title: Current Mathematical Models for Analyzing Anti-Malarial Antibody Data with an Eye to Malaria Elimination and Eradication.
abstract: The last decade has witnessed a steady reduction of the malaria burden worldwide. With various countries targeting disease elimination in the near future, the popular parasite infection or entomological inoculation rates are becoming less and less informative of the underlying malaria burden due to a reduced number of infected individuals or mosquitoes at the time of sampling. To overcome such problem, alternative measures based on antibodies against specific malaria antigens have gained recent interest in malaria epidemiology due to the possibility of estimating past disease exposure in absence of infected individuals. This paper aims then to review current mathematical models and corresponding statistical approaches used in antibody data analysis. The application of these models is illustrated with three data sets from Equatorial Guinea, Brazilian Amazonia region, and western Kenyan highlands. A brief discussion is also carried out on the future challenges of using these models in the context of malaria elimination.
authors.affiliation: London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; Centro de Estatística da Universidade de Lisboa, Faculdade de Ciências, Universidade de Lisboa, Bloco C6, Piso 4, Campo Grande, 1749-016 Lisboa, Portugal.
authors.forename: Nuno
authors.initials: N
authors.lastname: Sepúlveda
authors.affiliation: London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
authors.forename: Gillian
authors.initials: G
authors.lastname: Stresman
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Medical School Building, Norfolk Place, London W2 1PG, UK; Division of Population Health and Immunity, Walter and Eliza Hall Institute, 1G Royal Parade, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia.
authors.forename: Michael T
authors.initials: MT
authors.lastname: White
authors.affiliation: London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
authors.forename: Chris J
authors.initials: CJ
authors.lastname: Drakeley
mesh_terms: D000818:Animals; D000913:Antibodies, Protozoan / Q000627:therapeutic use*; D000962:Antimalarials / Q000627:therapeutic use*; D001938:Brazil; D066264:Datasets as Topic; D016703:Equatorial Guinea; D006801:Humans; D007167:Immunotherapy; D007630:Kenya; D008288:Malaria / Q000276:immunology / Q000628:therapy*; D017780:Malaria Vaccines / Q000276:immunology*; D008962:Models, Theoretical; D010961:Plasmodium / Q000276:immunology*
chemical_list: D000913:Antibodies, Protozoan; D000962:Antimalarials; D017780:Malaria Vaccines