Additional file 1 of Geographical information system and spatial–temporal statistics for monitoring infectious agents in hospital: a model using Klebsiella pneumoniae complex
Creators: name: da Silva, Priscila Pinho
name: da Silva, Fabiola A.
name: Rodrigues, Caio Augusto Santos
name: Souza, Leonardo Passos
name: de Lima, Elisangela Martins
name: Pereira, Maria Helena B.
name: Candella, Claudio Neder
name: de Oliveira Alves, Marcio Zenaide
name: Lourenço, Newton D.
name: Tassinari, Wagner S.
name: Barcellos, Christovam
name: Gomes, Marisa Zenaide Ribeiro
Publisher: name: figshare
Year: 2021
Subjects: subject: Space Science
subject: Medicine
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: Cancer
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Additional file 1: Table S1. Distribution of wards and beds, and the number of Klebsiella pneumoniae complex isolates per type of ward, unit and floor in the Main and Annex buildings. Fig. S1. Thematic hospital map in QGis format. Table S2. Rectal swab protocol for surveillance of antimicrobial resistant Enterobacteriaceae. Table S3. Categories and antimicrobial agents used for susceptibility testing on K. pneumoniae complex. Algorithm 1. K. pneumoniae complex isolates included and excluded according to the hospital sectors of detection and the reason for exclusion. Fig. S2. Mapped distribution of K. pneumoniae complex isolates. Fig. S3. Thematic hospital maps of annual detection of K. pneumoniae complex according to the antimicrobial susceptibility profiles and regardless of clinical or surveillance samples. Fig. S4. Monthly incidence density of patients infected/colonised by K. pneumoniae complex per 1000 patient-days according to respective phenotypes. Fig. S5. Minimal inhibitory concentration (MIC) of meropenem and imipenem among carbapenem-resistant K. pneumoniae (CRKp) complex recovered from inpatients. Fig. S6. Time series analysis of patients harbouring CRKp complex adjusted by number of microbiological exams performed monthly. Fig. S7. Seasonal Trend decomposition using LOESS (STL) - Time series analysis of patients harbouring CRKp complex. Fig. S8. Seasonal Trend decomposition for data anomaly taking into the account time series data of patients harbouring CRKp complex. Fig. S9. Pattern of annual distribution of patients harbouring CRKp complex. Fig. S10. Space and time circulation of all patients carrying CRKp complex by ward of admission; before, at the time and after the detection of CRKp complex colonisation or infection. Fig. S11. Number of patients infected or colonised by CRKp complex by clustered wards and month of hospitalization, during the first and the second pre-cluster, cluster and post-cluster period. Table S4. Epidemiological and microbiological characteristics and outcome of patients involved in the first and second cluster. Fig. S12. Epidemiological link between patients colonised or infected by CRKp complex during the first cluster and the second cluster.