title: Modeling malaria and typhoid fever co-infection dynamics.
abstract: Malaria and typhoid are among the most endemic diseases, and thus, of major public health concerns in tropical developing countries. In addition to true co-infection of malaria and typhoid, false diagnoses due to similar signs and symptoms and false positive results in testing methods, leading to improper controls, are the major challenges on managing these diseases. In this study, we develop novel mathematical models describing the co-infection dynamics of malaria and typhoid. Through mathematical analyses of our models, we identify distinct features of typhoid and malaria infection dynamics as well as relationships associated to their co-infection. The global dynamics of typhoid can be determined by a single threshold (the typhoid basic reproduction number, R0(T)) while two thresholds (the malaria basic reproduction number, R0(M), and the extinction index, R0(MM)) are needed to determine the global dynamics of malaria. We demonstrate that by using efficient simultaneous prevention programs, the co-infection basic reproduction number, R0, can be brought down to below one, thereby eradicating the diseases. Using our model, we present illustrative numerical results with a case study in the Eastern Province of Kenya to quantify the possible false diagnosis resulting from this co-infection. In Kenya, despite having higher prevalence of typhoid, malaria is more problematic in terms of new infections and disease deaths. We find that false diagnosis-with higher possible cases for typhoid than malaria-cause significant devastating impacts on Kenyan societies. Our results demonstrate that both diseases need to be simultaneously managed for successful control of co-epidemics.
authors: Department of Mathematics and Statistics, University of Missouri-Kansas City, Kansas City, MO 64110, USA.
authors: Jones M
authors: JM
authors: Mutua
authors: Department of Natural Science in the Center for General Education, Chang Gung University, Kwei-Shan, Taoyuan 333, Taiwan.
authors: Feng-Bin
authors: FB
authors: Wang
authors: Department of Mathematics and Statistics, University of Missouri-Kansas City, Kansas City, MO 64110, USA. Electronic address: vaidyan@umkc.edu.
authors: Naveen K
authors: NK
authors: Vaidya
mesh_terms: D050936:Basic Reproduction Number; D015897:Comorbidity; D003951:Diagnostic Errors; D006801:Humans; D007630:Kenya / Q000453:epidemiology; D008288:Malaria / Q000175:diagnosis / Q000453:epidemiology*; D008962:Models, Theoretical; D014435:Typhoid Fever / Q000175:diagnosis / Q000453:epidemiology*
keywords: Co-infection; False diagnosis; Malaria; Mathematical analysis; Reproduction numbers; Typhoid