Infectious diseases and resistance to antimicrobial agents grow as threats to human and animal welfare worldwide and drain limited resources. To contain and manage infecting microbes and their resistance genes, we need to know where they are and where they are going. Thousands of microbiology laboratories around the world generate results daily which could permit tracking and targeted control interventions, yet healthcare providers and public health agencies struggle to collect, integrate, and utilize data from fragmented systems. To address this challenge, our team at the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance has developed and disseminated the WHONET software for over 20 years in collaboration with the World Health Organization. WHONET is the leading free public health software to support electronic laboratory-based surveillance of antimicrobial resistance, and supports surveillance activities in over 90 countries and 1300 hospital, public health, food, and animal laboratories. This project will transform this initiative through creation of a multilevel (local, national, regional, global) web- based system to support automated, real-time collaborative surveillance of infections and antimicrobial resistance. Key objectives include: 1) a secure multi-tiered web architecture for data management, analysis, and presentation;2) web-enabled multilevel analytics with automated alerts to healthcare professionals and national authorities of findings of public health importance;3) pilot implementation of the new platform in four partner networks;and 4) an implementation guide for creation of production implementations. The lack of data transformation tools for incompatible information systems has proved the primary technical obstacle to broad data sharing, and our data normalization utilities developed over the past 20 years to address this challenge have proved crucial to WHONET's successful expansion. We will transfer the accrued expertise and translation resources to web-based solutions to decrease barriers to collaborative surveillance. Automated iterative multilevel data analysis permits the identification of new threats in any pathogen in any location at any time. Geo-referenced public libraries of quantitative multidrug resistance patterns and routine biochemical markers will permit the phenotypic delineation of microbial subpopulations improving the sensitivity and specificity of WHONET's space-time outbreak detection algorithms and facilitating the early recognition, tracking, and containment of previously unrecognized strains of public health or evolutionary importance. Microbes move - between people, hospitals, animals, continents - and evolve. Through automated, real-time mobilization and vigilance of a rich yet largely untapped resource - the cumulative efforts of the world's microbiology laboratories - our goal is the development of free solutions in the public sector that can be applied worldwide to mobilize, share, and interpret these data to guide timely and effective public health action.
The WHONET software developed by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance is the leading free public health software for electronic laboratory-based surveillance of antimicrobial resistance and supports surveillance activities in over 1300 healthcare facilities in over 90 countries. We propose development of the WHONET Surveillor, a web-based system for automated, real-time, multilevel vigilance for emerging microbial threats in communities, nations, and worldwide utilizing routinely available microbiology test results. By decreasing barriers to collaborative surveillance, we aim to link a rich yet largely untapped resource - the cumulative efforts of the world's microbiology laboratories - to prompt and effective public health action.
|Natale, Alessandra; Stelling, John; Meledandri, Marcello et al. (2017) Use of WHONET-SaTScan system for simulated real-time detection of antimicrobial resistance clusters in a hospital in Italy, 2012 to 2014. Euro Surveill 22:|
|Park, Rachel; O'Brien, Thomas F; Huang, Susan S et al. (2016) Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan. Expert Rev Anti Infect Ther 14:1097-1107|
|Chang, Hsiao-Han; Cohen, Ted; Grad, Yonatan H et al. (2015) Origin and proliferation of multiple-drug resistance in bacterial pathogens. Microbiol Mol Biol Rev 79:101-16|
|O'Brien, Thomas F; Stelling, John (2014) The world's microbiology laboratories can be a global microbial sensor network. Biomedica 34 Suppl 1:9-15|
|Siedner, Mark J; Galar, Alicia; Guzmán-Suarez, Belisa B et al. (2014) Cefepime vs other antibacterial agents for the treatment of Enterobacter species bacteremia. Clin Infect Dis 58:1554-63|
|Galar, Alicia; Kulldorff, Martin; Rudnick, Wallis et al. (2013) Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection. PLoS One 8:e84313|
|Viñas, María R; Tuduri, Ezequiel; Galar, Alicia et al. (2013) Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina. PLoS Negl Trop Dis 7:e2521|
|Stelling, J; Yih, W K; Galas, M et al. (2010) Automated use of WHONET and SaTScan to detect outbreaks of Shigella spp. using antimicrobial resistance phenotypes. Epidemiol Infect 138:873-83|