Malaria and Chagas disease in non-endemic settings in Brazil: a comparative analysis of national surveillance data (2007-2024).

BACKGROUND

Malaria and Acute Chagas disease (ACD) are neglected tropical diseases with distinct epidemiological profiles in Brazil. Although malaria transmission is concentrated in the Amazon region and ACD has historically been associated with areas of sustained vectorial transmission, both conditions pose significant challenges in non-endemic settings, where delayed diagnosis and higher severity may occur.

METHODS

We conducted an ecological study using secondary data from the Brazilian Notifiable Diseases Information System (SINAN), including confirmed malaria and ACD cases reported between 2007 and 2024 in non-endemic areas of Brazil. Sociodemographic, clinical, and diagnostic variables were analyzed descriptively. Temporal trends were assessed using Prais-Winsten regression, and future projections were estimated with ARIMA models. Spatial autocorrelation and clustering were evaluated using the Getis-Ord Global and local statistics.

RESULTS

A total of 10,146 confirmed cases were analyzed (9755 malaria; 391 ACD). Malaria predominated among males (78%) and adults aged 20-39 years (47.8%), with most cases classified as non-autochthonous (89.7%). ACD cases were slightly more frequent among females (50.1%) and individuals aged ≥40 years (37.1%), with oral transmission accounting for 53.2% of reported routes. Malaria showed a significant decreasing temporal trend (β = -0.0174; p = 0.0397), whereas ACD demonstrated a significant increasing trend (β = 0.0342; p = 0.0267). Spatial analysis identified five malaria hotspots in southeastern and southern states (Global G = 0.0797; p < 0.001) and one ACD hotspot in Piauí (Gi* = 2.09; p = 0.0366), without significant global clustering for ACD. Forecast models indicated stable incidence for both diseases through 2030, with no evidence of sustained growth.

CONCLUSIONS

Despite low endemicity, malaria and ACD remain epidemiologically relevant in non-endemic regions, exhibiting distinct demographic profiles, temporal trajectories, and spatial clustering patterns. Strengthening surveillance systems, enhancing clinical awareness, and adapting infection control strategies to non-endemic healthcare settings are essential to mitigate morbidity and prevent severe outcomes.