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Keywords:

  • Mycobacterium leprae;
  • leprosy;
  • epidemiology;
  • clustering;
  • Indonesia

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We conducted a population-based survey on five small islands in South Sulawesi Province (Indonesia) to collect baseline data previous to a chemoprophylactic intervention study aiming at interrupting the transmission of Mycobacterium leprae. Here we describe the present leprosy epidemiology on these geographically isolated islands. Of the 4774 inhabitants living in the study area 4140 were screened for leprosy (coverage: 87%). We identified 96 leprosy patients (85 new and 11 old patients), representing a new case detection rate (CDR) of 205/10 000 and a prevalence rate of 195/10 000. CDRs were similar for males and females. Male patients were more often classified as multibacillary (MB) than women. Of the new patients, 33 (39%) were classified as MB, 16 (19%) as paucibacillary (PB) 2–5 lesions and 36 (42%) as PB single lesion. In this area of high leprosy endemicity leprosy patients were extensively clustered, i.e. not equally distributed among the islands and within the islands among the houses.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

For many years leprosy control has been based on passive and active detection of patients followed by multi-drug treatment (MDT). The implementation of short-term MDT has resulted in a decline of the leprosy prevalence, but still there is no evidence that case detection rates (CDRs) are declining at a global level (WHO 2000a). New approaches and strategies to definitely eliminate leprosy as a public health problem are required. These new strategies should be linked to the local epidemiological situation (Visschedijk et al. 2000). Pockets of high leprosy prevalence still exist in remote areas with only limited access to health care (Naik et al. 1999). In such areas, where awareness, patient motivation, and diagnostic procedures are identified as inadequate, active case finding is desirable (Visschedijk et al. 2000).

In this paper we describe the results of an active leprosy survey before a chemoprophylactic intervention study. Five islands in Indonesia were chosen as study area, because their populations are relatively stable due to the isolated location and their demarcation is very clear. The islands were presumed to be highly endemic for leprosy and to have no systematic leprosy control established yet. In such a relatively unexplored area with regard to leprosy control, it is interesting to know people who are most at risk of developing leprosy.

Methodology

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Selection and description of study area and population

Five small islands, Tampaang, Pelokang, Kembanglemari, Sailus besar and Sapuka besar, were selected. These are part of Pangkep District of South Sulawesi Province in Indonesia and belong to the 30-island archipelago Liukang Tangaya, situated in the Flores Sea, about 30 h by boat from Makassar. This archipelago was selected as the study area because of its geographical isolation and the absence of a routine leprosy control programme. The islands measure less than 15 km2 each, and at the time had a population of about 5000. The inhabitants belong to different tribes – such as Bugis, Makassar and Mandar – that originated from Sulawesi.

Most people lived in wooden houses built on stilts. Facilities for drinking water and sanitation were poor. Most houses did not have access to the few generators producing electricity at night. The main income-generating activity of the men was fishing. Irregular leprosy MDT services started on the islands in 1993. The two bigger islands, Sapuka and Sailus, had a puskesmas (Community Health Centre). As a rule a doctor and a nurse were present on Sapuka and only a nurse on Sailus.

Data and sample collection

Before the study was undertaken we received ethical clearance from the Ethical Research Committee of Hasanuddin University and from the Ministry of Health of the Republic of Indonesia. Prior to the survey, local health care workers attempted to register the house number, name, age and sex of all inhabitants. All registered inhabitants received a personal code. All houses on the five islands were numbered and detailed maps of the islands were prepared, giving the location of all the houses.

Data were collected by means of a cross-sectional study during two surveys. In June/July 2000 we screened the population for leprosy. In November 2000 we visited the study area again to examine persons who were not screened during the first visit. The same team of 15 people – doctors, leprosy workers, nurses, technicians and researchers – visited the five islands during both periods. Everybody was clinically examined at central points near the houses. For reasons of privacy, women were always examined inside a building. People who did not come to these central points were visited at home.

Experienced leprosy workers carried out a detailed skin examination including testing for anaesthesia. The diagnosis was confirmed by one of the doctors and in case of doubt this doctor did a complete re-examination. Leprosy classification was in first instance based on clinical symptoms in conjunction with skin lesion counting [1–5 lesions is paucibacillary (PB), more than five lesions is multibacillary (MB)]. Single-lesion leprosy patients (PB1) were those who had only one lesion, and no nerve trunk involvement (WHO 1998a). Three slit-skin smears were taken from all new patients detected during the first survey (in most cases one from each ear and one from a lesion) to determine the bacterial index (BI) by microscopy using acid-fast staining. Clinically diagnosed PB patients who had a positive BI at any one site (= skin smear positive) were re-classified as MB patients. The leprosy register at Sapuka, covering the five islands, was checked to see if there were persons who had been treated for leprosy before. From those already treated persons at least one skin smear was taken from one ear. When this smear was positive, they were classified as patients having active MB leprosy to prevent undertreatment and risk of continuous infection. Other reasons for classifying already treated patients as having active leprosy were clinical symptoms and defaulting treatment. These patients are referred to as ‘old patients’. We also took a skin smear from one ear from household contacts of leprosy patients. Treatment of patients according to the national guidelines started immediately after diagnosis. Single-lesion PB leprosy patients were treated with the standard PB treatment regimen. The upper arms of everybody were checked for a scar indicating BCG vaccination.

Definitions of contacts

For this study the concept of contacts of leprosy patients was broadened to include not only household contacts, but also direct neighbours (neighbour 1) and next neighbours (neighbour 2) (van Beers et al. 1999). Household contacts were defined as persons who lived or had lived with a patient in the same household (= house). Neighbour 1 contacts were defined as persons who lived or had lived in one of the directly adjacent houses of the house of a patient with not more than 50 m distance between the houses (usually: one to the left, one to the right, one directly across the street and one at the back). Neighbour 2 contacts were defined as persons who lived or had lived next to a neighbour 1 house with not more than 50 m distance between the houses. For all contact types the duration of the contact should have lasted at least 6 months and the contact should not have ended longer than 6 months prior to the first survey.

Prevalence rate and CDR

The leprosy prevalence rate was defined as the ratio of leprosy cases registered for therapy at the end of the second survey over the total population at that time. This means that patients who moved outside the study area or died after the first survey were not included in the prevalence. The CDR was defined as the number of newly detected, previously untreated, cases during the first and second survey divided by the population examined (WHO 1998a). Age and sex standardized CDRs were calculated using weighted averages of the stratum-specific prevalence rates. The total study population was used as standard to calculate the weights (Rothman & Greenland 1998). Prevalences and CDRs are given per 10 000 persons as this is customary in leprosy control.

Data analysis

All data were recorded on special forms and immediately entered into Epi-Info, version 6. Data were analysed using SPSS. All tests described used an alpha of 5% and were 2-sided. For the comparison of percentages the chi-squared test was used.

The distribution of leprosy patients among houses was examined by comparing the observed and expected number of patients per household size in a goodness-of-fit test [Σ(O – E)2/E]. The expected frequency of houses with different numbers of leprosy patients was calculated per household size using a binomial distribution with probability P, where P is the number of patients over the total population. The expected number of houses with each frequency of patients per household size was then obtained by multiplication of the expected frequency with the number of houses in each size category.

We analysed whether leprosy patients were clustered in specific types of clusters. Three types of clusters were defined: House; A house and its neighbours 1; A house and its neighbours 1 and neighbours 2. With the help of the maps, we determined for each patient for the three different types of clusters whether he/she is living with at least one other patient in the same cluster. When this was the case the patient was scored ‘positive’ for living in a cluster with another patient. The sum of the ‘positive’ patients was calculated as a percentage of the total number of patients. The same calculation was carried out for a control group. This group consisted of the same number of persons as there were patients randomly chosen per island stratified for age corresponding to the age distribution of the patients. The patients and controls were compared with a chi-squared test.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Demographic features and coverage of the study

A population of 4774 persons, living in 1111 houses, was registered on the five islands (average: 4.3 persons per house). Between the first and the second survey 15 persons were newly registered and nine people moved or died. Of the registered population 48% were male. Young children (0–10 years) comprised 30% of the population (Figure 1). The median age was 20 years (mean 24 years), varying from 17 years on Kembanglemari to 22 years on Sapuka.

image

Figure 1. Distribution of the registered andexamined population by age and sex onthe five islands

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In total 4140 persons were clinically examined (1863 males and 2277 females): 3987 persons during the first survey and 153 during second survey, giving a total coverage of 86.7%, varying from 81% in males to 91.5% in females and between islands from 83% on Sapuka to 92% on Kembanglemari. Most people who were not screened were not present at the time of examination because of other activities such as fishing. Table 1 presents the number of inhabitants and screened population per island.

Table 1.  Coverage of the study and leprosy case detection rate per island
 InhabitantsScreenedScreened (%)New leprosy patients CDR* /10 000Age and sex adjusted CDR/10 000Old leprosy patients
  • *

     CDR = case detection rate.

  • † 

    Patients treated before, but not cured (no distinction possible between defaulted treatment, re-infected or relapsed).

Tampaang 225 20088.9% 2100 83 0
Pelokang 393 35690.6% 8225229 1
Kembanglemari 637 58391.5%24412406 4
Sailus1451128488.5%27210201 0
Sapuka2068171783.0%24140142 6
Total4774414086.7%8520511

The proportion of people with a BCG-scar was very low, varying from 1.4% on Sailus to 7.6% on Sapuka for the total population. The BCG-vaccination percentage among children under 5 (average: 12%) varied from 2.9% on Pelokang to 22.0% on Sapuka indicating that BCG coverage had recently improved only little.

Leprosy CDR and prevalence

During the two surveys 85 individuals (80 during the first survey and five during the second survey) were newly diagnosed with leprosy. This represented an overall CDR of 205 per 10 000 [95% confidence interval (95% CI): 162–248], ranging from 100 on Tampaang to 412 on Kembanglemari (Table 1).

Twenty-nine individuals had been registered for MDT treatment on the five islands between 1993 and 1998, 17 of them could be traced during screening in 2000.

Furthermore, four patients, who had taken treatment before but were not listed in the leprosy register at Sapuka, were identified during screening. Nobody was taking MDT at the start of this study. Of the 21 (17 + 4) previously treated patients who could still be traced, 11 were classified as having active leprosy (‘the old leprosy patients’); five were clinically diagnosed as MB and skin smear positive, one was clinically inactive, but skin smear positive (MB) and five had not completed a full course of medication and still had active lesions, but were skin smear negative (four mB and one PB).

The 10 remaining patients who had been treated before had no more active lesions, were skin smear negative, reported to have completed a full course of MDT and were therefore marked as patients released from treatment (RFT) and not included in the prevalence. Between the first and second survey one patient from Sailus had moved away and two patients from Pelokang had died from non-leprosy treatment-related causes. The overall prevalence rate was 195 per 10 000 (95% CI: 156–234), ranging from 89 on Tampaang, 145 on Sapuka, 179 on Sailus, 181 on Pelokang, to 440 per 10 000 on Kembanglemari.

Characteristics of leprosy patients

Of the 85 newly detected patients 33 (39%) were classified as MB, 16 (19%) as PB patients with 2–5 lesions (PB2–5) and 36 (42%) as PB1. Of the 11 old patients 10 (91%) were classified as MB and one as PB (9%). Overall 45% (43/96) of the patients were classified as MB, 17% (16/96) as PB2–5 and 39% (37/96) as PB1. The proportion of MB patients varied between 41% on Sailus and 50% on Sapuka and Tampaang (Table 2).

Table 2.  Classification of all active patients per island
 PB1PB2–5PB (%)MBMB (%)Total
Tampaang 1 050% 150% 2
Pelokang 4 156% 444% 9
Kembanglemari13 357%1243%28
Sailus11 559%1141%27
Sapuka 8 750%1550%30
Total37 (39%)16 (17%)55%4345%96

Although there were more female (45; 53%) than male (40; 47%) new leprosy patients, the CDR for males (40/1863; 215/10 000) and females (45/2277; 198/10 000) did not differ significantly (P = 0.7). New female patients were more often classified as PB1 (24/45; 53%) than men (12/40; 30%) (P = 0.030). New male patients were more often classified as MB (20/40; 50%) than women (13/45; 29%) (P = 0.046). Of the 11 old patients eight were female and of the 10 RFTs two were female.

The age of the patients ranged from 6 to 73 years. The mean age for all patients was 29.8 years (median 27 years). Nineteen children < 16 years were diagnosed with leprosy. They represented 21.2% (95% CI: 12.5–29.9%) of newly detected patients and 19% (95% CI: 10.9–26.6%) of all detected patients (18/96). None had taken treatment before. The CDR in children < 16 years was 111/10 000 (19/1718). Figure 2 shows the CDR per age group and sex. Although the numbers of patients per age/sex group were relatively small, ranging from 0 to 9 patients, differences were seen between males and females. The CDR of females was relatively stable over the different age-categories with a lower CDR at age 21–35 years. The men had peaks in CDR at ages 21–30 years and ages 46–50 years. At age 21–30 years the CDR of males was significantly higher than the CDR of females (505/10 000 vs. 151/10 000; P = 0.005). Seven female patients were older than 50 years. Only two male patients were found in this age group. Of the 85 newly detected patients, five (6%) had a disability grade 2, as did five (45%) of the 11 old patients. All patients with a disability were MB. The disability rate (grade 2) among the patients differed per island, varying from 20% (6/30) on Sapuka to 0% (0/9) on Pelokang. Nerve enlargement was documented in 20/85 (23%) of the new patients and in 5/11 (45%) of the old patients.

image

Figure 2. Case detection rate in 2000 by age and sex on the five islands. (Numbers in bars are absolute numbers of detected patients).

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Skin-smear positivity

We collected skin smears from 90 patients (16 with positive and 74 with negative result); for six new patients the result was missing (two children and four patients detected during the second survey). The proportion of skin smear positivity among the new cases detected was 13% (10/79). As the classification of patients was mainly based on clinical symptoms, not all MB patients were skin smear positive. Ten of 31 new MB (32%) and six of 10 old MB (60%) patients were skin smear positive. Two clinically diagnosed PB patients were skin smear positive with BIs of 1+ and 2+ at all three sites and re-classified as MB. One household contact was found skin smear positive; upon re-examination the disease was also clinically confirmed. Differences were seen in the proportion of skin smear positive MB patients between the islands, which varied from 60% at Sapuka, 50% at Pelokang, 27% at Sailus to 17% at Kembanglemari.

Clustering of patients

The 96 patients were living in 78 of the 1111 houses on the islands (7.0%), varying between 4.6% on Sapuka and 19% on Kembanglemari. To examine whether patients were equally distributed among all households, the observed and expected number of patients among households were compared (Table 3). Sixty-five dwellings housed a single patient, 10 houses two patients, two houses three patients and one house five patients. The number of houses with two or more patients was higher than expected, so the patients were significantly more often living together. On the other hand, significantly more patients were living alone (4/96) compared with non-patients (60/4678) (P = 0.047).

Table 3.  Distribution of the number of observed and expected leprosy patients among households
Number of patientsNumber of houses
per houseObservedExpectedChi-squared
  1. χ2 = 23021; degrees of freedom = 5; P < 0.0001.

010331018.92     0.19
1  65  88.21     6.11
2  10   3.76    10.38
3   2   0.11    33.26
4   0   0.00     0
5   1   0.0022 971
Total1111111123 021

Thirty-one patients (32%) were a household contact of another patient (cluster 1), 50 patients (52%) were a household or neighbour 1 contact (cluster 2) and 61 (64%) patients were household, neighbour 1 or neighbour 2 contact (cluster 3). Table 4 shows the values for the patients and the controls. Part of the observed clustering of patients could be explained by chance (see controls). However, for all three types of clusters the percentage of patients clustered was significantly higher than the percentages caused by chance. This effect diminished when widening the cluster. The same analysis, excluding the PB1 patients, was performed for the group of MB and PB2–5 patients. This gave the same results.

Table 4.  Percentage of patients and controls living in different types of clusters with at least one other patient, respectively, control, all islands combined
Type of clusterPatients (%)Controls (%) Pat./Con.P-value
  • *

     N1 = Neighbour 1 (direct neighbours).

  •  N2 = Neighbour 2 (next neighbours).

House32162.070.007
House + N1*52301.750.002
House + N1 + N264471.340.029

The distribution of patients between islands differed: a comparison of the age and sex adjusted CDRs (Table 1) showed an uneven distribution (P = 0.002), with a concentration of patients on Kembanglemari. On this high prevalence island the distribution of patients and controls in houses and neighbouring houses were similar and thus clustering of patients could not be detected. The islands with lower prevalence rates, on the other hand, did show clustering of patients.

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Although leprosy control programmes try their best to reach the WHO goal of eliminating leprosy as a public health problem, defined as reduction of the leprosy prevalence to a level below 1/10 000 population at a national level per 2005 (WHO 2000b), pockets with extremely high leprosy prevalence still exist. The latest available information showed a 1.1/10 000 prevalence in Indonesia and a detection rate of 8.3/100 000 per year (WHO 2000a). Comparing these figures with the prevalence (195 per 10 000) and detection rate (205/10 000) found in this study confirms that leprosy is not evenly distributed in Indonesia.

As no regular leprosy control programme was operating in the study area, patients have been accumulating over a long period of time, making comparison between the figures of our study and those of the WHO difficult. This accumulation means that there may have been a backlog of undetected cases that was now found at one time point. However, this is contradicted by the observation that only 6% of the patients had grade 2 disability. MDT services started in 1993, but until 1998 only 29 patients had been put on treatment. During our surveys in 2000, 85 new patients were detected through active case finding, and 11 of the old patients still had active leprosy. Surveys conducted in remote areas in India and in areas not covered by leprosy control services found similar high prevalence rates of 32/10 000, 109/10 000 and 20/10 000 (Naik et al. 1999).

The specificity and sensitivity of the screening are important in discussing the high CDRs. Overdiagnosis could play a role in the high number of newly detected cases. On the other hand, some patients are always missed. By taking a skin smear of 56% of the household contacts > 5 years (94% were clinically examined), we aimed to reduce the risk of missing patients in this high risk group.

The reasons for the high endemicity of leprosy in our study area could be, among others, the irregular leprosy control and inadequate general health care facilities on the islands. The low BCG immunization coverage could be a reason, because several studies have indicated a protective effect of BCG vaccination against the development of leprosy (Fine 1988). Other factors such as socio-economic status, nutrition, immune response, environmental mycobacteria and genetic factors may all have an effect on the transmission of leprosy. The overall CDR for female and male patients were similar, while most reviews report that the CDR for males is higher than for females (Fine 1982; Noordeen 1985; Van Beers et al. 1996; Jacobson & Krahenbuhl 1999). Noordeen (1985) stated that males are affected more frequently than females, often in the ratio of 2:1. This reported male excess could be the result of a difference in examining males and females or to unequal availability of health services for men and women. As this was a total population survey, we aimed at examining all men and women. Moreover, we took all precautions to ensure that women and men were equally well examined. Noordeen also said that the male preponderance is much more pronounced in lepromatous leprosy than in tuberculoid leprosy. This latter statement is in line with our findings that men have a higher chance of being MB compared with women. The lower CDR in women of reproductive age (21–35) is surprising, because pregnant women, who form a substantial part of this age group, are thought to be at increased risk of developing the disease, relapse and reactions (Shale 2000). During pregnancy immunological changes occur which may weaken cell-mediated immunity and strengthen humoral immunity (Wegmann et al. 1993), permitting intracellular infectious diseases such as leprosy to develop or exacerbate. Only very few studies have investigated the incidence of leprosy in pregnant women.

In 1997, 41% of the new patients detected around the world were classified as MB (WHO 1998b). In Indonesia this percentage was much higher (79%) (WHO 1998c). The proportion of MB cases found during leprosy elimination campaigns (LECs) in Indonesia was 59% (WHO 2000c). The proportion of MB cases found in the present study was 39% of the newly detected cases. It appears that the more active the case finding, the lower the proportion of MB cases. One explanation may be that during active surveys patients with single lesions are also detected and classified as PB, but they may heal spontaneously when not detected (Fine 1982) and escape passive case detection.

In 1997 on average 7% of the new cases detected in 32 endemic countries had a disability of grade 2 (WHO 1998b). In our study the proportion of cases with disability grade 2 was 6% among the 85 newly detected cases and 45% among the 11 old patients (overall 10.4%). This is comparable with the proportion of detected cases with a grade 2 disability (9%) found during LECs carried out in Indonesia (WHO 2000c). As active surveys have a higher proportion of single lesion patients, the disability rate among new MB patients and PB2–5 patients (10%) gives a better figure.

In 1997, the proportion of children below 15 years among all leprosy patients was on average 14% in 32 endemic countries (WHO 1998b). The proportion of children <15 years among the new cases detected in this study was 21% (18/85). However, the age distribution ofapopulation plays an important role in these figures. Apopulation with many children will find in absolute numbers more children with leprosy than a population with a smaller proportion of children. The CDR among children is a better measure. The generally described age pattern of leprosy incidence rates: a peak at ages 10–14 years followed by a depression which in turn is followed by a rise and a plateau covering ages 30–60 (Fine 1982; Noordeen 1985) differs from the pattern found on the islands. Here we do not see this peak in CDR early in life.

We found that patients are not only clustered within houses, but also in a wider cluster of houses and neighbouring houses. This is in line with our earlier findings (van Beers et al. 1999) that by expanding the criteria of contact status beyond that of households, including neighbours and social relationships, most incident leprosy patients can be related to previous cases. Our data are also in line with the idea that clustering is less important as prevalence increases and conversely more important as prevalence decreases. On Kembanglemari, the island with the highest leprosy CDR (412/10 000), clustering of leprosy patients could not be demonstrated, indicating that on this island everybody has an equally high risk of developing the disease.

In the cluster analysis we only used patients undergoing treatment. Those RFT were excluded, because it was not clear whether they had moved since the end of therapy. However, of these 10 persons RFT four were living in houses with present patients and two were direct neighbours of present patients. Our way of analysing the clustering of patients seems to have the risk of potential over-estimation of the effect because of double counting. For example if case A is a neighbour of case B then case B also becomes a neighbour of A and this could result in double counting. However, this potential overestimation of the effect also occurred at a similar rate in the control group and is thus corrected.

Treatment of patients following a diagnosis based on clinical examination only, including lesion counting, would have led to an undertreatment of two of the 10 smear positive new patients (20%). Croft et al. (1998) and Bührer et al. (2000) found slightly lower results in their studies, respectively, 11% (18/163) and 15% (19/130). When MB patients are defined as those with a BI > 0 at any one site, our diagnosis based on clinical examination only would have resulted in overtreatment of 21 of 69 skin smear negative new patients (30%). This illustrates the limitations of the current classification system of the WHO based on clinical symptoms only (Croft et al. 1998).

General data on leprosy often face problems in reliability as a result of missed cases, different policies for special groups and difficulties in diagnosis. Conclusions drawn from epidemiological surveys examining entire populations in a defined area are less susceptible to sampling error. This study describes epidemiological data of leprosy collected by examining almost the entire population of a well-defined area, and reveals a highly leprosy endemic area with extensive clustering within a country that has almost reached the WHO elimination goal.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We highly appreciate the financial support of this study, which is part of the project ‘Development of strategies for pro-active case finding in leprosy control’, of the Netherlands Leprosy Relief. We thank Dr H.M. Noor, head of the Health District Pangkep for permission and active support. We thank H. Hasan Basri and H. Baso Datu of the P2M Province, H. Azis Nur of the P2M district Pangkep, I. Nengah Sudja of the P2M District Maros, Hj. Asriah of the laboratory of Maros and Mr Saeni of the laboratory of Pangkep who were involved in the supervision of the clinical and laboratory examinations. Furthermore we are grateful to Dr Henry, head of the Health Centre Liukang Tangaya Pangkep. We thank Hj. Rabiah (ass. head), Amril (nurse), Arief (nurse), Sufrianti (nurse) and Syahuni (nurse), Mr Romy Usman (technician), Mr Marwani (technician), Mr Syafri (technician) and Mr Mus Jebaru of the Hasanuddin University and Pim Jansen (medical student) for their participation in the fieldwork. We thank all the inhabitants of the five islands: Sapuka Besar, Sailus Besar, Kembanglemari, Pelokang and Tampaang for their co-operation. We thank Prof. C. Smith, Prof. W.R. Faber, Dr P. Feenstra, Dr J. Visschedijk, Dr S. van Beers and Dr S. Bührer-Sékula for critically reading the manuscript and giving their comments.

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  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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