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      Diagnostic tools for soil-transmitted helminths control and elimination programs: A pathway for diagnostic product development

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          Abstract

          Introduction The 2020 Roadmap goals endorsed by the World Health Organization (WHO) for soil-transmitted helminths (STHs) (Ascaris lumbricoides, Ancylostoma duodenale, Necator americanus, Trichuris trichiura) are focused on mass drug administration (MDA) of anthelmintics to control morbidity associated with moderate- and heavy-intensity infection [1]. As the STH community approaches the 75% coverage target for preschool- and school-aged children, there is increasing interest in exploring post-2020 goals that transition from simply monitoring program coverage to strengthened monitoring of a program’s impact on transmission of infection and determining whether enhanced MDA can break STH transmission with minimal risk of recrudescence [2–4]. Diagnostics play a critical role in guiding both the deployment of existing STH program resources and the implementation and evaluation of STH intervention strategies. Currently used coproscopic methods to detect and quantify STH-specific eggs, such as the Kato-Katz method, have practical advantages; test kits are inexpensive and relatively easy to perform in low-resourced field settings. They also have significant disadvantages, including moderate labor costs, lower than optimal sensitivity, and poor reproducibility in most program settings. Several academic and small-business efforts continue to develop tools with improved diagnostic performance [5–7]. However, an objective assessment on the value proposition offered by these tools has been complicated, as the diagnostic needs of a multiphased STH program have not been defined [8]. This report shares a user-centered framework developed by a diverse group of key opinion leaders convened over the past year by the Bill & Melinda Gates Foundation to define circumstances in which population-level diagnostic data could guide an STH program manager’s decision to transition a program to the next phase. The use-cases and companion target product profiles (TPPs) are intended to provide the community with a pathway for the research, development, evaluation, and implementation of diagnostic tools designed for STH programs. This framework can also be used to prioritize research or product development resources based on immediate and anticipated program needs. Current landscape of STH program diagnostics The number of adult STH worms harbored by an individual determines both their risk of morbidity and contribution to overall transmission [9]. Worm expulsion studies required to quantify worm burden have suboptimal accuracy, are laborious, and are rarely done. Thus, STH programs employ indirect methods to infer worm burden, such as microscopy-based technologies for visual identification and quantification of STH-specific eggs from a stool sample. WHO recommends the use of the Kato-Katz method, a low-cost, simple, and standardized tool that provides sufficient sensitivity for morbidity control programs aiming to reduce prevalence of moderate- and heavy-intensity infections to less than 1% [10]. A key limitation of the method is its suboptimal sensitivity, particularly in low transmission settings where egg counts are typically low [11]. Alternatives to Kato-Katz include the Mini-FLOTAC and McMaster methods, although these tools lack WHO recommendations for programs and thus have been limited to research use [5, 11–13]. Recent technology development efforts have also focused on improved analytical sensitivity, such as molecular assays [6, 14–17] and enhanced visualization of helminth eggs [7, 18]. Another early area of investigation includes serological and urine-based measurements [19, 20]. However, all these methods potentially incur additional costs-per-test and resource requirements for STH programs that need to be considered, relative to the benefits of enhanced efficiency and accuracy [21]. Table 1 highlights other opportunities to improve coproscopic methods. 10.1371/journal.pntd.0006213.t001 Table 1 Limitations and opportunities for improving coproscopy, with the Kato-Katz method as a predicate technique. Limitations    • Low sensitivity for very low-intensity infections    • Variable test results impact prevalence measurements, particularly if eggs are highly clustered or in low abundance    • Intra-individual variation in egg excretion during the day and between consecutive days    • Operator-based variability in test results    • Exposure of operator to infectious agents in stool    • Need to process stool samples quickly after collection, particularly for hookworm analysis Opportunities for improvement    • Integrated quality control/quality assurance for preparation (homogenization) and analysis of stool samples    • Increased throughput    • Electronic connectivity, test results accessible for remote interpretation Starting from the end: STH diagnostic use-cases and TPPs Diagnostics are required at different decision points in STH programs, ranging from mapping endemic geographies to monitoring and evaluation, assessing whether MDA can be stopped, and post-MDA surveillance [22]. Use-cases depict the link between a specific program decision to the interpretation of a diagnostic test result, regardless of the technology or method used to make the measurement [8]. A group of key opinion leaders represented the voice of the diagnostic user by describing and predicting scenarios faced by STH programs, creating a series of problem statements and decisions that each can be addressed by a hypothetical diagnostic. Each solution is further detailed in a TPP as a list of technical characteristics, such as type of measurement and implementation requirements. One practical use of a TPP is to provide an objective framework for evaluating existing technologies and innovations to determine opportunities for product development (Table 2). The breakdown of an STH program into diagnostic use-cases also ensures that research and product development resources are aligned with program time lines by considering global progress of STH programs and goals (controlling morbidity, interruption of transmission), maturity of technology landscape, and time lines when technologies will be needed. This framework is not intended to prevent the development of a single technology that addresses multiple use-cases; however, a platform must meet the requirements described in each of the various TPPs. 10.1371/journal.pntd.0006213.t002 Table 2 Planning processes for product development. Output Objective Stakeholders responsible for definition Use-cases • Requires understanding of program workflow; infrastructure; resources to identify needs, preferences, limitations for implementation• Define link between phase of program and criteria, with implications of diagnostics-based decision• Frame epidemiological/biological characteristics• Identify stakeholders (data users, test implementers, policy, payors) • Programs/implementers• WHO STH program guidelines or recommendationsWith input from:• Research (laboratory, epidemiology, field) TPP • Requires defined use-case• Define “must-have” criteria for a diagnostic to meet program needs for each use-case• Assess feasibility of meeting TPP requirements via landscape of existing research/methods/technologies/available patient specimens• Define evaluation criteria and methods for assessing new products and regulatory pathway• Account for cost-effectiveness, scalability, manufacturability • Programs/implementers• Research• Product developmentWith input from:• WHO STH program guidelines or recommendations• Regulatory Product development pathway • Requires use-case and TPP• Define regulatory pathway• Define requirements in accordance with existing or new STH program policies/guidelines/recommendations• Define pathway for translating existing reagents/methods into prototype• Define verification criteria that prototype meets TPP to lock/freeze design• Define validation criteria to evaluate adherence to TPP in actual operating conditions• Define product launch plan• Define payors/donors for program’s diagnostic infrastructure• Define user-support, quality assurance, monitoring, supply chain requirements• Define manufacturing and distribution plans • Research• Product development• Regulatory• WHO STH program guidelines or recommendationsWith input from:• Country programs• Representatives from Ministries of Health• Program donors• Implementing nongovernment organizations Abbreviations: STH, soil-transmitted helminth; TPP, target product profile. Previous works by Solomon et al. [22] and Hawkins et al. [23] have provided high-level TPPs. This report builds on these efforts by providing a more comprehensive framework that links program decision points to detailed use-cases and TPPs. The diagnostic end user is the STH program manager who requires a population-wide diagnostic assessment to determine the transition of a program to the next planned phase. This introduces a unique challenge for developing diagnostic TPPs for population-based intervention programs, as performance requirements for individual-level assays are in context of decisions informed by population-level indicators. Following previous work [22], four broad decision points were used to categorize each use-case against a hypothetical reduction in population-level infection resulting from program intervention, as shown in Fig 1. Embedded within this illustration is a spectrum of program decisions to initiate, continue, suspend, or transition to the next planned program phase, in the context of a program’s goal of morbidity control or elimination of transmission. Those decisions that are hypothetically guided by diagnostic test results are described in the algorithm shown in Fig 2 and form the basis of the use-case categories: use-case #1. Determine STH transmission and identify type of MDA, use-case #2. Assess progress against program goals, use-case #3. Confirm a decision to stop intervention and transition to surveillance, use-case #4. Verify sustained break in transmission. 10.1371/journal.pntd.0006213.g001 Fig 1 Hypothetical prevalence curve (dots) for a successful STH elimination program, overlaid with program phase (diamond for transition points) and diagnostic use-cases. MDA, mass drug administration; STH, soil-transmitted helminth. 10.1371/journal.pntd.0006213.g002 Fig 2 Diagnostic use-cases, described by program decision algorithm. Dashed box indicates a decision not described under current WHO guidelines for controlling STH morbidity but that may be important for a program aiming to eliminate transmission of STH. Dx, diagnostic; KK, Kato-Katz; MDA, mass drug administration; SAC, school-aged children; STH, soil-transmitted helminth. An additional level of detail is provided in the spreadsheet within the supplementary materials of this article (S1 File). Several factors were considered in prioritizing a diagnostic that confirms a break in transmission (use-case #3). There is strong interest in leveraging the successes of increased MDA coverage to further reduce STH transmission beyond the level of morbidity control toward interruption of transmission [2, 3]. Achievement of this goal would allow programs to stop regular MDA with minimal risk of recrudescence, but there currently lacks a reliable tool to confirm this end point. However, as discussed later, evidence from research is needed to develop a rigorous TPP for such a diagnostic. On the shorter term, there may be opportunities to strengthen STH programs by providing access to technologies that are superior to the Kato-Katz method (Table 1) for monitoring impact on transmission (use-case #2) [24]. The development of a TPP for use-case #4 was felt to be premature and not to be pursued until evidence demonstrates that a strategy for sustained interruption of transmission is feasible and can be scaled for STH programs. The biomarker landscape that would meet this context of use is also at its early stages, and resources required to implement the scale and coverage for this type of surveillance infrastructure need to be further defined [25]. Across all use-cases is an option to integrate and leverage the resources of other public health programs. For instance, many STH programs are integrated with schistosomiasis control efforts due to co-endemicity [8, 26], with the Kato-Katz method also able to detect infection by Schistosoma mansoni and S. japonicum. Non–stool-based biomarkers may provide opportunities for simultaneous detection of infection by S. haematobium. Post-elimination surveillance would likely leverage multiple disease surveillance programs through centralized laboratory analysis. Use-case #1—Initiate and determine type of MDA The assay described in this use-case provides results that identify populations that warrant MDA and determines the frequency of MDA and the frequency of future monitoring. These decisions are currently based on measurements of two parasitological indicators in school-aged children: overall prevalence of any STH infection and proportion of individuals harboring an infection of moderate to heavy intensity [27]. The first indicator relies on aggregated results from individual-level diagnostic tests to determine whether the prevalence of STH infection is below 20%, exceeds 20%, or is 50% and above. These thresholds have been defined by WHO and are based on fecal egg counts (FECs) derived from a Kato-Katz measurement to guide an STH control program in not providing MDA or providing annual or biannual MDA. Because these programs are currently focused on controlling morbidity from moderate- to heavy-intensity infection, there are no recommendations for prevalence less than 20%, nor is the Kato-Katz method suitable for measuring low FEC. However, a “low transmission” category was included in the population stratification (Fig 2) in the hypothetical event that STH elimination programs would be initiated in lower transmission settings and that a tool that detects lighter infections would be available. To meet the needs of the second indicator, a test provides individual-level quantitative results that are combined to estimate the proportion harboring moderate to heavy intensities of infection by any STH, thresholds currently based on species-specific FEC (Table 3, [1]). These test results also provide a baseline measurement for monitoring the impact of an intervention, as described in latter use-cases. 10.1371/journal.pntd.0006213.t003 Table 3 Classes of intensity, based on Kato-Katz measurements [1]. STH Individual intensity of infection (in eggs per gram of stool) Light Moderate Heavy Ascaris lumbricoides 1–4,999 5,000–49,999 ≥50,000 Trichuris trichiura 1–999 1,000–9,999 ≥10,000 Hookworms 1–1,999 2,000–3,999 ≥4,000 Abbreviation: STH, soil-transmitted helminth. Use-case #2—Assess progress against program goals This use-case applies to STH programs that have initiated intervention and seek to evaluate progress in reducing prevalence and intensity of infection [28]. By comparing population-level results from previous or baseline measurements, programs that meet their milestones would continue the intervention strategy as planned. However, an under-performing program would conduct additional evaluations to determine potential causes, such as assessments of population migration, environment, workforce, drug quality, treatment adherence, and anthelmintic drug resistance. Decisions made from these quantitative tests are dependent on the type of program and this use-case was divided into two. Morbidity control programs are initiated in moderate- to high-prevalence settings and rely on two indicators, overall prevalence of infection by any STH and the proportion of individuals with moderate and heavy infections (e.g., use-case #2A, as described in S1 File). An STH program targeting interruption of transmission would initiate or continue efforts in lower transmission settings and would be focused solely on monitoring the reduction of overall prevalence (e.g., use-case #2B), because it is unlikely that there will be any moderately to heavily infected individuals [29]. The Kato-Katz method provides sufficiently reliable analytical data to meet use-case #2A and is suitable for morbidity control programs focused on moderately to heavily infected individuals, but improvements to FEC measurements that address reproducibility and throughput challenges (Table 1) would enhance program efficiency as well as create opportunities for programs to proceed beyond morbidity control [30, 31]. Technologies that meet the needs of use-case #2B can also be used in moderate and high transmission settings by STH control programs but offer greater value in lower transmission settings, where the Kato-Katz method fails to provide reliable data. For practical considerations, a preferred technology would be a platform that addresses multiple use-cases by meeting the requirements described in each of the associated TPPs. Use-case #3—Confirm a decision to stop intervention and transition to post-MDA surveillance This use-case applies to programs aiming to interrupt transmission of any STH in low- to very-low- prevalence settings. In this circumstance, program progress and other transmission measurements would lead a program manager to initiate a test that confirms that a program can stop MDA and/or other population-directed interventions. Diagnostic results that confirm a break in transmission with minimal risk of recrudescence would transition program goals from active intervention to surveillance for recrudescence (use-case #4) or, in the event of discordant results, would initiate additional assessments. The low- to very-low-prevalence threshold that describes the transmission breakpoint is species specific and has yet to be established, although it can be approximated through mathematical and animal models [32]. Based on studies with A. lumbricoides, worm dynamics behave differently at low worm burdens compared to high burdens, such that the number of fertile eggs no longer have a linear relationship to worm burden, making any individual-level coproscopic measurement unreliable for determining very light intensities of infection relevant to the population-level transmission breakpoint [33]. Nonmicroscopy biomarkers with a linear relationship to low worm burden, detectable within a dynamic range relevant to the transmission breakpoint, are needed. Table 4 provides a high-level overview of desired characteristics for any biomarker meeting this use-case. 10.1371/journal.pntd.0006213.t004 Table 4 General desired characteristics of use-case #3 and #4 biomarkers. • Biomarker measurement correlates to active infection by specific species-level STH• Biomarker clears within 1 year of last prescribed intervention, in absence of reinfection• Specific for each STH, no cross-reactivity with other pathogens• Detected in populations residing in geographies with less than 2% prevalence of any STH infection• Detected in infected individuals who are Kato-Katz negative• Sufficient abundance in readily accessible body fluid (nonstool)• Detection maximizes cost-efficiencies (e.g., amenable to pooling, simplified collection and shipment, testing in young children born after presumed transmission breakage)• Easily translatable to accessible diagnostic platforms Abbreviation: STH, soil-transmitted helminth. Use-case #4—Verify sustained break in transmission This use-case applies to programs that have successfully interrupted STH transmission (use-case #3) and seek to verify sustained elimination of transmission [34] or have reason to believe that there may be a risk of recrudescence. A program would investigate the potential causes of unexpected results if qualitative test results indicate ongoing transmission. Ideally, the test detects other diseases under surveillance and requires a specimen that is easier to collect than stool, such as urine, saliva, or blood, to encourage participation in screening events, with analysis performed in a centralized laboratory. The aspirational list of biomarker characteristics described in Table 4 are similar for use-cases #3 and #4, and stricter definitions warrant further discussion. Similar tests for other diseases have relied on detecting host-response antibodies of infection [35], a class of biomarker convenient for integrated surveillance. These biomarkers of host response should ideally be specific for active infection, not exposure. Alternatively, exposure-based biomarkers could be measured within indicator subpopulations born after transmission has been broken, as these groups should not have been exposed to STH infection in geographies remaining absent of transmission [36]. Although species-specific detection is listed in Table 4, it remains unclear if a pan-STH biomarker would suffice for this use-case. Use-cases to TPPs The TPP describes technical performance and implementation requirements for an assay to meet the decision needs of a program’s specific use-case. Each requirement is defined in a TPP as minimal or optimal criteria, reflecting a consensus of accepted compromises. To reduce risks and time lines for developing a product and accelerating adoption, criteria should consider the capacity, resources, and diagnostic workflows of STH programs in the context of existing research, methodology, and technology landscape. Requirements for technology performance and implementation are linked and criteria consider trade-offs for supporting a new test within an existing diagnostic system versus costs for adapting or creating infrastructure. Implementation considerations include: survey design (population targeted for testing, sampling size), available workforce, workflow (specimen collection and transportation, sample preparation and analysis), throughput and turnaround time for test results, data requirements, and criteria for reimbursing test costs. Other considerations include external quality assurance requirements and regulatory pathway as well as program recommendations, policies, and guidelines. Because diagnostics only approximate a true state of infection, mathematical models can be used to further inform performance requirements by estimating the impact of different levels of uncertainty on the accuracy of program decision-making and ultimately on health outcomes [37]. Models can also provide a health economics framework to justify performance requirements by weighing the predicted health outcomes against costs incurred by a program to conduct a survey as well as resources deployed in the event of an incorrect decision [3]. Minimum criteria describe performance characteristics that must be achieved for a test to be used by most STH programs. Optimal criteria describe attributes that expand the value of the assay but would not be required by most STH programs. Simply, minimum criteria describe “must-have” requirements, whereas “nice-to-have” options are listed as optimal, details that guide product development and evaluation priorities as well as resource allocation. In addition to setting targets for technology development, these requirements are also criteria for clinical and field trials and should consider availability and access to patient specimens from geographies representing the epidemiological and individual context of intended-use populations. These specimens must naturally represent the diversity and range of biomarkers to validate the performance claims of a prototype assay, with appropriate analytical and clinical benchmarks. Excessive technical complexity beyond actual program needs should be avoided, as each claim needs to be validated with available patient samples. For example, qualitative yes/no results may be a sufficient level of detail that most programs require from a test result, such as presence or absence of transmission within a population (e.g., use-case #3). In this instance, the minimum requirement listed in a TPP would be a qualitative test result, for interpretation by a program manager. It is important to differentiate the presentation of a test result from the method of analysis, as this qualitative output could be derived from the quantitative analysis of aggregated individual-level data or pooled specimens. If some programs have the resources and capacity to also act on test results that provide species-specific intensities of infection, then quantitation could be listed as optimal criteria. However, validating that a test reliably provides quantitative test results for each STH species also requires access to statistically powered quantities of accessible patient specimens that contain the natural dynamic range of intensities for each STH. As mentioned earlier, the use-case for monitoring program impact was divided into two similar use-cases, #2A and #2B, to address programs that intend to reduce transmission beyond morbidity control (S1 File). However, a TPP for use-case #2B was not developed, as a lower limit of detection (LOD) would approximate the transmission breakpoint, a species-specific indicator that requires further definition. At these lower transmission settings, a program manager might be solely interested in prevalence, unlike morbidity control programs, in which intensities of infection are an additional program metric. Two TPPs were developed and finalized by this group of STH stakeholders. Use-cases #1 and #2A were combined because there is little demand for a diagnostic dedicated to use-case #1, with the current pace of coverage by STH programs (S2 File). Diagnostic tools that address both use-cases would likely be similar, given the current landscape of coproscopy technologies. There was agreement on current WHO recommendations for using the Kato-Katz method in morbidity control programs, but this technique would not meet all requirements described in this new TPP. With an intent to strengthen a program’s ability to monitor impact, new diagnostic products must satisfy all minimum requirements described in this joint TPP. The second TPP described a tool to confirm a sustained break in transmission, a use-case that only requires a qualitative test result (S3 File). Conceptually, a platform that meets the needs of use-case #3 might also satisfy use-case #1–#2 if the test offered quantitative test results with appropriate upper limits of quantitation, but this warrants further discussion in the context of this type of multi-parametric test result. The complete TPPs are available as supplemental materials that accompany this article, with key sections for use-case #3 discussed below. Discussion on select components of use-case #3 TPP—Confirming break in transmission Section 1: Intended use This diagnostic confirms that transmission of each STH has been sustainably suppressed below its breakpoint, a qualitative population-level test result provided by statistical analysis of pooled specimens or data aggregated from multiple individual-level tests. A negative test result confirms the decision to wind down an active intervention and transition program goals to surveillance for recrudescence (use-case #4). A positive test result indicates that transmission has not been broken, requiring the program to investigate causes of confounding results. An STH program manager would use this test when other metrics indicate that the intervention has likely met its end point and seeks confirmation with a diagnostic survey of a targeted population. These nondiagnostic indicators to initiate testing have yet to be defined and will be clarified through ongoing research assessing the strategy for interrupting transmission [38]. The minimum detection requirement is species-level infection by A. lumbricoides, T. trichiura, and hookworms (A. duodenale, N. americanus). Hookworm differentiation is not required because interventions are the same for the two species. However, some STH programs or the research community may be interested in differentiation between A. duodenale and N. americanus or detection of infections by A. ceylanicum and Strongyloides stercoralis, and these possibilities were listed as optimal criteria. It was noted that neither infections by A. ceylanicum nor S. stercoralis are treated by MDA-based interventions [39]. In addition to hookworms, optimal requirements also considered integration of STH programs with those focused on controlling schistosomiasis (S. mansoni, S. japonicum, and S. haematobium) [1, 26]. The intended use of this assay also describes the ideal scenario for implementing a test. These details are described in Section 4 of the TPP and must be realistic to the workflow and resources available to an STH program. These considerations also define criteria for additional methods and accessories required to support the use of the test, such as those for specimen collection and preservation. Health economics and community-acceptability studies that provide a cost-effectiveness and implementation framework for elimination programs are needed to determine the ideal diagnostic scenario. Section 2: Population needs and performance characteristics The results from a test meeting the needs of use-case #3 provide an indicator of worm and population dynamics to determine if an intervention has reduced parasite reproduction to a point at which local extinction is highly probable (i.e., transmission breakpoint) [40]. In this use-case, criteria for clinical sensitivity is based on an individual’s intensity of infection in relation to this transition point in transmission dynamics, with a true positive test result identifying an individual who is transmitting any STH infection [41]. Phenotypic characteristics related to the number of worms harbored by an individual who would be classified as positive under this use-case remain undefined, as individuals classified as test negative may still be infected with STH but not contributing to transmission. Early-stage research is aimed at developing biomarkers that are fit for this context of use and can be measured in non–stool-based specimens. As with any biomarker-based measurement, it is important to assess the reliability of results by addressing potential sources of interindividual variability, including age, nutritional status, and social dynamics. These variables might be approximated by mathematical and animal modeling to guide biomarker and epidemiological research [40]. The early-stage nature of these investigations is reflected in this version of the TPP and is subject to updates, as additional evidence justifies a rigorous performance requirement. Analytical sensitivity describes technical performance of the assay (e.g., with spiked samples) and defines the required minimum concentrations of a target analyte that must be measured reliably (95% confidence). Only the lower LOD needs to be defined for a qualitative test and set below the confidence intervals for a diagnostic cutoff. Since this cutoff cannot yet be defined, key opinion leaders agreed that a test must have superior analytical sensitivity compared to current FEC methods. Given the current lack of validated analytical comparators in this range of light infection, in the interim, the LOD was defined as less than 1 egg per 41.7 mg of homogenized stool (equivalent to 24 eggs per gram). This section will be updated in future TPPs as evidence becomes available to justify an appropriate unit of measurement related to clinically relevant diagnostic cutoffs for this use-case, with validated analytical benchmarks that are not egg-based measurements or limited to stool samples. Quality control requirements address confidence in test results and consider costs for integrating controls within an individual assay as well as costs and resources for external assessments. For stool-based specimens, there was consensus that individual assays require internal controls as a pre-analytical assurance that stool samples were uniformly homogenized and prepared, addressing some of the challenges described in Table 1. There was also agreement that external quality assessment programs would be needed to ensure that STH testing locations that likely vary in infrastructure and workforce are providing consistent results [42, 43]. Section 3: Regulatory and statutory needs The regulatory pathway for global health diagnostics was not defined when the Kato-Katz method was recommended by WHO in 1985 for schistosomiasis control programs [44]. This method would likely not have passed current regulatory requirements if introduced today, given the risk of variable test results and lack of quality control. There was consensus that quality results and reproducibility will be required for any new tests and that these products must be developed using design-control processes [45] and standards defined by ISO13485 [46]. The latter is an internationally recognized standard for developing medical devices through documented processes that ensure consistent attention to quality considerations, from design and development to manufacture and delivery. In addition to adherence to International Organization for Standardization (ISO) processes, the product-development process will also be defined by the regulatory labeling of the tool for research use only (RUO), investigational use only (IUO), or as an in vitro diagnostic (IVD). Beyond ISO and design control requirements, the regulatory pathway for this assay is currently not known and will be updated in future TPPs. Tests that guide individual-level treatment decisions are typically classified as IVDs and may also require WHO’s prequalification (PQ) for use in global health settings, in addition to clearance by stringent national regulatory authorities, before they can be procured and used within a program [47]. Unlike traditional IVDs, STH programs do not make individual-level treatment decisions but instead focus on MDA with albendazole or mebendazole. The assay described in use-cases #1 and #3 guide treatment decisions that have population health implications for correct and incorrect results; premature cessation of population-based treatment could result in recrudescence [48]. An alternative consequence is overtreatment and wasted program resources. These types of assays would likely be developed following a regulatory pathway for an IVD, whereas RUO may be suitable for use-cases #2 and #4. Future discussions are needed to determine the regulatory pathway of tests described in all four use-cases. One important consideration is the implication of a decision based on an incorrect test result and steps to mitigate unintended health outcomes. For use-case #3, an increased risk of recrudescence due to premature wind-down of a program might be mitigated if tests described in use-case #4 are in place and populations remain under surveillance. Likewise, an increased risk of overtreatment due to late wind-down of a program might be mitigated if monitoring tests described in use-case #3 are in place. For use-cases #2 and #4, if the intended purpose of monitoring and surveillance tests is to trigger confirmatory testing or initiate testing to investigate inconsistent results, then these assays would only guide program testing, not treatment decisions. These hypothetical scenarios exemplify the intertwining nature of program guidelines with the regulatory pathway for developing an assay. Section 4: Healthcare/program system needs This section includes requirements for the successful implementation of a diagnostic. Because targeted population-level data are required for the program decision, minimum data requirements also include geospatial information. There was no advantage for receiving the test result at the point of contact (e.g., rapid diagnostic test) because population-level data is required for program decisions, with acceptable turnaround time for results being over a period of weeks and months. For the testing environment, key opinion leaders agreed that the testing site should be in proximity to a community or school, preferably at a district-level health center or through a mobile van campaign, to increase community participation and adherence in MDA events. This was based on reports of community involvement in improving the health outcome provided by MDA, particularly because STH infection is predominantly driven by an individual’s interaction with their local environment, including access to clean water and sanitation [49, 50]. The global neglected tropical disease (NTD) agenda is also aligned with aims to strengthen general healthcare services within impoverished communities, increasing opportunities for developing an STH diagnostic on platforms that address other community health needs [51]. District-level settings often have sufficient resources to perform simple diagnostic tests, such as microscopy or rapid diagnostic tests, with access to running water and sufficient electricity during test operation and at least one individual who can be trained to perform a simple test. These settings rarely have sterile work stations and minimal biosafety resources; thus, TPP requirements address the safety of the test operator and local environment by reducing exposure to biospecimens and reagents through design (e.g., self-containment and safety lock) as well as simple disposal processes. Optimal requirements would be met if the test did not require consistent electricity to operate, such as through a battery, and thus were operational in less-resourced settings. Conclusion The success of the current WHO STH control strategy has catalyzed interest in moving beyond coverage estimates and morbidity control to improving program efficiency and exploring the prospect of breaking the transmission of STHs to reduce resources required for sustaining vertical STH programs. These aspirations require surveys of the targeted populations, and the aim of the hypothetical use-cases was to simulate STH program decisions requiring diagnostic information. The context within these use-cases frame performance and implementation requirements for the design and evaluation of existing and new tools. This approach ensures that user needs are the destination of a research and product development road map, instead of forcing the adoption of an imperfect technology. In the best-case scenario, one technology is able meet the requirements of multiple TPPs. The current TPP for use-case #1 and #2A addresses the needs of morbidity control programs but does not address the needs of elimination programs that would initiate or continue in lower transmission settings (e.g., <20% apparent prevalence). The Kato-Katz method meets most, but not all, of the minimum criteria in this TPP, as it offers sufficient analytical and clinical sensitivity but does not meet precision and reproducibility criteria (§2.5 and 2.6), nor does it meet regulatory requirements (§3.1). New tools that meet all requirements described in this TPP are needed as one step towards strengthening STH program efficiency. Opportunities for improvement are also highlighted in Table 1, and as with any new tool, it is important to consider manufacturability, use, and cost-effectiveness from the program perspective. STH programs that aim to move beyond morbidity control towards interruption of transmission are described in use-cases #2B, #3, and #4. Tests for use-case #2B will require a lower LOD than use-case #2A, but there is insufficient information to provide definitive criteria, as this approximates the transmission breakpoint. There is a need to define the epidemiological characteristics of a transmission breakpoint to understand the risk criteria of an individual’s contribution to STH transmission within a given population. This is challenging given the wide range of contextual factors that define population heterogeneity, such as seasonality, individual health/nutritional status, environmental exposure, and/or social behaviors. These factors may influence STH transmission and thus, also, breakpoints [52]. Mathematical modeling and animal studies can approximate the extent of these potential contributions to guide definitions of phenotypic characteristics (§2.1), information necessary for defining clinical utility requirements of biomarkers. A TPP for use-case #2B and #3 diagnostics also requires proof of concept that programs can interrupt transmission in a scalable and cost-effective manner, with a strategy that verifies decision points requiring diagnostic surveys and test implementation scenarios (timing, sampling size, etc.). Diagnostic needs will adjust over time as emerging research continues to evolve program strategies. These TPPs and use-cases are living documents that capture the current trajectory of STH programs to identify gaps that can be addressed through research and product development. Key learning points The soil-transmitted helminth (STH) community has started exploring opportunities to strengthen a control program’s ability to monitor changes in prevalence of infection, potentially to a reduction that is sustained below transmission breakpoints. Current global strategies have been successful with existing diagnostics, and more ambitious program end points would likely require different tools to evaluate the impact of population-directed interventions. Newly created target product profiles (TPPs) described in this article aim to direct the development and evaluation of diagnostic tools that improve the efficiency of control and elimination programs. The STH community lacks a tool to confirm a break in transmission, and based on the new TPP, critical evidence to inform the development of this diagnostic is currently unavailable. Additional research is needed to define species-specific transmission breakpoints and guide the translation of individual-level test results to population-level transmission indicators. Supporting information S1 File Overview of diagnostics use-cases for STH control and elimination programs. STH, soil-transmitted helminth. (PDF) Click here for additional data file. S2 File Target product profile for STH use-case #1 and #2A diagnostic (mapping, monitoring population-level intervention). STH, soil-transmitted helminth. (PDF) Click here for additional data file. S3 File Target product profile for STH use-case #3 diagnostic (confirming decision to stop population-level intervention). STH, soil-transmitted helminth. (PDF) Click here for additional data file.

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          Population biology of infectious diseases: Part II.

          In the first part of this two-part article (Nature 280, 361--367), mathematical models of directly transmitted microparasitic infections were developed, taking explicit account of the dynamics of the host population. The discussion is now extended to both microparasites (viruses, bacteria and protozoa) and macroparasites (helminths and arthropods), transmitted either directly or indirectly via one or more intermediate hosts. Consideration is given to the relation between the ecology and evolution of the transmission processes and the overall dynamics, and to the mechanisms that can produce cyclic patterns, or multiple stable states, in the levels of infection in the host population.
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            Sensitivity of diagnostic tests for human soil-transmitted helminth infections: a meta-analysis in the absence of a true gold standard

            1 Introduction Reliable, sensitive and practical diagnostic tests are an essential tool in disease control programmes, including those for neglected tropical diseases. The requirements and expectations for a diagnostic tool in terms of technical performance, feasibility and costs change as control programmes progress through different phases, from initially high levels of infections to the confirmation of absence of infections. More precisely, during initial mapping to identify priority areas for control, when infection levels are typically highest, a diagnostic test with moderate sensitivity is acceptable, although the chosen tool needs to be easy to use, cost-effective and allow for the high-throughput screening of large populations (McCarthy et al., 2012; Solomon et al., 2012). Since mapping data can also serve as a baseline for the monitoring and evaluation of programme impact, diagnostic tests must have sufficient performance to detect changes in the prevalence and intensity of infection (Solomon et al., 2012). In later stages of programmes, when infection prevalence and intensity have decreased significantly, more sensitive diagnostic tools are needed to establish an endpoint of treatment programmes. If test sensitivity is insufficient at this point, light infections might be missed and this runs the risk of stopping control programmes too early, before programme endpoints have been achieved. Highly sensitive tests are also required for surveillance once treatment has been stopped to detect the potential re-occurrence of infections (McCarthy et al., 2012; Solomon et al., 2012). Finally, diagnostic tests play an important role in the assessment of treatment efficacy (Albonico et al., 2012) and in patient management. For the detection of the human soil-transmitted helminth (STH) species, Ascaris lumbricoides, Trichuris trichiura and the hookworms (Necator americanus and Ancylostoma duodenale), The World Health Organization (WHO) currently recommends the use of the Kato-Katz method, based on duplicate slides (WHO, 2002). Other commonly used methods include direct smear microscopy, formol-ether concentration (FEC), McMaster, FLOTAC and Mini-FLOTAC. All of these techniques rely on visual examination of a small sample of stool to determine the presence and number of STH eggs (WHO, 1994). Due to intra- and inter-sample variation in egg counts (Booth et al., 2003; Krauth et al., 2012), microscopy-based techniques can have differing sensitivities, especially in low transmission settings. Moreover, diagnostic methods vary considerably in the quantification of egg counts, which is necessary to establish intensity of infection and to evaluate treatment effects (Knopp et al., 2011; Albonico et al., 2012; Levecke et al., 2014). In order to better understand the suitability of diagnostic tools for various transmission settings and stages of disease control programmes, we performed a meta-analysis of the most commonly used copro-microscopic STH diagnostic tests. Our main study objective was an independent and global assessment of the relative performance of commonly used diagnostic methods for STH, as well as factors associated with heterogeneity in test sensitivity. Previous evaluations of STH diagnostics have generally relied on comparisons with a combined reference standard (generated by adding the results of several compared tests or consecutively obtained samples), an approach which has been widely criticised (Enoe et al., 2000; Ihorst et al., 2007). Moreover, the absence of a common reference standard has been a major obstacle for combined evaluations of diagnostic tests in the form of a meta-analysis. We have addressed this problem by using Bayesian latent class analysis (LCA), which allows simultaneous estimation of the unknown true prevalence of infection and the sensitivities and specificities of compared diagnostic tests. This approach has been previously applied to the evaluation of imperfect diagnostic tests for Chagas disease, leishmaniasis and malaria (Menten et al., 2008; de Araujo Pereira et al., 2012; Goncalves et al., 2012), as well as specific studies evaluating STH diagnostic methods (Booth et al., 2003; Tarafder et al., 2010; Assefa et al., 2014; Knopp et al., 2014). The approach has also been used for the meta-analyses of diagnostic test performance (Ochola et al., 2006; Menten et al., 2008; Limmathurotsakul et al., 2012). The current paper presents a Bayesian meta-analysis of different diagnostic tests for the detection of STH species. 2 Materials and methods 2.1 Literature search A systematic literature search was performed to identify publications presenting the evaluation of diagnostic techniques for the human STH species, A. lumbricoides, T. trichiura and hookworms (N. americanus and A. duodenale). Systematic searches were performed (date of search 25th February 2014) using the electronic databases PubMed (http://www.ncbi.nlm.nih.gov/), MEDLINE and EMBASE (via OvidSP) (http://ovidsp.uk.ovid.com/) and the medical subject headings and search terms as detailed in Supplementary Data S1. Articles were considered if written in English, German, French or Spanish. The search was validated by verifying that a number of previously identified key readings were included in the retrieved search results. The titles of initially obtained search results were screened for suitable content and all abstracts mentioning studies on helminths were retrieved. The abstracts were subsequently screened for studies using more than one diagnostic test for the determination of infections, even if not directly mentioning a comparison of test performances. Full texts were read and information on test outcomes, egg counts, age-groups, countries of the studies and years of publication was extracted where results were presented in a suitable format as explained below. Reference lists were screened for additional publications. The literature selection process is outlined in Fig. 1. Data were collected separately for A. lumbricoides, T. trichiura and hookworms, and restricted to the most commonly used diagnostic methods for STH, namely Kato-Katz (Katz et al., 1972), direct microscopy (WHO, 1994), formol-ether concentration (FEC) (Ritchie, 1948), McMaster (Ministry of Agriculture Fisheries and Food, 1986), FLOTAC (Cringoli et al., 2010) and Mini-FLOTAC (Barda et al., 2013a). Other techniques such as midi-Parasep, Koga Agar Plate, Willis technique and Spontaneous tube sedimentation technique (SSTT) were not included due to a lack of suitable data. As performance during field surveys was the main interest, evaluations of diagnostic tests on samples from diagnostic laboratories of hospitals were excluded. Only data provided in the form of 2 × 2 comparisons (T1+T2+, T1+T2−, T1−T2+, T1−T2−, where T1 and T2 are the two diagnostic methods and + and − indicate the observed positive or negative results) were retained. This also included data for which these 2 × 2 comparisons could be created by transforming the original data provided, e.g. where comparisons were made against a combined ‘gold standard’ of two diagnostic methods. Additionally, data on egg counts obtained by the various techniques were retrieved, including those studies that did not provide data in a suitable format for the LCA. Arithmetic mean egg counts were the most commonly reported measures and therefore used for the analysis. For articles where data could not be directly extracted, corresponding authors were invited to contribute additional study results. Three authors replied and provided four datasets for the analysis; we were also able to contribute a further two datasets to the analysis. 2.2 Bayesian LCA A Bayesian latent class model was used to estimate the sensitivity of different diagnostic tests as described elsewhere (Dendukuri and Joseph, 2001; Branscum et al., 2005). LCA allows estimation of the sensitivity and specificity of imperfect diagnostic tests by assuming a probabilistic model for the relationship between five unobserved, or latent, parameters: true disease prevalence π k and the sensitivities S i , S j and specificities C i , C j of diagnostic methods i and j (Pepe and Janes, 2007). The model additionally incorporates the covariance terms covD ij + , covD ij - to account for conditional dependency between compared diagnostic tests amongst infected and non-infected individuals, which is necessary as the included diagnostic tests are based on the same biological principle (detection of eggs under a microscope) and therefore factors other than the true infection status are likely to influence both test outcomes simultaneously (Dendukuri and Joseph, 2001). Thus, the joint distribution of the results of a 2 × 2 table follows a multinomial distribution, ( X k + + , X k + - , X k - + , X k - - ) ∼ Multi ( p k + + , p k + - , p k - + , p k - - , N k ) with the multinomial probabilities calculated as follows: p k + + = P ( T i + , T j + | k th population ) = [ S i S j + covD ij + ] π k + [ ( 1 - C i ) ( 1 - C j ) + covD ij - ] ( 1 - π k ) p k + - = P ( T i + , T j - | k th population ) = [ S i ( S j - 1 ) - covD ij + ] π k + [ ( 1 - C i ) C j - covD ij - ] ( 1 - π k ) p k - + = P ( T i - , T j + | k th population ) = [ ( S i - 1 ) S j - covD ij + ] π k + [ C i ( 1 - C j ) - covD ij - ] ( 1 - π k ) p k - - = P ( T i - , T j - | k th population ) = [ ( S i - 1 ) ( S j - 1 ) + covD ij + ] π k + [ C i C j + covD ij - ] ( 1 - π k ) The conditional correlations between two test outcomes for infected and non-infected individuals were calculated as ρ D + = covD + S i ( 1 - S i ) S j ( 1 - S j ) and ρ D - = covD - C i ( 1 - C i ) C j ( 1 - C j ) , respectively. Uninformative prior information was provided for the sensitivity and underlying true prevalence (using a beta distribution with the shape parameters alpha and beta equal to 1). For the covariance terms, a uniform prior distribution was assumed with limits as described in Dendukuri and Joseph (2001) and Branscum et al. (2005) to ensure that probabilities are confined to values between 0 and 1. Specificity was included as a fixed term based on the most parsimonious, best-fitting model (i.e. that with the lowest deviance information criterion (DIC) value) and was assumed to be the same for all compared methods. This was justified on the dual assumption that false positives are rarely obtained by any type of copro-microscopic technique (Knopp et al., 2011; Levecke et al., 2011) and the necessity to restrict the number of estimated parameters for the identifiability of the model. The models, built separately for A. lumbricoides, T. trichiura and hookworms, were computed using WinBUGS software version 14 (Spiegelhalter, D., Thomas, A., Best, N., Gilks, W., 1996. BUGS: Bayesian Inference Using Gibbs Sampling. MRC Biostatistics Unit, Cambridge). Models were also developed separately for low and high intensity settings. Stratification was based on reported arithmetic mean egg counts (in eggs per gram of faeces, epg). Empirical cut-offs of 2500 epg, 400 epg and 165 epg average infection intensity were used for A. lumbricoides, T. trichiura and hookworms, respectively. These cut-offs were established based on the overall average infection intensity of studies included in the meta-analysis. Data with only geometric means reported were excluded from this analysis unless the geometric mean, which is lower than the average egg count, exceeded the cut-off value. Further details of model parameterisation, including handling of multiple slides, are provided in Supplementary Data S2. 2.3 Comparison of quantitative performances To compare the various diagnostic tests in terms of their quantitative performance, we compared the arithmetic mean egg count obtained by various techniques. Statistical significance of differences was assessed using the non-parametric paired Wilcoxon signed-ranks test and the linearity of the relationship between counts was assessed by scatter plots of log-transformed (natural logarithm) average egg counts. Moreover, we evaluated the percentage of studies reporting egg counts of other techniques that were lower/higher than the Kato-Katz method, which currently forms the basis of the WHO defined intensity thresholds. To allow for a small variation in counts, egg counts were considered as lower or higher than the Kato-Katz method if these were lower or higher than the Kato-Katz egg count plus or minus 10%. Due to the limited availability of data and the fact that faecal egg counts do not vary significantly by the sampling effort for Kato-Katz analysis, all versions of Kato-Katz were combined (Levecke et al., 2014). 3 Results 3.1 Identification of diagnostic test comparisons The initial literature search identified 56 articles which were retrieved for full-text review. Of these, 32 studies fulfilled the inclusion criteria and 2 × 2 comparison data could be obtained for 20 studies (Table 1) (see Fig. 1 for an outline of literature selection steps). The number of extracted 2 × 2 comparisons by species and diagnostic methods is shown in Fig. 2. The included studies were published between 2003 and 2014 and conducted in 12 countries, primarily among school-aged children. The inclusion of only recent studies was somewhat surprising. Even though the original literature search had retrieved studies published since 1967, the non-availability of 2 × 2 data, the type of compared techniques and the evaluation of methods in laboratory or hospital samples led to their exclusion. The evaluation of diagnostic tests was mainly based on comparison with a combined reference-standard (14 of 20 studies); few studies used predicted estimates as a reference (1/20), an LCA approach (1/20) or a combination of the two (1/20). Three studies did not provide sensitivity estimates. The most widely applied method was the Kato-Katz method in 18 of 20 studies (mostly 1-slide or 2-slides on a single sample). The main characteristics of included studies are summarised in Table 1. 3.2 LCA of diagnostic test sensitivities (presence of infection) For all STH species, the models allowing for dependency between compared diagnostic tests showed a better fit, indicated by a lower DIC (not shown). Significant positive correlation between diagnostic test outcomes for infected individuals was observed, especially for comparisons of a 1-slide 1-sample Kato-Katz test with other diagnostic tests (details are provided in Supplementary Data S2). Taking this dependency into account, the sensitivities of selected diagnostic methods were estimated separately for A. lumbricoides, T. trichiura and hookworm and are provided in Table 2 and Fig. 3. Generally, sensitivities of all compared tests were higher for T. trichiuria (Fig. 3B) than for hookworm (Fig. 3C) and A. lumbricoides (Fig. 3A). The obtained sensitivities were highest overall for the FLOTAC method with 79.7% (95% Bayesian credible interval (BCI): 72.8–86.0%), 91.0% (95% BCI: 88.8–93.5%), and 92.4% (95% BCI: 87.6–96.2%) for A. lumbricoides, T. trichiura and hookworm, respectively (Table 2). The lowest sensitivity was observed for the direct microscopy method with 52.1% (95% BCI: 46.6–57.7%), 62.8% (95% BCI: 56.9–68.9%), and 42.8% (95% BCI: 38.3–48.4%), respectively. The estimated sensitivity of the 2-slide 1-sample Kato-Katz test for A. lumbricoides was 64.6% (95% BCI: 59.7–69.8%), for T. trichiura was 84.8% (95% BCI: 82.5–87.1%) and for hookworm was 63.0% (95% BCI: 59.8–66.4%). These estimates were only a slight improvement upon the sensitivities of a 1-slide 1-sample Kato-Katz test. However, increased sensitivities could be observed for 1-slide Kato-Katz performed on two consecutive samples. The sensitivity for Kato-Katz tests performed on three consecutive samples was only slightly further improved. Test specificities were not the main outcome and were fixed at 99.6% for A. lumbricoides, 97.5% for T. trichiura and 98.0% for hookworm, based upon model fit. 3.3 Effect of infection intensity on diagnostic test sensitivity The obtained sensitivity estimates by intensity group are presented in Table 3 and Fig. 4. For all tests and STH species evaluated in both intensity groups, sensitivity varied markedly and most strongly for the Kato-Katz method. For example, for A. lumbricoides the 1-slide Kato-Katz method had a sensitivity of 48.8% (95% BCI: 37.6–58.2%) in the low intensity group compared with 95.8% (95% BCI: 91.8–98.5%) in the high intensity group. Interestingly, in the low intensity group the sensitivity of Kato-Katz was improved markedly by performance of a second slide on the same sample. The sensitivity of the FLOTAC method was highest at 81.8% (95% BCI: 65.5–90.3%) at low intensity compared with 97.1% (95% BCI: 93.1–99.7%) at high intensity. 3.4 Comparison of quantitative test performances A total of 17, 16 and 27 comparisons of average Kato-Katz A. lumbricoides, T. trichiura and hookworm egg counts with other diagnostic methods were obtained from 11 articles (Table 1, analysis 2). The majority of comparisons were between versions of Kato-Katz and FLOTAC or McMaster techniques. Only a few studies compared egg counts between Kato-Katz and FEC or Mini-FLOTAC methods; none with direct microscopy. Table 4 shows that the FLOTAC method generally underestimates the average egg counts compared with Kato-Katz, even though the difference is not statistically significant for T. trichiura. The McMaster technique, however, resulted in a higher egg count for six of 11 comparisons (55%) for T. trichiura and four of 12 comparisons (33%) for hookworm whilst A. lumbricoides egg counts were significantly lower. The relationships between the logarithmic average measurements of Kato-Katz and FLOTAC or McMaster techniques followed a linear trend as shown by the scatter plots presented in Fig. 5. 4 Discussion A global assessment of STH diagnostic test sensitivities and their extent of variation is required to investigate the suitability of diagnostic tools for different transmission settings or stages of STH control programmes. Here we present, to our knowledge, the first meta-analysis of STH diagnostic method performance using a Bayesian LCA framework to overcome the absence of a true gold standard (Dendukuri and Joseph, 2001; Branscum et al., 2005). Our results demonstrate that sensitivities of evaluated diagnostic tests are low overall and cannot be generalised over different transmission settings. Sensitivity, overall and in both intensity groups, was highest for the FLOTAC method, but was comparable for Mini-FLOTAC and Kato-Katz methods. Test sensitivities are strongly influenced by intensity of infection and this variation needs to be taken into account for the choice of a diagnostic test in a specific setting. Moreover, reduced test sensitivity at low infection intensities is of increasing importance as ongoing control programmes reduce the prevalence and intensity of STH infections within endemic communities. The Kato-Katz method is the most widely used and reported diagnostic method, due to its simplicity and low cost (Katz et al., 1972), and is recommended by the WHO for the quantification of STH eggs in the human stool (WHO, 2002). Even though the overall sensitivity of the Kato-Katz method was low, the results of the stratified analysis suggest a high sensitivity of 74–95% when infection intensity is high, which is likely the case for mapping and baseline assessment. However, the test sensitivity dropped dramatically in low transmission settings, making the method a less valuable option in later stages of control programmes. This is likely a reflection of methodological problems specific to the Kato-Katz method, especially when diagnosing multiple STH species infections, as different helminth eggs have different clearing times (Bergquist et al., 2009). In high intensity settings, little value was added by performing a 2-slide test on the same sample, even though this is the currently recommended protocol; whereas in low intensity settings sensitivity was improved by performing a second slide. Sensitivity increased significantly when performing the Kato-Katz method on multiple consecutive samples, which is most likely explained by daily variations of egg excretions and the non-equal distribution of eggs in the faeces leading to substantial variation in egg numbers between stool samples from the same person (Booth et al., 2003; Krauth et al., 2012). For all investigated STH species, sensitivity was highest for the FLOTAC method, even when evaluated in low intensity settings, a finding which is consistent with previous evaluations (Utzinger et al., 2008; Knopp et al., 2009b; Glinz et al., 2010). However, despite its improved performance compared with other copro-microscopic methods, FLOTAC has several practical constraints including higher associated costs, necessity of a centrifuge and longer sample preparation time, decreasing its value as a universal diagnostic method (Knopp et al., 2009a). To enable its use in settings with limited facilities, the Mini-FLOTAC method, a simplified form of FLOTAC, was developed (Barda et al., 2013a). Our findings suggest that the sensitivity of Mini-FLOTAC is much lower than FLOTAC, and it does not outperform the less expensive Kato-Katz method according to a recent study in Kenya (Speich et al., 2010; Assefa et al., 2014). A recognised advantage of the Mini-FLOTAC method, however, is that it can be performed on fixed stools, enabling processing at a later date in a central laboratory. This can help to increase the quality control process and overcomes some of the logistical difficulties in examining fresh stool samples in the field on the day of collection (Barda et al., 2013a). The obtained Mini-FLOTAC sensitivity estimates have relatively high uncertainty, visible in the wide confidence intervals, probably due to the limited number of studies available for the analysis and their evaluation primarily in low transmission settings, where the number of positive individuals is very limited. The detection or failure of detection of a single individual therefore might have a large impact on the sensitivity estimate. In remote areas where microscopy is often unavailable, studies can also use FEC, which allows the fixation of stool samples for later examination (WHO, 1994); several authors have also suggested the use of the McMaster technique as it is easier to standardise than Kato-Katz (Levecke et al., 2011; Albonico et al., 2012). Overall, the observed relative performances of these diagnostic tests when compared with the Kato-Katz method are consistent with those presented in the literature: the performance of Kato-Katz and McMaster methods were comparable, although this did vary by setting (Levecke et al., 2011; Albonico et al., 2013). Similarly, even though FEC had predominantly lower sensitivity than Kato-Katz in included studies, the reported relative performance varies in the literature (Glinz et al., 2010; Speich et al., 2013). The sensitivity of direct microscopy was consistently lower than the Kato-Katz method. Other available methods which were not included in our meta-analysis due to limited data availability, such as the midi-Parasep, do not show any improved test performance in their previous evaluations (Funk et al., 2013). Although we present an improved approach for evaluating diagnostic test performances, accounting for the absence of a perfect gold standard by estimating the true unmeasured infection status and allowing for conditional dependency between the test outcomes, our analysis is subject to several limitations. The results presented here are limited by the low availability of comparable data for each diagnostic test, especially when performing the analysis stratified by intensity group. Direct microscopy was primarily evaluated in low intensity settings, which could have led to the lower observed sensitivity estimates, whereas the Kato-Katz method was evaluated in a full range of settings. The cut-off value to define high and low intensity groups of study populations was chosen based on the data included in the meta-analysis, but does not necessarily represent two main types of transmission settings. Nevertheless, the groupings demonstrate the substantial differences in test performance across varying infection intensities. As the investigated range of transmission settings was limited, further diagnostic test evaluations in specified transmission settings will be needed to provide concrete test performance estimates for each of the settings. To take into account the conditional dependency between compared diagnostic tests, we used a fixed effects model, assuming that conditional dependency is the same for all study settings. Different approaches allowing for varying correlations by using random effects to model sensitivities and specificities as a function of a latent subject-specific random variable could be explored further (Dendukuri and Joseph, 2001). Moreover, our findings might be biased towards results from studies comparing multiple diagnostic tests at the same time, as these are underpinned by a larger amount of data. Assumptions had to ensure identifiability of the model by limiting the number of parameters to be estimated. We focussed our analysis on the sensitivity of diagnostic tests, assuming that specificity of various methods do not differ largely, and therefore included the specificity of all single sample diagnostic tests as one fixed parameter. This assumption can be questioned, as for example Kato-Katz slides are more difficult to read than FLOTAC slides due to debris (Glinz et al., 2010); however, it is still an improvement on the assumption of 100% test specificity for all diagnostic tests as applied in previous publications (Booth et al., 2003; Knopp et al., 2011; Levecke et al., 2011). Using uninformative priors instead of fixed terms did not improve model fit and led to slightly wider BCIs. Importantly, the current model assumes that sensitivities are identical within all populations, which is not fulfilled if sensitivity varies by study setting (Toft et al., 2005). Indeed, the stratified analysis showed that sensitivity varied by infection intensity; however, there were not sufficient data to obtain good estimates for all tests in various transmission settings. Additionally, sensitivity in a specific study setting might be affected by other factors including stool consistency and diet, standardisation and adherence to protocols, equipment quality and human error (Bogoch et al., 2006; Bergquist et al., 2009; Levecke et al., 2011). To overcome the limited comparability of evaluations from different studies, purposeful evaluations of test sensitivity over a continuous range of infection intensities in comparable populations, for example before and after treatment rounds, are clearly necessary to better refine sensitivity estimates, and could be used to identify intensity categories within which sensitivity remains comparable. Results could then be transformed into recommendations for the use of diagnostic tests for different stages of disease control programmes. The performance of a diagnostic tool should not only be measured in terms of sensitivity, but also needs to consider the ability of the test to quantify faecal egg counts. Current infection and treatment effect indicators are based on the Kato-Katz method, and the question arises whether the increasing use of other methods will constitute a problem for standardised recommendations (WHO, 2002). The comparison of average egg counts obtained by Kato-Katz and FLOTAC methods shows a broad agreement with previous studies with generally higher Kato-Katz egg counts (Knopp et al., 2009b, 2011; Albonico et al., 2013). The quantitative performance of the McMaster technique, however, varied in comparison to the Kato-Katz method as higher McMaster average egg counts were observed in several studies, especially for T. trichiura and hookworms (Levecke et al., 2011; Albonico et al., 2012, 2013). The current analysis has focussed on copro-microscopic diagnostic tests, which are based on examination of stool samples. There is current interest in developing more sensitive assays that allow a high sample throughput for screening of large populations using other biological samples and the simultaneous detection of several parasite species in co-endemic settings (Bergquist et al., 2009; Knopp et al., 2014). Recently, assays based on PCR have been developed for the detection of STH (Verweij et al., 2007; Schar et al., 2013; Knopp et al., 2014); however, we did not include this method in our meta-analysis due to limited data availability from field settings. Nonetheless, a recent study showed that the sensitivity of PCR methods was comparable with the Kato-Katz method, especially in low endemicity settings (Knopp et al., 2014). In conclusion, we provide a first known meta-analysis of the sensitivity and quantitative performance of STH diagnostic methods most widely used in resource-limited settings. Our results show that the FLOTAC method had the highest sensitivity both overall and in low intensity settings; however this technique requires a centrifuge and has relatively low throughput. Our results further show that the sensitivities of the Kato-Katz and Mini-FLOTAC techniques were comparable and in high intensity settings both techniques provide a practical and reliable diagnostic method. A particular advantage of the Kato-Katz method is the ability to simultaneously detect STH and schistosome species at low cost; whereas the Mini-FLOTAC method has the advantage that it can be used on preserved samples. As control programmes reduce the intensity of infection, there is a need for diagnostic methods which are more sensitive than these currently used. In evaluating the performance of new diagnostic methods we recommend a standardised evaluation in multiple transmission settings, using the robust statistical methods presented here, as well as a consideration of the cost-effectiveness of alternative methods (Assefa et al., 2014).
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              The cross-cutting contribution of the end of neglected tropical diseases to the sustainable development goals

              The Sustainable Development Goals (SDGs) call for an integrated response, the kind that has defined Neglected Tropical Diseases (NTDs) efforts in the past decade. NTD interventions have the greatest relevance for SDG3, the health goal, where the focus on equity, and its commitment to reaching people in need of health services, wherever they may live and whatever their circumstances, is fundamentally aligned with the target of Universal Health Coverage. NTD interventions, however, also affect and are affected by many of the other development areas covered under the 2030 Agenda. Strategies such as mass drug administration or the programmatic integration of NTD and WASH activities (SDG6) are driven by effective global partnerships (SDG17). Intervention against the NTDs can also have an impact on poverty (SDG1) and hunger (SDG2), can improve education (SDG4), work and economic growth (SDG8), thereby reducing inequalities (SDG10). The community-led distribution of donated medicines to more than 1 billion people reinforces women’s empowerment (SDG5), logistics infrastructure (SDG9) and non-discrimination against disability (SDG16). Interventions to curb mosquito-borne NTDs contribute to the goals of urban sustainability (SDG11) and resilience to climate change (SDG13), while the safe use of insecticides supports the goal of sustainable ecosystems (SDG15). Although indirectly, interventions to control water- and animal-related NTDs can facilitate the goals of small-scale fishing (SDG14) and sustainable hydroelectricity and biofuels (SDG7). NTDs proliferate in less developed areas in countries across the income spectrum, areas where large numbers of people have little or no access to adequate health care, clean water, sanitation, housing, education, transport and information. This scoping review assesses how in this context, ending the epidemic of the NTDs can impact and improve our prospects of attaining the SDGs. Electronic supplementary material The online version of this article (doi:10.1186/s40249-017-0288-0) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                1 March 2018
                March 2018
                : 12
                : 3
                : e0006213
                Affiliations
                [1 ] Global Health Division, The Bill & Melinda Gates Foundation, Seattle, United States of America
                [2 ] College of Public Health, University of Philippines, Manila, Philippines
                [3 ] bioMérieux, Marcy l’Etoile, France
                [4 ] Faculty of Veterinary Medicine, University of Calgary, Calgary, Canada
                [5 ] Faculty of Veterinary Medicine, Gent University, Merelbeke, Belgium
                [6 ] Department of Parasitology, Leiden University Medical Center, Leiden, the Netherlands
                [7 ] Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [8 ] Jimma University Institute of Health, Jimma, Ethiopia
                [9 ] Techion Group Ltd, Dunedin, New Zealand
                [10 ] Kenya Medical Research Institute, Nairobi, Kenya
                [11 ] Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
                [12 ] Janssen Diagnostics, Beerse, Belgium
                [13 ] Departments of Global Health, Medicine (Infectious Disease), Pediatrics and Epidemiology, University of Washington, United States of America
                [14 ] Natural History Museum, London, United Kingdom
                Miyazaki Daigaku Igakubu Daigakuin Ikagaku Kangogaku Kenkyuka, JAPAN
                Author notes

                Three of the coauthors are employed by commercial companies. Françoise Gay-Andrieu is employed by bioMerieux, Greg Mirams is employed by Techion Group Ltd, and Lieven Stuyver is employed by Janssen Diagnostics. None of these individuals received any form of compensation contributing to this manuscript, nor are any products/patents developed by their affiliated companies described within the manuscript.

                ¶ Membership of the Annecy STH diagnostic experts group is listed in the Acknowledgments.

                Author information
                http://orcid.org/0000-0003-3155-6522
                Article
                PNTD-D-17-01473
                10.1371/journal.pntd.0006213
                5832200
                29494581
                789f1743-a6c4-422d-9eeb-4d48aded97a7
                © 2018 Lim et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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                Page count
                Figures: 2, Tables: 4, Pages: 18
                Funding
                The authors received no specific funding for this work.
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