Molecular detection of rabies virus strain with N-gene that clustered with China lineage 2 co-circulating with Africa lineages in Monrovia, Liberia: first reported case in Africa.

Despite a long history of dog-transmitted human rabies outbreaks in Liberia, West Africa, no reports exist of molecular characterisation of the causative lyssaviruses. This study investigated Rabies lyssavirus (RABV) strains isolated at the dog-human interface in Monrovia, Liberia 2016 and 2017, by reverse transcription polymerase chain reaction, using primers specific for the nucleoprotein (N) gene. Out of 20 specimens (19 dog brain samples and one human saliva) tested as suspected rabies cases, three (15%) were positive. Purified amplicons from all three positive specimens were sequenced in both forward and reverse directions. Phylogenetic analysis was conducted in MEGA7 and PhyML3 to determine their relationship with RABV sequences accessioned in NCBI GenBank. The first of three RABV strains detected clustered with China lineage 2 RABVs of dogs (99% homology to KU963489 and DQ666322). The second strain segregated with Africa lineage 2 RABVs also of dog origin, and the third strain segregated with Africa lineage 3 RABVs of Southern Africa viverrids. Our results show a transcontinental strain of rabies virus co-circulating with Africa lineages in post-conflict Liberia. This finding should stimulate more effective sub-regional planning and execution of one-health actions, towards stepwise surveillance and elimination of rabies in West Africa by 2030.

Development of time-trend model for analysing and predicting case pattern of dog bite injury induced rabies-like-illness in Liberia, 2014-2017.

OBJECTIVE: The post-civil war records of dog bite injuries (DBI) and rabies-like-illness (RLI) among humans in Liberia is a vital epidemiological resource for developing a predictive model to guide the allocation of resources towards human rabies control. Whereas DBI and RLI are high, they are largely under-reported. The objective of this study was to develop a time model of the case-pattern and apply it to derive predictors of time-trend point distribution of DBI-RLI cases. METHODS: A retrospective 6 years data of DBI distribution among humans countrywide were converted to quarterly series using a transformation technique of Minimizing Squared First Difference statistic. The generated dataset was used to train a time-trend model of the DBI-RLI syndrome in Liberia. An additive detenninistic time-trend model was selected due to its performance compared to multiplication model of trend and seasonal movement. Parameter predictors were run on least square method to predict DBI cases for a prospective 4 years period, covering 2014-2017. RESULTS: The two-stage predictive model of DBI case-pattern between 2014 and 2017 was characterised by a uniform upward trend within Liberia's coastal and hinterland Counties over the forecast period. CONCLUSION: This paper describes a translational application of the time-trend distribution pattern of DBI epidemics, 2008-2013 reported in Liberia, on which a predictive model was developed. A computationally feasible two-stage time-trend permutation approach is proposed to estimate the time-trend parameters and conduct predictive inference on DBI-RLI in Liberia.