Epifil: a dynamic model of infection and disease in lymphatic filariasis.

Abstract

Abstract. The lack of a quantitative framework that describes the dynamic relationships between infection and morbidity has constrained efforts aimed at the community-level control of lymphatic filariasis. In this paper, we describe the development and validation of EPIFIL, a dynamic model of filariasis infection intensity and chronic disease. Infection dynamics are modeled using the well established immigration-death formulation, incorporating the acquisition of immunity to infective larvae over time. The dynamics of disease (lymphodema and hydrocele) are modeled as a catalytic function of a variety of factors, including worm load and the impact of immunopathological responses. The model was parameterized using age-stratified data collected from a Bancroftian filariasis endemic area in Pondicherry in southern India. The fitted parameters suggest that a relatively simple model including only acquired immunity to infection and irreversible progression to disease can satisfactorily explain the observed infection and disease patterns. Disease progression is assumed to be a consequence of worm induced damage and to occur at a high rate for hydrocele and a low rate for lymphodema. This suggests that immunopathology involvement may not be a necessary component of observed age-disease profiles. These findings support a central role for worm burden in the initiation and progression of chronic filarial disease.Lymphatic filariasis continues to be a significant source of chronic morbidity in the developing world, with more than 120 million people currently thought to be infected with either Wuchereria bancrofti or Brugia malayi, the major lymph-dwelling filariae of humans. 1,2 Despite the considerable advances in intervention options, 3 attempts to control the infection have met with variable success, partially because of inadequate understanding of the epidemiology of transmission and disease. 4,5 This gap in epidemiologic understanding stems from the intricate relationships between infection, immunity and the development of filarial disease. [3][4][5][6][7] This situation may also reflect the lack of a quantitative framework to assist understanding of the long-term effects and costs of intervention. 8 Such mathematical frameworks have played an important role in improving understanding of the epidemiology and control of other helminthiases, including intestinal nematodiases, 9-11 onchocerciasis, 12 and schistosomiasis. 13 Simple epidemiologic models, based on the catalytic models devised by Muench, 14 have been in existence for filariasis since the 1960s.15-17 These models have provided useful insights into the dynamics of filariasis in human populations, including improving the understanding of the roles of host immunity and parasite biology in the epidemiology of infection. Less work exists on the modelling of filarial disease, 5,6,18 despite the importance of morbidity models in improving understanding of the health impacts of parasite control and thus the ability to rationally evaluate different control options in s...

EPIFIL: The development of an age-structured model for describing the transmission dynamics and control of lymphatic filariasis

“…Our previous paper demonstrated that the observed distribution of infection intensity with age was consistent with the action of acquired immunity [18]. This mechanism is included in the model where it is assumed that past experience of infection results in a reduction in the rate of establishment of new infections.…”

“…In this paper, we have attempted to develop a realistic transmission model for lymphatic filariasis by extending an earlier version of the EPIFIL model [18]. This is achieved by incorporating the age structure of the human community and the dynamics of infection within the vector population.…”

“…The model described in this paper is developed from a cohort model described previously [18]. We extend this model to incorporate the whole transmission cycle, including the mosquito vector population.…”

“…Whereas schistosomiasis infection is generally most intense in children, the reverse is true of lymphatic filariasis. This is reflected in a different force of infection function ; we assume here, that the biting rate increases linearly until the age of 9 years after which it is constant throughout adulthood [18]. This reflects both behavioural differences and available skin area.…”

“…Recently, we developed and parameterized a constant force-of-infection cohort model [18]. In this paper, we extend the basic structure of this model by incorporating explicitly both host age structure and vector transmission dynamics in order to provide a more realistic framework for assessing the consequences of the different intervention options currently available for filariasis control.…”