Rapidly deployable mobile BSL-3 laboratory: A Response to Nipah virus outbreak in Kozhikode Kerala, India 2023
Sahay, R. R.; Patil, D. Y.; Shete, A. M.; Mohandas, S.; Gupta, N.; Mourya, D. T.; Yadav, P. D.
Show abstract
The Nipah virus (NiV) outbreak was declared in Kozhikode district, Kerala state, India on September 12, 2023. The local, state, and national authorities worked in an integrated way to tackle and control the outbreak. Indian Council of Medical Research (ICMR) deployed a team from ICMR-National Institute of Virology (NIV), Pune, India along with an indigenously developed and validated Mobile BSL-3 (MBSL-3) laboratory for providing onsite NiV diagnosis. The Kozhikode district of Kerala state has been an epicenter of three NiV outbreaks in May 2018, August 2021, and recently in September 2023. The Ernakulam district, Kerala also reported NiV outbreak in June 2019. In the 2023 outbreak, six confirmed NiV cases were detected with two deaths. During previous outbreaks in 2019 and 2021, the team from ICMR-NIV, Pune had successfully established the field laboratory utilizing the BSL-2 facility for NiV onsite diagnosis. The BSL-3 personnel protective equipment and standard operative procedures were used to handle the clinical specimens. Post COVID-19 pandemic, under the pioneering initiative of the Government of India, ICMR and Klenzaids Contamination Control Pvt Ltd, Mumbai developed a rapidly deployable, pragmatic, access control and containment laboratory on bus chassis. This MBSL-3 laboratory was utilized for the NiV onsite diagnosis for early containment of outbreak reducing the turnaround time to diagnosis to just 4 hours. MBSL-3 laboratory played a significant role in NiV outbreak response and could be utilized in the future also reaching the remotest areas of the country.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Evaluating diagnostic accuracies of Panbio ™ COVID-19 rapid antigen test and RT-PCR for the detection of SARS-CoV-2 in Addis Ababa, Ethiopia using Bayesian Latent-Class Models (BLCM) 95%
- Knowledge and occupational practices of beauticians and barbers in the transmission of viral hepatitis: a mixed-methods study in Volta Region of Ghana 95%
- SARS-CoV-2 detection in multi-sample pools in a real pandemic scenario: a screening strategy of choice for active surveillance 95%
Similar papers in this journal
- The role of Rwanda Field Epidemiology and Laboratory Training Program graduates and residents in response to the first Marburg Virus Disease outbreak in Rwanda 94%
- Application of diagnostic network optimization in Kenya and Nepal to design integrated, sustainable and efficient bacteriology and antimicrobial resistance surveillance networks 93%
- Assessments of Effectiveness of Technologies Utilizations in VIHSCM Among Selected Health Facilities in Tanzania Mainland 93%
Similar papers in this journal
- Understanding SARS-CoV-2 Infection and Dynamics with Long Term Wastewater based Epidemiological Surveillance 96%
- The Burden Of Poor Household Drinking-Water Quality On HIV/AIDS Infected Individuals In Rural Communities Of Ugu District Municipality, Kwazulu-Natal Province, South Africa 95%
- Experimental efficacy of the face shield and the mask against emitted and potentially received particles 93%
Similar papers in this journal
Similar papers in this journal
- Evaluation of seven different rapid methods for nucleic acid detection of SARS-COV-2 virus 96%
- Detection of Lumpy Skin Disease Virus Reads in the Human Upper Respiratory Tract Microbiome Requires Further Investigation 94%
- Analysis Of Four Different Transport And Preservation Medium Kits For SARS-COV-2 Diagnosis From Nasopharyngeal Swab By Real-Time PCR: Adapting To The Constantly Increasing Demand Of Sampling Processing And Stock-Outs During The Pandemic 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.