Climate, soil type, and geographic distribution of actinomycetoma cases in Northeast Mexico: A cross-sectional study

Mycetoma is a chronic, granulomatous infection of subcutaneous tissue, that may involve deep structures and bone. It can be caused by bacteria (actinomycetoma) or fungi (eumycetoma). There is an epidemiological association between mycetoma and the environment, including rainfall, temperature and humidity but there are still many knowledge gaps in the identification of the natural habitat of actinomycetes, their primary reservoir, and their precise geographical distribution. Knowing the potential distribution of this infection and its ecological niche in endemic areas is relevant to determine disease management strategies and etiological agent habitat or reservoirs.

This was an ambispective descriptive study of 31 patients with actinomycetoma. We determined the biophysical characteristics including temperature, precipitation, soil type, vegetation, etiological agents, and mapped actinomycetoma cases in Northeast Mexico. We identified two disease cluster areas. One in Nuevo Leon, with a predominantly kastanozems soil type, with a mean annual temperature of 22°, and a mean annual precipitation of 585.2 mm. Herein, mycetoma cases were produced by Actinomadura pelletieri, Actinomadura madurae, Nocardia brasiliensis, and Nocardia spp. The second cluster was in San Luis Potosí, where lithosols soil type predominates, with a mean annual temperature of 23.5° and a mean annual precipitation of 635.4 mm. In this area, all the cases were caused by N. brasiliensis. A. madurae cases were identified in rendzinas, kastanozems, vertisols, and lithosols soils, and A. pelletieri cases in xerosols, kastanozems, and rendzinas soils. Previous thorn trauma with Acacia or Prosopis plants was referred by 35.4% of subjects. In these states, the presence of thorny plants, such as Acacia spp., Prosopis spp., Senegalia greggi, Vachellia farnesiana and Vachellia rigidula, are common.

Mapping this neglected tropical infection aids in the detection of disease cluster areas, the development of public health strategies for early diagnosis and disease prediction models; this paves the way for more ecological niche etiological agent research.