99 U/mL, or EBV DNA, quantitative, real-time PCR > 2.29 Log copies/mL.

IntroductionRacial, ethnic, sexual, and gender minoritized groups are considered historically excluded groups and have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. The influence of social determinants of health (SDOH), including access to screening and treatment, and other systemic and structural factors are largely responsible for these disparities. Primary care practitioner (PCP) competence in culturally responsive screening practices will be critical to reducing the impact of systemic and structural factors serving as barriers to screening and treatment. Correspondingly, improving the capacity of PCPs to communicate with patients in a culturally responsive manner may influence improved screening and treatment outcomes for minoritized groups related to COVID-19. This scoping literature review aims to determine the current breadth of literature on culturally responsive communication (CRC) in regard to COVID-19 vaccination screening for historically excluded, or minoritized groups. Results from this review will inform the development of a training series and social marketing campaign to improve PCPs capacity in CRC. This manuscript provides details on our study protocol.ObjectivesThis scoping literature review aims to analyze existing literature on culturally responsive COVID-19 vaccinations between PCPs and patients in the U.S., specifically for racial, ethnic, sexual, and gender minoritized groups. Results of this scoping review will inform the development of a training series and social marketing campaign to improve capacity of PCPs in this area. Additionally, the review will inform recommendations for future research.Materials and methodsThis scoping review will be performed following the framework of Arksey and O’Malley and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR). Relevant studies between the years 2019–2022 were identified using a rigorous search strategy across four databases: MEDLINE (via PubMed), Scopus, Cochrane (CENTRAL; via Wiley), and CINAHL (via EBSCO), using Boolean and Medical Subject Headings (MeSH) search terms. Studies will be uploaded to the data extraction tool, Covidence, to remove duplicates and perform a title/abstract screening, followed by a full-text screening.ResultsThe data extraction and analysis phases of the scoping review are in progress. Data will be analyzed for themes related to culturally responsive COVID-19 screening practices in clinical encounters with the identified study populations. Results will be reported by theme and align to PRISMA-ScR guidelines.DiscussionTo our knowledge, this is the first study to use scoping methods to investigate the barriers and facilitators to CRC of COVID-19 vaccine screening for historically excluded communities in the U.S. The work and results from this research will be directly utilized for the development of nationally-accessible, continuing medical education materials to teach PCPs about CRC, as well as other materials to influence relevant policy changes within the healthcare landscape.

BackgroundCoronavirus Disease-19 (COVID-19) convalescents are at risk of developing a de novo mental health disorder or worsening of a pre-existing one. COVID-19 outpatients have been less well characterized than their hospitalized counterparts. The objectives of our study were to identify indicators for poor mental health following COVID-19 outpatient management and to identify high-risk individuals.MethodsWe conducted a binational online survey study with adult non-hospitalized COVID-19 convalescents (Austria/AT: n = 1,157, Italy/IT: n = 893). Primary endpoints were positive screening for depression and anxiety (Patient Health Questionnaire; PHQ-4) and self-perceived overall mental health (OMH) and quality of life (QoL) rated with 4 point Likert scales. Psychosocial stress was surveyed with a modified PHQ stress module. Associations of the mental health and QoL with socio-demographic, COVID-19 course, and recovery variables were assessed by multi-parameter Random Forest and Poisson modeling. Mental health risk subsets were defined by self-organizing maps (SOMs) and hierarchical clustering algorithms. The survey analyses are publicly available (https://im2-ibk.shinyapps.io/mental_health_dashboard/).ResultsDepression and/or anxiety before infection was reported by 4.6% (IT)/6% (AT) of participants. At a median of 79 days (AT)/96 days (IT) post-COVID-19 onset, 12.4% (AT)/19.3% (IT) of subjects were screened positive for anxiety and 17.3% (AT)/23.2% (IT) for depression. Over one-fifth of the respondents rated their OMH (AT: 21.8%, IT: 24.1%) or QoL (AT: 20.3%, IT: 25.9%) as fair or poor. Psychosocial stress, physical performance loss, high numbers of acute and sub-acute COVID-19 complaints, and the presence of acute and sub-acute neurocognitive symptoms (impaired concentration, confusion, and forgetfulness) were the strongest correlates of deteriorating mental health and poor QoL. In clustering analysis, these variables defined subsets with a particularly high propensity of post-COVID-19 mental health impairment and decreased QoL. Pre-existing depression or anxiety (DA) was associated with an increased symptom burden during acute COVID-19 and recovery.ConclusionOur study revealed a bidirectional relationship between COVID-19 symptoms and mental health. We put forward specific acute symptoms of the disease as “red flags” of mental health deterioration, which should prompt general practitioners to identify non-hospitalized COVID-19 patients who may benefit from early psychological and psychiatric intervention.Clinical Trial Registration[ClinicalTrials.gov], identifier [NCT04661462].

According to Cognitive Market Research, the value of the global alkaptonuria treatment market is anticipated to increase at a CAGR of 8.2% from 2023 to 2030. Increased Prevalence of Genetic Disorders to Provide Viable Market Output

One of the major drivers of the market's expansion is the increased prevalence of genetic illnesses and disorders.

In industrialized countries, congenital abnormalities and genetic diseases affect between 2% and 5% of all live births, causing up to 30% of pediatric hospital admissions and nearly 50% of infant deaths.

(Source:www.emro.who.int/emhj-volume-3-1997/volume-3-issue-1/article18.html)

Over the projected period, it is anticipated that an increasing number of people will be affected by alkaptonuria diseases, driving up sales and demand for alkaptonuria medications. Government rules encouraging product development, such as the Orphan Drug Act, which grants the orphan drug classification to potential drug candidates created by pharmaceutical corporations, are anticipated to assist industry growth. Furthermore, growing genomics research activities have led to the development of effective biological therapies for alkaptonuria diseases.

Market Dynamics of Alkaptonuria Treatment

Market Expansion is Constrained by Tight Regulatory Approvals and Guidelines

Due to their important and delicate roles in the global economy and their direct effects on consumers, the healthcare and pharmaceutical industries are subject to stringent rules and regulations. For instance, approving and releasing a novel drug without sufficient testing and review could have unfavorable effects that could be fatal to users. Protecting consumer interests requires a careful evaluation of the benefits and drawbacks of these treatments as well as a speeding up of the approval procedures. As a result, strict legal restrictions apply to the creation, evaluation, distribution, and use of drugs, therapies, and treatments for alkaptonuria. The government's stringent rules would hamper the market's expansion.

Impact of COVID–19 on the Alkaptonuria Treatment Market

Patients with rare and undiagnosed disorders have been dealing with serious health issues throughout the COVID-19 epidemic. The difficulties include diagnosis and/or prognosis uncertainty, medical complexity and poor health outcomes. Due to the growing epidemic, the pharmaceutical and healthcare industries' dynamics are radically changing. Hospitals in many countries struggle to find the medicines, vaccines, and medical equipment they need. Additionally, the COVID-19 pandemic has impacted clinical trials for rare disorders. For clinical trials, the pandemic has produced several difficulties. The challenges in locating, recruiting, and retaining patients with rare illnesses have significantly impacted clinical studies. Introduction of Alkaptonuria Treatment

An uncommon inherited metabolic condition called alkaptonuria makes the body retain homogentisic acid. People with this illness may have dark urine or pee that turns black when exposed to air because they may not have enough functioning levels of an enzyme needed to break down homogentisic acid. However, this alteration typically goes unrecognized and may not appear for several hours following urination. During the anticipated period, the market for alkaptonuria treatment will experience revenue growth due to an increase in the number of newly reported cases of the disease, higher awareness of this condition, and clinical exploratory treatments.

In the medical literature, more than 1,000 impacted people have been listed. Alkaptonuria's prevalence is not known with certainty. According to estimates, it affects 1 in 250,000 to 1,000,000 live births in the United States.

(Source:rarediseases.org/rare-diseases/alkaptonuria/#affected)

Additionally, one of the factors projected to fuel the growth of the alkaptonuria drug market is the patient aid programs and other support programs in terms of treatment and research performed by various organizations for alkaptonuria.

Abstract

COVID-19 has taken many lives worldwide and millions of persons are in grief. When the grief process lasts longer than 6 months, the sufferer is at risk of developing Complicated Grief Disorder (CGD). DGD is characterized by intense emotional distress that can last longer than socially expected and that causes a disability in the person's daily functioning, and endangers their health and well-being. Interventions can be applied to reduce the probability of developing CGD. In developing countries like Mexico where psychological services are scarce, self-applied interventions are a possible way to prevent CGD.

The Project designed an online self-applied intervention, the COVID Grief Platform, composed of 12 modules focused on decreasing the risk of developing CGD. A Randomized Controlled Trial was then conducted with participants assigned to an intervention. The interventions included elements of Cognitive Behavioral Therapy, Acceptance and Commitment Therapy, and Mindfulness and Positive Psychology. To analyse the outcomes, multiple (4) mixed between-within subjects ANOVA tests and post-hoc tests were conducted. Between-group comparisons with experimental and control groups were also carried out from Time 1 to Time 4. Finally a separate study was undertaken on the efficacy of the intervention in 2021.

Analysis unit

Individuals

Kind of data

Qualitative data

Mode of data collection

Internet

Research instrument

Data was collected online during a clinical trial using an online COVID Grief platform.

A set of interviews with NHS COVID-19 frontline staff to investigate the influence of COVID deployment on non-technical factors for healthcare delivery (leadership, social support & cohesion, communication, shared mental models, co-ordination) and expected moderating factors (occupational background, preparedness, work-life balance and home situation, proximity, workforce allocation models) and the impact on perceived teamwork, performance, individual team member well-being, resilience and team member employment retention intentions for NHS COVID-team members. The interviews with medical staff consisted of demographic questions collecting some special category data (e.g., ethnicity, job title, living arrangements during COVID), a 12-item standardised measure of wellbeing (administered using the GHQ-12, a short form General Health Questionnaire) and an 8 item Work Life Balance Scale (Schwartz et al., 2019; Sexton et al., 2017). These are not included in the interview transcripts. The interview schedule then followed a topic based semi-structured component (informed by themes identified in our previous work (Reid et al., 2018; 2016; Schilling, 2019), the wider literature, and our preliminary conceptual framework across these four main areas: 1) the creation of teams and the experience of teamwork, social support, shared communication patterns, co- ordination and mental models; 2) the role of leaders in establishing teamwork, social support, shared communication patterns, co-ordination and mental models; 3) perceived individual and team performance, well-being, resilience and retention intentions; 4) moderating factors including occupational background, preparedness, home life, work-life balance and any other issues arising during COVID-team membership.A key component of the NHS (and global) response to the COVID-19 pandemic has been to reinforce acute and critical care capacity, through an unprecedented re-deployment of personnel from different care pathways into fluid teams consisting of volunteers, student doctors and nurses, and in some cases military personnel [1-4]. These COVID-teams provide a unique opportunity to examine the interaction of many of the established factors for successful delivery of medical teamwork and care. Current evidence suggests that without common teamwork, shared communication patterns and clear leadership structures, the ad-hoc and fluid nature of these COVID-teams increases risk to patient outcomes, delivery of care [5-9] and team member resilience, mental-health and retention [10,11]. This project will examine how non-technical factors for healthcare delivery (leadership, social support; cohesion, communication, shared mental models, co-ordination) and expected moderating factors (occupational background, preparedness, work-life balance, home situation, proximity, workforce allocation models) impact on perceived COVID-teamworking and performance, individual team member well-being and team member employment retention intentions. It will be a mixed methods cross-sectional exploratory study of COVID-team members, clinical directors and senior hospital managers across a wide range of partnered NHS Trusts. Qualitative interviews will identify key themes and will be followed up by a more widely recruited confirmatory survey examining longer term individual well-being and retention intentions. Participant recruitment for the interviews was through two methods 1) Identification of eligible potential participants through the NHS research sites. Potential participants identified by relevant staff in the NHS Trusts. This will be achieved by asking the NHS research sites to identify relevant gate keepers in the trust who can identify eligible potential participants (those staff who have previously or currently have worked in Covid-teams and clinical directors/managers). Those gate keepers forwarded a recruitment email provided by the researchers for the eligible potential participants. Participants were then contacted and guided to the study website, reading the participant information and completing the online consent form. 2) Self-identification through a UK wide recruitment call, using Linkedin, twitter and facebook adverts. Potential participants will identify through visiting the study website, reading the participant information and completing the online consent form. Once the consent form was received (either online or via email) by the research team then participants were contacted by the research team, and provided a copy of the PIS form, the privacy notice and asked to schedule an interview. Only participants who are eligible (i.e., have worked on a COVID ward) and completed informed consent were contacted for an interview. Upon start of the interview, participants were again asked verbally for their informed consent. Participants are all adults over the age of 18 and will either have worked in a critical care COVID ward/ HDU in a patient facing role. Participants were interviewed individually online with video and audio by a researcher using a standardised schedule.

This is a compilation of COVID-19 research insights published from 11th – 17th January 2021 in these fields: Medicine and Health Science and Engineering Social Science, Humanities and Public Policy About www.covid19bibliometrics.org Introduction: The number of confirmed cases during the current Covid-19 pandemic is escalating exponentially. At the same time, the public are constantly being inundated with a formidable quantity of information, from innumerable sources, and containing both genuine as well as fake news. The Covid-19 “infodemic” is here. Health professionals including medical doctors and nurses are busy fighting the virus on the front line in our communities and hospitals and struggling to treat the ever-growing number of cases. Scientists and technicians at their bench-tops and computers in their research laboratories, are racing to find solutions, create new protective equipment, and ideally develop a vaccine. They all need accurate, timely and reliable information upon which they can make their decisions, find solutions, and help defeat this pandemic. This initiative aims to provide reliable and timely (initially at least twice a week) web updates on the relevant published literature. “Reliable” and “timely” means that it can be trusted and it is up to date; “relevant” and “published” means that it is focused on what health professionals and scientists need when facing both the pandemic and the infodemic, and it can be trusted as sound science. We plan to make the material succinct and accessible, and to provide key bibliometric indices such as source and citation. Objectives: 1. To update the global scientific community on current Covid-19 related published papers in an accessible, timely and trusted format 2. To analyse the published papers for trends and to provide insights 3. To identify gaps in research 4. To promote international research collaboration with a view to overcoming Covid-19 and promoting recovery Methodology: Covid-19 related publications to be searched using the Scopus database using as a minimum the following keywords: 2019-nCoV, SARS-CoV-2, Covid-19, novel Coronavirus. Papers then to be categorized according to topic, research fields, institutions, countries, etc. Abstracts and papers to be reviewed for findings, trends, key insights, etc. To read previous COVID-19 research insights, please go to: https://zenodo.org/communities/covid19bibliometrics/ More information, please go to https://www.covid19bibliometrics.org/

Digital Cognitive Biomarker Platforms Market Outlook

According to our latest research, the global Digital Cognitive Biomarker Platforms market size reached USD 2.1 billion in 2024, reflecting robust expansion driven by advancements in digital health technologies and the increasing integration of artificial intelligence in healthcare. The market is poised to grow at a CAGR of 23.7% from 2025 to 2033, and is forecasted to reach USD 16.4 billion by 2033. This remarkable growth is underpinned by rising demand for non-invasive, objective, and scalable cognitive assessment tools across clinical trials, disease diagnosis, and patient monitoring applications, as well as the growing adoption of precision medicine and digital therapeutics.

One of the primary growth drivers for the Digital Cognitive Biomarker Platforms market is the surging prevalence of neurodegenerative and psychiatric disorders globally. With the aging population, conditions such as Alzheimer’s disease, Parkinson’s disease, and various forms of dementia are on the rise, creating a pressing need for early and accurate detection methods. Digital cognitive biomarkers, which leverage data from smartphones, wearables, and other connected devices, offer a promising solution by enabling continuous, real-time monitoring of cognitive function. These platforms facilitate early intervention and personalized treatment, which are essential for improving patient outcomes and reducing the overall burden on healthcare systems. Additionally, the integration of machine learning and artificial intelligence in these platforms enhances the accuracy and predictive power of cognitive assessments, further fueling market growth.

Another significant factor propelling the Digital Cognitive Biomarker Platforms market is the increasing use of these technologies in clinical trials and pharmaceutical research. Traditional cognitive assessment methods are often subjective, time-consuming, and susceptible to bias, limiting their utility in large-scale studies. Digital platforms, on the other hand, provide objective, quantifiable, and reproducible data, making them ideal for use in multi-center clinical trials and longitudinal studies. Pharmaceutical and biotechnology companies are increasingly adopting these platforms to streamline patient recruitment, monitor treatment efficacy, and identify potential adverse effects in real-time. This not only accelerates the drug development process but also enhances the reliability of trial outcomes, thereby attracting significant investments from industry stakeholders.

The rapid adoption of telemedicine and remote patient monitoring, particularly in the wake of the COVID-19 pandemic, has further accelerated the growth of the Digital Cognitive Biomarker Platforms market. As healthcare providers and patients become more comfortable with digital health solutions, there is a growing emphasis on remote cognitive assessment and monitoring. This trend is particularly evident in regions with well-established digital infrastructure, such as North America and parts of Europe. The ability of digital cognitive biomarkers to facilitate remote, scalable, and cost-effective monitoring of cognitive health is expected to drive widespread adoption across various healthcare settings, from hospitals and clinics to home care environments. Moreover, ongoing advancements in data security, interoperability, and user experience are addressing key barriers to adoption and paving the way for sustained market expansion.

Regionally, North America dominates the Digital Cognitive Biomarker Platforms market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of leading technology providers, robust healthcare infrastructure, and favorable regulatory frameworks in these regions have contributed to rapid market uptake. However, Asia Pacific is expected to exhibit the fastest growth over the forecast period, driven by increasing investments in healthcare digitization, rising awareness of mental health issues, and expanding access to connected devices. Latin America and the Middle East & Africa are also witnessing gradual adoption, supported by improving healthcare infrastructure and growing government initiatives to promote digital health. Overall, the global market is characterized by significant regional disparities, but the underlying trend toward digitalization and personalized medicine is expected to drive convergence in adoption rates over time.

Experimental Cynomolgus Monkey Market Outlook

The global experimental cynomolgus monkey market size was valued at approximately $450 million in 2023 and is projected to reach $750 million by 2032, growing at a compound annual growth rate (CAGR) of 6.1%. This market growth can be primarily attributed to the rising demand for reliable animal models in pharmaceutical research and development, as well as the increased focus on preclinical studies to ensure drug efficacy and safety.

One of the primary growth factors driving the experimental cynomolgus monkey market is the expanding pharmaceutical industry, which relies heavily on animal models for drug discovery and development. Cynomolgus monkeys, due to their genetic, anatomical, and physiological similarities to humans, provide invaluable insights into the efficacy and toxicity of new drugs. Additionally, the rising prevalence of chronic diseases such as cancer, diabetes, and cardiovascular diseases has led to an increased demand for effective treatments, thereby propelling the need for extensive preclinical testing using cynomolgus monkeys.

Another significant factor contributing to market growth is the increasing investment in biomedical research, particularly in the fields of neuroscience and vaccine development. Cynomolgus monkeys are often used in neuroscience research due to their complex brain structure and cognitive abilities, which closely mimic those of humans. This makes them ideal for studying neurological disorders and potential treatments. Furthermore, the global push for the development of vaccines, especially in the wake of the COVID-19 pandemic, has underscored the importance of reliable animal models, further boosting the market.

Ethical considerations and stringent regulatory requirements also play a crucial role in shaping the experimental cynomolgus monkey market. The use of non-human primates in research is subject to rigorous ethical scrutiny and regulatory oversight to ensure humane treatment and minimize suffering. This has led to the adoption of advanced technologies and methodologies aimed at reducing the number of animals used in research while still obtaining valuable data. Such advancements are expected to drive market growth by making research more efficient and ethically responsible.

Regionally, North America holds a dominant position in the experimental cynomolgus monkey market, followed closely by Europe and Asia Pacific. The presence of leading pharmaceutical companies, well-established research facilities, and favorable regulatory frameworks in these regions contribute to their market leadership. Additionally, the increasing focus on innovative research and development activities in emerging economies in Asia Pacific presents significant growth opportunities for the market in this region.

Application Analysis

The pharmaceutical research segment is a major contributor to the experimental cynomolgus monkey market. Pharmaceutical companies utilize these monkeys extensively for preclinical trials to evaluate the safety and efficacy of new drugs. The high genetic similarity between cynomolgus monkeys and humans makes them an ideal choice for such studies, reducing the risk of adverse reactions when the drugs move to human trials. The increase in drug discovery and development activities, driven by the rising prevalence of chronic diseases, strongly supports the growth of this segment.

The toxicology studies segment also holds significant market share. Toxicology studies are essential to ensure that new drugs do not pose severe health risks before they are administered to humans. Cynomolgus monkeys are frequently used in these studies due to their physiological resemblance to humans, which provides more accurate toxicity data compared to other animal models. The growing emphasis on drug safety and regulatory compliance further bolsters the demand for cynomolgus monkeys in toxicology studies.

In vaccine development, cynomolgus monkeys have been instrumental, especially in the context of emerging infectious diseases. The urgency to develop effective vaccines rapidly, as seen during the COVID-19 pandemic, has intensified the need for reliable animal models. Cynomolgus monkeys' immune system responses closely mimic those of humans, making them invaluable in assessing vaccine efficacy and safety before clinical trials. This segment is expected to witness significant growth due to ongoing and future vaccine development initiatives.

Neuroscience research is another critical application area where cynomolgu