• Acquisition of virulence genes by a carrier strain gave rise to the ongoing epidemics of meningococcal disease in West Africa

      Brynildsrud, OB; Eldholm, V; Bohlin, J; Uadiale, K; Obaro, S; Caugant, DA (National Academy of Sciences, 2018-05-07)
      In the African meningitis belt, a region of sub-Saharan Africa comprising 22 countries from Senegal in the west to Ethiopia in the east, large epidemics of serogroup A meningococcal meningitis have occurred periodically. After gradual introduction from 2010 of mass vaccination with a monovalent meningococcal A conjugate vaccine, serogroup A epidemics have been eliminated. Starting in 2013, the northwestern part of Nigeria has been affected by yearly outbreaks of meningitis caused by a novel strain of serogroup C Neisseria meningitidis (NmC). In 2015, the strain spread to the neighboring country Niger, where it caused a severe epidemic. Following a relative calm in 2016, the largest ever recorded epidemic of NmC broke out in Nigeria in 2017. Here, we describe the recent evolution of this new outbreak strain and show how the acquisition of capsule genes and virulence factors by a strain previously circulating asymptomatically in the African population led to the emergence of a virulent pathogen. This study illustrates the power of long-read whole-genome sequencing, combined with Illumina sequencing, for high-resolution epidemiological investigations.
    • Spatial and Temporal Dynamics of Superspreading Events in the 2014-2015 West Africa Ebola Epidemic

      Lau, MSY; Dalziel, BD; Funk, S; McClelland, A; Tiffany, A; Riley, S; Metcalf, CJE; Grenfell, BT (National Academy of Sciences, 2017-02-13)
      The unprecedented scale of the Ebola outbreak in Western Africa (2014-2015) has prompted an explosion of efforts to understand the transmission dynamics of the virus and to analyze the performance of possible containment strategies. Models have focused primarily on the reproductive numbers of the disease that represent the average number of secondary infections produced by a random infectious individual. However, these population-level estimates may conflate important systematic variation in the number of cases generated by infected individuals, particularly found in spatially localized transmission and superspreading events. Although superspreading features prominently in first-hand narratives of Ebola transmission, its dynamics have not been systematically characterized, hindering refinements of future epidemic predictions and explorations of targeted interventions. We used Bayesian model inference to integrate individual-level spatial information with other epidemiological data of community-based (undetected within clinical-care systems) cases and to explicitly infer distribution of the cases generated by each infected individual. Our results show that superspreaders play a key role in sustaining onward transmission of the epidemic, and they are responsible for a significant proportion ([Formula: see text]61%) of the infections. Our results also suggest age as a key demographic predictor for superspreading. We also show that community-based cases may have progressed more rapidly than those notified within clinical-care systems, and most transmission events occurred in a relatively short distance (with median value of 2.51 km). Our results stress the importance of characterizing superspreading of Ebola, enhance our current understanding of its spatiotemporal dynamics, and highlight the potential importance of targeted control measures.