Mathematical modeling of malaria transmissin considering heterogenity in exposure na susceptibility of hosts

Background Brazil has the lowest malaria burden in 35 years. After being substantially reduced in last decades, Brazilian Ministry of Health launched in November 2015 the Plan for Malaria Elimination. The success of the plan depends on focusing in a small number of transmission areas where malaria still persists even after several governmental actions. In this sense, more elaborated studies considering new analytical tools should be taken in consideration in order to improve existing models. Mathematical models contribute to the understanding of epidemiological patterns and can be used to guide public policies. However, most of malaria models have their parameters calibrated with statistical means, i.e., they consider homogeneity in the individuals susceptibility. The current work aims to improve models for malaria transmission taking into account susceptibility peculiarities from individuals living in risk areas. Materials and Methods The work is based in two data sources. The first regards all Malaria cases registered by Brazilian government during two years in two cities where malaria incidence was considerably high - more than 50.000 cases. The data contains patient identifications, date, location and result (P. falciparum and/or P. vivax or P. malarie) of exams, amount of parasitemia, information of pregnancy, presence or not of symptoms and prescribed treatments. The second data source is the cohort study from the project entitled “Bases científicas para a eliminação da malária residual na Amazônia brasileira”, where data from 9.136 people from the urban area of Mâncio Lima city were collected. The data includes GPS coordinates of all houses and their respective infrastructure information. Moreover, socio-economic aspects and cultural behaviours were also registered. Both data are combined and patterns of exposure and risk heterogeneity of populations are mathematically described. Results The comparison of malaria transmission dynamics described by models that consider exposure and risk heterogeneity with the dynamics of models that consider homogeneous population highlights distortions generated on the efficacy estimates of governmental initiatives to combat malaria transmission. Conclusions Proposed models can be used as reference for governmental initiatives in order to improve local malaria elimination.