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Spatial analysis of factors implicated in Mycobacterium ulcerans infection in Ghana

  • A.A. Duker

Research output: Thesis › external PhD, WU

Abstract

Buruliulcer (BU), the common terminology for the disease caused by Mycobacteriumulcerans (MU) infection manifests as disfiguring skin ulceration which is difficult to treat. In its advanced stage the disease does not respond to drugs and requires surgery, often limb amputation. It sometimes results in death. It is most widespread inWest Africa.

InGhana, the first BU case was reported in 1971 and between 1991 and 1997 more than 2000 cases were reported. Approximately 6000 cases were recorded in a national survey in 1999. Of the 110 districts inGhana, at least 90 of them were found to have BU cases of whichAmansieWest District (the study area) had the highest rate with a prevalence of 150.8 per 100,000. The district is made up of about 310 settlements with a total population of about 108,726. High incidence of BU occurs in settlements in close proximity to theOffinRiver.

Infection is acquired through MU in the natural environment. Knowledge gaps about the exact mode of transmission and factors that pre-dispose to infection motivate this study. It employs a spatial approach to the relation between BU and postulated risk factors in part of theAmansieWest District of Ghana.

Arsenic is implicated in several types of skin diseases including skin cancers. This may be due to its immunosuppressive affects, which enhance susceptibility to infection. This study takes as risk factors different pathways of potential exposure to enhanced levels of arsenic in the environment.

Arsenic concentrations in stream sediment were used to infer relative arsenic levels in surface waters and floodplain soils. The incidence of BU per settlement was then related to the arsenic levels of these domains by proximity analysis. The results showed that mean BU prevalence in settlements along arsenic-enriched drainages and within arsenic-enriched farmlands is greater than elsewhere. However, mean BU prevalence is greater along arsenic-enriched drainages (0.7%) than within arsenic-enriched farmlands (0.6%).

Arsenic concentrations in surface (stream) waters and ground (wells) waters were determined for abstraction points used by inhabitants of settlements of the study area. These arsenic data and BU prevalence per settlement were employed in exposure-responsemodellingusing linear regression. The results showed that BU prevalence has a significant positive relationship with arsenic levels in surface water ( R 2 = 0.82, p < 0.05) but not with arsenic levels in groundwater ( R 2 = 0.10, p = 0.60).

Arsenic liberation into the environment by oxidation ofarsenopyriteduringartisanalgold mining rendersminesitesa postulated risk factor for BU. Cases increased since the promulgation in 1989 of the Small Scale Mining Law, which legalized and increased such mining. The results of proximity analysis showed that most settlements relatively near toartisanalminesitesexhibited disproportionately higher BU incidence ( R 2 = 0.48, p < 0.01) than elsewhere in the study area ( R 2 = 0.00, p = 0.90).

An integrated spatial-statistical model showed that settlement elevation, inferred arsenic floodplain soils, and distance tominesiteswere significantly correlated with BU. Surface water has a positive association with disease but not at statistically significant level. The results suggest that chronic ingestion of elevated concentrations of arsenic in drinking water and of arsenic taken up byfoodcropsproduced in arsenic-enriched soils adversely impact human health, perhaps by disruption of immune mechanisms, compromisingdefenceagainst opportunistic infections such as MU.

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Stein, A., Promotor
  • Hale, M., Promotor, External person
  • Carranza, J., Co-promotor, External person
Award date1 Jul 2005
Place of Publication[s.l.
Print ISBNs9789085042433
DOIs
Publication statusPublished - 1 Jul 2005

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • diseases
  • symptoms
  • spatial distribution
  • geographical information systems
  • ulcers
  • arsenic
  • statistical analysis
  • ghana

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