A Systematic Review of High Quality Diagnostic Tests for Chagas Disease

Anna M Afonso
Department of Epidemiology and Biostatistics
University of Georgia
AthensGeorgiaUnited States of America

Mark H Ebell
Department of Epidemiology and Biostatistics
University of Georgia
AthensGeorgiaUnited States of America

Rick L Tarleton
Center for Tropical and Emerging Global Diseases and Department of Cellular Biology
University of Georgia
AthensGeorgiaUnited States of America

A Systematic Review of High Quality Diagnostic Tests for Chagas Disease

Background: There is significant heterogeneity in reported sensitivities and specificities of diagnostic serological assays for Chagas disease, as might be expected from studies that vary widely according to setting, research design, antigens employed, and reference standard. The purpose of this study is to summarize the reported accuracy of serological assays and to identify sources of heterogeneity including quality of research design. To avoid associated spectrum bias, our analysis was limited to cohort studies.Methods:We completed a search of PubMed, a bibliographic review of potentially relevant articles, and a review of articles identified by a study author involved in this area of research. Studies were limited to prospective cohort studies of adults published since 1985. Measures of diagnostic accuracy were pooled using a Der Simonian Laird Random Effects Model. A subgroup analysis and meta regression were employed to identify sources of heterogeneity. The QUADAS tool was used to assess quality of included studies and Begg's funnel plot was used to assess publication bias.Results: Eighteen studies and 61 assays were included in the final analysis. Significant heterogeneity was found in all predetermined subgroups. Overall sensitivity was 90% (95% CI: 89%-91%) and overall specificity was 98% (95% CI: 98%-98%).Conclusion: Sensitivity and specificity of serological assays for the diagnosis of Chagas disease appear less accurate than previously thought. Suggestions to improve the accuracy of reporting include the enrollment of patients in a prospective manner, double blinding, and providing an explicit method of addressing subjects that have an indeterminate diagnosis by either the reference standard or index test.

Introduction

Chagas disease, or American Trypanosomiasis, is caused by the parasite Trypanosoma cruzi. The World Health Organization estimates that approximately 10 million individuals are currently infected with T. cruzi and are at risk for developing cardiac or gut pathology normally associated with chronic Chagas disease [1]. T. cruzi is transmitted to humans by infected triatomine bugs that infest housing, take blood meals from the inhabitants, and then defecate, leaving the infective metacyclic stages of T. cruzi to be scratched into wounds or mucosal sites. Although Chagas disease was once confined to the Americas, primarily Latin America, migration from endemic countries has led to the appearance of Chagas disease in non-endemic regions as well [1]. In both endemic and non-endemic settings, transmission of T. cruzi is also possible through blood transfusion, tissue transplantation, and congenitally. Control programs and improvements in housing have led to a reduction in the incidence of disease in Latin America, but screening blood donors and diagnosing chronic, often asymptomatic patients, remains a major challenge.

T. cruzi infection is generally controlled by a highly effective immune response but is rarely completely cleared, resulting in a persistent, but low level infection. Early in the infection with T. cruzi, parasites may be detected in the bloodstream either by direct observation of blood or by various culture techniques. Unfortunately, infection at this early stage often goes undetected because symptoms are nonspecific or absent. Once the immune response to T. cruzi is established, parasite detection is very difficult and diagnosis of the infection is based largely upon the detection of anti-T. cruzi antibodies by serological techniques. Conventional serological tests include primarily immunofluorescence assays (IFA), enzyme-linked immunosorbent assays (ELISA) and indirect hemagglutination assays (IHA).

Because there is currently no single reference standard test, the World Health Organization (WHO) recommends that diagnosis of an individual utilize two conventional tests based on different principles and detecting different antigens [2]. In the case of ambiguous or discordant results, a third technique should be used [2]. The goal of this study is to summarize the evidence on the accuracy of diagnostic tests for Chagas disease from high quality diagnostic test studies. Previous research has found that use of a case-control design overestimated the diagnostic odds ratio (DOR) by 3-fold compared to studies employing a cohort design [3]. In order to more accurately assess the sensitivity and specificity of serological assays used to screen patients for Chagas disease, we limited our review to studies that prospectively enrolled patients using a cohort study design.

Methods

Inclusion and Exclusion Criteria

Criteria for inclusion in this systematic review were that the study 1) be available in English, Spanish, Portuguese, or German; 2) be published since 1985; 3) use human subjects rather than model organisms; 4) include a minimum of 50 samples; 4) prospectively enroll patients without knowledge of T. cruzi infection status using a cohort design; 5) examine a serologic assay based on measuring antibody levels in the blood (e.g. ELISA, IHA, IFA, immunochromatographic assay, complement fixation), rather than a PCR assay, urine analysis, or saliva test; 6) provide enough information to determine sensitivity and specificity of a serologic assay compared with a reference standard of some kind; 7) enroll primarily adolescents or adult patients (12 years or older).

The year 1985 was chosen as a cutoff to capture the time period during which conventional tests of IFA, IHA, and ELISA came into wide use in Latin America [4]. Studies involving exclusively immunodeficient adults, patients with HIV or TB, children, infants, neonates, or pregnant women were excluded. We excluded any study designed to evaluate serologic tests as a means to assess cure of Chagas disease, as the purpose of this systematic review is to evaluate the performance of diagnostic tests in patients with unknown disease status. Case-control studies that identified a group of well characterized cases and well characterized normal controls, often from different sources, were excluded because this is an important methodological limitation [3]. Data for patients with the acute stage of T. cruzi infection were excluded from the analysis, given that these data represented only a small proportion of all studies and provided extremely heterogeneous results. Furthermore, it has been shown that the reactivity of IgG antibodies to various antigens varies between patients with the acute and chronic form of Chagas disease [5].

Search Strategy

We used several strategies to identify relevant articles, including searching PubMed with multiple search strategies, reviewing bibliographic citations from both included and excluded articles, and reviewing studies known to be relevant by one of the study authors, an expert in the field of Chagas diagnostics. The following strategy was used in PubMed/Medline to identify studies providing a quantitative evaluation of diagnostic tests for Chagas disease: (''chagas disease/diagnosis''[MeSH Major Topic]) AND (''sensitivity and specificity''[MeSH Terms] OR ''likelihood ratio''). We identified 156 articles, of which 121 were identified as potentially relevant by one or more authors based on a review of the abstracts. These articles were then assessed for inclusion criteria based on a review of the full text of each article.

Medline (PubMed) was also searched for previous systematic reviews on the diagnosis of Chagas disease. ). This search identified 12 studies, one of which was considered potentially relevant based on a review of abstracts [6]. This systematic review, however, was excluded after a review of the full text.

Eight full text articles were provided by a study author (RLT) as being potentially relevant. In addition to reviewing these articles, we reviewed the bibliographies of all included studies, as well as bibliographies of studies excluded based on the criteria of having a case control rather than cohort design. We also performed a search of LILACS to capture articles that may have been missed by other methods. Our search strategy was to use the search term ''Chagas,'' limit study type to cohort studies and limit clinical aspect to ''diagnosis.'' This identified 15 studies, of which none met our study criteria. We also performed this search using ''Trypanosoma cruzi'' and ''T. cruzi'' as the search term. We found no additional studies.

Data Abstraction

Abstracts and full texts were evaluated for inclusion criteria by three blinded reviewers; one assessed all articles and each of the other two reviewers assessed about half of the articles. Information regarding the characteristics of each study and the data needed to create a contingency (''262'') table comparing each index test with its reference standard were abstracted into a worksheet by two reviewers in a blinded fashion. If a study reported sera that were indeterminate by the index test, we considered indeterminate results as a positive index test, and incorporated them into the assessment of accuracy of the test whenever possible. The methodological quality of each included study was also independently assessed by two reviewers using the QUADAS tool (Quality Assessment of Diagnostic Accuracy Studies) [7]. Differences between reviewers were resolved through consensus discussion.

Statistical Analysis

Sensitivity, specificity, positive likelihood ratios (LR+), and negative likelihood ratios (LR-) with 95% CI's were calculated for each test and then pooled using a Der Simonian Laird Random Effects Model. For studies with cells in the 262 table containing a value of zero, 0.5 was added to all cells to avoid division by zero. Heterogeneity of pooled sensitivity and specificity was estimated with the I 2 statistic, where a value for I 2 of 0 indicates perfect homogeneity (all of the variance is within study) whereas a value of 1.0 indicates perfect heterogeneity (all of the variance is between studies). The area under a summary ROC curve for pooled results was also calculated using a Der Simonian Laird Random Effects Model. Because there was little variation in specificity estimates, a

Author Summary

Chagas disease, an infectious disease endemic to Latin America, is caused by the protozoan parasite Trypanosoma cruzi. T. cruzi can be transmitted through blood transfusions, organ transplants, or from mother to fetus, although it is most commonly transmitted through insect vectors. Infections can remain silent for many years before manifesting as potentially fatal damage to the cardiac and/or digestive system. Diagnosis of Chagas disease during its chronic asymptomatic phase is crucial to preventing future infections with T. cruzi and is often performed using serological tests that detect antibodies in the blood. Because there is currently no gold standard for serological diagnostic tests, multiple forms of serologic testing are often used in conjunction. The purpose of this study was to compare reports on the accuracy of serological tests. After limiting studies by certain criteria, the authors found a lower estimate of accuracy than has previously been reported in the literature and suggest quality improvements that can be made to standardize future reports.

bivariate method was not used. Calculations were performed with MetaDisC ver 1.4 (Madrid, Spain).

Sources of heterogeneity were assessed by meta-regression using the metareg command in Stata version 11.0 (College Station, TX) under a random effects model. The independent variable was the log of the diagnostic odds ratio (DOR), which compares the odds of having a positive test result in those with T. cruzi compared to the odds of having a positive test result in those uninfected with T. cruzi [8]. It is calculated as (TP/FP)/(FN/TN) [9]. Within study variance was estimated by the standard error of the ln(DOR), calculated as the square root of [(1/TP)+(1/FP)+(1/FN)+(1/TP)] [9]. A random effects meta regression does not assume that all variability exist within a study but also takes into account between study variability in the model [10]. Between study variance was estimated by a restricted likelihood method using an iterative procedure. A fixed effects meta-regression was not performed because this model assumes that all the heterogeneity can be explained by the posited covariates [11] while a random effects model allows for unexplained heterogeneity. Publication bias and small study bias were assessed with a Begg funnel plot using the metabias command in Stata Version 11.0 (College Station, TX).

Results

Included Studies

Eighteen studies met the inclusion criteria. Thirteen studies were included based on a search of Medline, one more was included from the personal file of a study author, and four more were included based on a review of citations of included studies and non-included case-control studies. The included cohort studies were published between 1988 and 2010. All but one included study took place in Central America or South America. The one remaining study took place in Switzerland, although participants were Latin American immigrants. Seven studies (39%) were conducted with blood bank donors. The remaining studies came from ''field studies'', population surveys, or other settings.

Twelve studies (67%) used subjects with unknown symptoms, while the remaining studies classified participants as asymptomatic or with clinical evidence of Chagas disease. Participants consisted mainly of adults with a mean age in the mid twenties; 8 studies did not report any information on the age of subjects, while 10 did not report any information regarding the sex distribution of participants. The characteristics of each study included in this analysis are outlined in Table S1.

Study Quality

A QUADAS score was created by assigning one point to all QUADAS criteria answered positively, 0.5 of a point for studies in which it was unclear whether a criteria was met, and zero points when a study clearly did not meet a QUADAS criteria. Figure 1 summarizes the percentage of studies meeting each of the QUADAS quality criteria, and Figure 2 provides an overview of the quality criteria for each study.

Index Tests

Of the 61 tests assessed, 44 were ELISA, 3 were immunofluorescence assays, 7 were indirect hemagglutination assays, 4 were immunochromatographic assays, one was a chemilimunescence  assay, one was a Dot-ELISA, and one was a multiple antigen binding assay (MABA). Antigens used in each of the assays are described in Table S2. Twenty six of sixty one assays (43%) did not report the antigen used in an assay; among those that did, 15 assays used a form of recombinant antigen while 28 used a fixed or whole form of the parasite. Of the 61 assays included in this review, 36 were commercial assays. Details regarding type of commercial assay used are also described in Table S2.

We were unable to use information regarding cutoffs to complete a threshold analysis because of the limited number of studies that reported cutoffs used. In fact, 39 (64%) did not report the exact cutoff or even methodology used to determine the cutoff (i.e. 2.5 SD's above the mean of uninfected patients).

Reference Standards

Because there is no single widely accepted reference standard test for assessing Chagas disease, included studies used a wide variety of methods to classify true positives and true negatives. Four of eighteen studies used a single test as the reference standard. Because the reference standard was either positive or negative, there was no issue of having discordant test results for the reference standard. However, a single reference standard test is unlikely to correctly classify the index test [2]. Four studies used a reference standard of 2 or more out of 3 serological tests being positive as a true positive; three studies considered 2 out of 2 tests as a true positive and everything else as a true negative; and two studies considered 3 out of 3 positive tests as a true positive. Two studies used latent class analysis, which uses the results of index tests to approximate the true unobserved disease state [12] to identify true positives and negatives. Three studies used another method or did not describe the method used for determining true positives and negatives. Details of the reference standard methodology are summarized in Table S1. Only 4 of 18 studies reported the number of samples that were discordant by the combination of serological assays used to determine the true status of a sample.

Diagnostic Accuracy

The area under the summary ROC curve (Figure 3) for all assays was 0.99 (SE = 0.002). In the summary ROC curve, it appears that there may be a positive correlation between sensitivity and (1-specificity), suggesting that some of the heterogeneity in sensitivity and specificity estimates is due to the use of differing cutoffs. However, when we performed a Spearman rank correla-  tion, there was little evidence of a threshold effect (Spearman correlation coefficient = 0.04, p = 0.76). An apparent outlier in the summary ROC curve is a study [13] that reported a low sensitivity for nearly all assays. This reduced accuracy is likely due to the fact that each assay included only one recombinant antigen, while most conventional assays use a combination of multiple antigens or whole parasite extracts. Removing this outlier only increased the sensitivity slightly but did not change the specificity (Table 1). A Forest plot (Figure 4) of sensitivity and specificity estimates for each study (with 95% CI's) reveals that specificity is high and consistent between studies, while estimates of sensitivity vary more widely. While we report summary estimates for sensitivity and specificity, they should be interpreted with great caution given the significant heterogeneity and design limitations of the included studies. Results of the metaregression, which examined the independent effect of study design characteristics on the diagnostic odds ratio,  Table 2. Study design characteristics significantly associated with the diagnostic odds ratio included whether an ELISA or other assay was employed (relative diagnostic odds ratio [RDOR] = 4.22), whether a study utilized latent class analysis as the reference standard (RDOR = 90), and whether the index test was blinded to the reference standard (RDOR 0.03). Thus, studies that were blinded reported a lower estimate of diagnostic accuracy, while those using latent class analysis and those using an ELISA assay reported a higher estimate of accuracy. One limitation of this analysis is that the sample size for the metaregression is the number of studies, not the number of patients, and thus there may not be sufficient power to detect other important effects [10].

Publication bias is the tendency of smaller studies with null results to go unpublished while studies showing an effect are more likely to appear in the literature [10]. To assess this effect, we built a funnel plot ( Figure 5) of the log of the diagnostic odds ratio against the standard error of the log of the diagnostic odds ratio, an indicator for sample size. Each open circle in the funnel plot represents an individual assay and the line in the center represents the summary diagnostic odds ratio. A gap in the plot of missing values below the summary DOR line is an indication of publication bias.

In a regression of the standardized effect estimates against their precisions, we found a positive association between smaller studies and a higher reported DOR (slope = 4.47, 95% CI: 3.6-5.3, t = 10.47, p,0.001). The intercept of the fitted line can be interpreted as a measure of bias [14] (Intercept: 20.58; 95% CI: 23.71, 2.63; t = 20.35; p = 0.732). A gap in the expected funnel shape of the scatter plot indicates that there may be publication bias, with a lack of smaller studies reporting negative findings.

Discussion

Previous studies have reported extremely high values for the sensitivity and specificity of serologic tests for Chagas disease. For example, the recent systematic review by Brasil and colleagues found summary estimates of sensitivity and specific for ELISA of 97.7% (96.7%-98.5%) and 97.5% (88.5%-99.5%) respectively. Summary estimates for commercial ELISA were a pooled sensitivity of 99.3% (97.9%-99.9%) and a pooled specificity of 97.5% (88.5%-99.5%). Despite these supposedly high sensitivity/ specificity levels for tests, a number of groups recommend or advise the use of multiple tests for accurate diagnosis [6,15] suggesting that many experts are still skeptical of the high accuracy of individual tests reported in the literature.

As can be seen in the QUADAS table (Figure 2), there are several biases inherent in the manner in which the reference standard was applied. In some studies, sera with results borderline by the index test were excluded [16,17,18], thereby inflating estimates of sensitivity and specificity. Several studies based the decision to apply the reference standard on the results of the index  test, incorporated the index test into the reference standard, or did not apply a uniform reference standard to all sera in the study. In one study, only patients with a positive index test and a random selection of negative samples received the reference standard [19]. In other studies RIPA was only applied as part of the reference standard if the index or reference test was positive, while those initially negative either did not receive this test or only a random sample received the RIPA test [17,20]. In another study, only samples positive by the index ELISA test were submitted to another ELISA test, and only those positive by both ELISA tests were submitted to a Western Blot. Those reactive by all three tests were considered positive. However, only those positive by the index test were even eligible to be considered positive; any false negatives misclassified by the index test received no other verification and would be assumed to be true negatives. One study [21] repeated tests for which the index test and reference standard test were discordant. However, when the index test is applied in clinical settings, there will be no such gold standard to monitor the veracity of a test. In other studies [16,22], initially positive or indeterminate samples were evaluated in duplicate and considered positive only when a repeated test was positive. Therefore, it is important to acknowledge that the reported accuracy in many studies is not that of the index test alone, but rather the accuracy of the entire testing strategy that was implemented.

An important source of bias in these studies is dealing with samples that are discordant by the reference standard. In four of the eighteen studies, discordant samples were reported to have been discarded from sensitivity and specificity calculations (as sensitivity and specificity of a test cannot be calculated with knowledge of the true disease status). This would tend to inflate estimates of sensitivity and specificity. Although eight studies reported the manner in which they handled samples discordant by the reference standard, only four reported the number of samples which were discordant by the reference standard. In these four cases, the percentage of discordant samples out of the total was 7% (23/335) [17], 4% (40/1025) [18], 4% (17/398) [23], and 0.3% (3/999) [24]. In a study by Zicker and colleagues, results for IFA and HA were reported for all sera without specifying a clear reference standard. We chose to consider all specimens with both serology tests positive as a true positive and all other sera as true negatives. This study reported a much lower sensitivity (88%; 95%CI: 84%-91%) and somewhat lower specificity (94%; 95%CI: 93%-95%) than the pooled estimates (97%; 95% CI: 96%-98% and 96%; 95%CI: 95%-96%) for the other studies in that subgroup (those using a reference standard of 2/2 positive tests). All other studies in this subgroup reported a sensitivity greater than 95% and specificity greater than 95%. Because we created the reference standard groupings, we are certain that there were no discordant samples discarded, most likely accounting for the approximately 10% discrepancy in sensitivity estimate. This raises the question of whether other studies had a significant number of unreported discordant samples that would inflate the sensitivity of their tests.

Study design characteristics associated with biased estimates of sensitivity and specificity included different reference tests for those with a positive and negative index tests, failure to blind or mask, and case-control instead of cohort design [3]. In our study, only five of eighteen studies reported that the results of the diagnostic tests and reference tests were both blinded to the other, and only thirteen of eighteen studies applied a uniform reference standard to all or a random sample of subjects.

Our findings are consistent with these general principles of diagnostic study design, as we found increased estimates of sensitivity and specificity in studies with lower quality (QUA-DAS,10 points) and in unblinded studies. This highlights the serious limitations in the existing literature. We are concerned that the sensitivity of current tests is lower than generally reported in lower quality studies, leading to the potential for underdiagnosis. This is a particular concern when these tests are used as a screening test for blood bank samples. The use of case control design continues to be the most widespread method to evaluate diagnostic tests for T. cruzi infection. Based on this analysis, we recommend that future studies use a prospective cohort design with clear reporting, masking, and an appropriate reference standard to provide a more accurate estimate of the diagnostic accuracy of tests for Chagas disease. Our results also suggest that better tests are still needed to assure the safety of transfusions and to improve the public health of countries where the disease is endemic.

Supporting Information

Table S1 Characteristics of studies and reference standards. Appendix S1 Criteria used for QUADAS scoring. Because we limited our analysis to cohort studies, the majority of studies were considered to have a spectrum of patients representative of those that would be tested in clinical practice. Studies using two or more serologic tests or Latent Class Analysis as a reference standard were considered to have an adequate reference standard. Studies failing to report screening methodology used for both non-Chagasic and Chagasic groups were scored as unclear. Studies using only one reference standard were considered to have an inadequate reference standard. For the majority of studies, the timeline for implementing the index test and reference standard was unclear, making it impossible to determine whether the condition under study was likely to have changed between the index and reference standard. In most cases, the whole sample received the reference standard and the application of the reference standard was not based on the index test. This is more likely to be the case among cohort studies as the disease status of patients is unknown when index tests and the reference standard is applied. Blinding was reported in few studies, and it was generally unclear what information was available to the readers of diagnostic assays. (DOC) Figure S1 PRISMA flow diagram. This flow diagram maps the identification of records identified, included, and excluded at different phases of the systematic review. (DOC) Checklist S1 PRISMA checklist. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISM) is an evidenced-based checklist that clearly demonstrates essential items reported in this systematic review. (DOC) Author Contributions

Figure 1 .
1Overall percentage of studies that met QUADAS guidelines. * RS = Reference standard. doi:10.1371/journal.pntd.0001881.g001

Figure 2 .
2Quality assessment of individual studies using QUADAS tool. * RS = Reference standard. doi:10.1371/journal.pntd.0001881.g002

Figure 3 .
3Summary receiver operating characteristic curve with 95% CI for all tests. Each circle represents the sensitivity and specificity of an individual assay. The size of the circles reflects the number of patients in a study. Area under the curve = 0.99. doi:10.1371/journal.pntd.0001881.g003

Figure 4 .
4Forest plot of sensitivity and specificity for all studies. doi:10.1371/journal.pntd.0001881.g004 are shown in

Figure 5 .
5Assessment of publication bias with Begg's funnel plot. The measure of effect is ln(DOR) and the standard error of the ln(DOR) is the measure of variance. Note relative deficit of smaller studies showing lower accuracy in the lower right quadrant of the figure. doi:10.1371/journal.pntd.0001881.g005

* The above abbreviations are defined as follows: TESA: Trypomastigote excreted-secreted antigen; ELISA: Enzyme-linked immunosorbent assay; EIA: Enzyme immunoassay; IHA: Indirect hemagglutination test; iIF: Indirect immunofluorescence assay; IFA: Immunofluorescence Assay; Ch: Chagasic; Non-Ch: Non Chagasic; IND: Indeterminate; RIPA: Radioimmunoprecipitation assay; OD: Optical density; DHA: Direct-hemagglutination test; WB: Western blot; SD: Standard deviation; CSP: Chagas Stat-Pak; sens: sensitivity; spec: specificity; LCA: Latent class analysis. (DOCX) Table S2 Description of studies and assays. ELISA = enzyme linked immunosorbent assay; IHA = Indirect Hemagglutination; IIF = Indirect Immunofluorescence; IFA = Immunofluorescence Assay. (DOCX)

The following strategy was used: (''diagnosis''[Subheading] OR ''diagnosis''[All Fields] OR ''diagnosis''[MeSH Terms]) AND Chagas[All Fields]) AND systematic[sb] = (Diagnosis Chagas) AND systematic[sb]

Table 1 .
1Pooled results with an assessment of heterogeneity.No assays No studies N

Sens (95% CI)

I 2

Range
Spec (95% CI)

I 2

Range
LR+ (95% CI) LR2 (95% CI)

AUC

SE(AUC)

All studies

61

18

18, 458
0.90 (0.89,0.91)

96%

0.17-1.00
0.98 (0.98,0.98)

97%

0.76-1.0
73 (51, 104)

0.09 (0.06, 0.15)

0.99

0.002

Outlier study removed

57

17

18,210
0.93 (0.93-0.94)

94%

0.17-1.00
0.98 (0.98-0.98)

97%

0.76-1.00
94 (65,136)

0.08 (0.05, 0.13)

1.0

0.001

ELISA

45

15

14, 882
0.90 (0.89,0.91)

96%

0.44-1.00
0.98 (0.98, 0.98)

97%

0.82-1.00
82 (54, 126)

0.09 (0.05, 0.15)

0.99

0.002

Not ELISA

16

9

3,576
0.90 (0.88,0.92)

96%

0.17-1.00
0.98 (0.97, 0.98)

98%

0.76-1.00
57 (26, 125)

0.10 (0.03, 0.36)

0.99

0.004

Commercial Tests

36

12

7,930
0.95 (0.94,0.95)

94%

0.17-1.00
0.99 (0.99, 0.99)

97%

0.76-1.00
113 (68, 190)

0.07 (0.03,0.18)

1.00

0.001

Non Commercial Tests

25

11

10,528
0.81 (0.80, 0.83)

96%

0.44-1.00
0.97 (0.97,0.98)

97%

0.82-1.00
44 (26, 74)

0.17 (0.10,0.28)

1.00

0.005

Reference standard
Single test positive

16

4

1,815
0.75 (0.73, 0.78)

94%

0.17-1.00
0.93 (0.92, 0.94)

96%

0.76-1.00
19 (9.1, 38)

0.29 (0.17, 0.48)

0.96

0.018

2/3 positive

10

4

2,717
0.84 (0.80, 0.87)

93%

0.46-1.00
1.00 (1.00, 1.00)

94%

0.89-1.00
180 (35, 924)

0.14 (0.06, 0.32)

1.00

0.002

2/2 positive

6

3

8,246
0.97 (0.96, 0.98)

95%

0.88-1.00
0.96 (0.95, 0.96)

97%

0.94-1.00
80 (23, 274)
0.02 (0.007, 0.081) 1.00

0.002

3/3 positive

4

2

1,408
0.42 (0.35, 0.49)

88%

0.27-1.00
0.99 (0.99, 1.0)

76%

0.99-1.00
86 (31, 243)

0.53 (0.31, 0.89)

0.98

0.013

Latent Class Analysis

10

2

2,351
0.98 (0.97, 0.99)

74%

0.60-1.00
0.99 (0.99, 0.99)

97%

0.87-1.00
52 (23, 115)
0.02 (0.007, 0.08) 1.00

0.0013

Other

15

3

1,921
0.97 (0.95, 0.98)

82%

0.60-1.00
1.00 (1.00, 1.00)

80%

0.96-1.00
293 (131,654)

0.09 (0.04, 0.24)

1.00

0.0008

Blinding Reported

32

7

5,391
0.84 (0.82-0.85)

96%

0.27-1.00
0.99 (0.99-0.99)

95%

0.82-1.00
96 (53-175)

0.11 (0.07-0.19)

0.99

0.0022

Blinding not Reported

29

11

13,067
0.95 (0.94-0.96)

93%

0.17-1.00
0.97 (0.97-0.97)

97%

0.76-1.00
57 (35, 93)

0.08 (0.04-0.17)

0.99

0.0025

Blinding Reported and
Adequate Reference
standard

7

2

2,369
0.53 (0.46-0.59)

94%

0.27-1.00
1.00 (1.00-1.00)

40%

0.99-1.00
344 (79-1488)

0.31 (0.15-0.63)

1.00

0.0001

Blinding and Adequate
Reference standard not
present

54

16

16, 089
0.92 (0.91-0.93)

95%

0.17-1.00
0.98 (0.97-0.98)

97%

0.76-1.00
56 (40-79)

0.09 (0.05-1.42)

0.99

0.0022

Rec with outlier removed 11

8

2,724
0.90 (0.88-0.91)

98%

0.27-1.00
0.99 (0.98-0.99)

92%

0.89-1.00
94 (33, 264)

0.05 (0.01-0.20)

1.00

0.002

Recombinant

15

9

2,972
0.82 (0.80, 0.84)

98%

0.27-1.00
0.98 (0.97, 0.98)

95%

0.82-1.00
37 (17, 84)

0.08 (0.02, 0.27)

0.99

0.007

Not recombinant

28

9

12,805
0.95 (0.94, 0.96)

92%

0.50-1.00
0.98 (0.98, 0.98)

97%

0.91-1.00
117 (65, 214)

0.07 (0.04, 0.14)

1.00

0.001

Blood bank

35

7

7,295
0.96 (0.94, 0.97)

82%

0.17-1.00
0.99 (0.99, 0.99)

97%

0.76-1.00
136 (74,249)

0.09 (0.04, 0.19)

1.0

0.002

Not blood bank

26

11

11,163
0.88 (0.87, 0.89)

98%

0.27-1.00
0.96 (0.96, 0.96)

94%

0.82-1.00
33 (21, 54)

0.09 (0.05, 0.18)

0.99

0.004

Unknown only

41

12

15,422
0.91 (0.89,0.92)

94%

0.27-1.0
0.99 (0.99, 0.99)

96%

0.94-1.0
194 (112, 338)

0.10 (0.06, 0.19)

1.0

0.001

Other

20

6

3,036
0.90 (0.88,0.91)

97%

0.17-1.0
0.94 (0.93, 0.94)

96%

0.76-1.0
16 (9.9, 26)

0.07 (0.03, 0.17)

0.98

0.008

Discordants reported

8

4

2,754
0.94 (0.93, 0.95)

99%

0.27-1.00
0.98 (0.98, 0.98)

95%

0.90-1.00
62 (25, 153)
0.03 (0.003, 0.28) 1.0

0.002

Discordants not reported 53

14

15,704
0.88 (0.87, 0.89)

94%

0.17-1.00
0.98 (0.98, 0.98)

97%

0.76-1.00
76 (51, 113)
0.12 (0.076, 0.18) 0.99

0.002

QUADAS high (.10)

35

9

11,707
0.80 (0.79,0.82)

91%

0.44-1.00
0.98 (0.98,0.99)

97%

0.82-1.00
127 (71, 228)

0.17 (0.12, 0.25)

0.99

0.002

QUADAS low (0-10)

26

9

6,751
0.96 (0.95, 0.96)

97%

0.17-1.00
0.98 (0.97, 0.98)

97%

0.76-100
42 (26, 67)

0.04 (0.01, 0.14)

0.99

0.002

doi:10.1371/journal.pntd.0001881.t001

Table 1
1shows pooled results for several predetermined subgroup analyses. Studies with a QUADAS score above 10 (better designed studies) had a lower sensitivity than less well designed (80% [95% CI:79-82%] vs 96%[95%CI:95-96%], p = 0.07). ELISA tests and non-ELISA tests were similarly sensitive and specific. Commercial tests were more sensitive than non-commercial tests (95% [95%CI: 94-95%] vs 81% [95% CI: 80-
83%],p = 0.08) but had similar specificity (99% [95%CI:99-55%]
vs 97% [95%CI:97-98%], p = 0.57). Sensitivity and specificity
were higher in studies conducted with blood bank samples
compared to tests evaluated in field studies (96% [95%CI: 94-
97%] vs 88% [95%CI: 87%-89%], p = 0.24 sensitivity and 99%
[95%CI:99-99%] vs 96%[95%CI:96-96%], p = 0.44 specificity).
In the stratification by reference standard used, sensitivity was
lowest among studies requiring 3/3 positive tests as a reference
standard (42% [95%CI:35-49%]). Overall, sensitivity and spec-
ificity were low for studies using a single test as a reference
standard (75% [95%CI:73-78%]) and 93%[95%CI: 92-94%],
respectively).

Table 2 .
2Meta regression analysis.Covariate

PLOS Neglected Tropical Diseases | www.plosntds.org
November 2012 | Volume 6 | Issue 11 | e1881

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Evaluation of Serological Tests To Identify Trypanosoma cruzi Infection in Humans and Determine Cross-Reactivity with Trypanosoma rangeli and Leishmania spp. Z Caballero, O Sousa, W Marques, A Saez-Alquezar, E Umezawa, Clin Vaccine Immunol. 141045Caballero Z, Sousa O, Marques W, Saez-Alquezar A, Umezawa E (2007) Evaluation of Serological Tests To Identify Trypanosoma cruzi Infection in Humans and Determine Cross-Reactivity with Trypanosoma rangeli and Leishmania spp. Clin Vaccine Immunol 14: 1045.

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Diagnostic Pathology Serendipia: Castilla-La Mancha telepathology network

Carlos Peces firstname.lastname@example.com
Information Technologies Department of the Regional Health Care Services of Castilla-La Mancha (SESCAM)
Calle Huérfanos CristinosN°5. 45071ToledoSpain

Marcial García-Rojo marcialgarcíaemail@example.com
Department of Pathology. Hospital General de Ciudad Real. Calle Tomelloso s/n
13004Ciudad RealSpain

José Sacristán
Information Technologies Department of the Regional Health Care Services of Castilla-La Mancha (SESCAM)
Calle Huérfanos CristinosN°5. 45071ToledoSpain

Antonio José Gallardo
Information Technologies Department of the Regional Health Care Services of Castilla-La Mancha (SESCAM)
Calle Huérfanos CristinosN°5. 45071ToledoSpain

Ambrosio Rodríguez
Information Technologies Department of the Regional Health Care Services of Castilla-La Mancha (SESCAM)
Calle Huérfanos CristinosN°5. 45071ToledoSpain

Diagnostic Pathology Serendipia: Castilla-La Mancha telepathology network
10.1186/1746-1596-3-S1-S5BioMed Central Page 1 of 3 (page number not for citation purposes) Proceedings * Corresponding author
Nowadays, there is no standard solution for acquiring, archiving and communication of Pathology digital images. In addition, there does not exist any commercial Pathology Information System (LIS) that can manage the relationship between the reports generated by the pathologist and their corresponding images. Due to this situation, the Healthcare Service of Castilla-La Mancha decided to create a completely digital Pathology Department, the project is called SERENDIPIA.SERENDIPIA project provides all the necessary image acquiring devices needed to cover all kind of images that can be generated in a Pathology Department. In addition, in the SERENDIPIA project an Information System was developed that allows, on the one hand, it to cover the daily workflow of a Pathology Department (including the storage and the manage of the reports and its images), and, on the other hand, the Information System provides a WEB telepathology portal with collaborative tools like second opinion.

Introduction

Pathology images are being used in a digital format in most Pathology Departments. However, management of these digital images is usually very inefficient. Nowadays, there is no standard solution for acquiring, archiving and communication of these digital images. The use of medical digital image standards, like DICOM (Digital Imaging and Communications in Medicine) and JPEG2000 are the ground in order to create this standard solution [1]. In addition, there does not exist any commercial Pathology Information System (LIS) that can manage the relation-ship between the reports generated by the pathologist and its corresponding images.

Due to this situation, the Healthcare Service of Castilla-La Mancha decided to create a completely digital Pathology Department, the project is called SERENDIPIA. From the very beginning, one of the most important goals of the project was to be able to create the first Regional Telepathology Network.

Aims

The main aims of SERENDIPIA project are: ▪ To provide all the necessary image acquiring devices and computer equipment needed in a digital Pathology Department.

▪ To develop an Information System that allows Pathology Departments to storage and manage the reports and its images.

▪ To develop a WEB application that allows the communication between the different Pathology Departments, sharing reports and images.

The scope of the first phase of the SERENDIPIA project includes seven hospitals of Castilla-La Mancha region. Three of these hospitals are small hospitals dependent on a reference hospital. Therefore, the project has to provide all the mechanisms and tools for the collaborative work between hospitals.

Methods

In the SERENDIPIA project, the main expense was due to image acquiring devices. Different types of devices were purchased to cover all kind of images that can be generated in a Pathology Department, including grossing images (biopsy and autopsy), microscopic images, and virtual slides.

For this purpose, the Pathology Department is provided with:

▪ Digital cameras with WIFI technology for autopsy room.

▪ Digital imaging systems for the grossing room with touch screen and camera remote control.

▪ Digital cameras adapted to optical microscopes to do Photomicroscopy.

▪ Digital Scanners for creating digital slide images [2].

At the moment, because of the slowness of digital scanners (around 15 minutes per images at 40×), not every case is being digitized. Initially, only those requiring collaborative work and those of high scientific or teaching interest are digitized.

On the other hand, the project also provides a specimen identification system using barcode printers and readers for containers, cassettes and slides. Using one-dimensional (code 39), and two-dimensional (Datamatrix) barcodes.

Results

The technical implementation of the project is divided into two parts. Each part is an independent Information System but strongly interconnected with the other.

The first Information System is deployed in each hospital, and its main aim is to cover the daily workflow of a Pathology Department [3]. For that, the functionalities of the system are:

▪ Integration with the Hospital Information System (HIS). This allows it to obtain the patient demographics data, the scheduled patient appointments and all the order requests associated to the pathological examination performed at the hospital.

▪ Integration with all image acquiring devices (called modalities) using the DICOM worklist. Each modality will receive a worklist, which contains the information about the specimens that will be digitized.

▪ Storage of all the images generated by the Pathology Department in the PACS (Picture Archiving and Communication Systems), including virtual slides.

▪ A unique viewer that allows it to show, at the same time, macroscopic images, microscopic images and virtual slides. ▪ A reporting system that allows the management of autopsy, biopsy and cytology reports. In addition, it can retrieve from the PACS all the images associated with a report.

The second Information System is a centralized system that consists of a WEB telepathology portal. Its goal is to offer the following collaborative tools:

▪ Second opinion: this allows a pathologist to make a consultation about a case with other colleagues to obtain a second opinion of the case.

▪ Consultation forum: the forum is composed of several topics, such as skin pathology or soft tissue pathology. The forum allows a pathologist to make a consultation with a group of pathologists belonging to a topic, and then have a discussion about the case.

▪ Pedagogical public library: this is a pathology atlas with studies that are of high scientific or teaching interest. All the images and reports shown are anonymous. This tool will be very useful for improving the training of medical students and, in the future, other specialities can be included in the atlas, such as dermatopathology or hematopathology.

Publish with Bio Med Central and every scientist can read your work free of charge The development of the SERENDIPIA project is based on medical standards in accordance with the guidelines described in the Pathology Technical Framework of IHE (Integrating the Healthcare Enterprise). IHE is an initiative promoted by healthcare professionals and industry to improve the way computer systems share healthcare information. IHE promotes the coordinated use of established standards such as DICOM and HL7 (Health Level 7) to address specific clinical needs in support of optimal patient care. Systems developed in accordance with IHE communicate with one another better, are easier to implement, and enable care providers to use information more effectively [4].

Conclusion

The digitalization of Pathology images will allow them to be included in the Electronic Medical Record project of the Healthcare Service of Castilla-La Mancha. This solution will allow other specialists, like dermatologist or haematologist, to have access to this kind of images. As well as improve the training of students and medical residents.

Using the teleconsultation and the distance diagnostics through digital imaging will offset the shortage of specialist in Castilla-La Mancha region.

Finally, by using the medical standard in the development of the SERENDIPIA project, it will provide, in the future, an interconnection with others telepathology networks for access, exchange, and upgrade electronic medical records through the Internet.

"(
BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours -you keep the copyright Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.page number not for citation purposes)

from 9th European Congress on Telepathology and 3rd International Congress on Virtual Microscopy Toledo, Spain. 15-17 May 2008
(page number not for citation purposes)
AcknowledgementsThis article has been published as part of Diagnostic Pathology Volume 3 Supplement 1, 2008: New trends in digital pathology: Proceedings of the 9th European Congress on Telepathology and 3rd International Congress on Virtual Microscopy. The full contents of the supplement are available online at http://www.diagnosticpathology.org/supplements/3/S1
The Application of JPEG2000 in Virtual Microscopy. V J Tuominen, J Isola, J Digit Imaging. in pressTuominen VJ, Isola J: The Application of JPEG2000 in Virtual Microscopy. J Digit Imaging 2007 in press.

Critical Comparison of 31 Commercially Available Digital Slide Systems in Pathology. M Garcia-Rojo, G Bueno, C Peces, J González, International Journal of Surgical Pathology. 144Garcia-Rojo M, Bueno G, Peces C, González J: Critical Compari- son of 31 Commercially Available Digital Slide Systems in Pathology. International Journal of Surgical Pathology 2006, 14(4):285-305.

Almacenamiento de imágenes microscópicas en un Servicio de Anatomía Patológica. Sociedad Española de Informática y Salud. C Peces, M Garcia-Rojo, 56Peces C, Garcia-Rojo M: Almacenamiento de imágenes micro- scópicas en un Servicio de Anatomía Patológica. Sociedad Española de Informática y Salud 2006, 56:23-27.

Refining DICOM for Pathology -Progress from the IHE and DICOM Pathology working groups. Le Bozec, C Henin, D Fabiani, B Schrader, T Garcia-Rojo, M Beckwith, B , Stud. Health Technol. Inform. 129Le Bozec C, Henin D, Fabiani B, Schrader T, Garcia-Rojo M, Beckwith B: Refining DICOM for Pathology -Progress from the IHE and DICOM Pathology working groups. Stud. Health Technol. Inform 2007, 129:434-438.


Threats and opportunities for post-closure development in dolomitic gold mining areas of the West Rand and Far West Rand (South Africa) -a hydraulic view Part 1: Mining legacy and future threats

Frank Winde firstname.lastname@example.com
North-West University
Private Bag X60012520Potchefstroom Campus, PotchefstrooSouth Africa

E J Stoch
North-West University
Private Bag X60012520Potchefstroom Campus, PotchefstrooSouth Africa

Threats and opportunities for post-closure development in dolomitic gold mining areas of the West Rand and Far West Rand (South Africa) -a hydraulic view Part 1: Mining legacy and future threats
D320EF8A74FA62A05CCD4287CAF23919Received 5 August 2009; accepted in revised form 9 December 2009.gold miningWest RandFar West Randdolomitekarstdewateringwater pollutiontailingsuraniummine closurere-watering
For long periods in the history of South Africa gold mining formed the backbone of an otherwise agriculturally-dominated economy, initiating rapid urbanisation in often remote and underdeveloped farming areas.This paper explores examples from a mined-out goldfield west of Johannesburg (West Rand), where consequences of mine closure can currently be observed, as well as from an active goldfield on the Far West Rand.Both areas are linked by the Wonderfonteinspruit, a stream drawing much national and international media attention for its high levels of radioactive pollution.Dating back more than 120 years, the impacts of gold mining and later uranium mining on the natural environment are profound and complex, perhaps most affecting the rich groundwater resources found in the exceptionally well-karstified dolomite that underlies most of the catchment area.Mining-related impacts such as large-scale land degradation associated with dewatering of karstic aquifers and widespread pollution of surface water and groundwater systems are discussed.Based on this, potential threats and opportunities for post-mining scenarios are identified in a series of 3 papers.Part 1 of this series outlines impacts of mining, particularly on the natural water resources, and possible consequences associated with the future re-watering of currently de-watered dolomitic compartments.The need for a regionally-integrated approach to the closure of highly interconnected mines is stressed and timelines of the closure process estimated.In Part 2 the emphasis is on identifying possible opportunities for post-mining development centred mainly around the utilisation of exceptional karst features and associated water resources.Part 3 aims to quantify uncertainties associated with planning in miningdominated environments by comparing historical predictions with factual developments.

Introduction

Gold-mining activities in the Wonderfonteinspruit (WFS) area of South Africa date back more than 120 years, initiating rapid urbanisation which turned largely rural and underdeveloped areas into densely-populated regions boasting 1 st class infrastructure which includes roads, railway lines, water and electricity systems, schools, hospitals, supermarkets, etc.Many towns, such as Randfontein, Westonaria and Carletonville, owe their very existence to gold mining, and gold mines are still the most important source of direct or indirect income, raising concerns about implications of (inevitable) mine closure in the future.There are fears of socio-economic breakdown based on well-known 'ghost town' scenarios in other mining regions.This is exacerbated by a legacy of environmental degradation caused by century-old mining.Much of the degradation has been caused by large-scale dewatering of some of South Africa's most important aquifers, resulting in the widespread and devastating occurrence of sinkholes and dolines.In addition, water, sediments and soils have been contaminated with radioactive uranium (Winde, 2006a).

Presented in 3 parts, this paper aims to analyse impacts of mining on natural resources in order to assess the potential resulting threats to post-mining developments (Part 1).Based on this analysis, Part 2 outlines opportunities for post-mining development, centring largely on the utilisation of the abundant dolomitic water resources in the area.In the last part of the series (Part 3), predictions of historical planning documents are compared to actual developments subsequently observed in the area in order to illustrate the degree of uncertainty often associated with planning in mining-dominated environments.

Gold mining in the study area: historical development and environmental impacts

The West Rand goldfield Soon after the discovery of gold in 1886, on a farm in the middle of the semi-arid interior plateau known as the 'Highveld', rapid urbanisation led to the development of Johannesburg, today one of the largest metropolitan areas in Africa.Aided by capital from the diamond fields in Kimberley, gold mining rapidly expanded along the outcropping gold ore ('reef') to the east and west of the site of discovery, later known as the 'Central Rand'.The term 'Rand' is derived from the Afrikaans 'Witwatersrand' ('ridge of white waters'), used to describe an outcrop of exceptionally hard layers of sedimentary rock, lending its name not only to the world's largest-known gold deposit (the Witwatersrand Basin) but also to the currency of South Africa, indicating the economic significance of gold mining for the country.In 1887, only 1 year later, gold mining had moved 30 km west of Johannesburg, with 'West Rand Consolidated' the 1 st mining company to operate in a newly-established 70 goldfield known as 'West Rand' (WR).In April of the same year the Transvaal Government established the town of Krugersdorp (named after then President Paul Kruger) to serve as administrative centre for the public gold diggings proclaimed in the area (Erasmus, 2004;Robb and Robb, 1998;Marais, 2000) (Fig. 1)

In 1890, (Sir) JB Robinson, a successful diamond magnate from Kimberley, established the Randfontein Estates Gold Mine (REGM) together with the town of Randfontein ('spring on the ridge') to accommodate the large workforce needed for the increasingly labour-intensive underground mining (Anderson et al., 1986;Robb and Robb, 1998;Erasmus, 2004).Migrant workers from China were brought to South Africa in order to combat the shortage of skilled underground labourers soon felt by the rapidly expanding mines.One of the first shafts in which highly-polluted water from the flooded mine void surfaced some 100 years later, and which could not be found on any plan (today referred to as the 'Black Reef Incline Shaft'), is believed to have originated from the efforts of these early Chinese miners.

Continuing to rely on imported (migrant) labour, gold mines later preferred to recruit workers from countries geographically closer to South Africa, such as Lesotho (from where, apparently, the best shaft sinkers come), Mozambique, Botswana and others, often through formalised bilateral agreements at Governmental level (Wiehahn, 1982).While the overwhelming majority of contracted migrant workers were housed in large, dedicated single-sex hostels located on-site, other, mainly Black, job-seeking migrants flocking to the area had to settle outside 'White' mining towns in so-called 'townships' and 'locations' or informal settlements (Mohlakeng, Toekomsrus, Bekkersdal and others).Today, urban growth encroaches ever closer onto abandoned (and often contaminated) mine property.In some instances shacks have been built directly onto old slimes dams exposing inhabitants to a range of potential health risks including radon exhalation, radiation, dust and other tailings-related hazards.

As the last operational mine on the West Rand, REGM ceased active underground mining in the 1990s.From then on a system of interlinked voids, collectively known as 'Western Basin' and created by 4 different mines over more than a century, started to fill up with naturally inflowing water.This water finally reached the surface in 2002, displaying extremely poor quality mainly due to underground chemical processes known as 'acid mine drainage' (Fourie and Associates, 2004).Amongst other constituents, the radioactive heavy metal uranium, which accompanies gold in the mined reefs, was elevated to such an extent that the National Nuclear Regulator (NNR) of South Africa declared the site at which the water surfaced ('decant site') an access-restricted 'radiation area'.

Although much of the mine void expands below the headwater area of the WFS, which drains towards the Atlantic Ocean, most of the mine-water crosses below the sub-continental divide decanting into a small (normally non-perennial) stream known as Twee Lopiespruit East ('Two course stream' East) which finally drains into the Indian Ocean.With an estimated 15-30 Mℓ/d (rising up to 50 Mℓ/d during wet periods) of highly polluted water running through the Krugersdorp Game Reserve, located a short distance below the decant point, and further towards the Sterkfontein Caves, concerns have been raised about health implications for animals in the Game Reserve (Du Toit, 2006) and also Sterkfontein's ('strong fountain') UNESCO World Heritage status as the 'Cradle of Humankind' (Fourie andAssociates, 2004). Du Toit (2006) reports the death of 27 animals (9 lions and 18 springbuck) in the Game Reserve within months of the decant, although no clear cause-effect relationship between mine-water and animal deaths could be established, partly due to a lack of scientific data for wild (i.e.non-domestic) animals.

After it was initially considered to supply this water to platinum mines in the north where water scarcity had already curbed production, a later-issued DWAF directive urged the responsible mine (Harmony Gold Mine (GM)) to capture the decant water and, after reducing uranium, iron and sulphate levels, to divert it into the WFS.Interestingly, the facility currently used by the mine for the water treatment and uraniumremoval (now operated by Rand Uranium) is built on the remains of a former uranium-production plant.Companies such as Mogale Gold have been extracting gold from old tailings dams and sand dumps intermittently, but since 2003 a sharp increase in the price of uranium has sparked renewed interest in large-scale reworking of uraniferous tailings deposits (in South Africa termed 'slimes dams').This has transformed many of the old slimes dams, formerly an environmental liability to their owners, into economic assets, many of which are now exploited by joint-venture companies specifically established for this purpose (Hill, 2008 a;b).This continues a history which started in 1952 when the 1 st fully-operational uranium plant in South Africa was commissioned at the West Rand Consolidated Gold Mine (Erasmus, 2004) (Fig. 1).

The Far West Rand goldfield

Attempts to mine gold south of the WR (e.g. by the Pullinger brothers in 1911) failed initially as large volumes of water from dolomitic karst aquifers flooded the newly-sunken shafts.It was only in 1934 that the recently-developed cementation technology allowed the Venterspost Gold Mine to sink shafts successfully through water-bearing dolomite, tapping into the riches of a new goldfield known today as Far West Rand (FWR) (Fig. 1).This was soon followed by other mines established down the catchment of the WFS.The newly-discovered gold reefs proved to be the richest mined in South Africa.Gold mines such as Blyvooruitzicht and later West-Driefontein were, in their heyday, the world's richest gold mines (GFL, 2005).

West Driefontein GM applied to government for permission to dewater overlying dolomitic compartments in an effort to reduce the ever-increasing pumping costs that many mines incurred in more than 3 km-deep mine workings.After a 4-yr inter-departmental investigation, in 1964 the Government finally granted permission to GMs to dewater 2 dolomitic compartments, which de facto had already commenced years before (Jordaan et al., 1960).Starting with the Venterspost (1947) and Oberholzer (1959) compartments, dewatering was later extended to the Bank (1969) and Gemsbokfontein (1986) compartments.In order to provide a legal framework for compartment dewatering, the Irrigation and Water Conservation Act (No. 8 of 1912) was replaced by the Water Act (No. 54 of 1956).This was the 2 nd time that water issues in the WFS catchment had set a precedent for water law in South Africa, as Chapter 3 of the Irrigation and Water Conservation Act was amended to replace the authority of the Governor-General and increase the Minister of Water Affairs' power over dolomitic water (Swart et al., 2003a).

By pumping out more water from the underlying mine void than was naturally replenished in the dolomite, and discharging the pumped water downstream of the affected compartments, the groundwater level was lowered by up to 1000 m in places.Apart from the (anticipated) drying up of irrigation boreholes and some of the strongest karst springs in South Africa, which historically fed into the WFS dewatering also (unexpectedly) caused a massive acceleration of karst-related ground instability in the form of sinkholes and dolines, frequently with dire consequences for residents and local infrastructure.The most catastrophic sinkhole on record occurred in 1962 at West-Driefontein GM, where the 7-storey-high screening, crusher and sorting plant disappeared completely, trapping 29 workers, none of whom could be rescued, followed by a sinkhole in 1964 at Blyvooruitzicht village killing a family of 5 (GFL, 2005).In order to compensate affected farmers and other parties for the loss of land, Government and the Chamber of Mines reached an Agreement to form the Far West Rand Dolomitic Water Association (FWRDWA), of which it is itself a member, represented by 2 officials from the Department of Minerals and Energy (DME, recently renamed as the Department of Mineral Resources) and 1 official from the Department of Water Affairs and Forestry (DWAF, which was recently reconstituted as 2 Departments headed by 1 Minister, namely, the Department of Water Affairs (DWA) and Department of Environmental Affairs; in this paper the acronym 'DWA' will be used to refer to what was formerly the DWAF).The FWRDWA was expected to speedily resolve dewatering-related claims, including the provision of alternative water.As part of the planned dewatering of the Bank Compartment, the very settlement after which the Compartment was named ('Bank') was evacuated and subsequently dismantled.Today, most of the dolomitic land overlying the affected compartments on both sides of the WFS is owned by the FWRDWA, of which Government is an indirect two-thirds shareholder.

Over the past 50 years or so, well over 1 000 sinkholes have formed in the area, many of them directly in the streambed of the WFS, where karstification naturally is most intense (Swart et al., 2003a).By intercepting much of the streamflow and diverting it to the underlying mine void, sinkholes in the streambed drastically increased pumping costs for affected mines.

Triggered by an exceptionally wet period between 1974 and 1978, in 1977 the WFS was diverted into a 32 km-long pipeline of 1 m diameter (commonly referred to as '1 m-pipeline') carrying water across the 3 dewatered compartments.Government at the time paid approximately two-thirds of the construction cost amounting to a total of USD 5 m.With a maximum capacity of some 130 Mℓ/d, the pipeline can, however, not accommodate all runoff generated in the relatively steep, non-dolomitic head-water region of the WFS, especially after intensive storm events.During the said wet period in the mid-1970s, up to 3 500 Mℓ/d overflowed from Donaldson Dam (Fig. 1) towards the pipeline, resulting in more than 96% of the runoff bypassing the pipeline and entering the streambed at a section where, since 1954, a total of 166 sinkholes had formed.Accepting up to 40 000 ℓ/s, sinkholes in the streambed diverted the entire runoff into the underlying mine void causing groundwater levels to rise to as close as 10 m below the streambed, almost reaching pre-dewatering levels again.The concentrated water input during this wet period caused an increase in pumping volumes of affected mines for a further 12 years before normal pumping levels were again reached (Swart et al., 2003b).

In order to reduce the significant volume of stormwater that runs into sinkholes, several attempts were made to fill sinkholes with a mixture of waste rock and tailings material.After further deterioration of the streambed, Gold Fields of South Africa in the 1990s filled 271 sinkholes occurring within 100 m of each side of the WFS streambed with a total of 2.45 • 10 6 m³ of material (Swart et al., 2003b).Some sinkholes accepted the daily tailings production from nearby metallurgical plants for several months before they were finally filled.In a number of instances, however, the tailings suddenly disappeared overnight into underlying karst receptacles (Swart et al., 2003b).Similar problems were encountered at numerous slimes dams often placed directly onto cavernous dolomite to facilitate drainage of pore-water and support dam stability.This, in turn, resulted in significant volumes of tailings seepage, accelerating subsurface erosion of fine material in karst cavities and subsequently causing the formation of sinkholes in several slimes dams (SD).At one particular slimes dam (No. 3 of Doornfontein GM), a total of 52 sinkholes occurred over a period of 12 years, releasing large amounts of uraniferous material directly into the underlying aquifer.Where affected SDs are located in dewatered compartments, operating gold mines are likely to 'suck in' possible seepage together with pumped dolomitic groundwater.In some instances, however, sinkhole-ridden SDs are located in the full (i.e.not-dewatered) Boskop-Turffontein Compartment at the lower end of the catchment, which currently provides a large proportion of the drinking water of downstream communities such as Potchefstroom.Continuously deteriorating water quality over the past 35 or so years, as observed in a downstream karst spring (Gerhard Minnebron Eye), may well be an indicator of long-term groundwater pollution caused by upstream gold mining (DWAF, 2005).

Apart from groundwater, uranium is also found, and often in much higher concentrations, in surface water bodies, including the WFS.Owing to a range of chemical and physical processes which remove dissolved uranium from the water phase, contamination is not confined to water but also affects fluvial sediments in dams, wetlands and floodplains (Winde, 2006b;c).Following the recent publication of studies indicating the possibility of radioactive pollution causing adverse health effects in local residents as well as downstream water users (Wade et al., 2006;Winde, 2006d;Barthel, 2007), the WFS currently receives extensive media coverage at local, national and even international levels.In response to mounting pressure from NGO's and members of the public, government has currently given an undertaking to address these risks and remediate pollution where necessary (DWAF, 2007).

Through successive consolidation, most mines in the study area are now part of one of the 4 major mining houses operating in South Africa, namely, Gold Fields Limited (GFL), Harmony Gold, AngloGold Ashanti and Durban Roodepoort Deep (DRD).An exception to this is the former No. 4 shaft of Harmony (previously N-shaft of Western Areas), which is now operated by Simmer & Jack as a uranium mine ('Ezulwini') (Hill, 2007) after previous plans to rewater this part of the Gemsbokfontein Compartment (which links the area to the WFS) were abandoned.

In many cases consolidation may have buffered possible effects of closure of smaller mines, through retaining staff and using existing infrastructure to supplement adjacent operating mines with services such as pumping, ventilation, hoisting, etc., as illustrated at the former Ventersdorp and Libanon GMs which now form part of Kloof Division (GFL).A most recent example is the South Deep GM (formerly Western Areas -South Mine) which was acquired by GFL with the intention of accessing the world's largest-known, single gold reserve through existing infrastructure of the adjacent Kloof Mine.By joining underground workings of different gold mines, vast interlinked mine voids are created, which, as recently proven by the Western Basin, will be difficult to model once mining has ceased and data have been lost.Creating up-to-date databases is further complicated by frequent changes in ownership, names and staff of mines and the accompanying loss of site-specific expertise, especially where the periods run over several decades.With such 'loss of institutional memory' afflicting mining companies and governmental regulators alike, it is particularly challenging to retain sufficient data, information, knowledge and expertise for reliably predicting post-closure scenarios.

Mine closure

Experiences from other goldfields suggest that mine closure will most probably be a gradual process, that can stretch over decades, during which mines cease operation at different points in time, according to their profitability.During this extended period influxes of water from abandoned voids into operational mines proved to be a major threat to the profitability of affected mines, as examples from the East Rand (ERPM) and the Klerksdorp goldfields (AngloGold Ashanti) illustrate.Future plans for post-mining development must therefore take into account the implications of interconnected mine voids, by approaching mine closure proactively in a regionally-integrated fashion.

Owing to the increased costs of mining ever-deeper gold reefs, the output of South African gold mines has continued to decline since 1970 but is still sufficient to make South Africa the 3 rd largest producer of gold in the world, surpassed only by China (which overtook South Africa in 2007) and Canada (Robb and Robb, 1998;Campell, 2004;West, 2009).Fuelled by rising demand for mineral resources from rapidly industrialising countries such as China and India, prospects are good that mining in South Africa will continue to be a significant foundation industry for decades to come (Campell, 2004).In the case of gold this is underpinned by a historically unique situation in which an all-time price high is accompanied not by a strengthened Rand (ZAR), as is commonly the case for currencies of mining-dependent economies (thus reducing the USD -based revenue for South African gold mines), but by a local currency which continues to weaken.This combination of exceptionally high gold-prices and a comparably weak ZAR resulted in record ZAR gold prices of ZAR320 000/kg in February 2009 almost 4 times higher than it was in 2004.However, significant increases of production costs to a current average of approximately ZAR251 000/kg limited the net profit (West, 2009).Using current technology, South African gold mines can still access 15 000 t of gold with another 20 000 t available at depths greater than 3 km, for which a new (ultra-deep) mining technology is required (Campell, 2004).As a result lifespans of gold mines in the Far West Rand have significantly been extended, in some cases by up to several decades.With accompanying deepening projects it is envisaged that at the end of mining in the FWR goldfield, the world's 3 deepest mines will be located here (Mponeng, AngloGold Ashanti: 4 300 m; Driefontein, GFL: 4 121 m and Kloof, GFL: 4 020 m; (Venter, 2007;Creamer, 2008)).While gold output and number of employees may continue to decline, mine closure in the FWR is still 2 generations away.An indication of the healthy state of gold mining is, for example, the operating profit of GF,L as a major mining house in the area, which rose from ZAR2.3 bn. in 2005 to ZAR4.4 bn. in 2006 (Brown, 2006), and that was well before the gold price approached the current record highs in late 2007.Renewed interest in uranium, following sharp rises for the radioactive metal since 2003, may also revive the uranium mining for which the area was known.With the re-opening of the former Western Areas North shaft to mine uranium, as well as plans for large-scale uranium extraction from tailings of almost all mining houses in the area, not only gold-but also uranium mining is set to continue in the WFS area for many years to come (Hill, 2008 a;b).

Mining-related urbanisation

Before assessing the implications for urban development of closing gold mines, the extent of mining-related urbanisation is briefly outlined.Settlements initiated or associated with gold mining in the FWR area include: Carletonville (established 1948, named after Guy Carleton Jones, the Canadian-born chief engineer of Gold Fields of South Africa), Blyvooruitzicht villages (associated with the mine of the same name which started active mining in 1943), West-and East-Driefontein villages  Westonaria (est. 1959, originally linked to Western Areas GM).At the time of establishment of many of the towns, apartheid policy forced Black job seekers and workers not living on mine property to settle in townships such as Bekkersdal (associated with Westonaria), Khutsong (associated with Carletonville) and several smaller 'locations' next to 'White' mining towns.Currently an estimated total of 600 000 people live in the area, of which approximately 50% stay in previously 'Black' townships that still suffer from substandard infrastructure including water and sanitation systems (DWAF, 2004).In view of the fact that a census for Khutsong alone established a population of 180 000 (compared to a figure of 68 000 reported by DWAF (2004)), this population estimate is most likely too low.With an estimated population growth of 10% per year, further extensions of current settlements are to be expected (Spies, 2007).Since limited access to resources generally increases the need for (cheap) alternatives, inhabitants of townships are commonly more likely to use polluted media (water, soil, tailings), even in cases where they are aware of potential dangers or where this is illegal.This, again, increases exposure to pollutants in the very population which is most vulnerable owing to inadequate medical and health care, malnutrition, poverty and related stress such as drug abuse as well as effects of other environmental stressors including indoor air and dust pollution.

Mining legacy and resulting future threats

Many of the towns and, to a lesser extent, the townships benefited from mining-related infrastructure, such as hospitals, schools, sport facilities, and 1 st class infrastructure including 4-lane highways, well-maintained reticulation systems for water and electricity and a range of recreational sites such as dams and golf courses, etc.With almost the entire economy in towns such as Carletonville or Westonaria somehow dependent on the mines, ranging from suppliers, craftsmen and consultants to supermarkets, cafés and hairdressers, the (inevitable) closure of mines is perceived as a fundamental threat to the economic future of these municipalities.Adding to the bleakness of such prospects of economic collapse and unemployment is often a mining legacy of environmental degradation and social problems such as increased HIV infection rates and xenophobia, both linked to the migrant labour system employed by mines for decades (Turton, 2008).Combined with slow or lacking progress in service delivery, this has already fuelled social unrest and riots in Khutsong, a township mostly populated by foreign migrant workers who did not return to their home country.It is therefore conceivable that bleak future prospects are, indeed, a real threat, not only to the economy but also to the social fabric and political stability of mining-dependent communities in the entire area.

The near-hysteria evoked by the recent media attention to mining-related pollution of the WFS may well be a subconscious indicator and a means for the venting of such fears.This could be especially true for the WR, where former benefits from mining in the form of employment and income are fading, while environmental degradation becomes more apparent by the day.Ad hoc interviews of residents in Carletonville, where mining still exists, about their perception of mining-related risks such as sinkholes and water pollution, revealed that the overwhelming majority preferred to either ignore such risks or discount them for benefits derived from the mines (NWU, 2006).

Judging by the dire consequences that the uncontrolled rewatering in the WR has had on the environment, it is of utmost importance that effects associated with the flooding of the much larger mine void in the FWR, and subsequent re-watering of dewatered dolomitic compartments, are well understood before they are allowed to happen.Aspects of particular concern include: • A period of severely-reduced water availability during the re-watering phase when no water will be pumped by mines into the Wonderfonteinspruit • The question of whether or not dried-up karst springs will flow, thus making irrigation possible again • Where potential decant points will be located and what the water quality of the decanting water will be • Whether ground stability will be affected by recovering water tables possibly leading to the activation of old, and/or formation of new, sinkholes.

The fact that more than 10 000 households are currently earmarked for relocation from Khutsong North, where a number of sinkholes have formed over many years, to another (also dolomitic) area further south illustrates the magnitude of this aspect (U&E Development Economists, 2005).

Owing to the interconnectivity of the different mine voids in the FWR, similar problems to the ones recently encountered in dolomitic parts of the East Rand and Klerksdorp goldfields, as mentioned earlier, are to be expected.Owing to difficulties in apportioning water volumes to different voids, it is often problematic to find amicable solutions for sharing pumping costs, especially for non-revenue generating mines (Winde et al., 2006).

In growing recognition of the degree to which different mines are impacting on each other, governmental authorities such as the DWA and the Department of Mineral Resources increasingly demand regionally-integrated approaches from different gold mines applying for water use licences and closure certificates, respectively (Van der Merwe, 2008).

Conclusions

Over more than a century of deep-level gold mining the WFS catchment has been profoundly impacted both positively as well as negatively.While providing 1 st class infrastructure and income to a large number of people in a previously underdeveloped area, mining also adversely affected natural resources through large-scale land degradation as an unforeseen side effect of dewatering karstic aquifers as well as through longterm pollution of the environment.In view of the adverse impacts of uncontrolled re-watering currently experienced in the mined-out WR goldfield, it is of utmost importance that comparable impacts are avoided in the FWR, where a much larger interconnected mine void and higher volumes of potentially decanting mine-water could have even more catastrophic effects.To this end it is recommended that data, expertise and information needed for reliably modelling and predicting the effects of future re-watering are secured, for as long as the mines hosting most of this information are still operational.In developing concepts related to mine closure it is necessary to adopt an integrated regional approach taking into account accumulating and combined effects of individual mines on 74 natural resources such as surface water and groundwater, as well as impacts on each other.Overcoming potentially devastating effects of mine closure should be the first and most important step in securing sustainable post-mining development.Opportunities for the latter are discussed in Part 2 of this paper (Winde and Stoch, 2008).

REGM

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