{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T08:27:45Z","timestamp":1761553665897,"version":"build-2065373602"},"reference-count":59,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["TropicalMed"],"abstract":"<jats:p>Background: Cryptococcosis, a systemic mycosis, remains a neglected disease in Brazil due to the absence of systematic national surveillance. This study developed an interactive dashboard to analyze cryptococcosis-related deaths (2000\u20132022) and forecast trends through regional ARIMA modeling. Methodology: The Cross-Industry Standard Process for Data Mining framework was employed to extract mortality data from the Brazilian Mortality Information System, utilizing the microdatasus package in R Studio software, with R version 3.4.0. The records were then filtered using the International Classification of Diseases, Tenth Revision codes (B45 series) to identify primary and associated causes of death. After data extraction, a series of data preprocessing steps was implemented, including deduplication, variable recoding, and the management of missing values. The Shiny framework was employed to construct an interactive dashboard, incorporating Plotly and DT packages, with time-series visualizations, demographic variables, and multilingual support (Portuguese\/English). Results: Among 12,308 deaths (2227 primary; 10,081 associated causes), most occurred in males aged 21\u201360 years. Data completeness was high for age\/residence (100%) but lower for education (82%). The dashboard enables dynamic exploration of trends, demographic patterns, and open-data downloads. Regional ARIMA models revealed heterogeneous forecasts, with the Southeast projecting a decline (193 deaths in 2025; 95% CI: 146\u2013240) and the South showing stability (141 deaths; 95% CI: 109\u2013173). Conclusions: This tool bridges a critical gap in cryptococcosis surveillance, enabling dynamic mortality trend analysis, identification of high-risk demographics, and regional forecasting to guide public health resource allocation. While the absence of HIV serostatus data limits etiological analysis, the dashboard\u2019s open-source framework supports adaptation for other neglected diseases.<\/jats:p>","DOI":"10.3390\/tropicalmed10110304","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T07:31:58Z","timestamp":1761550318000},"page":"304","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Web-Based Dashboard for Tracking Cryptococcosis-Related Deaths in Brazil (2000\u20132022)"],"prefix":"10.3390","volume":"10","author":[{"given":"Eric Renato Lima","family":"Figueiredo","sequence":"first","affiliation":[{"name":"Postgraduate Program in Tropical Diseases, Nucleus of Tropical Medicine, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucca","family":"Nielsen","sequence":"additional","affiliation":[{"name":"Department of Preventive Medicine, University of S\u00e3o Paulo Medical School, S\u00e3o Paulo 01246-903, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4681-8532","authenticated-orcid":false,"given":"Jo\u00e3o Sim\u00e3o de","family":"Melo-Neto","sequence":"additional","affiliation":[{"name":"Postgraduate Program in Public Health in the Amazon, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1913-7176","authenticated-orcid":false,"given":"Claudia do Socorro Carvalho","family":"Miranda","sequence":"additional","affiliation":[{"name":"Laboratory of Epidemiology and Geoprocessing of Amazon, University of the State of Par\u00e1 (UEPA), Bel\u00e9m 66050-540, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0276-9318","authenticated-orcid":false,"given":"Nelson Veiga","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Laboratory of Epidemiology and Geoprocessing of Amazon, University of the State of Par\u00e1 (UEPA), Bel\u00e9m 66050-540, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rita Catarina Medeiros","family":"Sousa","sequence":"additional","affiliation":[{"name":"Postgraduate Program in Tropical Diseases, Nucleus of Tropical Medicine, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anderson Raiol","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Postgraduate Program in Tropical Diseases, Nucleus of Tropical Medicine, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dollo, I., Menu, E., Dudouet, P., Aubry, C., L\u2019Ollivier, C., and Ranque, S. 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