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 (). Specimens from these participants were used to conduct 47,110 diagnostic tests (). Of the 47,110 tests performed, 7481 test results (15.9%) were excluded from the subsequent analyses due to invalid or indeterminate test results (). 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
, and S3
Specimens and tests performed by country of origin.
Invalid or indeterminate test results by country (excluded from remaining analyses).
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 <18 units. The resulting ROC plots provided strong evidence that the cut-off for defining an Og4C3 positive result should be 34 units.
Determining the cut-point for the antibody assay Bm14, using the ROC, was more problematic. An antibody response is the first identifiable marker following exposure
to filarial infection, it is therefore impossible to define true-positive infections
by the presence of antibody. Assay sensitivity can be determined with respect to microfilaremia or antigenemia; however, specificity cannot be conceptually assessed (see Discussion
). Indeed ROC analysis for the Bm14 cut-off proved to be inconclusive. Instead it was decided that positivity and negativity be discriminated on the basis of Optical Density values, based on a standard curve run for each test plate 
. Therefore, the value of 64 units was used as the cut-off, which follows the manufacturer's recommendations and is consistent with the available ROC findings.
As shown in , 22.8% of participants' specimens had valid results for the full battery of seven tests while almost two thirds of participant specimens had valid results for five or more tests. Bm14 had the highest prevalence of positive results, with country-specific prevalence reaching 53.1% in Haiti (). The PanLF antibody and urine SXP antibody tests had the second and third highest positivity, with the highest prevalence found in Haiti (41.5%, ) and French Polynesia (22.5%, ), respectively. Across all countries, 17.5% of specimens were positive by PanLF and 20.5% by urine SXP (). At the country-level, antigen positivity ranged from around 0.5% in Sri Lanka to over 21.2% in Haiti (), while overall approximately 9% were positive by ICT and 8% by Og4C3 (). The tests with the least number of positive results were PCR and blood smear, with approximately 1.5% of specimens testing positive overall, though again positivity varied at the country-level.
Number of valid* tests performed on participants specimens.
Prevalence of positive results by test and country.
Prevalence of positive results by age group (all countries).
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) (). 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 (, , ,) 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 (). 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.
Positive-to-positive concordance in school survey.
Positive-to-positive concordance in community survey.
Negative-to-negative test concordance in school survey.
Negative-to-negative test concordance in community survey.
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 (). 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 () 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) (). 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 (). 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.
Sensitivity, specificity, and predictive values for antigen tests.
The sensitivity of the antibody tests at detecting microfilaremic individuals was 81% for Bm14, 73% for PanLF and 55% for SXP in urine (). 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.
Sensitivity, specificity, and predictive values for antibody tests.