Journal Article
Feasibility of the Bag-Mediated Filtration System for Environmental Surveillance of Poliovirus in Kenya
Nicolette A. Zhou; Christine S. Fagnant-Sperati; Evans Komen; Benlick Mwangi; Johnstone Mukubi; James Nyangao; Joanne Hassan; Agnes Chepkurui; Caroline Maina; Walda B. van Zyl; Peter N. Matsapola; Marianne Wolfaardt; Fhatuwani B. Ngwana; Stacey Jeffries-Miles; Angela Coulliette-Salmond; Silvia Peñaranda; Jeffry H. Shirai; Alexandra L. Kossik; Nicola K. Beck; Robyn Wilmouth; David S. Boyle; Cara C. Burns; Maureen B. Taylor; Peter Borus; John Scott Meschke
Food and Environmental Virology · Vol. 12, Issue 1 · pp. 35-47 · 2020
Abstract
The bag-mediated filtration system (BMFS) was developed to facilitate poliovirus (PV) environmental surveillance, a supplement to acute flaccid paralysis surveillance in PV eradication efforts. From April to September 2015, environmental samples were collected from four sites in Nairobi, Kenya, and processed using two collection/concentration methodologies: BMFS (> 3 L filtered) and grab sample (1 L collected; 0.5 L concentrated) with two-phase separation. BMFS and two-phase samples were analyzed for PV by the standard World Health Organization poliovirus isolation algorithm followed by intratypic differentiation. BMFS samples were also analyzed by a cell culture independent real-time reverse transcription polymerase chain reaction (rRT-PCR) and an alternative cell culture method (integrated cell culture-rRT-PCR with PLC/PRF/5, L20B, and BGM cell lines). Sabin polioviruses were detected in a majority of samples using BMFS (37/42) and two-phase separation (32/42). There was statistically more frequent detection of Sabin-like PV type 3 in samples concentrated with BMFS (22/42) than by two-phase separation (14/42, p = 0.035), possibly due to greater effective volume assayed (870 mL vs. 150 mL). Despite this effective volume assayed, there was no statistical difference in Sabin-like PV type 1 and Sabin-like PV type 2 detection between these methods (9/42 vs. 8/42, p = 0.80 and 27/42 vs. 32/42, p = 0.18, respectively). This study demonstrated that BMFS can be used for PV environmental surveillance and established a feasible study design for future research.