Spatio-temporal modeling of visceral leishmaniasis in Midwest Brazil: An ecological study of 18-years data (2001–2018)

Abstract

Visceral leishmaniasis (VL) is a neglected vector-borne disease associated with socioeconomic and environmental issues. In Brazil, epidemics of VL have occurred in major cities since 1980. Applied models for medical and epidemiological research have been used to assess the distribution and characteristics of disease endpoints and identify and characterize potential risk factors. This study described the demographic features of VL and modeled the spatio-temporal distribution of human VL cases and their relationship with underlying predicitve factors using generalized additive models. We conducted an ecological study covering an 18-year period from the first report of an autochthonous case of VL in Campo Grande, state of Mato Grosso do Sul, in 2001 to 2018. The urban area of the city has 74 neighborhoods, and they were the units of analysis of our work. Socioeconomic and demographic data available from Brazilian public databases were considered as covariables. A total of 1,855 VL cases were reported during the study period, with an annual mean incidence rate of 13.23 cases per 100,000 population and a cumulative crude incidence of 235.77 per 100,000 population. The results showed the rapid transition from epidemic to endemic and the centrifugal dispersal pattern of the disease. Moreover, the model highlighted that the urban quality of life index, which is calculated based on income, education, housing conditions, and environmental sanitation data, plays a role in VL occurrence. Our findings highlighted the potential for improving spatio-temporal segmentation of control measures and the cost-effectiveness of integrated disease management programs as soon as VL is difficult to control and prevent and has rapid geographical dispersion and increased incidence rates.

Epidemiological aspects of visceral leishmaniasis in Brazil and in international border regions

“…According to an epidemiological bulletin on VL in Mato Grosso do Sul between 2011 and July 2020, 1,741 cases were confirmed, with an annual average of 174.1 cases and 124 deaths (Bogiani & Oliveira, 2020). In the municipality of Campo Grande, Mato Grosso do Sul, from 2001 to 2018, 1,855 VL cases were reported, with an annual average of 103.0 cases and annual average incidence rate of 13.23 cases/100,000 inhabitants, demonstrating the rapid transition from epidemic to endemic (Oliveira et al, 2020). These data corroborate the present findings.…”

“…With regard to sociodemographic aspects, according to the Epidemiological Bulletin on VL that was published in 2020, the most affected age group in the state of Mato Grosso do Sul was 35-49 years old (22.9%), followed by 1-4 years old (17.1%), most of whom were male (65.0%) (Bogiani & Oliveira, 2020). In Campo Grande, the most affected age groups were children up to 5 years old and adults over 40 years old, and the highest incidence was in males (Oliveira et al, 2020). In the present study, the most affected age groups in Mato Grosso do Sul and Corumbá were up to 5 years old and 20-59 years old, and the most affected were also male (p < 0.05).…”

Hierarchical spatiotemporal modeling of human visceral leishmaniasis in Rio Grande do Norte, Brazil

“…The connection between socioeconomic status and risk of VL in Brazil is strongly supported by prior literature [22,45,46]. Mediating factors PLOS NEGLECTED TROPICAL DISEASES such as sanitation [47,48] and literacy [4,11] contribute to risk in the same direction as the present analysis.…”

“…Human visceral leishmaniasis (VL) is endemic in Brazil [1][2][3][4][5][6][7][8][9][10][11][12] and is recognized as a neglected tropical disease by the World Health Organization [13]. In Brazil, VL etiology stems from the protozoan Leishmania infantum, where the domestic dog serves as a sentinel host with the phlebotomine sand fly as the typical vector [14].…”

Modelling spatiotemporal patterns of visceral leishmaniasis incidence in two endemic states in India using environment, bioclimatic and demographic data, 2013–2022

“…These studies have applied either spatial models or geostatistical models to determine the predictors of CL incidence. To our knowledge, only two studies in Brazil [ 26 ] and Ethiopia [ 27 ], have applied spatiotemporal models to identify the underlying risk factors of human VL incidence. The study in Brazil used GAM (generalized additive models) and showed that quality of life in an urban area (a composite index related to income, education, housing, and environmental sanitation) was inversely related to VL incidence.…”