Beyond open data: realising the health benefits of sharing data

The lymphatic filariasis treatment study landscape: A systematic review of study characteristics and the case for an individual participant data platform

BACKGROUND

Lymphatic filariasis (LF) is a neglected tropical disease (NTD) targeted by the World Health Organization for elimination as a public health problem (EPHP). Since 2000, more than 9 billion treatments of antifilarial medicines have been distributed through mass drug administration (MDA) programmes in 72 endemic countries and 17 countries have reached EPHP. Yet in 2021, nearly 900 million people still required MDA with combinations of albendazole, diethylcarbamazine and/or ivermectin. Despite the reliance on these drugs, there remain gaps in understanding of variation in responses to treatment. As demonstrated for other infectious diseases, some urgent questions could be addressed by conducting individual participant data (IPD) meta-analyses. Here, we present the results of a systematic literature review to estimate the abundance of IPD on pre- and post-intervention indicators of infection and/or morbidity and assess the feasibility of building a global data repository.

METHODOLOGY

We searched literature published between 1st January 2000 and 5th May 2023 in 15 databases to identify prospective studies assessing LF treatment and/or morbidity management and disease prevention (MMDP) approaches. We considered only studies where individual participants were diagnosed with LF infection or disease and were followed up on at least one occasion after receiving an intervention/treatment.

PRINCIPAL FINDINGS

We identified 138 eligible studies from 23 countries, having followed up an estimated 29,842 participants after intervention. We estimate 14,800 (49.6%) IPD on pre- and post-intervention infection indicators including microfilaraemia, circulating filarial antigen and/or ultrasound indicators measured before and after intervention using 8 drugs administered in various combinations. We identified 33 studies on MMDP, estimating 6,102 (20.4%) IPD on pre- and post-intervention clinical morbidity indicators only. A further 8,940 IPD cover a mixture of infection and morbidity outcomes measured with other diagnostics, from participants followed for adverse event outcomes only or recruited after initial intervention.

CONCLUSIONS

The LF treatment study landscape is heterogeneous, but the abundance of studies and related IPD suggest that establishing a global data repository to facilitate IPD meta-analyses would be feasible and useful to address unresolved questions on variation in treatment outcomes across geographies, demographics and in underrepresented groups. New studies using more standardized approaches should be initiated to address the scarcity and inconsistency of data on morbidity management.

Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness

BACKGROUND

Improving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness.

METHODS

Twelve people with lived experience of mental illness took part in semi-structured interviews via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use.

RESULTS

Thematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place.

CONCLUSIONS

There was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness.

Health system use and outcomes of urgently triaged callers to a nurse-managed telephone service for provincial health information after initiation of supplemental virtual physician assessment: a descriptive study

BACKGROUND

British Columbia's 8-1-1 telephone service connects callers with nurses for health care advice. As of Nov. 16, 2020, callers advised by a registered nurse to obtain in-person medical care can be subsequently referred to virtual physicians. We sought to determine health system use and outcomes of 8-1-1 callers urgently triaged by a nurse and subsequently assessed by a virtual physician.

METHODS

We identified callers referred to a virtual physician between Nov. 16, 2020, and Apr. 30, 2021. After assessment, virtual physicians assigned callers to 1 of 5 triage dispositions (i.e., go to emergency department [ED] now, see primary care provider within 24 hours, schedule an appointment with a health care provider, try home treatment, other). We linked relevant administrative databases to ascertain subsequent health care use and outcomes.

RESULTS

We identified 5937 encounters with virtual physicians involving 5886 8-1-1 callers. Virtual physicians advised 1546 callers (26.0%) to go to the ED immediately, of whom 971 (62.8%) had 1 or more ED visits within 24 hours. Virtual physicians advised 556 (9.4%) callers to seek primary care within 24 hours, of whom 132 (23.7%) had primary care billings within 24 hours. Virtual physicians advised 1773 (29.9%) callers to schedule an appointment with a health care provider, of whom 812 (45.8%) had primary care billings within 7 days. Virtual physicians advised 1834 (30.9%) callers to try a home treatment, of whom 892 (48.6%) had no health system encounters over the next 7 days. Eight (0.1%) callers died within 7 days of assessment with a virtual physician, 5 of whom were advised to go to the ED immediately. Fifty-four (2.9%) callers with a "try home treatment" disposition were admitted to hospital within 7 days of a virtual physician assessment, and no callers who were advised home treatment died.

INTERPRETATION

This Canadian study evaluated health service use and outcomes arising from the addition of virtual physicians to a provincial health information telephone service. Our findings suggest that supplementation of this service with an assessment from a virtual physician safely reduces the overall proportion of callers advised to seek urgent in-person visits.

Open video data sharing in developmental science and clinical practice

In behavioral research and clinical practice video data has rarely been shared or pooled across sites due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-heavy computer-based approaches are involved. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing an established and video-based diagnostic tool for detecting neurological deficits. We demonstrated for the first time that, for analyzing infant neuromotor functions, pseudonymization by face-blurring video recordings is a viable approach. The redaction did not affect classification accuracy for either human assessors or artificial intelligence methods, suggesting an adequate and easy-to-apply solution for sharing behavioral video data. Our work shall encourage more innovative solutions to share and merge stand-alone video datasets into large data pools to advance science and public health.

What constitutes equitable data sharing in global health research? A scoping review of the literature on low-income and middle-income country stakeholders' perspectives

INTRODUCTION

Despite growing consensus on the need for equitable data sharing, there has been very limited discussion about what this should entail in practice. As a matter of procedural fairness and epistemic justice, the perspectives of low-income and middle-income country (LMIC) stakeholders must inform concepts of equitable health research data sharing. This paper investigates published perspectives in relation to how equitable data sharing in global health research should be understood.

METHODS

We undertook a scoping review (2015 onwards) of the literature on LMIC stakeholders' experiences and perspectives of data sharing in global health research and thematically analysed the 26 articles included in the review.

RESULTS

We report LMIC stakeholders' published views on how current data sharing mandates may exacerbate inequities, what structural changes are required in order to create an environment conducive to equitable data sharing and what should comprise equitable data sharing in global health research.

CONCLUSIONS

In light of our findings, we conclude that data sharing under existing mandates to share data (with minimal restrictions) risks perpetuating a neocolonial dynamic. To achieve equitable data sharing, adopting best practices in data sharing is necessary but insufficient. Structural inequalities in global health research must also be addressed. It is thus imperative that the structural changes needed to ensure equitable data sharing are incorporated into the broader dialogue on global health research.

Geometric variation of the human tibia-fibula: a public dataset of tibia-fibula surface meshes and statistical shape model

Background

Variation in tibia geometry is a risk factor for tibial stress fractures. Geometric variability in bones is often quantified using statistical shape modelling. Statistical shape models (SSM) offer a method to assess three-dimensional variation of structures and identify the source of variation. Although SSM have been used widely to assess long bones, there is limited open-source datasets of this kind. Overall, the creation of SSM can be an expensive process, that requires advanced skills. A publicly available tibia shape model would be beneficial as it enables researchers to improve skills. Further, it could benefit health, sport and medicine with the potential to assess geometries suitable for medical equipment, and aid in clinical diagnosis. This study aimed to: (i) quantify tibial geometry using a SSM; and (ii) provide the SSM and associated code as an open-source dataset.

Methods

Lower limb computed tomography (CT) scans from the right tibia-fibula of 30 cadavers (male n = 20, female n = 10) were obtained from the New Mexico Decedent Image Database. Tibias were segmented and reconstructed into both cortical and trabecular sections. Fibulas were segmented as a singular surface. The segmented bones were used to develop three SSM of the: (i) tibia; (ii) tibia-fibula; and (iii) cortical-trabecular. Principal component analysis was applied to obtain the three SSM, with the principal components that explained 95% of geometric variation retained.

Results

Overall size was the main source of variation in all three models accounting for 90.31%, 84.24% and 85.06%. Other sources of geometric variation in the tibia surface models included overall and midshaft thickness; prominence and size of the condyle plateau, tibial tuberosity, and anterior crest; and axial torsion of the tibial shaft. Further variations in the tibia-fibula model included midshaft thickness of the fibula; fibula head position relative to the tibia; tibia and fibula anterior-posterior curvature; fibula posterior curvature; tibia plateau rotation; and interosseous width. The main sources of variation in the cortical-trabecular model other than general size included variation in the medulla cavity diameter; cortical thickness; anterior-posterior shaft curvature; and the volume of trabecular bone in the proximal and distal ends of the bone.

Conclusion

Variations that could increase the risk of tibial stress injury were observed, these included general tibial thickness, midshaft thickness, tibial length and medulla cavity diameter (indicative of cortical thickness). Further research is needed to better understand the effect of these tibial-fibula shape characteristics on tibial stress and injury risk. This SSM, the associated code, and three use examples for the SSM have been provided in an open-source dataset. The developed tibial surface models and statistical shape model will be made available for use at: https://simtk.org/projects/ssm_tibia.

Risk reduction via spatial and temporal visualization of road accidents: a way forward for emergency response optimization in developing countries

To achieve an effective emergency response and road safety, this study aims to assist a semi-automated dynamic system to analyze and predict the spatial distribution and temporal pattern of road crashes. Kasur, an intermediate city of Pakistan, was selected and data including location, time and reasons of accidents for five years (2014-2018) was utilized. Radar charts, Getis-Ord Gi* statistic, Moran's I spatial auto-correlation, and time series indices were engaged to present temporal, spatial and spatial-temporal variation of accidents, using python-based tools and jupyter notebook. A dynamic user interface was created using Github and Tableau to visualize a real-time zoom-able spatiotemporal variation of accidents. The results explain that out of 12 months, October faces the peak while April sees the least of road accidents. 7am is the peak hour for accidents and the weekends record a significantly higher number of road accidents as compared to weekdays. The city core witnesses the major hotspot areas with huge cluster of accidents. The findings contribute towards a well-informed decision support system, the knowledge of spatial analytics and its application in road safety science, and the preparedness of the rescue agencies for rapid response to reduce the impacts of road accidents.

A focus groups study on data sharing and research data management

Data sharing can accelerate scientific discovery while increasing return on investment beyond the researcher or group that produced them. Data repositories enable data sharing and preservation over the long term, but little is known about scientists' perceptions of them and their perspectives on data management and sharing practices. Using focus groups with scientists from five disciplines (atmospheric and earth science, computer science, chemistry, ecology, and neuroscience), we asked questions about data management to lead into a discussion of what features they think are necessary to include in data repository systems and services to help them implement the data sharing and preservation parts of their data management plans. Participants identified metadata quality control and training as problem areas in data management. Additionally, participants discussed several desired repository features, including: metadata control, data traceability, security, stable infrastructure, and data use restrictions. We present their desired repository features as a rubric for the research community to encourage repository utilization. Future directions for research are discussed.

Regulatory Frameworks for Clinical Trial Data Sharing: Scoping Review

Background

Although well recognized for its scientific value, data sharing from clinical trials remains limited. Steps toward harmonization and standardization are increasing in various pockets of the global scientific community. This issue has gained salience during the COVID-19 pandemic. Even for agencies willing to share data, data exclusivity practices complicate matters; strict regulations by funders affect this even further. Finally, many low- and middle-income countries (LMICs) have weaker institutional mechanisms. This complex of factors hampers research and rapid response during public health emergencies. This drew our attention to the need for a review of the regulatory landscape governing clinical trial data sharing.

Objective

This review seeks to identify regulatory frameworks and policies that govern clinical trial data sharing and explore key elements of data-sharing mechanisms as outlined in existing regulatory documents. Following from, and based on, this empirical analysis of gaps in existing policy frameworks, we aimed to suggest focal areas for policy interventions on a systematic basis to facilitate clinical trial data sharing.

Methods

We followed the JBI scoping review approach. Our review covered electronic databases and relevant gray literature through a targeted web search. We included records (all publication types, except for conference abstracts) available in English that describe clinical trial data–sharing policies, guidelines, or standard operating procedures. Data extraction was performed independently by 2 authors, and findings were summarized using a narrative synthesis approach.

Results

We identified 4 articles and 13 policy documents; none originated from LMICs. Most (11/17, 65%) of the clinical trial agencies mandated a data-sharing agreement; 47% (8/17) of these policies required informed consent by trial participants; and 71% (12/17) outlined requirements for a data-sharing proposal review committee. Data-sharing policies have, a priori, milestone-based timelines when clinical trial data can be shared. We classify clinical trial agencies as following either controlled- or open-access data-sharing models. Incentives to promote data sharing and distinctions between mandated requirements and supportive requirements for informed consent during the data-sharing process remain gray areas, needing explication. To augment participant privacy and confidentiality, a neutral institutional mechanism to oversee dissemination of information from the appropriate data sets and more policy interventions led by LMICs to facilitate data sharing are strongly recommended.

Conclusions

Our review outlines the immediate need for developing a pragmatic data-sharing mechanism that aims to improve research and innovations as well as facilitate cross-border collaborations. Although a one-policy-fits-all approach would not account for regional and subnational legislation, we suggest that a focus on key elements of data-sharing mechanisms can be used to inform the development of flexible yet comprehensive data-sharing policies so that institutional mechanisms rather than disparate efforts guide data generation, which is the foundation of all scientific endeavor.

Pharmacokinetics of chloroquine and primaquine in healthy volunteers

Background

Vivax malaria is a neglected disease. There is an irrefutable need for better treatments with higher acceptability and efficacy. The treatment efficacy is influenced by many factors, including bioavailability. Hence, a straightforward strategy to improve vivax malaria treatment efficacy is the deployment of good quality formulations of primaquine and chloroquine. As these treatments were developed more than 70 years ago, many of the available data on blood levels of both drugs are based on obsolete analytical methodologies or pharmaceutical formulations, which are not available anymore. Herein, the results of three bioequivalence studies are presented, providing individual pharmacokinetic data on chloroquine and primaquine of more than a hundred healthy volunteers and using up-to-date analytical methods.

Methods

Three trials were designed as a single centre, randomized, single dose, open label, fasting, crossover bioequivalence studies comparing a new coated chloroquine tablet to the uncoated tablet, and 5 and 15 mg primaquine formulations to either an international reference product or the currently distributed tablets. Plasma concentrations of chloroquine and primaquine were measured using a validated HPLC–MS/MS method in accordance with current international regulatory requirements for bio-analytical methods.

Results

In total, a hundred eleven healthy volunteers of both genders were included in the three studies (n = 32; 30 and 56 respectively). No serious adverse events occurred. Drugs levels were measured in 5,520 blood samples. The estimated ratio of the geometric means of Cmax, AUC0-t and AUC0-inf of test and reference drugs and their 90% CI for chloroquine 150 mg, primaquine 15 mg and primaquine 5 mg were: 95.33% (89.18; 101.90), 86. 85% (82.61; 91.31), and 84.45% (76.95; 92.67); 93.28% (81.76; 106.41), 94.52% (86.13; 103.73) and 93.93% (85.83; 102.79); 97.44% (90.60; 104.78), 93.70% (87.04; 100.87) and 91.36% (85.27; 97.89), respectively. As Cmax and AUC0-t 90% CI were within the acceptance interval of 80–125% in all cases, the formulations tested were bioequivalent.

Conclusions

In conclusion, the three studies provided detailed chloroquine and primaquine pharmacokinetic data in accordance with current regulatory standards. Together with other open data initiatives, this individual data may increase the accuracy of pharmacokinetic models guiding best dose, new combinations, regimens and formulations to optimize the current chloroquine and primaquine treatments for vivax malaria. The data presented here may support the deployment of high-quality drugs and evidence-based public health policies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-04035-z.

Improving anthelmintic treatment for schistosomiasis and soil-transmitted helminthiases through sharing and reuse of individual participant data

The Infectious Diseases Data Observatory (IDDO, https://www.iddo.org) has launched a clinical data platform for the collation, curation, standardisation and reuse of individual participant data (IPD) on treatments for two of the most globally important neglected tropical diseases (NTDs), schistosomiasis (SCH) and soil-transmitted helminthiases (STHs). This initiative aims to harness the power of data-sharing by facilitating collaborative joint analyses of pooled datasets to generate robust evidence on the efficacy and safety of anthelminthic treatment regimens. A crucial component of this endeavour has been the development of a Research Agenda to promote engagement with the SCH and STH research and disease control communities by highlighting key questions that could be tackled using data shared through the IDDO platform. Here, we give a contextual overview of the priority research themes articulated in the Research Agenda-a 'living' document hosted on the IDDO website-and describe the three-stage consultation process behind its development. We also discuss the sustainability and future directions of the platform, emphasising throughout the power and promise of ethical and equitable sharing and reuse of clinical data to support the elimination of NTDs.

Privacy of study participants in open-access Health and Demographic Surveillance System data: A requirements analysis for data anonymisation (Preprint)

Background

Data anonymization and sharing have become popular topics for individuals, organizations, and countries worldwide. Open-access sharing of anonymized data containing sensitive information about individuals makes the most sense whenever the utility of the data can be preserved and the risk of disclosure can be kept below acceptable levels. In this case, researchers can use the data without access restrictions and limitations.

Objective

This study aimed to highlight the requirements and possible solutions for sharing health surveillance event history data. The challenges lie in the anonymization of multiple event dates and time-varying variables.

Methods

A sequential approach that adds noise to event dates is proposed. This approach maintains the event order and preserves the average time between events. In addition, a nosy neighbor distance-based matching approach to estimate the risk is proposed. Regarding the key variables that change over time, such as educational level or occupation, we make 2 proposals: one based on limiting the intermediate statuses of the individual and the other to achieve k-anonymity in subsets of the data. The proposed approaches were applied to the Karonga health and demographic surveillance system (HDSS) core residency data set, which contains longitudinal data from 1995 to the end of 2016 and includes 280,381 events with time-varying socioeconomic variables and demographic information.

Results

An anonymized version of the event history data, including longitudinal information on individuals over time, with high data utility, was created.

Conclusions

The proposed anonymization of event history data comprising static and time-varying variables applied to HDSS data led to acceptable disclosure risk, preserved utility, and being sharable as public use data. It was found that high utility was achieved, even with the highest level of noise added to the core event dates. The details are important to ensure consistency or credibility. Importantly, the sequential noise addition approach presented in this study does not only maintain the event order recorded in the original data but also maintains the time between events. We proposed an approach that preserves the data utility well but limits the number of response categories for the time-varying variables. Furthermore, using distance-based neighborhood matching, we simulated an attack under a nosy neighbor situation and by using a worst-case scenario where attackers have full information on the original data. We showed that the disclosure risk is very low, even when assuming that the attacker’s database and information are optimal. The HDSS and medical science research communities in low- and middle-income country settings will be the primary beneficiaries of the results and methods presented in this paper; however, the results will be useful for anyone working on anonymizing longitudinal event history data with time-varying variables for the purposes of sharing.

Systematic review of the scrub typhus treatment landscape: Assessing the feasibility of an individual participant-level data (IPD) platform

Background

Scrub typhus is an acute febrile illness caused by intracellular bacteria from the genus Orientia. It is estimated that one billion people are at risk, with one million cases annually mainly affecting rural areas in Asia-Oceania. Relative to its burden, scrub typhus is understudied, and treatment recommendations vary with poor evidence base. These knowledge gaps could be addressed by establishing an individual participant-level data (IPD) platform, which would enable pooled, more detailed and statistically powered analyses to be conducted. This study aims to assess the characteristics of scrub typhus treatment studies and explore the feasibility and potential value of developing a scrub typhus IPD platform to address unanswered research questions.

Methodology/principal findings

We conducted a systematic literature review looking for prospective scrub typhus clinical treatment studies published from 1998 to 2020. Six electronic databases (Ovid Embase, Ovid Medline, Ovid Global Health, Cochrane Library, Scopus, Global Index Medicus), ClinicalTrials.gov, and WHO ICTRP were searched. We extracted data on study design, treatment tested, patient characteristics, diagnostic methods, geographical location, outcome measures, and statistical methodology.

Among 3,100 articles screened, 127 were included in the analysis. 12,079 participants from 12 countries were enrolled in the identified studies. ELISA, PCR, and eschar presence were the most commonly used diagnostic methods. Doxycycline, azithromycin, and chloramphenicol were the most commonly administered antibiotics. Mortality, complications, adverse events, and clinical response were assessed in most studies. There was substantial heterogeneity in the diagnostic methods used, treatment administered (including dosing and duration), and outcome assessed across studies. There were few interventional studies and limited data collected on specific groups such as children and pregnant women.

Conclusions/significance

There were a limited number of interventional trials, highlighting that scrub typhus remains a neglected disease. The heterogeneous nature of the available data reflects the absence of consensus in treatment and research methodologies and poses a significant barrier to aggregating information across available published data without access to the underlying IPD. There is likely to be a substantial amount of data available to address knowledge gaps. Therefore, there is value for an IPD platform that will facilitate pooling and harmonisation of currently scattered data and enable in-depth investigation of priority research questions that can, ultimately, inform clinical practice and improve health outcomes for scrub typhus patients.

Scrub typhus is a febrile illness most commonly found in rural tropical areas. It is caused by a Gram-negative bacteria belonging to the family Rickettsiaceae and transmitted by mites when they feed on vertebrates. There is an estimate of one million cases annually, with an estimated one billion people at risk, mostly in Asia-Oceania. But relative to the scale of the problem, scrub typhus is largely understudied. Evidence-based treatment recommendations by policymakers vary or are non-existent. We searched databases and registries for prospective scrub typhus clinical treatment studies published from 1998 to 2020 and reviewed them. Data from clinical trials and particularly for specific groups, such as pregnant women and children, were minimal. The methods used to measure treatment efficacy were heterogeneous, making it difficult to directly compare or conduct a meta-analysis based on aggregated data. One way to improve the current level of evidence would be by pooling and analysing individual participant-level data (IPD), i.e. the raw data from individual participants in completed studies. This review demonstrated that there is scope for developing a database for individual participant data to enable more detailed analyses. IPD meta-analyses could be a way to address knowledge gaps such as optimum dosing for children and pregnant women.

Equitable data sharing in epidemics and pandemics

BACKGROUND

Rapid data sharing can maximize the utility of data. In epidemics and pandemics like Zika, Ebola, and COVID-19, the case for such practices seems especially urgent and warranted. Yet rapidly sharing data widely has previously generated significant concerns related to equity. The continued lack of understanding and guidance on equitable data sharing raises the following questions: Should data sharing in epidemics and pandemics primarily advance utility, or should it advance equity as well? If so, what norms comprise equitable data sharing in epidemics and pandemics? Do these norms address the equity-related concerns raised by researchers, data providers, and other stakeholders? What tensions must be balanced between equity and other values?

METHODS

To explore these questions, we undertook a systematic scoping review of the literature on data sharing in epidemics and pandemics and thematically analyzed identified literature for its discussion of ethical values, norms, concerns, and tensions, with a particular (but not exclusive) emphasis on equity. We wanted to both understand how equity in data sharing is being conceptualized and draw out other important values and norms for data sharing in epidemics and pandemics.

RESULTS

We found that values of utility, equity, solidarity, and reciprocity were described, and we report their associated norms, including researcher recognition; rapid, real-time sharing; capacity development; and fair benefits to data generators, data providers, and source countries. The value of utility and its associated norms were discussed substantially more than others. Tensions between utility norms (e.g., rapid, real-time sharing) and equity norms (e.g., researcher recognition, equitable access) were raised.

CONCLUSIONS

This study found support for equity being advanced by data sharing in epidemics and pandemics. However, norms for equitable data sharing in epidemics and pandemics require further development, particularly in relation to power sharing and participatory approaches prioritizing inclusion. Addressing structural inequities in the wider global health landscape is also needed to achieve equitable data sharing in epidemics and pandemics.

The Chagas disease study landscape: A systematic review of clinical and observational antiparasitic treatment studies to assess the potential for establishing an individual participant-level data platform

Background

Chagas disease (CD), caused by the parasite Trypanosoma cruzi, affects ~6–7 million people worldwide. Significant limitations still exist in our understanding of CD. Harnessing individual participant data (IPD) from studies could support more in-depth analyses to address the many outstanding research questions. This systematic review aims to describe the characteristics and treatment practices of clinical studies in CD and assess the breadth and availability of research data for the potential establishment of a data-sharing platform.

Methodology/Principal findings

This review includes prospective CD clinical studies published after 1997 with patients receiving a trypanocidal treatment. The following electronic databases and clinical trial registry platforms were searched: Cochrane Library, PubMed, Embase, LILACS, Scielo, Clintrials.gov, and WHO ICTRP.

Of the 11,966 unique citations screened, 109 (0.9%) studies (31 observational and 78 interventional) representing 23,116 patients were included. Diagnosis for patient enrolment required 1 positive test result in 5 (4.6%) studies (2 used molecular method, 1 used molecular and serology, 2 used serology and parasitological methods), 2 in 60 (55.0%), 3 in 14 (12.8%) and 4 or more in 4 (3.7%) studies. A description of treatment regimen was available for 19,199 (83.1%) patients, of whom 14,605 (76.1%) received an active treatment and 4,594 (23.9%) were assigned to a placebo/no-treatment. Of the 14,605 patients who received an active treatment, benznidazole was administered in 12,467 (85.4%), nifurtimox in 825 (5.6%), itraconazole in 284 (1.9%), allopurinol in 251 (1.7%) and other drugs in 286 (1.9%). Assessment of efficacy varied largely and was based primarily on biological outcome; parasitological efficacy relied on serology in 67/85 (78.8%) studies, molecular methods in 52/85 (61.2%), parasitological in 34/85 (40.0%), microscopy in 3/85 (3.5%) and immunohistochemistry in 1/85 (1.2%). The median time at which parasitological assessment was carried out was 79 days [interquartile range (IQR): 30–180] for the first assessment, 180 days [IQR: 60–500] for second, and 270 days [IQR: 18–545] for the third assessment.

Conclusions/Significance

This review demonstrates the heterogeneity of clinical practice in CD treatment and in the conduct of clinical studies. The sheer volume of potential IPD identified demonstrates the potential for development of an IPD platform for CD and that such efforts would enable in-depth analyses to optimise the limited pharmacopoeia of CD and inform prospective data collection.

Chagas disease, also known as American trypanosomiasis, is a neglected tropical disease transmitted by triatomine insects, first identified in 1909. Chagas disease affects approximately 6–7 million people globally and is highly prevalent in Latin America where most cases are reported. However, there is increasing evidence that Chagas disease is now an important public health issue outside the “classical” endemic countries due to population migration. Our understanding of Chagas disease, including its pathologies and factors relating to progression, remains to date limited, and is also challenged by lack of diagnosis and highly effective treatment. This systematic review aims to describe studies with Chagas patients receiving antiparasitic treatment. Databases were searched for relevant studies published after 1997, and the results of these searches were screened.

Although a large volume of studies was identified in the review, heterogeneity was observed in study design, diagnostic methods, outcome assessment, and treatment regimens. While this aspect will be a limitation in pooling individual patient data, the volume of data available should allow sufficient comparison to form the basis of guidelines for future studies. The results of this review demonstrate that development of a Chagas disease data platform for clinical research would enable optimisation of existing data to strengthen evidence for the treatment and diagnosis of Chagas disease.

A scoping review of considerations and practices for benefit sharing in biobanking

BACKGROUND

Despite the rapid global growth of biobanking over the last few decades, and their potential for the advancement of health research, considerations specific to the sharing of benefits that accrue from biobanks have received little attention. Questions such as the types and range of benefits that can arise in biobanking, who should be entitled to those benefits, when they should be provided, by whom and in what form remain mostly unanswered. We conducted a scoping review to describe benefit sharing considerations and practices in biobanking in order to inform current and future policy and practice.

METHODS

Drawing on the Arksey and O'Malley framework, we conducted a scoping review of the literature in three online databases (PubMed, Cochrane library, and Google Scholar). We extracted and charted data to capture general characteristics, definitions and examples of benefits and benefit sharing, justification for benefit sharing, challenges in benefit sharing, governance mechanisms as well as proposed benefit sharing mechanisms.

RESULTS

29 articles published between 1999 and 2020 met the inclusion criteria for the study. The articles included 5 empirical and 24 non-empirical studies. Only 12 articles discussed benefit sharing as a stand-alone subject, while the remaining 17 integrated a discussion of benefits as one issue amongst others. Major benefit sharing challenges in biobanking were found to be those associated with uncertainties around the future use of samples and in resultant benefits.

CONCLUSION

Most of the benefit sharing definitions and approaches currently in use for biobanking are similar to those used in health research. These approaches may not recognise the distinct features of biobanking, specifically relating to uncertainties associated with the sharing and re-use of samples. We therefore support approaches that allow decisions about benefit sharing to be made progressively once it is apparent who samples are to be shared with, the intended purpose and expected benefits. We also highlight gaps in key areas informing benefit sharing in biobanking and draw attention to the need for further empirical research.

Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures

Existing coronavirus named as a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has speeded its spread across the globe immediately after emergence in China, Wuhan region, at the end of the year 2019. Different techniques, including genome sequencing, structural feature classification by electron microscopy, and chest imaging using computed tomography, are primarily used to diagnose and screen SARS-CoV-2 suspected individuals. Determination of the viral structure, surface proteins, and genome sequence has provided a design blueprint for the diagnostic investigations of novel SARS-CoV-2 virus and rapidly emerging diagnostic technologies, vaccine trials, and cell-entry-inhibiting drugs. Here, we describe recent understandings on the spike glycoprotein (S protein), receptor-binding domain (RBD), and angiotensin-converting enzyme 2 (ACE2) and their receptor complex. This report also aims to review recently established diagnostic technologies and developments in surveillance measures for SARS-CoV-2 as well as the characteristics and performance of emerging techniques. Smartphone apps for contact tracing can help nations to conduct surveillance measures before a vaccine and effective medicines become available. We also describe promising point-of-care (POC) diagnostic technologies that are under consideration by researchers for advancement beyond the proof-of-concept stage. Developing novel diagnostic techniques needs to be facilitated to establish automatic systems, without any personal involvement or arrangement to curb an existing SARS-CoV-2 epidemic crisis, and could also be appropriate for avoiding the emergence of a future epidemic crisis.

Guidance for ensuring fair and ethical broad consent for future use. A scoping review protocol

Introduction: Broad consent for future use is the reuse of data and/or samples collected by a study by researchers who may not be affiliated with the original study team for purposes that may differ from the objectives of the original study. Sharing participant-level data and samples collected from research participants facilitates reuse and transparency and can accelerate drug or vaccine development, research findings, and translation. Data reuse and synthesis help prevent unnecessary research, thereby respecting research participants time and efforts and building their trust in the research process. Despite these myriad benefits, data and sample sharing represent a significant investment of time for the team that collected the data or samples, and may present additional risks for research participants, including that of re-identifiability and incidental findings, or for the source community. This scoping review will summarize existing guidance on broad consent for future use and highlight evidence gaps related to the ethical, equitable implementation of broad consent for future use. Methods and analysis: We will apply the Arskey and O'Malley scoping review methodology and best practice as outlined in the Joanna Briggs scoping review guidelines.  The research questions have been identified through a literature review and consultation with subject-matter experts. The systematic search will be conducted in three databases using a tailored search strategy. We will search the reference lists of included articles or related systematic reviews for additional citations. The title-abstract and full text screening and charting the data will be conducted independently by two reviewers. Discrepancies will be resolved by a third reviewer. Results will be summarized in narrative form. Ethics and dissemination: This scoping review summarizes findings from existing publications and grey literature rather than primary data and, as such, does not require ethics review. Findings will be disseminated through an open access publication and webinar.

Dataset decay and the problem of sequential analyses on open datasets

Open data allows researchers to explore pre-existing datasets in new ways. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. We go on to discuss a number of correction procedures that can reduce the number of false positives, and the challenges associated with these correction procedures.

Geneva Health Forum: The Forum of Innovative Practices in Global Health

In the past years, Global Health has interfaced with important challenges related to several dynamic changes. Technological progress, the digital revolution and the emergence of new actors in the field of health, increase the possibility of finding solutions to these unprecedented challenges. Starting from these assumptions, the idea of providing an adequate platform for good management of the health system has flowed into the creation of a meeting place that would allow a wide exchange of information, ideas sharing and proposals for new collaborations: the Geneva Health Forum (GHF). The GHF is a global health conference that aims to promote critical reflections and constructive debates on contemporary global health issues, thus influencing and informing policy formulation with experience from the field. The profile and impact of the Geneva Health Forum has grown year on year, establishing itself as a unique forum, ranging from more traditional sessions to innovative events.

Factors influencing harmonized health data collection, sharing and linkage in Denmark and Switzerland: A systematic review

INTRODUCTION

The digitalization of medicine has led to a considerable growth of heterogeneous health datasets, which could improve healthcare research if integrated into the clinical life cycle. This process requires, amongst other things, the harmonization of these datasets, which is a prerequisite to improve their quality, re-usability and interoperability. However, there is a wide range of factors that either hinder or favor the harmonized collection, sharing and linkage of health data.

OBJECTIVE

This systematic review aims to identify barriers and facilitators to health data harmonization-including data sharing and linkage-by a comparative analysis of studies from Denmark and Switzerland.

METHODS

Publications from PubMed, Web of Science, EMBASE and CINAHL involving cross-institutional or cross-border collection, sharing or linkage of health data from Denmark or Switzerland were searched to identify the reported barriers and facilitators to data harmonization.

RESULTS

Of the 345 projects included, 240 were single-country and 105 were multinational studies. Regarding national projects, a Swiss study reported on average more barriers and facilitators than a Danish study. Barriers and facilitators of a technical nature were most frequently reported.

CONCLUSION

This systematic review gathered evidence from Denmark and Switzerland on barriers and facilitators concerning data harmonization, sharing and linkage. Barriers and facilitators were strictly interrelated with the national context where projects were carried out. Structural changes, such as legislation implemented at the national level, were mirrored in the projects. This underlines the impact of national strategies in the field of health data. Our findings also suggest that more openness and clarity in the reporting of both barriers and facilitators to data harmonization constitute a key element to promote the successful management of new projects using health data and the implementation of proper policies in this field. Our study findings are thus meaningful beyond these two countries.

Broadening horizons: the case for capturing function and the role of health informatics in its use

Background

Human activity and the interaction between health conditions and activity is a critical part of understanding the overall function of individuals. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) models function as all aspects of an individual’s interaction with the world, including organismal concepts such as individual body structures, functions, and pathologies, as well as the outcomes of the individual’s interaction with their environment, referred to as activity and participation. Function, particularly activity and participation outcomes, is an important indicator of health at both the level of an individual and the population level, as it is highly correlated with quality of life and a critical component of identifying resource needs. Since it reflects the cumulative impact of health conditions on individuals and is not disease specific, its use as a health indicator helps to address major barriers to holistic, patient-centered care that result from multiple, and often competing, disease specific interventions. While the need for better information on function has been widely endorsed, this has not translated into its routine incorporation into modern health systems.

Purpose

We present the importance of capturing information on activity as a core component of modern health systems and identify specific steps and analytic methods that can be used to make it more available to utilize in improving patient care. We identify challenges in the use of activity and participation information, such as a lack of consistent documentation and diversity of data specificity and representation across providers, health systems, and national surveys. We describe how activity and participation information can be more effectively captured, and how health informatics methodologies, including natural language processing (NLP), can enable automatically locating, extracting, and organizing this information on a large scale, supporting standardization and utilization with minimal additional provider burden. We examine the analytic requirements and potential challenges of capturing this information with informatics, and describe how data-driven techniques can combine with common standards and documentation practices to make activity and participation information standardized and accessible for improving patient care.

Recommendations

We recommend four specific actions to improve the capture and analysis of activity and participation information throughout the continuum of care: (1) make activity and participation annotation standards and datasets available to the broader research community; (2) define common research problems in automatically processing activity and participation information; (3) develop robust, machine-readable ontologies for function that describe the components of activity and participation information and their relationships; and (4) establish standards for how and when to document activity and participation status during clinical encounters. We further provide specific short-term goals to make significant progress in each of these areas within a reasonable time frame.

Sharing linked data sets for research: results from a deliberative public engagement event in British Columbia, Canada

INTRODUCTION

Research using linked data sets can lead to new insights and discoveries that positively impact society. However, the use of linked data raises concerns relating to illegitimate use, privacy, and security (e.g., identity theft, marginalization of some groups). It is increasingly recognized that the public needs to be consulted to develop data access systems that consider both the potential benefits and risks of research. Indeed, there are examples of data sharing projects being derailed because of backlash in the absence of adequate consultation. (e.g., care.data in the UK).

OBJECTIVES AND METHODS

This paper describes the results of a public deliberation event held in April 2018 in Vancouver, British Columbia. The purpose of this event was to develop informed and civic-minded public advice regarding the use and the sharing of linked data for research with a focus on the processes and regulations employed to release data. The event brought together 23 members of the public over two weekends.

RESULTS

Participants developed and voted on 19 policy-relevant statements. Voting results and the rationale behind any disagreements are reported here. Taken together, these statements provide a broad view of public support and concerns regarding the use of linked data sets for research and offer guidance on measures that can be taken to improve the trustworthiness of policies and process around data sharing and use.

CONCLUSIONS

Generally, participants were supportive of research using linked data because of the value they provide to society. Participants expressed a desire to see the data access request process made more efficient to facilitate more research, as long as there are adequate protections in place around security and privacy of the data.

Data management and sharing policy: the first step towards promoting data sharing

BACKGROUND

Health-related research funders, regulators and journals expect that de-identified individual-level health data be shared widely, with as few restrictions as possible; yet, in reality, the volume of shared data remains low.

MAIN BODY

Health researchers and other data producers are reluctant to share their data unless they are confident that their datasets are of high quality and reliable, and that they are used in accordance with the values and aims of their institutions. We argue that having an institutional, departmental or group data management and sharing policy is the first step towards encouraging researchers and healthcare professionals to share their data more widely. Our paper outlines the elements of a data management and sharing policy, which should include aims consistent with those of the institution as well as with data management procedures, models of data sharing, request procedures, consent models and cost recovery mechanisms. A policy would help an institution, department or group maximise the use of its data and protect the interests of the institution and its members. We base our recommendations on our experience collecting and curating data for large clinical trials conducted in low- and middle-income countries, facilitating the sharing of datasets with secondary users, whilst teaching data management and conducting empirical research on data sharing. Although the fundamentals of a policy are general, the paper is focused on the low- and middle-income country context.

CONCLUSION

We argue that having an institutional, departmental or group data management and sharing policy is the first step in promoting data sharing.

Taking connected mobile-health diagnostics of infectious diseases to the field

Mobile health, or 'mHealth', is the application of mobile devices, their components and related technologies to healthcare. It is already improving patients' access to treatment and advice. Now, in combination with internet-connected diagnostic devices, it offers novel ways to diagnose, track and control infectious diseases and to improve the efficiency of the health system. Here we examine the promise of these technologies and discuss the challenges in realizing their potential to increase patients' access to testing, aid in their treatment and improve the capability of public health authorities to monitor outbreaks, implement response strategies and assess the impact of interventions across the world.

Challenges arising when seeking broad consent for health research data sharing: a qualitative study of perspectives in Thailand

BACKGROUND

Research funders, regulatory agencies, and journals are increasingly expecting that individual-level data from health research will be shared. Broad consent to such sharing is considered appropriate, feasible and acceptable in low- and middle-income settings, but to date limited empirical research has been conducted to inform the design of such processes. We examined stakeholder perspectives about how best to seek broad consent to sharing data from the Mahidol Oxford Tropical Medicine Research Unit, which implemented a data sharing policy and broad consent to data sharing in January 2016.

METHODS

Between February and August 2017 qualitative data were collected at two sites, Bangkok and the Thai-Myanmar border town of Mae Sot. We conducted eighteen semi-structured interviews. We also conducted four focus group discussions with a total of nineteen people. Descriptive and thematic coding informed analysis of aspects of data sharing that are considered most important to inform participants about, and the best ways to explain complex and abstract topics relating to data sharing.

RESULTS

The findings demonstrated that clinical trial participants prioritise information about the potential benefits and harms of data sharing. Stakeholders made multiple suggestions for clarifying information provided about data sharing on such topics. There was significant variation amongst stakeholders' perspectives about how much information should be provided about data sharing, and it was clear that effective information provision should be responsive to the study, the study population, the individual research participant and the research context.

CONCLUSIONS

Effectively communicating about data sharing with research participants is challenging in practice, highlighting the importance of robust and effective data sharing governance in this context. Broad consent should incorporate effective and efficient explanations of data sharing to promote informed decision-making, without impeding research participants' understandings of key aspects of the research from which data will be shared. Further work is required to refine both the development of core information about data sharing to be provided to all research participants, and appropriate solutions for context specific-challenges arising when explaining data sharing.

Sharing health research data - the role of funders in improving the impact

Recent public health emergencies with outbreaks of influenza, Ebola and Zika revealed that the mechanisms for sharing research data are neither being used, or adequate for the purpose, particularly where data needs to be shared rapidly. A review of research papers, including completed clinical trials related to priority pathogens, found only 31% (98 out of 319 published papers, excluding case studies) provided access to all the data underlying the paper - 65% of these papers give no information on how to find or access the data. Only two clinical trials out of 58 on interventions for WHO priority pathogens provided any link in their registry entry to the background data. Interviews with researchers revealed a reluctance to share data included a lack of confidence in the utility of the data; an absence of academic-incentives for rapid dissemination that prevents subsequent publication and a disconnect between those who are collecting the data and those who wish to use it quickly.  The role of the funders of research needs to change to address this. Funders need to engage early with the researchers and related stakeholders to understand their concerns and work harder to define the more explicitly the benefits to all stakeholders.  Secondly, there needs to be a direct benefit to sharing data that is directly relevant to those people that collect and curate the data. Thirdly more work needs to be done to realise the intent of making data sharing resources more equitable, ethical and efficient.  Finally, a checklist of the issues that need to be addressed when designing new or revising existing data sharing resources should be created. This checklist would highlight the technical, cultural and ethical issues that need to be considered and point to examples of emerging good practice that can be used to address them.

The FAIR guiding principles for data stewardship: fair enough?

The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order. The FAIR principles point the way forward for facilitating data sharing more systematically-provided that a number of ethical, methodological, and organisational challenges are addressed as well.

The Sharing of Research Data in the Cell & Tissue Engineering Area: Is It a Common Practice?

The availability of research data sets is an important milestone because it can enhance the dynamics of research. This study aims to analyze the PubMed Central repository to determine the availability and type of raw data sets in Cell & Tissue Engineering journals indexed in Journal Citation Reports. The number and types of files were registered. The main finding of this study is that, beyond the mandatory deposit of data in specific repositories that some journals require, the exchange of data as supplementary material in the Cell & Tissue Engineering journals is not a common practice since researchers are still reticent to do so.

Availability and Use of Shared Data From Cardiometabolic Clinical Trials

BACKGROUND

Sharing of patient-level clinical trial data has been widely endorsed. Little is known about how extensively these data have been used for cardiometabolic diseases. We sought to evaluate the availability and use of shared data from cardiometabolic clinical trials.

METHODS

We extracted data from ClinicalStudyDataRequest.com, a large, multisponsor data-sharing platform hosting individual patient-level data from completed studies sponsored by 13 pharmaceutical companies.

RESULTS

From January 2013 to May 2017, the platform had data from 3374 clinical trials, of which 537 (16%) evaluated cardiometabolic therapeutics (phase 1, 36%; phase 2, 17%; phase 2/3, 1%; phase 3, 42%; phase 4, 4%). They covered 74 therapies and 398 925 patients. Diabetes mellitus (60%) and hypertension (15%) were the most common study topics. Median time from study completion to data availability was 79 months. As of May 2017, ClinicalStudyDataRequest.com had received 318 submitted proposals, of which 163 had signed data-sharing agreements. Thirty of these proposals were related to cardiometabolic therapies and requested data from 79 unique studies (15% of all trials, 29% of phase 3/4 trials). Most (96%) data requesters of cardiometabolic clinical trial data were from academic centers in North America and Western Europe, and half the proposals were unfunded. Most proposals were for secondary hypothesis-generating questions, with only 1 proposed reanalysis of the original study primary hypothesis. To date, 3 peer-reviewed articles have been published after a median of 19 months (9-32 months) from the data-sharing agreement.

CONCLUSIONS

Despite availability of data from >500 cardiometabolic trials in a multisponsor data-sharing platform, only 15% of these trials and 29% of phase 3/4 trials have been accessed by investigators thus far, and a negligible minority of analyses have reached publication.

Future-proofing global health: Governance of priorities

The year 2015 was a significant anniversary for global health: 15 years since the adoption of the Millennium Development Goals and the creation of the Global Alliance for Vaccines and Immunization, followed two years later by the Global Fund to Fight AIDS, TB and Malaria. 2015 was also the 10-year anniversary of the adoption of the International Health Regulations (May 2005) and the formal entering into force of the Framework Convention on the Tobacco Control (February 2005). The anniversary of these frameworks and institutions illustrates the growth and contribution of 'global' health diplomacy. Each initiative has also revealed on-going issues with compliance, sustainable funding and equitable attention in global health governance. In this paper, we present four thematic challenges that will continue to challenge prioritisation within global health governance into the future unless addressed: framing and prioritising within global health governance; identifying stakeholders of the global health community; understanding the relationship between health and behaviour; and the role of governance and regulation in supporting global health.