Spatial Dynamics and High Risk Transmission Pathways of Poliovirus in Nigeria 2001-2013

• Published in: PloS one Vol. 11; no. 9; p. e0163065
• Main Authors: Mangal, Tara D, Aylward, R Bruce, Shuaib, Faisal, Mwanza, Michael, Pate, Muhammed A, Abanida, Emmanuel, Grassly, Nicholas C
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 26.09.2016; Public Library of Science (PLoS)
• Subjects: Biology and life sciences; Cellular telephones; Children; Computer networks; Computer simulation; Disease transmission; Enterovirus; Epidemics; Epidemiology; Gravitation; Gravity; Incidence; Infectious diseases; Influenza; Likelihood ratio; Local government; Measles; Medicine and Health Sciences; Model testing; Outbreaks; Pathways; People and Places; Physical Sciences; Picornaviridae; Poliomyelitis; Poliovirus; Population density; Radiation; Radiation models; Surveillance; Vaccines; United Kingdom > UK; Nigeria; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0163065

The polio eradication programme in Nigeria has been successful in reducing incidence to just six confirmed cases in 2014 and zero to date in 2015, but prediction and management of future outbreaks remains a concern. A Poisson mixed effects model was used to describe poliovirus spread between January 2001 and November 2013, incorporating the strength of connectivity between districts (local government areas, LGAs) as estimated by three models of human mobility: simple distance, gravity and radiation models. Potential explanatory variables associated with the case numbers in each LGA were investigated and the model fit was tested by simulation. Spatial connectivity, the number of non-immune children under five years old, and season were associated with the incidence of poliomyelitis in an LGA (all P < 0.001). The best-fitting spatial model was the radiation model, outperforming the simple distance and gravity models (likelihood ratio test P < 0.05), under which the number of people estimated to move from an infected LGA to an uninfected LGA was strongly associated with the incidence of poliomyelitis in that LGA. We inferred transmission networks between LGAs based on this model and found these to be highly local, largely restricted to neighbouring LGAs (e.g. 67.7% of secondary spread from Kano was expected to occur within 10 km). The remaining secondary spread occurred along routes of high population movement. Poliovirus transmission in Nigeria is predominantly localised, occurring between spatially contiguous areas. Outbreak response should be guided by knowledge of high-probability pathways to ensure vulnerable children are protected.