Spatial clustering of porcine cysticercosis in Mbulu district, northern Tanzania

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Abstract

Background: Porcine cysticercosis is caused by a zoonotic tapeworm, Taenia solium, which causes serious disease syndromes in human. Effective control of the parasite requires knowledge on the burden and pattern of the infections in order to properly direct limited resources. The objective of this study was to establish the spatial distribution of porcine cysticercosis in Mbulu district, northern Tanzania, to guide control strategies. Methodology/Principal Findings: This study is a secondary analysis of data collected during the baseline and follow-up periods of a randomized community trial aiming at reducing the incidence rate of porcine cysticercosis through an educational program. At baseline, 784 randomly selected pig-keeping households located in 42 villages in 14 wards were included. Lingual examination of indigenous pigs aged 2-12 (median 8) months, one randomly selected from each household, were conducted. Data from the control group of the randomized trial that included 21 of the 42 villages were used for the incidence study. A total of 295 pig-keeping households were provided with sentinel pigs (one each) and reassessed for cysticercosis incidence once or twice for 2-9 (median 4) months using lingual examination and antigen ELISA. Prevalence of porcine cysticercosis was computed in Epi Info 3.5. The prevalence and incidence of porcine cysticercosis were mapped at household level using ArcView 3.2. K functions were computed in R software to assess general clustering of porcine cysticercosis. Spatial scan statistics were computed in SatScan to identify local clusters of the infection. The overall prevalence of porcine cysticercosis was 7.3% (95% CI: 5.6, 9.4; n = 784). The K functions revealed a significant overall clustering of porcine cysticercosis incidence for all distances between 600 m and 5 km from a randomly chosen case household based on Ag-ELISA. Lingual examination revealed clustering from 650 m to 6 km and between 7.5 and 10 km. The prevalence study did not reveal any significant clustering by this method. Spatial scan statistics found one significant cluster of porcine cysticercosis prevalence (P = 0.0036; n = 370). In addition, the analysis found one large cluster of porcine cysticercosis incidence based on Ag-ELISA (P = 0.0010; n = 236) and two relatively small clusters of incidence based on lingual examination (P = 0.0012 and P = 0.0026; n = 241). These clusters had similar spatial location and included six wards, four of which were identified as high risk areas of porcine cysticercosis. Conclusion/Significance: This study has identified local clusters of porcine cysticercosis in Mbulu district, northern Tanzania, where limited resources for control of T. solium could be directed. Further studies are needed to establish causes of clustering to institute appropriate interventions. © 2010 Ngowi et al.

Figures

  • Figure 1. Flow of participants selected for analysis of spatial distribution of porcine cysticercosis prevalence in household pigs based on lingual examination, and of incidence in sentinel pigs based on Ag-ELISA. Mbulu district July 2002–April 2004. doi:10.1371/journal.pntd.0000652.g001
  • Figure 2. Spatial pattern (household level) of porcine cysticercosis prevalence based on lingual examination of household pigs in Mbulu district, northern Tanzania, 2002–2003.
  • Figure 3. Spatial pattern (household level) of porcine cysticercosis incidence in sentinel pigs monitored for a median of 4 months (range: 2–9 months) using Ag-ELISA and lingual examination in Mbulu district, northern Tanzania, July 2003–April 2004.
  • Figure 4. Differences between univariate K functions to test for spatial clustering of porcine cysticercosis, Mbulu district, Tanzania, 2003–2004. The difference between the univariate K functions is denoted here by K1-K2 while r represents the radius. (A) presents the results based on Ag-ELISA incidence while (B) and (C) present results based on lingual examination incidence and prevalence, respectively. Upper and lower 95% confidence limits for the K functions are indicated by dotted lines. doi:10.1371/journal.pntd.0000652.g004
  • Figure 5. Differences between univariate and bivariate K functions to test for spatial segregation of each individual pattern, Mbulu district, Tanzania, 2003–2004. The difference between the univariate and bivariate K functions for case households is denoted here by K1–K * 12. On the other hand, K2–K * 12 denotes the difference for control households, and r is the radius. Figure 5 A and B show the results based on Ag-ELISA incidence while C and D present results based on lingual examination incidence. Upper and lower 95% confidence limits for the K functions are indicated by dotted lines. doi:10.1371/journal.pntd.0000652.g005
  • Figure 6. Local clusters of porcine cysticercosis in Mbulu Ditrict, Tanzania, 2003–2004. This figure describes local clusters of porcine cysticercosis identified by the prevalence study (circle A) and incidence studies based on lingual examination (circles B and C) and Ag-ELISA (circle D), as revealed by spatial scan statistical analyses at household level. doi:10.1371/journal.pntd.0000652.g006
  • Table 1. Ward specific relative risks (RRs) of porcine cysticercosis based on different studies.

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CITATION STYLE

APA

Ngowi, H. A., Kassuku, A. A., Carabin, H., Mlangwa, J. E. D., Mlozi, M. R. S., Mbilinyi, B. P., & Willingham, A. L. (2010). Spatial clustering of porcine cysticercosis in Mbulu district, northern Tanzania. PLoS Neglected Tropical Diseases, 4(4). https://doi.org/10.1371/journal.pntd.0000652

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