Introduction

Malaria diagnostics are a key tool in controlling and eliminating malaria, a significant cause of morbidity and mortality, particularly among children in sub-Saharan Africa [1, 2]. Despite the World Health Organization’s recommendation to test all suspected malaria cases before treatment, a significant gap remains, with only half of febrile children in these regions receiving appropriate malaria testing [1]. Beyond their role in diagnosis to prevent disease progression, sensitive and affordable diagnostic tools are crucial for tracking control and elimination efforts [3]. Current diagnostic methods, primarily rapid diagnostic tests and microscopy, are essential but have limitations that impact treatment and policy decisions [2]. Rapid tests may lack accuracy due to changing parasite genetics and low-density infections, potentially resulting in false negative and false positive results [2, 4, 5]. Additionally, microscopy requires robust infrastructure and skilled technicians. To overcome the limitations of these widely used diagnostic approaches, there is an increasing need for more sensitive and specific diagnostic methods [2, 3, 6]. This necessity is driving ongoing innovation efforts. Despite progress, the urgent need for improved malaria diagnostics remains, underlining their importance in supporting effective malaria control and elimination strategies [3, 7].

In the broader context, access to high-quality diagnostics is essential for achieving universal health coverage [8]. The COVID-19 pandemic highlighted the vital role of diagnostics in healthcare, yet they often receive less attention, funding, and action compared to pharmaceuticals. This disparity is especially marked in resource-constrained settings where essential diagnostics are frequently unavailable, unaffordable, or unsuitable [9–11]. Initiatives like the WHO Essential Diagnostics List, the 2021 Lancet Commission on Diagnostics, and the 2023 World Health Assembly resolution have been established to strengthen diagnostic capacity and improve their equitable delivery [10, 12, 13]. These efforts align with the 2030 Sustainable Development Goals, specifically target 3.3, highlighting the importance of access to high-quality diagnostic tools in combating diseases like malaria [14].

The pathway from the conception of a diagnostic tool to its widespread adoption is a complex process, involving multiple stages and spanning global and national levels. The process involves a diverse range of stakeholders, including industry, governments, national and international organisations, funding bodies, regulatory authorities, researchers, healthcare providers, and end-users. Further, most malaria-endemic countries rely heavily on external funding and support for malaria control, making entities like The Global Fund to Fight AIDS, Tuberculosis and Malaria (Global Fund), the WHO, and other agencies influential in shaping the pathway [2, 15]. Each stakeholder has distinct goals and performs a range of activities to achieve these goals. Understanding and mapping this complete process is essential for guiding the development and implementation of effective malaria diagnostic tools [16]. While such pathways have been outlined for other health areas, a common framework for malaria diagnostics that captures the varied goals and tasks of all stakeholders is not readily available [16–18]. Developing this framework is not only beneficial in identifying key stakeholders but also in understanding the entire diagnostic pathway and its interconnected activities. This understanding is key to identifying potential bottlenecks, considering the sequencing of stages/activities to optimise the overall process, and ultimately improving the effectiveness and accessibility of malaria diagnostics [11, 16–19].

The malaria diagnostic pathway depends on a broad spectrum of evidence to support informed decision-making throughout the development, selection, and deployment of diagnostic tools [20]. Each stage of this pathway likely has unique evidentiary needs, influencing the types of evidence needed, its sources, and how it is used. Additionally, what constitutes appropriate evidence use may vary among stakeholders, shaped by their individual logic and goals [21]. For example, diagnostic test manufacturers might use malaria epidemiological data to guide their business strategies, while national malaria control programmes may use similar data to inform budgeting and resource allocation [16, 21].

Despite the critical role of evidence, reliable data is often limited, affecting informed decision-making across the diagnostic pathway [11]. The Lancet Commission identified this lack of data for diagnostics as a significant challenge requiring attention [10]. To address this, the Commission calls for improved data collection and more effective use of various types of evidence, including data on affordability, test performance, patient impact, as well as the broader operational structures, including workforce, infrastructure, supply chain management, and regulatory frameworks [10]. A fundamental initial step in tackling these challenges involves identifying the varied types of evidence used along the pathway. This process involves understanding how stakeholders perceive this evidence, recognising gaps, such as in availability or quality, and identifying barriers to effective evidence generation, sharing, and use.

In this paper, we address knowledge gaps by developing a malaria diagnostic pathway and examining the types and attributes of the data and evidence that inform activities across the pathway. We introduce a diagnostic framework mapping the key phases and tasks in the development and implementation of a malaria diagnostic product. This pathway builds on existing frameworks and incorporates expert insights, covering both global and national activities. We then present the results of a stakeholder survey involving key actors across the stages of the malaria pathway. Using the activities outlined in the pathway, we report on the types of evidence stakeholders use and their perceptions of its appropriateness, availability, and quality. We identify gaps in stakeholders’ abilities to generate and use evidence effectively, focusing on the barriers to accessing high-quality and relevant evidence, and propose solutions to improve evidence generation and dissemination across the malaria pathway. Our findings are intended for a broad audience, including policymakers, researchers, and industry professionals, offering insights to improve evidence use and the overall effectiveness of the malaria diagnostic pathway.

Methods

The study has two main objectives related to improving malaria diagnosis: i) to develop a diagnostic framework for malaria by identifying and mapping key activities from product innovation to delivery, and ii) to explore the types of evidence and data that inform these activities along the pathway, and identify gaps to improve the availability and quality of this evidence.

Results

Development of a malaria diagnostic pathway

Our review identified several frameworks for the development and adoption of diagnostics [11, 16–19, 26–28]. These frameworks focus on different contexts such as low-resource or global settings [16, 19, 28], point-of-care diagnostics [17], and specific diseases like tuberculosis [18, 26, 27]. These typically adopt a stage-gate model, dividing the process into distinct stages with decision points that guide progression to the next phase. The frameworks are largely similar in core stages, with some variations in their depiction, including differing terminology and breakdown of certain stages. These core stages include needs assessment, feasibility, product development and validation, regulatory approval, and product launch. Frameworks tailored to low-resource settings and tuberculosis often feature specialised activities for global stakeholder engagement in technology development and rollout, such as product development partnerships, WHO prequalification, and the involvement of global market shaping actors [16, 18, 26]. S2 Text provides an overview of these identified frameworks. We did not identify a framework specifically addressing malaria diagnostics.

To address this gap, we designed a malaria diagnostic pathway, informed by these existing frameworks and expert input. Table 1 presents this pathway, featuring six major stages and 31 associated activities. Our pathway aligns with the major stages found in existing frameworks but is tailored to malaria’s epidemiological and healthcare context, incorporating activities of global stakeholders identified in frameworks focused on low-resource settings [16, 18, 26]. Additionally, our framework integrates broader health systems features, including policy activities (e.g., product selection, guideline development [16, 18, 26]), education and training [18], advocacy [16, 18], and health system and laboratory capacity development, which are not consistently found in other pathways.

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Table 1. Malaria diagnostic pathway with associated activities by stage.

https://doi.org/10.1371/journal.pgph.0002957.t001

The pathway begins with the Needs assessment stage, establishing technology requirements and stakeholder engagement, forming the foundation for subsequent stages. Based on these findings, Feasibility, development, and validation follows, involving an iterative process to develop and optimise the technology, aligning with stakeholder needs and feedback. This is followed by the Approvals and manufacturing stage, focusing on international regulatory approvals, including WHO prequalification, and production scale-up. Preparation for launch involves global activities to support uptake of the tool, running parallel to in-country demonstration projects. Adoption and scale-up is aimed at integrating the tool effectively into healthcare systems. Finally, the Surveillance and impact measurement stage monitors implementation quality and optimises delivery strategies. While presented sequentially, the process is cyclic and iterative in practice, reflecting a continuous process of evaluation, adaption, and improvement. To increase efficiency, certain stages, like Preparation for launch, should ideally overlap and run concurrently with others, such as Adoption and scale-up, ensuring rapid and effective implementation.

Stakeholder perspectives on data and evidence needs

A total of 113 individuals consented to participate in the survey (Table 2). Respondents were mainly active in the Africa region and spanned a range of sectors, including academia, non-governmental organisations, international organisations, governmental bodies, healthcare professions, and industry representatives. Academia had a strong representation, accounting for 39% of respondents. All stages of the diagnosis pathway were represented in the sample, with most respondents involved in activities in more than one stage.

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Table 2. Characteristics of the survey respondents (n = 113).

https://doi.org/10.1371/journal.pgph.0002957.t002

Respondents utilised a wide range of data and evidence sources, from local context-specific data to global reports (Table 3). Both generic and specific sources were highlighted, with many being utilised across multiple stages. Commonly cited evidence types included epidemiological data, routine and operational data on case and testing numbers, health facility surveys, effectiveness and cost-effectiveness data, national plans, World Malaria Reports, and other global reports and guidelines (e.g., from the Global Fund, the Foundation for Innovative New Diagnostics [FIND], and WHO). Certain sources were identified as more stage-specific, such as WHO and FIND target product profiles (TPPs) (Needs assessment and Feasibility, development, and validation), manufacturer’s cost of goods data (Approvals and manufacturing), and pharmacovigilance data (Surveillance and impact measurement). Data sources included published literature, Health Management Information Systems [HMIS], health ministries and national malaria programmes, global organisations, and research institutions. In addition to publicly available data, many respondents also relied on self-generated data and significantly on informal channels of information, such as feedback and evidence shared through conversations, meetings, and discussions with colleagues, experts, donors, regulatory authorities, and global organisations (e.g., Global Fund and WHO).

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Table 3. Types of evidence used across the malaria diagnostic pathway.

https://doi.org/10.1371/journal.pgph.0002957.t003

Fig 1 presents the respondents’ perceptions of the four evidence attributes across different stages of the malaria diagnostic pathway. Overall, most respondents believed the evidence requirements for their activities were clear, with 58%-76% somewhat or strongly agreeing across the stages. The survey also indicated that most respondents believe the available data and evidence resources met their needs (47%-73% across the stages) and were accurate and reliable (47%-69%).

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Fig 1. Survey findings for the four key attributes across the different pathway stages.

https://doi.org/10.1371/journal.pgph.0002957.g001

The Approvals and manufacturing stage consistently showed higher levels of disagreement across all attributes, with 37%-47% of respondents indicating some level of disagreement, though this stage had a smaller sample size (n = 10 respondents). Conversely, evidence attributes for stages including Needs assessment, Feasibility, development, and validation, Preparation for launch, and Adoption and scale-up were more favourably perceived.

A consistent area of concern across all stages was the public and free availability of data. Between 21%-47% of respondents across the stages at least somewhat disagreed with this aspect. Data from Fig 1 is available in S3 Text.

Respondents identified several challenges and opportunities related to effective generation, sharing, and application of data and evidence across the malaria diagnostic pathway (Table 4). These were classified into four broad areas.

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Table 4. Summary of challenges and opportunities to improve the availability of evidence across the malaria diagnostic pathway.

https://doi.org/10.1371/journal.pgph.0002957.t004

1) Stakeholder collaboration.

A common theme among respondents across all stages was the desire for better data and evidence sharing, cooperation, and communication among stakeholders. For instance, one respondent stressed that “country partners implementing these strategies must communicate and share experiences regularly” [government; stages 1,5,6]. Another voiced frustration about researchers not adequately engaging with national malaria programmes: “too many rich world based researchers who don’t spend enough time working day-by-day with national malaria programs to develop findings that are actually used” [product development partnership/implementation partner; stages 2–6]. Poor coordination was reported to lead to siloed data, lack of cohesive action, evidence gaps, and missed opportunities for data integration into decision-making processes. To address this, respondents advocated for mechanisms to improve collaboration for early stages of diagnostic development, with one respondent recommending the creation of “a forum where all or most stakeholders are able to openly share plans” [government; stages 1,2,5,6].

Many respondents underscored the need for greater emphasis on patients’ and end-users’ needs and perspectives across all stages during the development and implementation of diagnostic tools. They identified that ineffective collaboration with these groups hinders the collection and utilisation of essential data. One respondent advocated for improved dialogue with intended users, stating: “more conversations with intended users and patients need to be brought into every stage of the process, but it’s hard to get donors to fund this” [implementation partner; stages 2–6]. Another sought “clearer information on user needs and expectations” [academic; stages 1,2,6], to better integrate these considerations into the diagnostic development process.

2) Data availability.

Several respondents emphasised the need for more, and better quality, data to inform their activities across the malaria diagnostic pathway. They expressed concern over the lack of available data necessary for certain activities or decisions: “often data required along the pathway are not available and need to be collected before certain activities can start or decisions made” [government; stages 1,5,6]. Respondents called for more reliable evidence on a range of aspects including local epidemiology, pricing, procurement, test consumption, scientific experimental data, pharmacovigilance, and program/intervention costs and cost-effectiveness.

The need for more detailed data was also emphasised, evident in one respondent’s wish for “more data at facility or CHW [community health worker] level; what do they see as shortcomings or limitations of the tools available” [international NGO; stages 1,2,3,5,6]. The capacity to generate operational and technical data was also a concern: “economic evaluations are a serious handicap in evidence to drive policy … capacity in operational research is also needed” [implementation partner/laboratory scientist; stages 5,6], suggesting the need for investments in capacity building for data collection, analysis, and use.

There was a call for better public availability and sharing of data and datasets from routine and research activities, with solutions including open-access publishing and the use of data repositories. Respondents suggested that such data could inform activities directly or be used secondarily to generate further evidence. For available data, they desired a better understanding of limitations: “for each data source, sufficient information to determine limitations of methods used to generate the data” [government; stages 1,5,6]. Calls for greater transparency were also evident, with requests for insight into failed tests, diagnostic trials, industry secrets, and access to unpublished data. One respondent recommended a “single virtual location where all these info on the pathways and how to implement them are situated” [international NGO/academic/laboratory scientist; stages 1,2,3,6].

Finally, some respondents reported challenges concerning the timeliness of data and evidence for decision-making and called for mechanisms to improve evidence sharing and dissemination. Specific issues mentioned included slow regulatory processes and delayed transfer of global evidence to the national level, for example, “it often takes many years before signals of diagnostic failure to change policy and the introduction of new tools is a long and laborious process” [international NGO/healthcare professional; stages 1,2,5,6].

3) Standardisation.

Participants reported issues related to standardisation of protocols and data requirements, particularly in the context of laboratory validations and clinical trials (i.e., stage 2: feasibility, development, and validation). For instance, one respondent stated: “no standardised protocols for field evaluation of diagnostics (e.g., level of blood screen by PCR) exist” [academic; stages 1,2,6]. They also underscored the need for clarity about the aspects of the test that need characterisation and the precise data and evidence required, especially data crucial for regulatory approvals.

4) Funding.

Funding constraints was frequently highlighted as a significant barrier, impacting both the generation and analysis of key data for each step on the malaria diagnostics development pathway, as well as the dissemination and utilisation of evidence-based practices. Respondents discussed the difficulty of securing funding for basic research: “funding for basic research which underpins each step is not available. There is no funding for basic research on diagnostics that I can secure or even apply for” [academic; stages 1,2] and advocated for increased funding from a range of sources.

Of note, while many respondents highlighted challenges, a few commented that the data available for malaria was already sufficient for their purposes and emphasised that “malaria diagnostics is much better documented than most other diseases, other than HIV and tuberculosis” [academic; stage 4].

Discussion

This study sought to map the malaria diagnostic pathway, highlighting key data and evidence needs at each stage and stakeholder perceptions of this evidence. While the main stages of our developed pathway echo existing frameworks, a malaria-specific pathway offers distinct advantages by integrating activities tailored to the specific challenges and context of malaria diagnosis [11, 16–19]. For instance, it integrates priority activities like WHO prequalification and endorsement processes–pivotal given the limited or complex diagnostics regulatory frameworks in many resource-constrained settings [16, 29]. It also promotes stakeholder collaboration, promoting better alignment with global and national malaria eradication and control efforts, and engages key players, like The Global Fund, WHO, and FIND, who provide vital financial, technical, and strategic support [16]. By focusing on malaria, the framework structures the interconnected activities essential to the malaria diagnostic process, serving as a targeted tool for planning, coordination, and action across different stages and sectors.

Expanding beyond malaria, our framework has broader potential applicability, especially for neglected tropical diseases (NTDs) and other high-priority pathogens with critical diagnostic challenges (e.g., Chagas disease, leishmaniasis, lymphatic filariasis, etc) [30–33]. The overarching challenges our study highlights, such as data scarcity and funding issues, are not exclusive to malaria and may be amplified for NTDs due to their limited attention and resources compared to the “big three” infectious diseases [34, 35].

The survey identified both strengths and weaknesses in data and evidence along the malaria diagnostic pathway. Respondents’ perceptions of the evidence were largely positive during stages like Feasibility, development, and validation, and they emphasised the good availability of evidence for malaria diagnostics compared to other diseases. The Approvals and manufacturing stage emerged as particularly challenging, with the highest rates of disagreement across all data attributes. Factors potentially contributing to this are complex regulatory processes and the reliance on confidential and proprietary information during this stage [36]. To addresses these issues, strategies such as financial incentives (e.g., grants), non-financial incentives (e.g., industry recognition or priority status in regulatory processes), or standardised data sharing agreements might be needed to improve data availability and transparency during this stage.

Addressing the key data challenges identified requires innovative solutions and concerted efforts across multiple sectors. Potential solutions, identified by stakeholders and the broader literature, are presented in Table 4 and include enhanced stakeholder coordination, improvements in data generation, availability, and sharing, and improved sustainable funding.

Effective stakeholder coordination from early development phases can bridge knowledge gaps, foster data sharing, and facilitate more informed decision-making, thereby accelerating diagnostics development and use. Bridging collaboration gaps can be achieved through forums or strategic partnerships focused on sharing plans, seeking feedback, and addressing evidence gaps. The GeneXpert TB test development and the Digital Diagnostics for Africa Network are examples of successful cross-collaboration models that bring together stakeholders from different fields and pathway stages to support evidence generation and sharing [37–39]. Additionally, a centralised resource hub for malaria diagnostics could improve transparency and collaboration by centralising research, guidelines, and data sources. The TB Diagnostics Critical Pathway website serves as an analogous model, illustrating the TB pathway and consolidating relevant resources, data, and evidence for each phase [18]. Beyond formal structures, our study highlights the important of informal networks and trusted personal collaborations as effective communication and evidence exchange channels, as observed in other health sector studies [40, 41]. Encouraging meetings, conferences, and reflective spaces for individuals at different stages of the pathway can serve as effective mechanisms for providing or requesting evidence.

Gaps in high-quality data can be mitigated by investing in capacity-building initiatives for data collection, analysis, and utilisation. A key intervention would be promoting the widespread adoption and improved use of routine electronic HMIS to obtain quality and timely real-world health and operational data. Investments in these systems, as well as the supporting associated infrastructure and personnel, can deliver comprehensive data on disease burden, service utilisation, and test performance, informing the targeted development and implementation of diagnostic tools tailored to the population and health system’s specific needs [10]. The District Health Information Software (DHIS2) platform serves as an exemplar, widely adopted in many countries [24]. Further, as diagnostic research, development, and manufacturing hubs gradually expand to include more middle- and low- income settings, there are new opportunities to ensure that the data collected on the diagnostic pathway reflect the needs of the target populations the diagnostics are designed to serve [42].

Promoting data and evidence sharing can support accessibility, enable transparency and validation of findings, and encourage the reuse of data for further research [43, 44]. Strategies include promoting open-access publishing and the use of online data repositories and registries (e.g., Figshare or Harvard Dataverse) [20, 43]. These efforts should be accompanied by progressive data management and sharing policies [45]. Recent advancements in data sharing policies, with mandates on using public data repositories for publication in certain journals and funding opportunities dependent on open-access publishing and a commitment to data sharing, highlight progress in this area [43, 46, 47]. However, these mechanisms remain underutilised. Concerns over loss of exclusivity, fears of challenging interpretations, data protection issues, and data formatting hurdles may discourage researchers from sharing data [43, 48]. Collective efforts from funders, industry, research institutions, researchers, and publishers are required to encourage an ecosystem where open and free data access is not only feasible but actively encouraged and rewarded.

Central to data sharing are efforts to champion diverse open-access resources, like the Global Health Data Exchange (for disease burden), the Malaria Atlas Project (for malaria epidemiology), PlasmoDB (for plasmodium informatics), and G-FINDER (for research and development investments) [49–52]. Expanding these open data initiatives across the diagnostic pathway could substantially improve data accessibility and ensure an evidence-based approach to diagnostic development. While there is consensus on the value of an open approach to data sharing, the extent to which the malaria community should leverage generalised platforms or develop malaria-specific ones remains a topic of discussion. We propose that a broader, more inclusive, effort would gain more traction.

Notably, available diagnostic databases frequently lack the comprehensiveness of their pharmaceutical counterparts. For example, while clinical trials registries provide comprehensive details on pharmaceutical trials, diagnostic accuracy studies are rarely registered [53]. Advocating for the mandatory, prospective registration of diagnostic trials can support a more thorough understanding of diagnostic efforts, amplifying transparency and reporting, and crucially encouraging the transparent reporting of negative results. Prioritising access to relevant evidence across the entire pathway, including data not typically published in journals and less favourable findings, is essential for improving accessibility and promoting an evidence-based approach to malaria diagnosis.

Inadequate funding also emerged as a key challenge, restricting essential data collection, analysis, and dissemination [10, 54, 55]. This challenge is accentuated for diseases like malaria and many NTDs that primarily affect lower-income settings. In these contexts, the demand for tailored diagnostic solutions–such as affordable rapid tests rather than cost-intensive platforms–is pressing, yet the modest market size often deters commercial diagnostic manufacturers from investing. Addressing this challenge necessitates advocacy for increased and diverse funding sources, including from donors, international organisation, and governments, specifically targeting the development, implementation, and evaluation of appropriate diagnostic tools for resource-constrained settings and data and evidence generation, sharing, and utilisation along the pathway. Strategies like dedicated funding mechanisms, innovative financing models, and public-private partnerships can incentivise stakeholders to contribute to the data ecosystem and overcome these challenges. For instance, prize funds for diagnostic data generation, similar to those that incentivise diagnostic development, offer a potential model [56].

While the study provides valuable insights, certain limitations should be considered when interpreting the findings. First, the survey could be subject to response bias, and its low response rate with overrepresentation from academia may not capture the full range of perspectives and experiences in the global malaria diagnostic landscape. Stages with fewer respondents, such as Approvals and manufacturing and Global preparation for launch, may be particularly susceptible to bias; further perspectives from stakeholders involved in these stages would be beneficial. The study was part of an explorative process and was not expected to represent an exhaustive summary of all data challenges. Second, the self-reported nature of the data could lead to biases like recall bias. Finally, focusing on a malaria-specific pathway may limit the generalisability of our findings across other diseases. Notably, our findings align to those suggested by an online expert panel in a study on global health diagnostic solutions, suggesting broader applicability of our findings [17]. The study did not investigate exactly how stakeholders use different types of evidence to inform decisions and activities, nor did it explore ways to optimise this, which represent key areas for future research, as seen in other malaria and health policy studies [21, 57–60].

This study offers valuable insights into the malaria diagnostic pathway, highlighting key challenges and direction for future efforts to improve the scope and availability of quality data and evidence across the pathway. Strengthening the generation and use of data and evidence to inform diagnostic development and policy requires a multifaceted approach, focused on improving the availability and accessibility of diverse and rich data, supported by effective stakeholder collaboration and sustainable funding. Overcoming these challenges and improving access to more diverse evidence forms is increasingly important as new and more innovative diagnostic tools are developed. Leveraging frameworks like the one proposed in this study can help identify data gaps and guide the evidence-based innovation and implementation of diagnostic tools. The framework and challenges identified has implications not only for malaria but can also serve as a model to be adapted for other diseases, especially NTDs, which face similar, if not more significant challenges.

Supporting information

Acknowledgments

We would like to thank the survey respondents for generously sharing their insights.