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      Comparison of antigen and antibody responses in repeat lymphatic filariasis transmission assessment surveys in American Samoa

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          Abstract

          Background

          Current WHO recommendations for lymphatic filariasis (LF) surveillance advise programs to implement activities to monitor for new foci of transmission after stopping mass drug administration (MDA). A current need in the global effort to eliminate LF is to standardize diagnostic tools and surveillance activities beyond the recommended transmission assessment survey (TAS).

          Methodology

          TAS was first conducted in American Samoa in 2011 (TAS 1) and a repeat TAS was carried out in 2015 (TAS 2). Circulating filarial antigen (CFA) and serologic results from both surveys were analyzed to determine whether interruption of LF transmission has been achieved in American Samoa.

          Principal findings

          A total of 1,134 and 864 children (5–10 years old) were enrolled in TAS 1 and TAS 2, respectively. Two CFA-positive children were identified in TAS 1, and one CFA-positive child was identified in TAS 2. Results of both surveys were below the threshold for which MDA was warranted. Additionally, 1,112 and 836 dried blood spots from TAS 1 and TAS 2, respectively were tested for antibodies to Wb123, Bm14 and Bm33 by luciferase immunoprecipitation system (LIPS) assay and multiplex bead assay. In 2011, overall prevalence of responses to Wb123, Bm14, and Bm33 was 1.0%, 6.8% and 12.0%, respectively. In 2015, overall prevalence of positive Bm14 and Bm33 responses declined significantly to 3.0% (p<0.001) and 7.8% (p = 0.013), respectively.

          Conclusions/Significance

          Although passing TAS 1 and TAS 2 and an overall decline in the prevalence of antibodies to Bm14 and Bm33 between these surveys suggests decreased exposure and infection among young children, there were persistent responses in some schools. Clustering and persistence of positive antibody responses in schools may be an indication of ongoing transmission. There is a need to better understand the limitations of current antibody tests, but our results suggest that serologic tools can have a role in guiding programmatic decision making.

          Author summary

          Lymphatic filariasis (LF), endemic in 72 countries, is a debilitating mosquito-transmitted parasitic disease caused by filarial worms. The Global Program to Eliminate Lymphatic Filariasis (GPELF) aims to interrupt transmission through mass drug administration (MDA) and to reduce suffering caused by the disease. At the start of GPELF in 2000 it was estimated that approximately 1.4 billion people were at risk for infection. By the end of 2016, primarily through successful MDA programs, the global number of people requiring interventions was reduced to 856.4 million. Current recommendations by the World Health Organization for LF surveillance advise programs to implement activities to monitor for new foci of transmission after stopping MDA. A current need in the global effort to eliminate LF is to standardize diagnostic tools and surveillance activities beyond the recommended transmission assessment survey (TAS). Two TAS were conducted in American Samoa; first in 2011 (TAS 1) and repeated in 2015 (TAS 2). In our evaluation, circulating filarial antigen and serologic results from both surveys were analyzed to determine whether interruption of LF transmission has been achieved in American Samoa. Despite passing TAS 1 and TAS 2, clustering and persistence of positive antibody responses in schools may be an indication of ongoing transmission. Results from our evaluation suggest that serologic tools can have a role in guiding programmatic decision-making.

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          Lymphatic filariasis and onchocerciasis.

          Mark Taylor, Achim Hoerauf, Moses J. Bockarie (2010)
          Lymphatic filariasis and onchocerciasis are parasitic helminth diseases that constitute a serious public health issue in tropical regions. The filarial nematodes that cause these diseases are transmitted by blood-feeding insects and produce chronic and long-term infection through suppression of host immunity. Disease pathogenesis is linked to host inflammation invoked by the death of the parasite, causing hydrocoele, lymphoedema, and elephantiasis in lymphatic filariasis, and skin disease and blindness in onchocerciasis. Most filarial species that infect people co-exist in mutualistic symbiosis with Wolbachia bacteria, which are essential for growth, development, and survival of their nematode hosts. These endosymbionts contribute to inflammatory disease pathogenesis and are a target for doxycycline therapy, which delivers macrofilaricidal activity, improves pathological outcomes, and is effective as monotherapy. Drugs to treat filariasis include diethylcarbamazine, ivermectin, and albendazole, which are used mostly in combination to reduce microfilariae in blood (lymphatic filariasis) and skin (onchocerciasis). Global programmes for control and elimination have been developed to provide sustained delivery of drugs to affected communities to interrupt transmission of disease and ultimately eliminate this burden on public health. Copyright © 2010 Elsevier Ltd. All rights reserved.
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            A Comprehensive Assessment of Lymphatic Filariasis in Sri Lanka Six Years after Cessation of Mass Drug Administration

            Ramakrishna Rao, Kumara Nagodavithana, Sandhya Samarasekera … (2014)
            Introduction Lymphatic filariasis (LF, caused by the mosquito borne filarial nematodes Wuchereria bancrofti, Brugia malayi, and B. timori), is a major public-health problem in many tropical and subtropical countries. The latest summary from the World Health Organization (WHO) reported that 56 of 73 endemic countries have implemented mass drug administration (MDA) with a combination of two drugs (albendazole with either ivermectin or diethycarbamazine), and 33 countries have completed 5 or more rounds of MDA in some implementation units [1]. With more than 4.4 billion doses of treatment distributed between 2000 and 2012, the Global Programme to Eliminate Lymphatic Filariasis (GPELF) is easily the largest public health intervention to date based on MDA. Bancroftian filariasis was highly endemic in Sri Lanka in the past [2]–[4]. The Sri Lankan Ministry of Health' Anti Filariasis Campaign (AFC) used a variety of methods to reduce filarial infection rates to low levels by 1999 [5], [6]. Sri Lanka was one of the first countries to initiate a LF elimination program based on GPELF guidelines [7]. The AFC provided annual MDA with diethylcarbamazine alone for three years starting in 1999. This was followed by five annual rounds of MDA with albendazole plus diethylcarbamazine in all 8 endemic districts (implementation units, IU) between 2002 and 2006. Various types of surveillance have been conducted by AFC and other groups since the MDA program ended in 2006 [8]–[12]. Post-MDA surveillance results (based on detection of microfilariae or Mf in human blood by microscopy) have consistently shown Mf rates much lower than the target value of 1% in all endemic areas [13]. The AFC also conducted school-based surveys for filarial antigenemia in 2008 according to WHO guidelines active at that time. Approximately 600 children were tested for circulating filarial antigenemia (CFA) in 30 schools in each of the 8 endemic districts, and no positive tests were observed (unpublished data, Sri Lanka Ministry of Health). WHO guidelines emphasize that LF elimination programs should provide care for people with acute and chronic clinical manifestations of filariasis [7], and the AFC has an excellent network of clinics that is devoted to this activity [13]. The present study represents a significant expansion of earlier post-MDA surveillance activities in Sri Lanka. Transmission assessment surveys (TAS) were performed according to current WHO guidelines [14], [15] for sampling primary school children to detect filarial antigenemia in each district. While TAS results may be useful for deciding whether MDA can be stopped, TAS cannot guarantee that LF transmission has been interrupted in evaluation units (EUs), which are typically districts with populations that may exceed 1 million. Therefore we conducted more intensive surveillance activities in smaller areas (Public Health Inspector “PHI” areas) that were considered to be at high risk for persistent filariasis to complement the TAS program. Provisional targets have been proposed for documenting the interruption of filariasis transmission based on studies of the effects of MDA in Egypt, which also has LF transmitted by Culex mosquitoes [16]. Targets proposed for treated populations after at least five years of effective MDA were 0.35 in two assays performed on different days were considered to be positive for antibody to Bm14. Microfilaria (Mf) testing was performed for people with positive filarial antigen tests (in community household surveys, school surveys, and TAS) with three-line blood smears (60 µl total volume of night blood tested). Detection of filarial DNA in mosquitoes Mosquitoes were sorted by experienced technicians. Blood fed, gravid, and semi-gravid Culex quinquefaciatus mosquitoes were identified by morphology and sorted into 4 pools of 20 mosquitoes per collection site. Two hundred and seventy-seven pools of mosquitoes (mean pool size of 17) were collected and tested from Peliyagodawatta in the pilot study that was performed in 2008. Approximately 200 pools were tested from each PHI area in later surveys. W. bancrofti DNA was detected in mosquito pools by qPCR as previously described [16], [20]. DNA isolation and PCR analysis for samples from the 2008 pilot study were performed by AFC personnel together with Washington University technicians in St. Louis. All subsequent PCR work was conducted by AFC personnel in the AFC laboratory in Colombo. Data collection and data management Demographic information including age, gender, documentation of informed consent, and a history of compliance with the previously administered MDA program was collected and entered into personal digital assistants (PDA) (Dell Axim ×51, Dell Inc. Round Rock, TX or HP iPAQ 211, Hewlett Packard, Palo Alto, CA) using a preloaded survey questionnaire. Participant data, specimen ID, and test results were linked using preprinted barcode labels as described by Gass et al [21]. AFC deployed 2 or 3 teams for blood collection and 2 or 3 teams for mosquito collection in each PHI, and teams were comprised of a mixture of personnel from the district and from AFC headquarters. Data collected by multiple teams were synchronized at AFC headquarters, and data were transferred to a laptop computer using LF field office data manager software designed by the Lymphatic Filariasis Support Center, Taskforce for Global Health, Decatur, GA. Transferred files were merged to create a master database, which was backed up using an external hard drive. Specimens and laboratory test results were linked to study subject numbers (or to trap site and pool number for mosquito data) using barcodes. Deidentified, cleaned data were transferred into Excel files (Microsoft Corp., Redmond, WA) for analysis at AFC and at Washington University. Spatial analysis GPS coordinates for human and mosquito sampling sites were plotted using ArcGIS 10.2.1 (ESRI, Redlands, CA) to show the location of households surveyed and mosquito trapping sites for each PHI. Waypoints were color coded to show the infection status of household residents and mosquitoes from these collection sites. School-based Transmission Assessment Surveys (TAS) TAS were performed in all 8 endemic districts in late 2012 or early 2013 according to WHO guidelines. The TAS program used districts as evaluation units (EUs) in 5 cases. However, 3 districts or areas with large populations (Colombo district plus Colombo town, Gampaha, and Galle) were each divided into two EUs for TAS. All EUs met criteria for conducting TAS by having completed 5 rounds of MDA in 2006 with high MDA compliance rates (>80%). All sentinel and spot check sites in each district had Mf prevalence rates well below 1% for several years prior to TAS. Since Sri Lanka has high primary school attendance rates (>95%), TAS surveys used the cluster method to sample students in 30–35 randomly selected schools per EU[15]. Systematic selection of school children was performed with Survey Sample Builder software, SSB.V.2.1 (http://www.ntdsupport.org/resources/transmission-assessment-survey-sample-builder). The TAS sampling strategy required filarial antigen testing of approximately 1500 primary grade children in each EU. Blood samples were collected with One Touch Ultra Soft lancet holders with disposable lancets (LifeScan, Inc., Milpitas, CA). Finger prick blood was collected into capillary tubes provided with the BinaxNow Filariasis cards, and 100 µl of blood was added directly to sample application pads of the cards according to the manufacturer's instructions. Tests were performed in the school auditorium, library, or health screening station immediately after blood collection, and read at 10 minutes. Antigen test results (positive or negative) were recorded manually using preprinted data collection forms. Children with positive filarial antigen tests were tested for microfilaremia with night blood smears as described above. Data analysis We used the software program PASW Statistics 18 (SPSS, now IBM Corporation, Armonk, NY) and JMP (SAS, Cary, NC). The Chi-square test was used to assess the significance of differences in categorical variables such as antigenemia rates. The correlation between human and mosquito infection parameters was analyzed by the Spearman rank test. Logistic regression was used to assess the independence of risk factors for filarial antigenemia. Graphs were produced with GraphPad Prism V. software (La Jolla, CA). Filarial DNA rates (maximum likelihood estimates with 95% confidence intervals) were calculated with PoolScreen 2.02 [22], [23]. To sharpen the analysis of risk factors for filarial infection, we limited the analysis to 14 PHI areas where one or more people had positive filarial antigen tests. All analyses were performed assuming simple random sampling for simplicity of exposition. A generalized linear mixed model was used to estimate design effects of household-based cluster sampling used in community surveys. This analysis was performed with data from the two PHIs with the highest surveyed CFA rates. Ethical review The study protocol for comprehensive surveillance in PHIs was reviewed and approved by institutional review boards at Washington University School of Medicine and at the University of Kelaniya in Sri Lanka (FWA 00013225). Prior to school surveys (both PHI surveys and TAS), study personnel held preliminary meetings with school principals and officials from the Sri Lankan Ministry of Education about the goals and procedures for the study. They also met with parents or guardians to discuss the study design and the significance of the study. Printed participant information sheets and written consent forms were provided to participants (or to parents/guardians) in Sinhalese, Tamil and English. Written consent was obtained from adults. Participation of minors required written consent from at least one parent or guardian plus assent by the child/minor. Consent was also documented electronically into PDAs by study personnel prior to collection of health information or blood samples. TAS surveys used preprinted paper forms for parental consent and other forms for data collection (school name, child name, age, sex, and CFA result). Results Community survey results Nineteen PHI surveys were conducted in 8 districts and in Colombo town between March 2011 and July 2013. Demographic information for survey participants is provided in Table 1, and results are summarized in Table 2 and Figure 1. Community CFA rates were 2% in 5 of 19 PHIs. Microfilaremia rates were 5%. Only three of 137 children with positive antibody tests (out of 6198 children tested for antibody from all 19 PHI areas) had positive CFA tests, and all three of these children were Mf negative. Antifilarial antibodies in community surveys Community antibody testing was performed in a subset of PHIs that were surveyed in the comprehensive surveillance study (Table S1). Although CFA and Mf rates in these communities were below provisional target levels, community antibody rates were high in all of these PHIs, and this probably reflects high infection rates that were present in these areas prior to implementation of the national MDA program. Relationships between different human filariasis parameters in community and school surveys Human filariasis parameters tended to be significantly correlated with each other [e.g., community Mf rate vs. community CFA rate (r = 0.63, P = 0.0018), school CFA rate vs. school antibody rate (r = 0.5, P = 0.0142), and community CFA rate vs. school CFA rate (r = 0.69; P = 0.0006)]. Transmission assessment survey results More than 17,000 primary grade school children were tested in TAS in 337 schools located in 11 EUs in 8 districts and in Colombo town (Table 5). The numbers of positive CFA tests were well below the TAS threshold level of 18 (critical cut-off value) in all EUs. Thus all EUs “passed” TAS including the coastal Galle District EU, where high rates for filariasis markers were noted in two PHI study areas. None of the 16 children with positive CFA tests in TAS surveys had microfilaremia. All CFA-positive children were treated with anti-filarial medications and follow-up surveys are in progress or planned to further assess people in areas with positive children. 10.1371/journal.pntd.0003281.t005 Table 5 Transmission assessment survey (TASa) results from 11 evaluation units (EUs) in 8 districtsb in in Sri Lanka. Evaluation Unit Population size/EU Number of primary grade schools included Number of primary grade children tested Number of children positive for filarial antigenemiac Colombo-RDHS 1,761,010 30 1716 2 (0.12, 0.03–0.4) Colombo-city 557,356 30 1555 2 (0.13, 0.04–0.4) Gampaha I 898,731 30 1642 1 (0.06, 0.01–0.3) Gampaha II 1,426,944 30 1462 0 (0) Kalutara 1,237,676 30 1585 4 (0.3, 0.10–0.6) Galle I 719,911 31 1557 7 (0.45, 0.22–0.9) Galle II 347,027 31 1543 0 (0) Matara 815,625 30 1591 0 (0) Puttalam 766,469 30 1583 0 (0) Kurunegala 1,629,958 35 1692 0 (0) Hambantota 607,404 30 1553 0 (0) Total 10,768,112 337 17479 16 (0.1, 0.06–0.1) a The critical cutoff value for assessing interruption of transmission was 18 in all EUs. b The 8 endemic districts were MDA implementation units. c BinaxNOW Filariasis tests were used for detection of filarial antigenemia. Data shown are the number of positive tests (% positive and 95% CI). Filarial DNA rates in mosquitoes Almost 3,900 pools (20 mosquitoes per pool) of blood fed, gravid or semi-gravid mosquitoes collected in 19 PHI areas were tested for filarial DNA by qPCR (Table 6). Filarial DNA rates exceeded the target of 0.25% in 10 of 19 PHIs. Mosquitoes from both PHIs surveyed in Galle district and one in Matara district had parasite DNA rates of more than 1%, and these rates were comparable to those seen in some filariasis endemic areas in Egypt with continued filariasis transmission following one or two rounds of MDA [24]. Upper confidence limits for filarial DNA rates were ≥1% in 5 of 19 PHIs surveyed. On the other hand, three of 19 PHIs surveyed had no positive mosquito pools. Most of the other filariasis parameters were also low in these PHIs. Mosquito DNA samples from Wattala were retested by qPCR at Washington University and confirmed to be negative. 10.1371/journal.pntd.0003281.t006 Table 6 Filarial DNA rates in Sri Lankan Culex quinquefasciatus mosquitoes by Public Health Inspector area. District PHI areaa PHI code Number of mosquitoes tested Number of pools tested b Number (%) of positive pools Filarial DNA rates in mosquitoes c Colombo Katukurunda C1 4000 200 3 (1.5) 0.07 (0.01–0.22) Sedawatta C2 4480 224 21 (9) 0.52 (0.31–0.80) Mattakkuliya C3 4000 200 13 (6.5) 0.34 (0.17–0.59) Borella C4 4000 200 26 (13) 0.69 (0.43–1.0) Gampaha Kelaniya G1 4320 216 22 (10) 0.54 (0.32–0.83) Wattala G2 4000 200 0 (0) 0 PeliyagodaW G3 4080 203 17 (8) 0.43 (0.24–0.71) Kalutara Panadura KA1 4000 200 9 (4.5) 0.23 (0.10–0.45) Kalutara N KA2 4080 204 28 (14) 0.74 (0.47–1.09) Galle Ambalangoda GL1 4000 200 52 (26) 1.49 (1.08–2.01) Unawatuna GL2 4000 200 54 (27) 1.56 (1.13–2.08) Matara Devinuwara M1 4160 208 9 (4) 0.22 (0.09–0.43) Weligama M2 4080 204 51 (25) 1.43 (1.03–1.92) Puttalam Chila town P1 4000 200 6 (3) 0.15 (0.05–0.34) Lunuwila P2 4160 208 0 (0) 0 Kurunegala Bamunawala KU1 4160 208 4 (1.9) 0.10 (0.02–0.25) Narammala KU2 4160 208 11 (5.2) 0.27 (0.13–0.50) Hambantota HT town H1 4000 200 0 (0) 0 Tanagalle H2 4080 204 2 (1) 0.05 (0.01–0.15) a Sentinel sites (PHIs) C3 and C4 were located in the city of Colombo. Sentinel site G3 is a PHFO area. b Each pool included 20 mosquitoes (blood fed, gravid and semigravid). c Filarial DNA was detected by qPCR. Rates of filarial DNA in mosquitoes (maximum likelihood and 95% CI) were estimated using PoolScreen2. Results are shown as pass (regular font), borderline (italics) or fail (bold) based on provisional endpoint criteria described in the Introduction. The percentages of positive mosquito trap sites were highly variable in different PHIs, and these rates were strongly correlated with percentages of pools positive for filarial DNA (r = 0.99, P 9) is to have an upper confidence limit of <2%. This target provides a very high level of confidence that the Mf rate will be less than 0.5% in the community with a much smaller sample size than what would be required for Mf testing. Additional studies will be needed to test the new proposed targets in different regions. We believe that these targets will be helpful for identifying areas that require continued surveillance. Next steps for areas that may have ongoing transmission following MDA Existing guidelines do not adequately address this issue. Four options to consider are resumption of MDA, implementation of test and treat programs, vector control, and watchful waiting. It may be difficult to justify resumption of MDA when Mf rates are well below 1% when one considers that many of those with persistent infections may have been noncompliant with MDA in the past. Test and treat campaigns may be more efficient for finding and treating those with persistent infections than MDA, and the Sri Lanka AFC has started to do this in Galle district. Our results suggest that adult males and people who do not recall having taken MDA in the past should be considered to be high priority target groups for test and treat programs. WHO has recommended vector control as a post MDA strategy [26]. Although vector control can be difficult to implement at the scale needed for LF elimination, surveillance results may identify hot spot areas where focused vector control may be feasible. Our finding that CFA rates were lower in people who reported using bed nets is interesting, although the logistic regression analysis suggested that lack of bed net use was not an independent risk factor for filarial infection. Bed nets are popular in Sri Lanka because of the mosquito nuisance factor and the risk of dengue. Beneficial effects of bed nets for LF have been reported from areas with Anopheles transmission [27], [28]. The Sri Lanka government should consider implementing a health education campaign to reinforce the popularity of bed nets and increase usage rates in areas with persistent LF. The longitudinal data from Peliyagodawatta are intriguing, because they suggest that some areas with filariasis parameters that do not meet our provisional criteria for interruption of transmission may spontaneously improve over time. Thus the strategy of watching, waiting, and retesting may be the best course of action for some areas with persistent LF. Other data from Peliyagodawatta on the natural history of filarial antigenemia in amicrofilaremic individuals in the post-MDA setting are reassuring. These results suggest that there is no pressing need to actively identify and treat asymptomatic and amicrofilaremic persons with positive filarial antigen tests following MDA. This is because the risk of such people developing microfilaremia is low, and antigenemia often clears over time without treatment. We believe that this study has contributed significant new information regarding post-MDA surveillance and low level persistence of filariasis following MDA. LF elimination is a dynamic process [29], and point estimates of persistent infection may be less important than trends over time. For this reason, we plan to restudy Peliyagodawatta and several other PHIs with elevated LF parameters three years after the evaluations described in this publication. Supporting Information Figure S1 Distribution of households and mosquito collection sites tested for filariasis in Chila Town PHI area in Puttalam district which has less evidence of persistent filariasis than Unawatuna PHI (shown in Fig 2). Panel A. Blue waypoints indicate households (HH) where all tested residents had negative filarial antigen tests; waypoints in red indicate houses with at least one infected subject (CFA positive). Panel B shows molecular xenomonitoring results. Trap sites with no mosquito pools positive for filarial DNA are shown in blue, and traps with one or more positive mosquito pools are shown in red. Filarial DNA was detected in mosquitoes collected in 10% of the traps in this PHI area. (TIFF) Click here for additional data file. Table S1 Community rates for circulating filarial antigenemia (CFA), microfilaremia (Mf), and IgG4 antibodies to filarial antigen Bm14 in selected public health inspector. (DOCX) Click here for additional data file. Table S2 Filarial infections by household and mosquito trap site in different Public Health Inspector (PHI) areas in Sri Lanka. (DOCX) Click here for additional data file. Checklist S1 STROBE statement. Checklist of items included in this cross-sectional study Rao et al., A Comprehensive Assessment of Persistent Lymphatic Filariasis in Sri Lanka Six Years after Cessation of Mass Drug Administration. (DOC) Click here for additional data file.
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              A Multicenter Evaluation of Diagnostic Tools to Define Endpoints for Programs to Eliminate Bancroftian Filariasis

              Katherine Gass, Madsen Beau de Rochars, Daniel Boakye … (2012)
              Introduction In 2000 the Global Programme to Eliminate Lymphatic Filariasis (GPELF) was launched, providing antifilarial drugs to millions of people through mass drug administration (MDA) programs. During the GPELF's first nine years over 2.6 billion treatments of antifilarial drugs were given to people in 48 countries through MDA programs [1]. The success of the GPELF has led to dramatic reductions of both microfilaremia and antigenemia levels in countries that have completed multiple rounds of MDA [2]; the challenge now is to determine when it is most appropriate to stop MDA [3]. The decision to stop MDA is complicated and a variety of tools have been suggested to guide the decision [4]. The first step is to define the parameter(s) that will be measured and the best diagnostic tool for assessing it. At least seven diagnostic tests are currently available for detecting indicators of LF exposure and infection. Selection of the best diagnostic test for use in stopping-MDA decisions requires consideration of each test's accuracy, technical requirements, programmatic feasibility and reliability [5], as well as confidence in test performance, especially since there is no single gold standard test for LF (see Discussion). Next, following the selection of a preferred diagnostic tool for defining the end-point of MDA, the question of how best to sample the population must be resolved. In response to these and other challenges, this study was planned to evaluate diagnostic tools to assess MDA program success by standardizing the tools now available, comparing their effectiveness in demonstrating the interruption of LF transmission, and selecting the most effective for deciding when MDA can be suspended [6]. A large multi-country study was conducted in 2007–2008 to compare the effectiveness of seven available diagnostic tests for detecting evidence of Wuchereria bancrofti infection or transmission following multiple rounds of MDA, in settings where infection prevalence was likely to be low. The goal of the study was to select the best diagnostic tool(s) that would allow for definition of program end-points that will maximize the likelihood that LF transmission has been interrupted. Such a tool(s) would be the cornerstone of programmatic decision-making. Methods Site Selection Studies were performed in French Polynesia, Ghana, Haiti, Sri Lanka, Zanzibar (United Republic of Tanzania) and Tuvalu, representing a broad diversity of settings in which LF is present. The study sites were believed to have low residual microfilaremia prevalence rates in the range of 0.5–2% following at least five rounds of MDA [7]. Participant Selection One community survey and one school survey were performed in each country. Community surveys sampled residents of selected households between the ages of 3 and 80. School surveys were performed in primary schools that serve children in the same villages as those selected for the community surveys. First and fourth year students (approximately 6 and 10 years old, respectively) were selected for inclusion in the school surveys. Children from the school survey were excluded if they had already been included in the community survey. Since the primary objective of this first phase of research was not to assess program end-points in the specific study sites, but rather to compare test effectiveness in the same groups of individuals late in program activities, convenience sampling was used to select both communities and schools. However, selection of participants within each site was conducted randomly whenever possible. Standard Operating Procedures A workshop with all the investigators was held in Atlanta, GA to establish the study protocols and Standard Operating Procedures (SOP) [7] prior to the start of the study. For each country, a team of experienced investigators traveled to the study site to train the local team on data collection methods and laboratory procedures in accordance with the SOP. Demographic Data Collection All information on the participants was collected using handheld personal digital assistants (PDA) (Dell Axim X50 or X51) that eliminated the need for paper records. Unique identifiers were printed on labels which provided visual identification of the number as well as barcodes acquired by a Bluetooth® scanner (CHS 7p v.1, Socket Mobile) to facilitate specimen management. The PDAs were equipped with GPS devices (GlobalSat, City of Industry, CA, USA) and GPS coordinates were captured at each house and school visited. A questionnaire was administered to collect demographic information that included age, gender, bednet use, self-reported filarial disease status and compliance with the most recent MDA. Multiple teams could register households at the same time, and data collected could be synchronized in the field to create one master database. Each night all data were uploaded to a field laptop and a backup of the data was created on an external drive. Data were electronically transmitted in the form of encrypted excel files to the central analysis database at the Task Force for Global Health (Atlanta, GA). Blood and Urine Collection All field sample collections and field and laboratory tests were conducted according to the SOP. Blood and urine samples were collected 6–24 months following the last MDA. The periodicity of W. bancrofti required that blood collection in the community surveys be performed during the peak hours of microfilaremia (during daytime hours for French Polynesia and Tuvalu and between 10 pm and 2 am in the remaining countries where the parasite was nocturnally periodic). In the areas with nocturnal periodicity, collection teams had the option of registering households during the day or night. Teams that registered households during the day later returned in the evening to take the blood samples. Approximately 0.3–0.4 ml of blood was collected by finger prick from each participant into an EDTA coated blood collection tube and stored in coolers overnight before assays were performed the next day in the field laboratory. Up to six diagnostic assays were performed (with the exception of Ghana, which conducted up to five assays). Three of the assays were conducted in the field laboratory: blood smear (MF), ICT (Immunochromatographic test, Binax, Scarborough, ME), and the PanLF Rapid (MBDr, Selangor, Malaysia). The one exception to this was French Polynesia where the blood smear, ICT and PanLF assays were processed at the Institut Louis Malardé. The Bm14 antibody detection and Og4C3 antigen detection assays were conducted in five reference laboratories (see Table 1) and the PCR (Polymerase Chain Reaction) tests were conducted at Smith College in Northampton, MA, USA. 10.1371/journal.pntd.0001479.t001 Table 1 Laboratory locations of diagnostic tests. Bm14 PanLF Urine SXP ICT Og4C3 Blood Smear PCR* French Polynesia ILM ILM Aichi ILM ILM ILM Smith Ghana Noguchi – – Field lab Noguchi Field lab Smith Haiti CDC Field lab Aichi Field lab CDC Field lab Smith Sri Lanka Wash U. Field lab – Field lab Wash U. Field lab Wash U. Tuvalu Wash U. Field lab Aichi Field lab Smith Field lab Smith Zanzibar Smith Field lab Aichi Field lab Smith Field lab Smith Aichi = Aichi Medical University (Japan). CDC = Centers for Disease Control and Prevention (USA). Field Lab = in-country laboratory created, or in use, by field team. ILM = Institut Louis Malarde (French Polynesia). Noguchi = Noguchi Memorial Institute for Medical Research (Ghana). Smith = Smith College (USA). Wash U = Washington University in St. Louis, Missouri (USA). *Based on 10 µl blood specimen. For school participants, four diagnostic assays were performed: two conducted on site (ICT and PanLF) and two conducted in reference laboratories (Bm14 and Og4C3). Because microfilaremia levels were not assessed in the school surveys, blood collection occurred during the day at the time of registration. Urine cups were labeled and distributed at the time of enrollment, and each participant was asked to provide a urine sample (with the exception of those in Ghana and Sri Lanka). In the field laboratory, approximately 5 ml of urine was transferred into a smaller vial and sodium azide (0.1%) was added as a preservative [8]. Urine vials were shipped to Aichi Medical University (Nagoya, Japan) for anti-filarial antibody testing using the W. bancrofti SXP recombinant antigen. Table 2 summarizes the tests by: survey, specimen, test type, and target detected. 10.1371/journal.pntd.0001479.t002 Table 2 Diagnostic test characteristics. Test Name Surveys Used Specimen Type Test Type Target Detected Bm14 Community & School Bloodspot ELISA Antifilarial antibody PanLF Community & School Blood Rapid cassette test Antifilarial antibody Urine SXP Community & School Urine ELISA Antifilarial antibody ICT Community & School Blood Rapid card test Filarial-antigen Og4C3 Community & School Bloodspot ELISA Filarial-antigen Blood Smear Community 60 µl Blood Blood film Microfilariae PCR * Community 10 µl Bloodspot qPCR Microfilariae *Based on 10 µl blood specimen. Field Tests Blood films were used to determine MF levels in the communities. Sixty microliters of blood was streaked onto a glass slide (3 lines×20 µl), stained with Giemsa and read in the field laboratories. Filarial-antigen status was determined by ICT (Binax, Scarborough, ME, USA). EDTA anti-coagulated blood was used and the test was performed according to manufacturer's instructions. Antigen positive individuals were offered treatment with albendazole plus DEC or ivermectin. Anti-filarial antibody status was determined using the PanLF Rapid (MBDr, Selangor, Malaysia) cartridge test. EDTA anti-coagulated blood (35 µl) was placed on the sample pad and the test was performed according to manufacturer's instructions. The remaining blood was spotted onto two filter paper disks (TropBio, Townsville, Australia) (60 µl per disk), dried and stored until shipped to participating laboratories for further testing. Both the ICT and PanLF tests were conducted at the schools and blood was spotted onto filter paper disks. All field test results were entered into the PDA immediately and subsequently uploaded to the field laptop each night. Laboratory Tests Three laboratory assays were performed on the specimens, all of which were previously validated against non-endemic samples. One bloodspot (10 µl) was used for an enzyme linked immunosorbent assay (ELISA) to determine anti-filarial antibody reactivity to the recombinant antigen Bm14 (Cellabs, Sydney, Australia). Bloodspots were eluted overnight at 4°C and processed the following day according to the agreed SOP. Three dried bloodspots (3×10 µl) were used to measure quantitative filarial antigen levels by the Og4C3 ELISA (TropBio, Townsville, Australia). Bloodspots were eluted overnight at 4°C and boiled the next day. Boiled samples were centrifuged and supernatants were incubated overnight on a 96-well microtiter plate pre-coated with an Og4C3 monoclonal capture antibody. Plates were processed the next day. One bloodspot (10 µl) was used for PCR to detect the presence of parasite DNA. Bloodspots were pooled into groups of 10 individuals for initial testing. DNA was extracted using the QIAGEN DNeasy kit (Valencia, CA, USA) and analyzed by real-time PCR (qPCR) [9]. If a pool was positive, each sample that comprised the positive pool was tested individually using an additional 10 µl bloodspot. Results for all laboratory tests were entered into a standardized Microsoft Excel® spreadsheet and sent electronically to the Task Force for Global Health to be entered into the analysis database. Ethics Statement The research proposal was submitted by the principal investigators of each participating country to the local review board, or in certain cases an outside review board, as deemed most appropriate. All proposals were accepted by the respective review boards before research took place. The US-based laboratories analyzing results received an exemption from the IRBs, since all specimens and results were de-linked from personal identifiers. All subjects provided informed consent to participate in the study. More detailed information regarding the IRB institution for each country and the method for obtaining participant consent are described below. In French Polynesia, the Ethics Committee approved the French Polynesian study protocol and work. A consent form was read to all a subjects and written agreement of consent was required from subjects in order to participate in the study. Assent was obtained from children and a written consent was required from their parent or guardian. In addition to obtaining written consent from participants, interviewers documented receipt of consent for all participants using handheld PDA devices. For Ghana, the Noguchi Memorial Institute for Medical Research's Institutional Review Board approved the study protocol and work. Informed written consents were obtained from all individuals 18 years of age and above. For individuals aged 6–17 years informed assent was sought from all individuals, in addition to written consent of the parent or responsible adult. In addition to obtaining written consent from participants, interviewers documented receipt of consent for all participants using handheld PDA devices. The procedure was explained to all children 3–5 years of age, in addition to written consent of the parent or designated guardian. In Haiti the Centers for Disease Control IRB committee approved an amendment to a previously approved study protocol. Informed consent was obtained from each participant. The CDC IRB granted the team the right to obtain oral consent (assent for children of age 6 years or younger and consent of their parents) because most participants were unable to read and the research presented no more than minimal risk of harm to the subjects. Interviewers documented receipt of verbal consent for all participants using handheld PDA devices. In Sri Lanka both the Washington University IRB and the Sri Lanka Ministry of Health approved the study protocol and work. Both institutions considered the survey to be public health practice (evaluation of the national LF elimination program) and as a result did not require formal IRB submission; waiver letters were obtained. Field teams used consent scripts and obtained verbal consent (assent from children). Participation by children required consent from at least one parent plus assent from the child. The Washington University IRB and Sri Lanka Ministry of Health both approved the collection of verbal consent for the survey because the research was deemed to present no more than minimal risk of harm to the subjects. Interviewers documented receipt of verbal consent for all participants using handheld PDA devices. For Tuvalu the human research ethics committee at James Cook University approved the protocol and study. The ethical review committee at James Cook University granted the right to obtain verbal consent, as opposed to written consent, for this study, as the study was considered to present minimal risk of harm to the subjects. Assent was obtained from children, along with verbal consent from their parent or guardian. Interviewers documented receipt of verbal consent for all participants using handheld PDA devices. Finally, the Ethical Review Committee in Zanzibar (Zanzibar Health/Medical Task Force) approved the Zanzibar study protocol and work. For the community all participants were given consent forms to sign while for the school children parents/guardians of the children were informed of the study through School Committee meetings and an informed consent letter was handed over to them to be signed. In addition to obtaining written consent from participants, interviewers documented receipt of consent for all participants using handheld PDA devices. Analyses All data were compiled and managed using SQL server (2005, Microsoft Corporation®) and imported to SAS® v.9.2 (Statistical Analysis System; North Carolina) for analyses. Unless otherwise stated, all statistically significant associations were determined by setting the probability of a Type I error at 5% (α = 0.05). Univariate analyses of country, age, and gender were calculated for all specimens with results reading “positive”, “negative”, and “indeterminate” (Tables 2 and Table 3). For all remaining analyses results were limited to specimens testing “positive” or “negative.” 10.1371/journal.pntd.0001479.t003 Table 3 Demographic information by country and survey location. Location Measure French Polynesia Ghana Haiti Sri Lanka Tuvalu Zanzibar All Countries Community Age (median) 33 17 17 26 39 24 25 Age (IQR) 16–48 10–40 10–28 13–40 25–50 14–41 13–43 Percent Male 48 43 41 49 47 39 44 Total Tested 1018 1107 999 1167 1124 1028 6443 School Age (median) 7 7 7 7 9 9 7 Age (IQR) 7–10 6–10 6–10 6–10 7–10 6–10 6–10 Percent Male 50 49 49 63 48 48 51 Total Tested 365 359 323 310 357 356 2070 All Age (median) 20 12 12 19 29 16 17 Age (IQR) 9–42 8–30 7–23 8–36 10–46 10–36 9–37 Percent Male 48 44 43 52 47 41 46 Total Tested 1383 1466 1322 1477 1481 1384 8513 While five of the seven diagnostic tests provided qualitative (positive/negative) results, two provided quantitative results (Og4C3 and Bm14) in the form of unit values. In order to dichotomize these quantitative results, a cut-off value was defined for the Og4C3 and Bm14 tests, independently, such that all results with a unit value greater than the cut-off were considered “positive.” Receiver Operating Characteristic (ROC) curves were used to determine the best cut-off values, by plotting ‘sensitivity’ by ‘1-specificity’ at various signal to cut-off ratios using SAS®. ROC analysis requires identifying clearly positive and negative specimens whose assay values can be applied to the analysis, but since there is no true ‘gold standard’ for defining LF infection, operational criteria based on multiple tests were used to define these groups. This manuscript followed the Standards for the Reporting of Diagnostic accuracy studies (STARD) (Checklist S1). Results A total of 8513 people from the six countries participated in the study; 6443 through the community surveys and the remaining 2070 through the school surveys (Table 3). Specimens from these participants were used to conduct 47,110 diagnostic tests (Table 4). Of the 47,110 tests performed, 7481 test results (15.9%) were excluded from the subsequent analyses due to invalid or indeterminate test results (Table 5). Among the excluded results were all of the Bm14 tests for Sri Lanka, Tuvalu and Zanzibar (4006 tests) due to changes in the performance of the commercially manufactured kits. In addition to the Bm14, all of the PanLF and blood smear results from Zanzibar (a total of 2,329 tests) were excluded due to technical uncertainties affecting the quality of the results. Diagrams describing the process by which participant specimens were tested, excluded and classified for each of the antibody, antigen and microfilariae tests are available in the supplementary Texts S1, S2, and S3. 10.1371/journal.pntd.0001479.t004 Table 4 Specimens and tests performed by country of origin. Test Name French Polynesia Ghana Haiti Sri Lanka Tuvalu Zanzibar All Countries PanLF 1372 0 1269 1399 1448 1377 6865 Bm14 1329 1159 1214 1463 1245 1298 7708 Urine SXP 1268 0 1285 0 955 1366 4874 ICT 1359 1372 1266 1449 1455 1316 8217 Og4C3 1355 1355 1179 1432 1333 1126 7780 PCR * 1005 972 893 1161 1063 886 5980 Blood Smear 713 1081 882 1043 1015 952 5686 TOTAL 8401 5939 7988 7947 8514 8321 47110 *Based on 10 µl blood specimen. 10.1371/journal.pntd.0001479.t005 Table 5 Invalid or indeterminate test results by country (excluded from remaining analyses). Test French Polynesia Ghana Haiti Sri Lanka Tuvalu Zanzibar All Countries PanLF 66 – 48 435 382 1377 2308 Bm14 0 0 0 1463 1245 1298 4006 Urine SXP 0 – 0 – 0 0 0 ICT 25 119 33 1 7 30 215 Og4C3 0 0 0 0 0 0 0 PCR * 0 0 0 0 0 0 0 Blood Smear 0 0 0 0 0 952 952 TOTAL 91 119 81 1899 1634 4009 7481 Note: These test results make up 15.9% of the total (47,110) results. *Based on 10 µl blood specimen. ROC curves were used to determine the unit value cut-point to distinguish ‘positive’ and ‘negative’ results for the Og4C3 and Bm14 tests. For the Og4C3 antigen assessment true positives were defined as those individuals with positive specimens for either the blood smear (MF) test or PCR (parasite DNA). True negatives were defined as individuals with negative blood smears and PCR results (both negative or one negative and the other not assessed), plus a negative by ICT and a Bm14 antibody value 50 50.3 402 28.7 691 42.8 612 11.3 954 11.2 935 2.4 882 1.9 942 TOTAL 37.0 3702 17.5 5861 20.5 4874 8.6 8049 7.6 7780 1.6 5686 1.3 5980 *Based on 10 µl blood specimen. Though the overall levels of positivity were similar within targets of detection (antibody, antigen or microfilaremia), at the individual level the tests differed significantly. A comparison of the blood smear and PCR results using McNemar's test, matched on participant, found a significant difference between the two tests (p = 0.024). Likewise, a comparison of the ICT and Og4C3 results found the two antigen tests to be significantly different (p = 0.003). The prevalence of antifilarial antibodies differed significantly (p<0.0001) between Bm14, PanLF, and urine SXP tests. The results from all seven diagnostic tests indicated a significant age-prevalence trend of increasing positivity with age (p<0.0001) (Table 8). Of the diagnostic tests, the Bm14 and PanLF were found to be the most reactive in the youngest age groups. In the school studies, which focused on a comparison of 5–7 and 9–11 year olds, there were no significant differences in test results between the two age groups, and the results were subsequently pooled. The test concordance tables (Tables 9, 10, 11,12) record the pair-wise comparisons of test results within the school and community surveys. The resulting estimates can be considered the pair-wise sensitivity of the test. In the school survey, Og4C3 picked up 57% of the ICT positive results, whereas ICT picked up 51% of the Og4C3 positive results (Table 9). Among the antibody tests, Bm14 identified 90% of the positive PanLF results, whereas PanLF only identified 41% of the Bm14 results. These differences reflect the greater sensitivity of the ELISAs compared to the rapid tests. The urine SXP tests consistently identified about a quarter of the positive results from the remaining four tests. 10.1371/journal.pntd.0001479.t009 Table 9 Positive-to-positive concordance in school survey. COMPARISON TEST (Numerator) INDEX TEST (Denominator) BM14 PANLFBC URSXP ICT OG4C3 BM14 120/292 (41%) 38/283 (13%) 45/311 (14%) 53/310 (17%) PanLF 120/133 (90%) 33/136(24%) 44/145 (30%) 54/138 (39%) Urine SXP 38/42 (90%) 33/44 (75%) 16/69 (23%) 18/64 (28%) ICT 45/61 (73%) 44/63 (69%) 16/66 (24%) 42/74 (57%) Og4C3 53/63 (84%) 54/64 (84%) 18/77 (23%) 42/82 (51%) Note: Fractions represent the number of positive results for each test (numerator) out of those that were positive by the index test (denominator). The results are of the form: proportion (%). The number of positive index tests (denominator) changes by column because it only includes specimens with valid results by the comparison test (numerator). 10.1371/journal.pntd.0001479.t010 Table 10 Positive-to-positive concordance in community survey. COMPARISON TEST (Numerator) INDEX TEST (Denominator) BM14 PANLFBC URSXP ICT OG4C3 BLOOD SMEAR PCR* BM14 463/903 (51%) 386/905 (43%) 231/1015 (23%) 237/1033 (22%) 54/904 (6%) 55/1044 (5%) PanLF 463/516 (90%) 370/714 (52%) 216/869 (25%) 220/841 (26%) 47/783 (6%) 47/854 (5%) Urine SXP 386/428 (90%) 370/582 (64%) 181/878 (21%) 193/829 (23%) 36/572 (6%) 36/853 (4%) ICT 231/357 (65%) 216/384 (56%) 181/455 (40%) 299/560 (53%) 70/468 (15%) 60/571 (11%) Og4C3 237/323 (73%) 220/292 (75%) 193/367 (53%) 299/485 (62%) 76/397 (19%) 68/503 (14%) Blood Smear 54/75 (72%) 47/65 (72%) 36/64 (56%) 70/88 (80%) 76/87 (87%) 52/85 (61%) PCR * 55/62 (89%) 47/60 (78%) 36/66 (55%) 60/77 (78%) 68/75 (91%) 52/69 (75%) Note: Fractions represent the number of positive results for each test (numerator) out of those that were positive by the index test (denominator). The results are of the form: proportion (%). The number of positive index tests (denominator) changes by column because it only includes specimens with valid results by the comparison test (numerator). *Based on 10 µl blood specimen. 10.1371/journal.pntd.0001479.t011 Table 11 Negative-to-negative test concordance in school survey. COMPARISON TEST (Numerator) INDEX TEST (Denominator) BM14 PANLFBC URSXP ICT OG4C3 BM14 334/347 (96%) 338/342 (98%) 628/644 (98%) 645/655 (98%) PanLF 334/506 (66%) 566/577 (98%) 905/924 (98%) 880/890 (98%) Urine SXP 338/583 (57%) 566/669 (84%) 1012/1062 (95%) 921/980 (93%) ICT 628/894 (70%) 905/1006 (89%) 1012/1065 (95%) 1740/1780 (97%) Og4C3 645/902 (72%) 880/964 (91%) 921/967 (95%) 1740/1772 (98%) Note: Fractions represent the number of negative results for each test (numerator) out of those that were negative by the index test (denominator). The results are of the form: proportion (%). The number of negative index tests (denominator) changes by column because it only includes specimens with valid results by the comparison test (numerator). 10.1371/journal.pntd.0001479.t012 Table 12 Negative-to-negative test concordance in community survey. COMPARISON TEST (Numerator) INDEX TEST (Denominator) BM14 PANLFBC URSXP ICT OG4C3 BLOOD PCR* BM14 827/880 (94%) 825/867 (95%) 1394/1520 (91%) 1524/1610 (94%) 1404/1425 (98%) 1585/1592 (99%) PanLF 827/1267 (65%) 1401/1613 (86%) 2376/2544 (93%) 2432/2504 (97%) 2137/2155 (99%) 2512/2525 (99%) Urine SXP 825/1344 (61%) 1401/1745 (80%) 2380/2654 (89%) 2296/2470 (92%) 1595/1623 (98%) 2519/2549 (98%) ICT 1394/2178 (64%) 2376/3029 (78%) 2380/3077 (77%) 4903/5089 (96%) 3966/3984 (99%) 5149/5166 (99%) Og4C3 1524/2320 (65%) 2432/3053 (79%) 2296/2932 (78%) 4903/5164 (94%) 4051/4062 (99%) 5281/5288 (99%) Blood Smear 1404/2254 (62%) 2137/2873 (74%) 1595/2131 (74%) 3966/4364 (90%) 4051/4372 (92%) 4375/4392 (99%) PCR * 1585/2574 (61%) 2512/3319 (75%) 2519/3336 (75%) 5149/5660 (90%) 5281/5716 (92%) 4375/4408 (99%) Note: Fractions represent the number of negative results for each test (numerator) out of those that were negative by the index test (denominator). The results are of the form: proportion (%). The number of negative index tests (denominator) changes by column because it only includes specimens with valid results by the comparison test (numerator). *Based on 10 µl blood specimen. In the community survey, Og4C3 detected 87% and 91% of the blood smear and PCR positive results, respectively, while ICT detected 80% and 78% of the blood smear and PCR positive results, respectively (Table 10). The positive concordance between ICT and Og4C3 ranged from 53% (ICT positives testing positive by Og4C3) to 62% (Og4C3 positives testing positive by ICT). Of the microfilaremic individuals (positive by blood smear) only 61% were positive by a 10 µl PCR. Conversely 75% of PCR positive individuals were also positive by blood smear. Among the antibody tests, Bm14 identified 90% of individuals positive by PanLF or urine SXP. Negative test concordance in the school survey (Table 11) revealed that 98% of antibody negative individuals (by Bm14 or PanLF) also tested negative by the antigen tests (ICT or Og4C3) (i.e. few people had filarial antigenemia in the absence of a detected antibody response). Bm14 had the poorest negative concordance with the remaining tests in the school surveys; only 66–72% of those specimens negative by PanLF, urine SXP, ICT or Og4C3 were also negative by Bm14. However, since antibody tests are expected to be the most sensitive at detecting exposure to LF, it is possible that specimens negative for antigenemia would still be ‘true positive’ for Bm14 antibody. The negative concordance of the antigen tests with the antibody tests was somewhat less in the community survey compared to the school survey, with 90–97% of antibody negative specimens (by Bm14 or PanLF) also testing antigen negative (by ICT or Og4C3) (Table 12). The pair-wise specificity of Bm14 was similarly low in the community survey, as compared to the school survey, with Bm14 identifying as negative approximately two thirds of results that were negative by any of the remaining tests. Comparatively PanLF identified as negative 74–94% of results that were negative by the remaining six tests. In the absence of a true gold standard test for LF infection, operational definitions of positive and negative gold standards were used to calculate sensitivity and specificity. To measure sensitivity, ‘true positives’ were defined as being either blood smear or PCR positive. The sensitivity of the assays therefore relates to the sensitivity for detecting microfilaremic infections, a measure of justifiable interest to the global LF elimination program, since microfilariae are required to transmit infection. It is more difficult to define a gold standard for specificity of assays since it is recognized that exposure alone can convert individuals to positive-antibody status. Consequently, ‘true negatives’ for antibody tests cannot be defined based on the results of the antigen and parasite tests, making it impossible to calculate the specificity for the antibody tests. Specificity of the antigen tests can be assessed if one evaluates the ability of the antigen assays to identify individuals who are amicrofilaremic and have no antibody evidence of infection or exposure to infection. ‘True negatives’ for the antigen tests were therefore defined based on negative blood smear and PCR results (both negative or one negative and the other not assessed) as well as negative results for both Bm14 and PanLF. It is important to note that this was a conservative definition of antigen specificity, as only antibody-negative individuals were eligible to be considered ‘true negatives’ by the antigen tests (see Discussion). Sensitivity and specificity of test performance was calculated using the best-estimate gold standards as defined above. These calculations were limited to French Polynesia, Ghana, and Haiti due to missing values for Bm14 in the remaining countries. Overall, the ICT test was found to be 76% sensitive at detecting microfilaremic infections and 93% specific at identifying individuals negative for both microfilariae and antifilarial antibody (Table 13). Using the same gold standard estimates, Og4C3 was found to be 87% sensitive and 95% specific. Stratifying the results by country revealed a high degree of variability in these estimates. ICT sensitivity ranged from 61% in Ghana to 79% in Haiti and French Polynesia, while ICT specificity ranged from 89% in Haiti to 94% in Ghana. Similarly, the sensitivity of Og4C3 assays ranged from 72% in Ghana to 93% in French Polynesia, while Og4C3 specificity ranged from 92% in Ghana to 99% in French Polynesia. It is important to note that a portion of the variability is due to the relatively small sample sizes in the country-specific results, caused by the gold standard criteria. 10.1371/journal.pntd.0001479.t013 Table 13 Sensitivity, specificity, and predictive values for antigen tests. ICT Og4C3 % (N) 95% Confidence Interval % (N) 95% Confidence Interval All Countries a Sensitivity 75.5 (94) (66.8, 84.2) 87.2 (94) (80.5, 94.0) Specificity 92.5 (1647) (91.2, 93.7) 94.6 (1647) (93.5, 95.7) Pos. Predictive Value 36.4 (195) (29.7, 43.2) 48.0 (171) (40.5, 55.4) Neg. Predictive Value 98.5 (1546) (97.9, 99.1) 99.2 (1570) (98.8, 99.7) French Polynesia Sensitivity 79.3 (29) (64.6, 94.1) 93.1 (29) (83.9, 100.0) Specificity 92.3 (517) (90.0, 94.6) 98.6 (517) (97.6, 99.6) Pos. Predictive Value 36.5 (63) (24.6, 48.4) 79.4 (34) (65.8, 93) Neg. Predictive Value 98.8 (483) (97.8, 99.8) 99.6 (512) (99.1, 100.0) Ghana Sensitivity 61.1 (18) (38.6, 83.6) 72.2 (18) (51.5, 92.9) Specificity 94.3 (754) (92.6, 96.0) 91.6 (754) (89.7, 93.6) Pos. Predictive Value 20.4 (54) (9.6, 31.1) 17.1 (76) (8.6, 25.6) Neg. Predictive Value 99.0 (718) (98.3, 99.7) 99.3 (696) (98.7, 99.9) Haiti Sensitivity 78.7 (47) (67.0, 90.4) 89.4 (47) (80.5, 98.2) Specificity 89.1 (376) (86.0, 92.3) 94.9 (376) (92.7, 97.2) Pos. Predictive Value 47.4 (78) (36.4, 58.5) 68.9 (61) (57.2, 80.5) Neg. Predictive Value 97.1 (345) (95.3, 98.9) 98.6 (362) (97.4, 99.8) Definition of antigen test accuracy. ‘True Positive’: Blood Smear or PCR (+). ‘True Negative’: Blood Smear and PCR not (+); Bm14 and PanLF not (+). a Includes French Polynesia, Ghana and Haiti only; others excluded due to missing values for Bm14. The sensitivity of the antibody tests at detecting microfilaremic individuals was 81% for Bm14, 73% for PanLF and 55% for SXP in urine (Table 14). Again, there was significant variability in these estimates at the country level, with Bm14 sensitivity estimates ranging from 50% in Ghana to 92% in French Polynesia. PanLF sensitivity ranged from 50% in Tuvalu to 77% in French Polynesia. Urine SXP sensitivity ranged from 32% in Haiti to 92% in French Polynesia. As with the antigen results, small sample size due to the limited number of microfilaremic individuals, is likely to account for some of the variability in the sensitivity estimates. 10.1371/journal.pntd.0001479.t014 Table 14 Sensitivity, specificity, and predictive values for antibody tests. PanLF Bm14 Urine SXP Rate 95% Confidence Interval Rate 95% Confidence Interval Rate 95% Confidence Interval All Countries Sensitivity 73.2 (82) (63.5, 82.8) 81.1 (74) (72.2, 90.0) 54.5 (77) (43.4, 65.7) Neg. Predictive Value 99.1 (2390) (98.7, 99.5) 98.2 (790) (97.3, 99.1) 97.7 (1522) (96.9, 98.5) French Polynesia Sensitivity 76.9 (26) (60.7, 93.1) 92.3 (26) (82.1, 100) 92.3 (26) (82.1, 102.6) Neg. Predictive Value 99.1 (675) (98.4, 99.8) 99.5 (438) (98.9, 100) 99.6 (539) (99.1, 100) Ghana Sensitivity – – 50.0 (16) (25.5, 74.5) – – Neg. Predictive Value – – 98.8 (680) (98.0, 99.6) – – Haiti Sensitivity 70.8 (48) (58.0, 83.7) 75.0 (48) (62.8, 87.2) 31.9 (47) (18.6, 45.2) Neg. Predictive Value 96.8 (447) (95.3, 98.5) 96.6 (336) (94.7, 98.5) 94.2 (554) (92.3, 96.2) Sri Lanka Sensitivity 66.7 (3) (13.3, 100) – – – – Neg. Predictive Value 99.9 (684) (99.6, 100) – – – – Tuvalu Sensitivity 50.0 (2) (0, 100) – – 50.0 (2) (0, 100) Neg. Predictive Value 99.8 (548) (99.5, 100) – – 99.7 (396) (99.3, 100) Zanzibar Sensitivity – – – – 42.9 (7) (6.2, 79.5) Neg. Predictive Value – – – – 99.3 (565) (98.6, 100) Definition of antibody test accuracy. ’True Positive’: Blood Smear or PCR (+). ‘True Negative’: Blood Smear and PCR not (+); ICT and Og4C3 not (+). Discussion Deciding whether or not to stop MDA will be expensive and laborious for countries because of both the sampling and testing requirements, so the selection of the diagnostic tool to use is of paramount importance. Accuracy, programmatic feasibility, testing requirements, time and cost must all be factored into the evaluation of the potential diagnostic tools [10]. The current study arose in response to this challenge. A summary of the features and performance of the seven diagnostic tests evaluated is presented in the supporting table at the end of this paper (Table S1). A common theme that emerges from this multi-country study is that the majority of the tests did not perform as well as expected, with regards to both accuracy and reliability. Though this finding is disappointing, it is important to note that the study represents an effectiveness trial, with the majority of the tests being conducted under varying conditions on-site or in field laboratories by local technicians. Though all the technicians were well-schooled, there were differences in adherence to established protocols. Indeed, the lessons learned with respect to test performance in this multi-country setting provide valuable insight and will hopefully lead to future test improvements. Some common areas identified for improvement across many of the tests include the need for thorough training of test-readers and lab technicians, along with simplification of logistical issues related to specimen storage, shipping and linking with test results. Another important concern identified was the need for improved standardization and rigorous quality control of commercially manufactured tests and kits, a problem noted particularly with variability in the lots of commercial kits measuring Bm14 antibodies (CELISA) and the TropBio Og4C3 antigen test. In addition, with an increasing reliance on laboratory tests for programmatic decision making, there is a critical need to provide laboratories with standard operating procedures and assay controls (e.g., samples for standard curves, positive and negative controls) that can be used across all labs. Both efforts are needed to guarantee that results generated across countries are comparable and can be used to make robust program decisions. Use of eluted filter paper blood spots rather than fresh serum in this study might have contributed to the sub-optimal performance of the Bm14 and Og4C3 ELISA tests. When this study was planned, all investigators on the project agreed that filter paper blood spots should be used for the ELISA tests. Multiple studies have described the equivalence of the blood spot and serum specimens for use in both the Bm14 and Og4C3 assays [11]–[14], but since this analysis was conducted, other studies have suggested that blood spots on filter paper might not perform as well as serum in the Bm14 ELISA, and there has been a call for additional studies to compare the two methods directly [15]. In the present study, project laboratories found that blood spot eluates sometimes produced variable and often high background OD values in the Bm14 ELISA, so that data from these countries had to be rejected (Table 5). When evaluating the best diagnostic tool for programmatic decision-making, the advantages of point-of-care tests are appreciable. In this study, the anticipated advantages of lab-based tests (i.e. better sensitivity and specificity) were outweighed by the convenience, comparable accuracy, and ability to standardize more easily the point-of-care tests. Given the challenges experienced with the lab-based tests (see Table S1) a point-of-care test appears to be most preferable for assessments leading to a decision on whether or not to stop MDA. Taking these aspects into consideration, we conclude that the ICT should be the primary tool recommended now for decision-making about stopping MDAs in areas with W. bancrofti infections. As a point-of-care card test, the ICT is relatively inexpensive, requires no laboratory equipment, and can be processed in 10 minutes, very consistent with programmatic use. As an antigen test, a “positive” ICT result is indicative of the presence of adult worms and the potential for ongoing transmission—arguably a more appropriate measure for establishing an end-point for MDA than antifilarial antibodies detecting exposure to infection. Additional research is needed to determine whether antibody tests are more appropriate for post-MDA surveillance. One concern with the ICT that arose from this study was the potential subjectivity involved in determining whether a weak-looking band indicates a positive or negative test. Fortunately, improvements to training and training materials can be expected to resolve some of this anxiety about the test's use. Indeed, with these improvements, the ICT appears as the diagnostic tool best suited for use even in low-resource settings to determine when the end-point for the MDA phase of the LF elimination program has been reached. This recommendation for the ICT test is not meant to undervalue the relatively good performance of the Og4C3 test, which was even more accurate than the ICT in identifying microfilaremic individuals in this study. However, as a laboratory-based assay, the Og4C3 test provided some additional challenges, including inconsistent product performance over time and quality control in the testing laboratories. The Og4C3 and other ELISA tests have performed well in research labs; our results and experience with quality control have illustrated the potential problems with translating these tools into an operational setting. The Og4C3 provides a satisfactory diagnostic alternative that may be appropriate in settings with well-equipped laboratories and the ability to adhere to a quality assurance strategy. Limitations and Areas of Future Research The absence of a true gold standard test for LF infection was a major limitation of this analysis. The need to define a best-estimate gold standard from the available tests further limited the analysis since tests used in the definition cannot be assessed by the same definition without entering into a tautology (an issue for both PCR and blood smear). To measure the sensitivity and specificity of the tests it was necessary to use the best-estimate gold standard to define “true positive” and “true negative” results and then limit the analysis to specimens falling within either category. Based on the criteria used, individuals who tested not positive by blood smear and PCR but positive by Bm14 or PanLF (n = 1737) were excluded from sensitivity and specificity calculations for antigen tests, as they were neither “true positive” nor “true negative”. It is important to note that such results are biologically plausible, as they may be indicative of individuals with increasing, but undetectable antigen levels, or they can represent individuals who are no longer infected but still have residual antifilarial antibodies. It is clear, though, that the definitions used to establish test sensitivity and specificity are imperfect because of the impossibility of defining a true gold standard of infection. The ROC analysis for determining Bm14 and Og4C3 cut-off levels was also contingent upon the best-estimate criteria. Therefore, any systematic errors resulting in misclassification of the tests used in the best estimate gold standard have the potential to influence this analysis. A sensitivity analysis was run, which evaluated the suspected ICT false positives, as well as false positive and false negative results with PCR and blood smear. The results from the sensitivity analysis indicate that the sensitivity and specificity of the tests, and conclusions drawn from this analysis, to be robust under various scenarios of misclassification (data not shown). For example, if all ICT-positive specimens with an Og4C3 quantitative result of “0” (N = 48) were considered “false positives” and recoded as ICT-negative, the sensitivity and specificity estimates would not change significantly. Finally, additional sources of error, common across many tests and countries, stemmed from external issues. Logistical constraints and risk of specimen contamination varied by country and is likely to have caused some of the variance in test performance. The possibility of reader error cannot be discounted. Some of this study's findings were unexpected and warrant future research and analysis. Though the overall prevalence of detection of antigen or antibody was similar for a given target, the distributions of the test results suggest that they are performing differently. Whether or not this difference is due to variability of test performance or to the tests' detecting different sub-populations of positive individuals is hard to determine. For example, the correlation between the ICT and Og4C3 antigen tests was much lower than expected (phi coefficient 0.53); however both tests identified similar overall prevalence of antigenemia. Part of the discordance may be explained by the cut-point selected for the Og4C3 test. Cut-points for Og4C3 were defined such that the only “true positive” specimens were those testing positive for microfilariae (blood smear or PCR). This is likely to have limited our ROC analysis to “strong positive” Og4C3 results (those with higher unit values), as previous studies have found Og4C3 unit values to be positively correlated with MF values [16]–[18]. Whether or not this biased our final cut-point is unclear. However, the poor correlation may also suggest that the ICT and Og4C3 test are capturing different aspects of antigenemia. A more controlled laboratory study would be needed to determine if this were the case. Next Steps The selection of the ICT as the best tool for establishing the MDA stopping criteria is a significant programmatic advance. However, further assessment is needed to develop the appropriate guidelines for country program managers eager to decide if they are ready to stop MDA. The selection of a diagnostic test is the first step, but it is necessary to define a “threshold” of positive results below which a country can safely discontinue its MDA program. With the less-than-perfect sensitivity and specificity of the diagnostic tools, such a threshold should be based on statistical criteria that can account for the level of error in the measurement with a 95% confidence interval [4]. Also integral to this assessment is the method by which the population will be sampled, as both sampling strategy and threshold will influence the sample size and power of the surveys used to determine if the stopping MDA criteria are met. Addressing these issues is the focus of ongoing research efforts. The global community has already made great progress on the path to elimination of lymphatic filariasis. The selection of the ICT test for defining the end-point of MDA, based on both the present study and earlier observations permits the WHO to develop appropriate guidelines that will allow many countries to move closer to stopping their MDA programs. Future studies to evaluate sampling strategies, ICT-based stopping thresholds, and long-term consequences of the stopping decision will increasingly strengthen the evidence base for the programmatic guidelines targeting LF elimination. Supporting Information Checklist S1 STARD Checklist. (DOC) Click here for additional data file. Table S1 A summary of the features and performance of the seven diagnostic tests evaluated. (DOC) Click here for additional data file. Flow Chart S1 STARD flow chart detailing the method for assessment of antibody diagnostic tests. (DOCX) Click here for additional data file. Flow Chart S2 STARD flow chart detailing the method for assessment of antigen diagnostic tests. (DOCX) Click here for additional data file. Flow Chart S3 STARD flow chart detailing the method for assessment of microfilariae diagnostic tests. (DOCX) Click here for additional data file.
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                Contributors
                Kimberly Y. Won:
                ORCID: http://orcid.org/0000-0003-2835-6140
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Keri Robinson: Role: InvestigationRole: Writing – review & editing
                Katy L. Hamlin: Role: InvestigationRole: Writing – review & editing
                Joseph Tufa: Role: Supervision
                Margaret Seespesara: Role: Supervision
                Ryan E. Wiegand: Role: Formal analysisRole: Writing – review & editing
                Katherine Gass: Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Joseph Kubofcik: Role: Investigation
                Thomas B. Nutman: Role: Investigation
                Patrick J. Lammie: Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Writing – review & editing
                Saipale Fuimaono: Role: Project administrationRole: SupervisionRole: Writing – review & editing
                Wilma A. Stolk: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS Negl Trop Dis
                Journal ID (iso-abbrev): PLoS Negl Trop Dis
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosntds
                Title: PLoS Neglected Tropical Diseases
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Print): 1935-2727
                ISSN (Electronic): 1935-2735
                Publication date (Electronic): 9 March 2018
                Publication date Collection: March 2018
                Volume: 12
                Issue: 3
                Electronic Location Identifier: e0006347
                Affiliations
                [1 ] Centers for Disease Control and Prevention, Division of Parasitic Diseases and Malaria, Atlanta, GA, United States of America
                [2 ] Swiss Tropical and Public Health Institute, Epidemiology and Public Health, Basel, Switzerland
                [3 ] University of Basel, Tropical and Public Health Sciences, Basel, Switzerland
                [4 ] Department of Health, Lymphatic Filariasis Elimination Program, Pago Pago, American Samoa
                [5 ] Task Force for Global Health, Neglected Tropical Diseases Support Center, Decatur, GA, United States of America
                [6 ] National Institutes of Health, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States of America
                Erasmus MC, NETHERLANDS
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2835-6140
                Article
                Publisher ID: PNTD-D-17-02085
                DOI: 10.1371/journal.pntd.0006347
                PMC ID: 5862496
                PubMed ID: 29522520
                SO-VID: 9ff54a91-a353-4ca0-bbc1-3cf138442f87
                License:

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                Date received : 2 January 2018
                Date accepted : 26 February 2018
                Page count
                Figures: 1, Tables: 5, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Award ID: 1053230
                Funded by: funder-id http://dx.doi.org/10.13039/100000200, United States Agency for International Development;
                Support for the field work came from the Coalition for Operational Research on Neglected Tropical Diseases (COR-NTD), which is funded at the Task Force for Global Health primarily by The Bill and Melinda Gates Foundation (Grant ID: 1053230), by the United Kingdom Department for International Development, and by the United States Agency for International Development (USAID) through its Neglected Tropical Diseases Program; laboratory testing was supported by USAID through an inter-agency agreement with The Centers for Disease Control and Prevention, Division of Parasitic Diseases and Malaria. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                Custom metadata
                PLOS Publication Stage vor-update-to-uncorrected-proof
                Publication Update 2018-03-21
                Data Availability All relevant data are within the paper and its Supporting Information files.

                ScienceOpen disciplines: Infectious disease & Microbiology
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