Proposing a Compartmental Model for Leprosy and Parameterizing Using Regional Incidence in Brazil

Abstract

Hansen’s disease (HD), or leprosy, is still considered a public health risk in much of Brazil. Understanding the dynamics of the infection at a regional level can aid in identification of targets to improve control. A compartmental continuous-time model for leprosy dynamics was designed based on understanding of the biology of the infection. The transmission coefficients for the model and the rate of detection were fit for each region using Approximate Bayesian Computation applied to paucibacillary and multibacillary incidence data over the period of 2000 to 2010, and model fit was validated on incidence data from 2011 to 2012. Regional variation was noted in detection rate, with cases in the Midwest estimated to be infectious for 10 years prior to detection compared to 5 years for most other regions. Posterior predictions for the model estimated that elimination of leprosy as a public health risk would require, on average, 44–45 years in the three regions with the highest prevalence. The model is easily adaptable to other settings, and can be studied to determine the efficacy of improved case finding on leprosy control.

Latent leprosy infection identified by dual RLEP and anti-PGL-I positivity: Implications for new control strategies

“…The global hidden prevalence is estimated at 3 million cases, but can be six times higher than the registered prevalence in some areas [ 4 ]. Recent mathematical models predict that elimination of leprosy as a public health risk by 2061 would require over 40 years in the three regions with the highest prevalence in Brazil (North, Northeast and Midwest), primarily due to the long delay in detection of cases [ 5 ]. Currently, Brazil is still the only country in the world that has not met the WHO goal of <1 new case per 10,000 population, with 27,863 new cases detected in 2019, around 1.3/10,000 nationally based on Brazil’s National Notifiable Diseases Information System (SINAN) [ 6 ].…”

Multibacillary and paucibacillary leprosy dynamics: a simulation model including a delay

“…Effective contact rate for multicibacillary leprosy transmission [17,18]. 0, 5 θ Rate of progress from an asymptomatic stage to the symptomatic stage of leprosy (average between the two rates of progress) [17,20].…”

“…Effective contact rate for multicibacillary leprosy transmission [17,18]. 0, 5 θ Rate of progress from an asymptomatic stage to the symptomatic stage of leprosy (average between the two rates of progress) [17,20]. In figure 2 you can see four graphs representing the different stages, in which the dynamics of the disease transmission of leprosy, considering a delay time τ = 5 that represents the average latency stage of the disease.…”

Dynamical Analysis and Design of Computational Methods for Nonlinear Stochastic Leprosy Epidemic Model

“…In 2021, Marathi et al developed a multi-dimensional mathematical model for the transmission of leprosy disease [3]. In 2016, Smith captured a compartmental model representing the present knowledge of susceptibility and pathogenesis to leprosy, adapted to different populations [4]. In 2007, Abubakar et al implemented the Markov decision model to decide the best cost of drugs for the treatment of leprosy disease [5].…”