Leishmaniose tegumentar americana no estado de Mato Grosso: análise espaço-temporal para vigilância de áreas de alto risco

Abstract

American Cutaneous Leishmaniasis (ACL) is a neglected cosmopolitan infectious disease and it is estimated that about 350 million people worldwide live in areas at risk for ACL infection. About 90% of all cases registered in the Americas are reported in Brazil and most of these cases are registered in the North, Midwest and Northeast regions, Mato Grosso being the state with the highest incidence in the Center-West region and one of the states with the highest incidence in the country. Epidemiology is a powerful tool for understanding the situation of ACL, but many studies have a traditionalist character, bringing generalist information and that do not provide robust data for the identification of high-risk areas for ACL infection in the state. In this way, this research was carried out, which had to analyze the spatio-temporal pattern of ACL and the determining factors of risk areas for the occurrence of the disease. This is an ecological study, in which the units of analysis were the municipalities of the state of Mato Grosso and the population consisted of positive cases for ACL between 2010 and 2019 registered in the System of Diseases and Notifications (SINAN) of the state of Mato Grosso. Thick. High risk areas were identified using the Scan statistic, also known as Scan. To identify the association between variables related to risk areas, a binary logistic regression model was used. In the period studied, 23,698 cases of ATL were identified, most of them men (n=18939; 79.9%) of mixed race (n=11356; 47.9%) with low education. Regarding the clinical form, most cases reported were cutaneous leishmaniasis (n=21973; 92.7%) and most cases progressed to cure (n=19722; 83.2%). We identified 17 clusters of risk for ACL infection with the highest Relative Risk (RR) of 5.52 (p< 0.001). There were also 5 risk areas for treatment abandonment, with the highest RR= 6.95 (p< 0.05). In the logistic regression model, the variables bovine herd (OR=1.000; 95% CI=1.000-1000), harvest area (OR=1.000; 95% CI=1.000- 1000) and precipitation volume (OR= 1.003; 95% CI= 1.001 -1006) (p< 0.05) showed a positive association with the high-risk areas identified in the scan statistics. The IDHM (OR=0.978; 95% CI=0.962-0.994) showed an association with risk areas, although negative. In the final logistic model, the value of the Nagelkerke coefficient R 2 was 34.6% and the Hosmer and Lemeshow test presented a value of p = 0.398 and a ROC curve of 0.789. The temporal trend showed a stationary result both for cases (Coefficient = -116.7987 to 14.95893; 95% CI) and for treatment abandonment (Coefficient = -1.061069 to 8.39306; 95% CI). The results obtained evidence the existence of high risk areas for ACL infection, as well as for the abandonment of the disease treatment, and that these indicators did not show a reduction during the decade investigated in this study. In addition, the results suggest that there are determinants that may be influencing the occurrence of cases and the maintenance of these risk regions. Multisectoral approaches focused on these locations and that strategically consider the variables identified in this study can collaborate to reduce the number of ACL infected people in the state of Mato Grosso. It is expected that the findings obtained can be a guide for the implementation of public policies that seek to control ACL in the state of Mato Grosso.