Revisiting area risk classification of visceral leishmaniasis in Brazil

Prevalence and risk factors of intestinal schistosomiasis on students at Bochesa Elementary School, around the wetlands of Lake Ziway, Ethiopia

Objectives

This study aimed to assess the prevalence and risk factors of intestinal schistosomiasis in students at Bochesa Elementary School in the wetlands of Lake Ziway.

Methods

A cross-sectional study of 384 students was conducted in May 2016. Intestinal schistosomiasis was examined using the Kato-Katz technique. For the association between the prevalence of intestinal schistosomiasis and categorical variables, the chi-square (χ2) test was used. A binary logistic regression was applied.

Results

The overall prevalence of intestinal schistosomiasis was 25.52%. Males were more infected (17.45%) than women (8.07%), and the difference was significant (χ2 = 17.756; P <0.05). Lower grade (1-4) students were more infected (20.83%) than grade 5-8 students (4.69%), and the difference was significant (χ2 = 19.558; P <0.05). Age groups of 7-14-year-old students were more infected (24.74%) than >15-year-old students (0.78%), and the difference was significant (χ2 = 4.788; P <0.05).

Conclusions

The result implied that the wetlands of Lake Ziway are conducive to schistosomiasis. Students should receive health education on the mode of schistosomiasis transmission and its prevention methods, and a buffer zone for the wetlands should be identified. Praziquantel treatment is crucial in reducing intestinal schistosomiasis in students.

Spatiotemporal changes in exposition risk to leishmaniases vector in residences within a fishing tourism area of Pantanal wetland

Miranda Municipality of Mato Grosso do Sul, borders the Pantanal wetland, a famous fishing destination visited by tourists from all over the world, and is a location where visceral leishmaniasis has been reported. To assess the risk of Leishmania infantum transmission, we studied the sandfly community, focusing on known vector and parasite presence. We conducted light trap collections twice per month at nine sites within the city (including two forested areas) for one year. We collected a total of 12,727 sand flies, 10,891 males and 1,836 females belonging to 11 species: Brumptomyia avellari, Evandromyia aldafalcaoae, Ev. evandroi, Ev. lenti, Ev. sallesi, Ev. walkeri, Lu. longipalpis, Nyssomyia whitmani, Psathyromyia bigeniculata, Pa. hermanlenti and Pa. punctigeniculata. Lutzomyia longipalpis, the proven vector of Leishmania infantum, was captured each month, and was the most abundant species observed, accounting for more than 99% of sand flies captured in most sites, especially where chicken coops were present. Evidence of Leishmania infantum infection was detected in 0.40% of Lu. longipalpis tested. We developed a generalized mixed multilevel model for Lu. longipalpis, that includes within-year seasonality, location of capture (indoors vs. outdoors), vector abundance, and sex ratio. The VL vector was abundant both inside and outside houses. Large numbers of Lu. longipalpis were observed in outdoor sites where domestic animals were present but were absent from forest sites. Our findings suggest high vector populations and Le. infantum presence in a city where tourists could be exposed to visceral leishmaniasis, with significant implications for more surveillance and control activities.

Temporal and spatial trends in human visceral leishmaniasis in an endemic area in Northeast Brazil and their association with social vulnerability

BACKGROUND

Visceral leishmaniasis is a neglected tropical disease of great importance to public health due to its wide distribution and close relationship with social and economic conditions. This study aimed to analyse the spatiotemporal dynamics of human visceral leishmaniasis (HVL) in an endemic state in the Northeast Region of Brazil and its spatial correlation with the Social Vulnerability Index (SVI) and the Municipal Human Development Index (MHDI).

METHODS

The study included all confirmed cases of HVL in Bahia from 2010 to 2017. A joinpoint regression model was used for trend analysis. Incidence rates were smoothed by a local empirical Bayesian model. Global and local Moran indices and space-time scan statistics were used for identification of spatial clusters. Bivariate and multivariate analyses were carried out to investigate the relationship between HVL incidence and the SVI and MHDI.

RESULTS

Cases of HVL demonstrated stationary behaviour during the period analysed. A significant association was observed between the HVL incidence rate and social vulnerability, with high-risk clusters concentrated in the central region of the state.

CONCLUSIONS

HVL has a strong correlation with social vulnerability in the state of Bahia. This study may provide assistance in planning actions and organizing health services to combat HVL.

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

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.

Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil

Nationwide disease surveillance at a high spatial resolution is desired for many infectious diseases, including Visceral Leishmaniasis. Statistical and mathematical models using data collected from surveillance activities often use a spatial resolution and scale either constrained by data availability or chosen arbitrarily. Sensitivity of model results to the choice of spatial resolution and scale is not, however, frequently evaluated. This study aims to determine if the choice of spatial resolution and scale are likely to impact statistical and mathematical analyses. Visceral Leishmaniasis in Brazil is used as a case study. Probabilistic characteristics of disease incidence, representing a likely outcome in a model, are compared across spatial resolutions and scales. Best fitting distributions were fit to annual incidence from 2004 to 2014 by municipality and by state. Best fits were defined as the distribution family and parameterization minimizing the sum of absolute error, evaluated through a simulated annealing algorithm. Gamma and Poisson distributions provided best fits for incidence, both among individual states and nationwide. Comparisons of distributions using Kullback-Leibler divergence shows that incidence by state and by municipality do not follow distributions that provide equivalent information. Few states with Gamma distributed incidence follow a distribution closely resembling that for national incidence. These results demonstrate empirically how choice of spatial resolution and scale can impact mathematical and statistical models.

Space-time analysis of the incidence of human visceral leishmaniasis (VL) and prevalence of canine VL in a municipality of southeastern Brazil: Identification of priority areas for surveillance and control

Human and canine visceral leishmaniasis (HVL and CVL, respectively) represent serious public health issues in Brazil. The surveillance and control measures currently employed have had limited effect in impeding the territorial expansion of the disease and in reducing the number of cases. We have investigated the space-time distribution of HVL incidence rates and CVL prevalence in the coverage areas of the 148 primary healthcare units in Belo Horizonte (MG, Brazil) during a 6-year period in order to identify those that should be prioritized for disease control actions. Data were smoothed using the empirical Bayes method and analyzed by space-time scanning and application of univariate global Moran's I index and local indicators of spatial association (LISA) statistics to identify spatial autocorrelations. Point data of CVL were analyzed using the Kernel method. Bivariate global Moran's I and LISA techniques were employed to identify spatial correlations between HVL and CVL. Based on our results, we were able to formulate two proposals for establishing the prioritization of coverage areas, namely: (i) classification of maximum priority areas as identified by bivariate LISA for HVL and CVL, and (ii) combination of maximum priority areas with high priority areas as identified by univariate LISA for HVL. According to our proposals, 27 coverage areas in Belo Horizonte were categorized as maximum priority and a further 13 were classified as high priority. Our proposals, which are based on practical, feasible and inexpensive statistical tools, will contribute to a better understanding of VL distribution in urban settings and improving the efficiency of governmental control programs.