Readiness for antimicrobial resistance (AMR) surveillance in Pakistan; a model for laboratory strengthening

Autor: Erum Khan, Imran Ahmed, Seema Irfan, Mohammad Zeeshan, Sadia Shakoor, Zabin Wajidali, Abdul Chagla, Rumina Hasan, Kausar Jabeen, Jason Rao, Afia Zafar, Dania Khalid Saeed, Joveria Farooqi, Mahwish Naim
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Antimicrobial Resistance and Infection Control, Vol 6, Iss 1, Pp 1-7 (2017)
Antimicrobial Resistance and Infection Control
ISSN: 2047-2994
Popis: Background Limited capacity of laboratories for antimicrobial susceptibility testing (AST) presents a critical diagnostic bottleneck in resource limited countries. This paper aims to identify such gaps and to explore whether laboratory networks could contribute towards improving AST in low resource settings. Methods A self-assessment tool to assess antimicrobial susceptibility testing capacity was administered as a pre-workshop activity to participants from 30 microbiology laboratories in 3 cities in Pakistan. Data from public and private laboratories was analyzed and capacity of each scored in percentage terms. Laboratories from Karachi were invited to join a support network. A cohort of five laboratories that consented were provided additional training and updates sessions over a period of 15 months. Impact of training activities in these laboratories was evaluated using a point scoring (0-11) tool. Results Results of self-assessment component identified a number of areas that required strengthening (scores of ≤60%). These included; readiness for AMR surveillance; 38 and 46%, quality assurance; 49 and 55%, and detection of specific organisms; 56 and 60% for public and private laboratories respectively. No significant difference was detected in AST capacity between public and private laboratories [ANOVA; p > 0.05]. Scoring tool used to assess impact of training within the longitudinal cohort showed an increase from a baseline of 1-5.5 (August 2015) to improved post training scores of 7-11 (October 2016) for the 5 laboratories included. Moreover, statistical analysis using paired t-Test Analysis, assuming unequal variance, indicated that the increase in scored noted represents a statistically significant improvement in the components evaluated [p
Databáze: OpenAIRE