A tale of two neglected tropical infections: using GIS to assess the spatial and temporal overlap of schistosomiasis and leprosy in a region of Minas Gerais, Brazil

Abstract

BACKGROUND Despite public health efforts to reduce the global burden of leprosy, gaps remain in the knowledge surrounding transmission of infection. Helminth co-infections have been associated with a shift towards the lepromatous end of the disease spectrum, potentially increasing transmission in co-endemic areas.OBJECTIVES Using this biologically plausible association, we conducted a geographic information systems (GIS) study to investigate the spatial associations of schistosomiasis and leprosy in an endemic area of Minas Gerais (MG), Brazil.METHODS Data on new cases of Mycobacterium leprae and Schistosoma mansoni infections from 2007-2014 were retrieved from the Brazilian national notifiable diseases information system for seven municipalities in and surrounding Vespasiano, MG. A total of 139 cases of leprosy and 200 cases of schistosomiasis were mapped to a municipality level. For one municipality, cases were mapped to a neighborhood level and a stratified analysis was conducted to identify spatial associations.FINDINGS A relative risk of 6.80 [95% confidence interval (CI) 1.46 - 31.64] of leprosy was found in neighborhoods with schistosomiasis. Incidence rates of leprosy increased with corresponding incidence rates of schistosomiasis, and the temporal trends of both infections were similar.CONCLUSIONS The associations found in this project support the hypothesis that helminth infections may influence the transmission of leprosy in co-endemic areas.

Poor WASH (Water, Sanitation, and Hygiene) Conditions Are Associated with Leprosy in North Gondar, Ethiopia

“…Overall WASH index scores were low for participants, particularly on the sanitation and hygiene ladders and, as predicted, our study found an association between several WASH factors, including soap access and open defecation, with leprosy infection. We also hypothesized that there would be an association between schistosomiasis and leprosy based upon previous studies linking helminth infection to leprosy infections and the immune response to helminth infections [ 7 , 8 ]. Helminth infections up-regulate the Th2 immune response and down-regulate the Th1 response, which reduces the immune system’s ability to control M. leprae infection.…”

“…Recent studies have suggested that soil-transmitted helminth infection may facilitate or increase the risk of leprosy infection [ 7 ]. Helminth infections typically up-regulate the Th2 immune response and down-regulate the Th1 immune response, meaning the diminished Th1 response may lead to a lesser likelihood of controlling M. leprae infection, and therefore a higher likelihood of leprosy, in particular, MB leprosy [ 8 ]. A geographic association of overlapping schistosomiasis and leprosy was found in a co-endemic area of Brazil [ 7 ].…”

Hyperendemicity, heterogeneity and spatial overlap of leprosy and cutaneous leishmaniasis in the southern Amazon region of Brazil

“…In addition, the integrated control of leprosy and CL facilitates targeted training of health professionals for the differential diagnosis of these two diseases, which is essential for a better prognosis (Moschella and Garcia-Albea, 2016;Mitjà et al, 2017). The occurrence of leprosy may also be influenced by the occurrence of CL, specifically in the areas highlighted by the BiLISA statistics, as has already been proposed for other infectious diseases in Brazil (Phillips et al, 2017) and abroad (Aturinde et al, 2019). These two diseases share certain clinical, immunological and epidemiological aspects (Martínez et al, 2018) as reported in relation to some cases of co-infection in Brazil (Costa et al, 2009;Mercadante et al, 2018).…”

“…First, we used secondary data which is generally susceptible to missing information and underreporting. However, leprosy and CL are both notifiable diseases in Brazil, and reporting is mandatory for subsequent treatment (Phillips et al, 2017). Second, due to the database structure it is not possible to determine whether diagnoses concern the same individual, nor can any causal relationship between them be identified.…”

Web-based health databases and real-time GIS-based disease surveillance for leprosy control: fighting ancient evil with modern tools

“…It also aids as a visualisation tool in conveying the risk and progress of the preventive actions. GIS-based disease surveillance has many advantages over the traditional systems such as it can detect clustering of events (that aggregated tabular data usually tends to overlook), identification of social and environmental factors that influence disease transmission, and revealing trends, dependencies and inter-relationships which is obscure (7)(8). The key areas that programme managers in leprosy control can use GIS include: carrying out focused screening strategies (community-Wijesinghe MSD.…”