Model Simulation for the Spread of Rabies in Sarawak, Malaysia

Abstract

There is a growing concern over the ongoing rabies epidemic in Sarawak that has remain unresolved ever since the outbreak began in July 2017. As of today, there has been 18 positive human rabies cases reported, which includes 17 fatalities, and one survivor who is now on life support after a severe neurological complications. Subsequently, the death rate now stands at approximately 94%. This paper is a preliminary report on the simulation of rabies transmission dynamics in Sarawak. At present, research is still lacking on the disease dynamics of rabies in Malaysia particularly in the state of Sarawak. We propose here a deterministic, compartmental model with SEIRS framework to fit actual data on the number of human infected rabies cases in Sarawak from June 2017 to January 2019. The simulation predicts that rabies in Sarawak will persist even with the current outbreak management and control efforts. Further, sensitivity analysis showed that dog vaccination rate is the most influential parameter and the basic reproduction number is estimated to be higher than 1. Henceforth, there is a need to increase the access to dog vaccines especially in remote rural areas with lack of health facilities. Our findings also suggest that controlling dog births could prevent the spread of rabies from perpetuating in the state. Neutering or using other fertility control methods would reduce the input of new susceptible domestic dogs into the population while Trap-Neuter-Vaccinate-Release (TNVR) method can be implemented to control new births of free-roaming strays. In summary, increasing the coverage of dog vaccination and reducing the number newborn dogs would be the more effective strategies to manage the current rabies outbreak in Sarawak.

Mathematical modelling and phylodynamics for the study of dog rabies dynamics and control: A scoping review

“…In recent years, researchers have been trying to identify external factors impacting the spatial dynamics of RABV spread (n = 5) [63,64,68,69,71] (Fig 2D and S1 Table). Contrary to phylodynamic studies, the modelling category gathers a diverse panel of models with aims that cover the implementation of new mathematical methodologies (n = 2) [42,46], the characterization of rabies dynamics (n = 11) [26,27,31,32,40,41,44,[47][48][49]51], the identification of factors driving the resurgence or maintenance of rabies (n = 9) [16,23,25,[33][34][35]37,38,43], the assessment of control strategies efficacy (n = 18) [16,23,24,[27][28][29]31,[33][34][35][36][42][43][44][45][49][50][51], the risk assessment of rabies introduction and the evaluation of outbreak preparedness in rabies-free areas (n = 3)…”

“…In studies from the modelling and interdisciplinary categories, authors generally simulated rabies epidemics (n = 24) [20,23,25,[28][29][30][31][32][33][34][35][36]38,40,[42][43][44][45][46][47][49][50][51]72], and thus predominantly relied on publicly available estimates of the natural history of rabies, dog demographics and dog ecology (S3 and S4 Tables). When models were fitted to incidence data (n = 13) [16,24,26,27,37,39,41,48,[73][74][75][76][77], human and/or dog case data from passive surveillance systems were used, or bite incidence data from thorough active surveillance.…”

“…Compared to phylodynamics, mathematical models display a large diversity of specifications and parametrizations. Compartmental models (n = 18) [20,23,24,26,27,33,34,[39][40][41][45][46][47][48][49]51,75,77] are the most represented models, followed by agent-based (n = 8) [16,30,31,35,36,[42][43][44] and metapopulation (n = 5) [25,28,32,37,50] models. Other model types such as network models or branching processes are also represented [29,38,73,74,76] (S3 and S4 Tables).…”

“…In compartmental models, population structure is integrated either as a set of strata (stray dogs, owned free-roaming dogs, owned confined dogs) interacting together [33], or by specifying a structured next-generation matrix from which R is generally derived [34]. Such models are also referred to as multi-host models and may integrate other hosts: humans [32,39,40,48,49,51,86], cattle [39], wildlife [27,41]. In agent-based and network models, population structure is defined at the individual level using spatial kernels [16,25,30,31,36,42], individual contact rates [30,35,44], vaccination status [30,36], life span, infectious period [16,31,44], etc.…”

“…Several studies also suggested an impact of dog birth rate reduction on the incidence of rabies [23,26,40,41,45,49]. However, the cost and feasibility of dog population management strategies such as sterilization render this unfeasible in many settings [88].…”