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ABSTRACT The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others. publications problem uptodate up date classifications context exception (CTFB http//fauna.jbrj.gov.br/, httpfaunajbrjgovbr http //fauna.jbrj.gov.br/ , jbrj gov br (http://fauna.jbrj.gov.br/) 2015 Brazil 80 specialists 1 2024 133691 133 691 133,69 125138 125 138 125,13 82.3%, 823 82 3 (82.3% 102000 102 000 102,00 7.69%, 769 7 69 (7.69% 11000 11 11,00 . 3,567 3567 567 (3,56 2,292 2292 2 292 (2,29 1,833 1833 833 (1,83 1,447 1447 447 (1,44 1000 1,00 831 (83 628 (62 606 (60 520 (52 50 users science health biology law anthropology education others http//fauna.jbrj.gov.br/ faunajbrjgovbr //fauna.jbrj.gov.br (http://fauna.jbrj.gov.br/ 201 8 202 13369 13 133,6 12513 12 125,1 82.3% (82.3 10200 10 00 102,0 7.69% 76 6 (7.69 1100 11,0 3,56 356 56 (3,5 2,29 229 29 (2,2 1,83 183 83 (1,8 1,44 144 44 (1,4 100 1,0 (8 62 (6 60 52 (5 5 http//fauna.jbrj.gov.br (http://fauna.jbrj.gov.br 20 1336 133, 1251 125, 82.3 (82. 1020 0 102, 7.69 (7.6 110 11, 3,5 35 (3, 2,2 22 (2, 1,8 18 (1, 1,4 14 4 ( 82. (82 7.6 (7. 3, (3 2, (2 (1 7. (7

In view of the need to manage and forecast the number of beds in the Intensive Care Units for critically ill patients in Covid-19, the Forecast UTI was developed: an open access application that allows the monitoring of hospital indicators based on historical data from the service health and the temporal dynamics of the epidemic. It is also possible to make short-term forecasts of the number of beds occupied daily by the disease and to establish possible care scenarios. This article presents the functions, mode of access and examples of use of Forecast UTI, a computational tool capable of assisting managers of public and private hospitals in the Unified Health System, since they support decision-making quickly, strategically and efficiently.

Frente à necessidade de gerenciamento e previsão do número de leitos de unidades de terapia intensiva (UTI) para pacientes graves de covid-19, foi desenvolvido o Forecast UTI, um aplicativo de livre acesso e que permite o monitoramento de indicadores hospitalares com base em dados históricos do serviço de saúde e na dinâmica temporal dessa epidemia por coronavírus. O Forecast UTI também possibilita realizar previsões de curto prazo sobre número de leitos ocupados pela doença diariamente, e estabelecer possíveis cenários de atendimento. Este artigo apresenta as funções, modo de acesso e exemplos de uso do Forecast UTI, uma ferramenta computacional destinada a auxiliar gestores de hospitais da rede pública e privada do Sistema Único de Saúde no subsídio à tomada de decisão, de forma rápida, estratégica e eficiente.

Resumo Frente à necessidade de gerenciamento e previsão do número de leitos de unidades de terapia intensiva (UTIs) para pacientes graves de COVID-19, foi desenvolvido o Forecast UTI, um aplicativo de livre acesso, que permite o monitoramento de indicadores hospitalares com base em dados históricos do serviço de saúde e na dinâmica temporal da epidemia por coronavírus. O Forecast UTI também possibilita realizar previsões de curto prazo do número de leitos ocupados pela doença diariamente, e estabelecer possíveis cenários de atendimento. Este artigo apresenta as funções, modo de acesso e exemplos de uso do Forecast UTI, uma ferramenta computacional destinada a auxiliar gestores de hospitais da rede pública e privada do Sistema Único de Saúde (SUS) no subsídio à tomada de decisão, de forma rápida, estratégica e eficiente.

Index code	Element
ti	article title
au	author
kw	article keywords
subject	subject (title words, abstract and keywords)
ab	abstract
ta	journal short title (e.g. Cad. Saúde Pública)
journal_title	journal full title (e.g. Cadernos de Saúde Pública)
la	publication language code (e.g. pt - Portuguese, es - Spanish)
type	document type
pid	publication identifier
publication_year	publication year of publication
sponsor	sponsor
aff_country	country code of the author's affiliation
aff_institution	author affiliation institution
volume	article volume
issue	article issue
elocation	elocation
doi	DOI number
issn	journal ISSN
in	SciELO colection code (e.g. scl - Brasil, col - Colômbia)
use_license	article usage license code

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