ehealth digital library

Digital library of
the Tanzania

Stochastic Simulation Models of Plasmodium Falciparum Malaria Epidemiology and Control

Maire, N. (2008) Stochastic Simulation Models of Plasmodium Falciparum Malaria Epidemiology and Control. Doctoral thesis, University of Basel.

Stochastic_Thesis.pdf - Other
Available under License Creative Commons Attribution Non-commercial.

Download (1MB)


Every year malaria causes an estimated 1.3–3 million deaths and around half a billion clinical episodes. The majority of deaths occur in children under the age ofyears. Malaria today occurs mostly in tropical and subtropical countries, particularly in subSaharan Africa and Southeast Asia. In developing countries malaria may account for as much as 40% of public health expenditure, 30-50% of hospital admissions, and up to 50% of outpatient visits to health facilities. Malaria is a vector borne disease caused by the protozoan parasites of the genus Plasmodium. Plasmodium falciparum causes the most severe form of the disease, and is responsible for half of the clinical cases and 90% of the deaths from malaria. Malaria control interventions in countries where the disease is endemic currently include personal protection against mosquito bites, vector control, and prophylactic drugs. There is currently no registered malaria vaccine, but this is an active field of research. The vaccine that is furthest advanced in clinical development is called RTS,S/AS02A. This is a preerythrocytic vaccine, which aims to kill the parasites before they enter the red blood cells. Predictive models can provide a rational basis for decisions on how to allocate resources for malaria control. Mathematical modeling of malaria has a long history, starting with the first models of malaria transmission dynamics by Ross a century ago. At the Swiss Tropical Institute, a malaria modeling project has generated algorithms for rational planning of malaria control. This model is implemented as an individual-based discrete-time simulation model. The behaviors and state changes of simulated human individuals are governed by a minimal set of sub-models that are considered crucial for making quantitative predictions of the impact of malaria control interventions. The integrated model includes components that capture relevant aspects of malaria transmission and epidemiology in the absence of control: the relationship between the entomologic inoculation rate and the force of infection; epidemiologic models for acute illness, severe morbidity, and mortality; infectiousness of human population. Another central model component, for natural immunity to asexual blood stages of P. falciparum, is described in this thesis. The use of the model for making quantitative predictions requires reliable estimates of the values of the parameters of the mathematical functions. The different model components were therefore fitted to a number of datasets from studies in various ecological settings and for various epidemiologic outcomes using a simulated annealing algorithm. Comparison of the model predictions with field data show that the model appears to reproduce reasonably well the parasitologic patterns seen in malariologic surveys in endemic areas. Epidemiologic patterns can be modified by control interventions. Because of the individualbased approach chosen, a number of different simulated interventions can be introduced by making assumptions on how they modify the processes described above. This thesis describes a model for case management to predict the impact of improved case management on incidence of clinical episodes and mortality while incorporating effects on persistence of parasites and transmission. It allows the simulation of different rates of treatment coverage and parasitologic cure rates, and makes it possible to look at how variations in transmission intensity might affect the impact of changes in the health system. It also defines a baseline environment that can be used the predict the impact of other control interventions. The second part of the thesis focuses on the prediction of the impact of a pre-erythrocytic stage vaccine. Different assumptions about how such a vaccine may lead to a measured reduction in the incidence of new infections in vaccinated individuals are discussed. The vaccine profile was chosen to match data from clinical trials of RTS,S/AS02A. The results demonstrate that an adequate simulation of the first two RTS,S/AS02A trials published can be achieved by assuming that vaccination completely blocks a certain fraction of infections that would otherwise reach the erythrocytic stages. The impact that such a vaccine would have on the epidemiology if introduced via the Expanded Program on Immunization (EPI) is then predicted. This is the first major attempt to combine dynamic modeling of malaria transmission and control with predictions of parasitologic and clinical outcome. The results suggest a significant impact on morbidity and mortality for a range of assumptions about the vaccine characteristics, but only small effects on transmission intensities. To make predictions of the cost-effectiveness of such a vaccination program, costing data are incorporated into a model of a health system that is currently in place in a low-income country context, based largely on data from Tanzania. Depending on the assumed vaccine characteristics and cost, the predicted cost-effectiveness ratios would make vaccination campaigns an attractive choice for health planners compared with other malaria control interventions. In addition to making quantitative predictions, the model points to data that may be important to make accurate predictions. In order to make mid- to longterm predictions, more data on the clinical epidemiology of malaria in adolescents and adults would be desirable. The work reported here creates a sound foundation for measuring the effects of introducing new antimalarial interventions, or scaling-up those that are already known to be efficacious and cost-effective. A challenge that remains is to make a comprehensive set of model predictions available to a non-modeler audience so it can be valuable both for informing malaria control strategies and research funding policy.

Item Type: Thesis (Doctoral)
Keywords: Plasmodium Falciparum, Malaria, Epidemiology , Public Health, Hospital, Vector, Malaria Control, Mosquito,Vector Control, Vaccine,
Subjects: Malaria > Vector control
Malaria > Diagnosis & treatment
Malaria > Vaccines
Divisions: Other
Depositing User: Mr Joseph Madata
Date Deposited: 15 Feb 2013 07:09
Last Modified: 15 Feb 2013 07:09

Actions (login required)

Edit Item Edit Item


Downloads per month over past year

View more statistics