Towards a comprehensive simulation model of malaria epidemiology and control | Parasitology | Cambridge Core (original) (raw)

Summary

Planning of the control of Plasmodium falciparum malaria leads to a need for models of malaria epidemiology that provide realistic quantitative prediction of likely epidemiological outcomes of a wide range of control strategies. Predictions of the effects of control often ignore medium- and long-term dynamics. The complexities of the Plasmodium life-cycle, and of within-host dynamics, limit the applicability of conventional deterministic malaria models. We use individual-based stochastic simulations of malaria epidemiology to predict the impacts of interventions on infection, morbidity, mortality, health services use and costs. Individual infections are simulated by stochastic series of parasite densities, and naturally acquired immunity acts by reducing densities. Morbidity and mortality risks, and infectiousness to vectors, depend on parasite densities. The simulated infections are nested within simulations of individuals in human populations, and linked to models of interventions and health systems. We use numerous field datasets to optimise parameter estimates. By using a volunteer computing system we obtain the enormous computational power required for model fitting, sensitivity analysis, and exploration of many different intervention strategies. The project thus provides a general platform for comparing, fitting, and evaluating different model structures, and for quantitative prediction of effects of different interventions and integrated control programmes.

References

Aron, J. L. (1988). Mathematical modeling of immunity to malaria. Mathematical Biosciences 90, 385–396.Google Scholar

Bailey, N. (1982). The Biomathematics of Malaria. Charles Griffin and Co Ltd, London.Google Scholar

Beier, J. C., Oster, C. N., Onyango, F. K., Bales, J. D., Sherwood, J. A., Perkins, P. V., Chumo, D. K., Koech, D. V., Whitmire, R. E. and Roberts, C. R. (1994). Plasmodium falciparum incidence relative to entomologic inoculation rates at a site proposed for testing malaria vaccines in western Kenya. American Journal of Tropical Medicine and Hygiene 50, 529–536.CrossRefGoogle Scholar

Bradley, D. J. (1982). Epidemiological models theory and reality. In The Population Dynamics of Infectious Diseases: Theory and Application (ed. Anderson, R. M.), pp. 320–361. Chapman Hall, London and New York.Google Scholar

Carneiro, I., Smith, T., Lusingu, J., Malima, R., Utzinger, J. and Drakeley, C. (2006). Modeling the relationship between the population prevalence of Plasmodium falciparum malaria and anemia. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 82–89.CrossRefGoogle ScholarPubMed

Chitnis, N., Steketee, R. W. and Smith, T. (2007). A mathematical model for the dynamics of malaria in mosquitoes feeding on a heterogeneous host population. Journal of Biological Dynamics (in press).Google Scholar

Collins, W. E. and Jeffery, G. M. (1999). A retrospective examination of sporozoite- and trophozoite-induced infections with Plasmodium falciparum: development of parasitologic and clinical immunity during primary infection. American Journal of Tropical Medicine and Hygiene 61, 4–19.CrossRefGoogle ScholarPubMed

Collins, W. E. and Jeffery, G. M. (2003). A retrospective examination of mosquito infection on humans infected with Plasmodium falciparum. American Journal of Tropical Medicine and Hygiene 68, 366–371.CrossRefGoogle ScholarPubMed

Dietz, K., Molineaux, L. and Thomas, A. (1974). A malaria model tested in the African savannah. Bulletin of the World Health Organization 50, 347–357.Google ScholarPubMed

Flessa, S. (2002). Malaria Und AIDS: Gesundheitökonomische Analysen auf der Grundlage von Disease Dynamic Modellen. Hans Jacobs, Lage.Google Scholar

Gatton, M. L. and Cheng, Q. (2004). Modeling the development of acquired clinical immunity to Plasmodium falciparum malaria. Infection and Immunity 72, 6538–6545.Google Scholar

Goodman, C. A., Coleman, P. G. and Mills, A. (2000). Economic Analysis of Malaria Control in Sub-Saharan Africa. Global Forum for Health Research, Geneva.Google Scholar

Habbema, J. D. F., Alley, E. S., Plaisier, A. P., van Oortmarssen, G. J. and Remme, J. H. (1992). Epidemiological modelling for onchocerciasis control. Parasitology Today 8, 99–103.Google Scholar

Holland, J. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.Google Scholar

Killeen, G. F., Ross, A. and Smith, T. (2006). Infectiousness of malaria-endemic human populations to vectors. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 38–45.Google Scholar

Killeen, G. F. and Smith, T. A. (2007). Exploring the contributions of bed nets, cattle, insecticides and excitorepellency to malaria control: a deterministic model of mosquito host-seeking behaviour and mortality. Transactions of the Royal Society of Tropical Medicine and Hygiene 101, 867–880.CrossRefGoogle ScholarPubMed

Kiszewski, A., Johns, B., Schapira, A., Delacollette, C., Crowell, V., Tan-Torres, T., Amenashewa, B., Teklehaimanot, A. and Nafo-Traoré, F. (2007). Estimated global resources needed to attain international malaria control goals. Bulletin of the World Health Organization 85, 623–630.CrossRefGoogle ScholarPubMed

Kitua, A., Smith, T., Alonso, P. L., Masanja, H., Urassa, H., Menendez, C., Kimario, J. and Tanner, M. (1996). Plasmodium falciparum malaria in the first year of life in an area of intense and perennial transmission. Tropical Medicine and International Health 1, 475–484.Google Scholar

Knols, B. G., De Jong, R. and Takken, W. (1995). Differential attractiveness of isolated humans to mosquitoes in Tanzania. Transactions of the Royal Society of Tropical Medicine and Hygiene 89, 604–606.CrossRefGoogle ScholarPubMed

Koella, J. C. and Zaghloul, L. (2008). Using evolutionary costs to enhance the efficacy of malaria control via genetically manipulated mosquitoes. Parasitology 135 (this special issue) Jan 24; 1–8 [E-pub ahead of print].CrossRefGoogle ScholarPubMed

Macdonald, G. (1957). The Epidemiology and Control of Malaria. Oxford University Press, London.Google Scholar

Maire, N., Aponte, J. J., Ross, A., Thompson, R., Alonso, P., Utzinger, J., Tanner, M. and Smith, T. (2006 a). Modeling a field trial of the RTS,S/AS02A malaria vaccine. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 104–110.CrossRefGoogle ScholarPubMed

Maire, N., Smith, T., Ross, A., Owusu-Agyei, S., Dietz, K. and Molineaux, L. (2006 b). A model for natural immunity to asexual blood stages of Plasmodium falciparum malaria in endemic areas. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 19–31.CrossRefGoogle Scholar

Maire, N., Tediosi, F., Ross, A. and Smith, T. (2006 c). Predictions of the epidemiologic impact of introducing a pre-erythrocytic vaccine into the expanded program on immunization in sub-Saharan Africa. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 111–118.CrossRefGoogle ScholarPubMed

Marsh, K. and Snow, R. (1999). Malaria transmission and morbidity. Parasitologia 41, 241–246.Google Scholar

McKenzie, F. E. and Bossert, W. H. (2005). An integrated model of Plasmodium falciparum dynamics. Journal of Theoretical Biology 232, 411–426.Google Scholar

Molineaux, L., Diebner, H. H., Eichner, M., Collins, W. E., Jeffery, G. M. and Dietz, K. (2001). Plasmodium falciparum parasitaemia described by a new mathematical model. Parasitology 122, 379–391.CrossRefGoogle ScholarPubMed

Molineaux, L. and Gramiccia, G. (1980). The Garki Project. World Health Organization, Geneva.Google Scholar

Owusu-Agyei, S., Smith, T., Beck, H.-P., Amenga-Etego, L. and Felger, I. (2002). Molecular epidemiology of Plasmodium falciparum infections among asymptomatic inhabitants of a holoendemic malarious area in northern Ghana. Tropical Medicine and International Health 7, 421–428.CrossRefGoogle ScholarPubMed

Plaisier, A. P., van Oortmarssen, G. J., Habbema, J. D. F., Remme, J. and Alley, E. S. (1990). ONCHOSIM: a model and computer simulation program for the transmission and control of onchocerciasis. Computer Methods and Programs in Biomedicine 31, 43–56.CrossRefGoogle Scholar

Port, G. R., Boreham, P. F. L. and Bryan, J. H. (1980). The relationship of host size to feeding by mosquitos of the Anopheles gambiae Giles complex (Diptera: Culicidae). Bulletin of Entomological Research 70, 133–144.Google Scholar

Rogier, C., Commenges, D. and Trape, J. F. (1996). Evidence for an age-dependent pyrogenic threshold of Plasmodium falciparum parasitemia in highly endemic populations. American Journal of Tropical Medicine and Hygiene 54, 613–619.Google Scholar

Roll Back Malaria (2005). World Malaria Report 2005. World Health Organization and UNICEF, Geneva.Google Scholar

Ross, A., Killeen, G. F. and Smith, T. (2006 a). Relationships of host infectivity to mosquitoes and asexual parasite density in Plasmodium falciparum. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 32–37.Google Scholar

Ross, A. and Smith, T. (2006). The effect of malaria transmission intensity on neonatal mortality in endemic areas. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 74–81.CrossRefGoogle ScholarPubMed

Ross, A., Maire, N., Molineaux, L. and Smith, T. (2006 b). An epidemiologic model of severe morbidity and mortality caused by Plasmodium falciparum. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 63–73.CrossRefGoogle ScholarPubMed

Rowe, A., Steketee, R., Arnold, F., Wardlaw, T., Basu, S., Bakyaita, N., Lama, M., Winston, C., Lynch, M., Cibulskis, R., Shibuya, K., Ratcliffe, A. and Nahlen, B. (2007). Viewpoint: evaluating the impact of malaria control efforts on mortality in sub-Saharan Africa. Tropical Medicine and International Health 12, 1524–1539.CrossRefGoogle ScholarPubMed

Sama, W., Killeen, G. and Smith, T. (2004). Estimating the duration of Plasmodium falciparum infection from trials of indoor residual spraying. American Journal of Tropical Medicine and Hygiene 70, 625–634.Google Scholar

Sama, W., Owusu-Agyei, S., Felger, I., Dietz, K. and Smith, T. (2006). Age and seasonal variation in the transition rates and detectability of Plasmodium falciparum malaria. Parasitology 132, 13–21.Google Scholar

Saul, A. (2008). Efficacy model for mosquito stage, transmission blocking vaccines for malaria. Parasitology 135 (this special issue) Feb 7; 1–10 [E-pub ahead of print].Google Scholar

Saul, A., Graves, P. M. and Kay, B. H. (1990). A cyclical feeding model for pathogen transmission and its application to determine vectorial capacity from vector infection-rates. Journal of Applied Ecology 27, 123–133.Google Scholar

Sinden, R. E., Dawes, E. J., Alavi, Y., Waldock, J., Finney, O., Mendoza, J., Butcher, G. A., Andrews, L., Hill, A. V., Gilbert, S. C. and Basáñez, M.-G. (2007). Progression of Plasmodium berghei through Anopheles stephensi is density-dependent. Public Library of Science Pathogens 3, e195.Google Scholar

Smith, D. L., McKenzie, F. E., Snow, R. W. and Hay, S. I. (2007). Revisiting the basic reproductive number for malaria and its implications for malaria control. Public Library of Science Biology 5, e42.Google ScholarPubMed

Smith, T., Killeen, G. F., Maire, N., Ross, A., Molineaux, L., Tediosi, F., Hutton, G., Utzinger, J., Dietz, K. and Tanner, M. (2006 a). Mathematical modeling of the impact of malaria vaccines on the clinical epidemiology and natural history of Plasmodium falciparum malaria: Overview. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 1–10.Google Scholar

Smith, T., Maire, N., Dietz, K., Killeen, G. F., Vounatsou, P., Molineaux, L. and Tanner, M. (2006 b). Relationship between the entomologic inoculation rate and the force of infection for Plasmodium falciparum malaria. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 11–18.Google Scholar

Smith, T., Ross, A., Maire, N., Rogier, C., Trape, J. F. and Molineaux, L. (2006 c). An epidemiological model of the incidence of acute illness in Plasmodium falciparum malaria. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 56–62.CrossRefGoogle Scholar

Smith, T. A. (2008). Estimation of heterogeneity in malaria transmission by stochastic modelling of apparent deviations from mass action kinetics. Malaria Journal 7, 12, 1–10.Google Scholar

Snow, R., Omumbo, J., Lowe, B., Molyneux, C. S., Obiero, J. O., Palmer, A., Weber, M. W., Pinder, M., Nahlen, B., Obonyo, C., Newbold, C., Gupta, S. and Marsh, K. (1997). Relation between severe malaria morbidity in children and level of Plasmodium falciparum transmission in Africa. Lancet 349, 1650–1654.Google Scholar

Stolk, W. A., de Vlas, S. J., Boors boom, G. J. J. M. and Habbema, J. D. F. (2008). LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages. Parasitology 135 (in press).CrossRefGoogle ScholarPubMed

Struchiner, C. J., Halloran, M. E. and Spielman, A. (1989). Modeling malaria vaccines. I: New uses for old ideas. Mathematical Biosciences 94, 87–113.Google Scholar

Tediosi, F., Hutton, G., Maire, N., Smith, T. A., Ross, A. and Tanner, M. (2006 a). Predicting the cost-effectiveness of introducing a pre-erythrocytic malaria vaccine into the expanded program on immunization in Tanzania. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 131–143.Google Scholar

Tediosi, F., Maire, N., Smith, T., Hutton, G., Utzinger, J., Ross, A. and Tanner, M. (2006 b). An approach to model the costs and effects of case management of Plasmodium falciparum malaria in sub-Saharan Africa. American Journal of Tropical Medicine and Hygiene 75 (Suppl 2), 90–103.CrossRefGoogle ScholarPubMed

Trape, J. F. and Rogier, C. (1996). Combating malaria morbidity and mortality by reducing transmission. Parasitology Today 12, 236–240.Google Scholar