Diversity of drugs against bacterial infections, and development of resistance to such drugs are increasing. We formulate and analyze a deterministic model for the population dynamics of sensitive and resistant bacteria to multiple bactericidal and bacteriostatic antibiotics, assuming that drug resistance is acquired through mutations and plasmid transmission. Model equilibria are determined from qualitative analysis, and numerical simulations are used to assess temporal dynamics of sensitive and drug-resistant bacteria. The model presents three possibilities: elimination of bacteria, persistence of only resistant bacteria, or coexistence of sensitive and resistant bacteria. Evolution to one of these scenarios depends on thresholds numbers involving sensitive and resistant bacteria.
In Colombia, malaria is a public health problem that affects a large part of its population. Above motivated us to formulate an optimal control problem considering the following control variables: bed nets (BN), intermittent prophylactic treatment in pregnancy (IPTp) and prompt and effective case management (PECM). The results reveal the importance of congenital transmission and death due to disease in the infection outcome. It is imperative that strategies be defined to reduce these risk factors.
This work aims to explain the behavior of the multi-drug resistance (MDR) percentage of Pseudomonas aeruginosa in Europe, through multivariate statistical analysis and machine learning validation, using data from the European Antimicrobial Resistance Surveillance System, the World Health Organization, and the World Bank. We ran a multidimensional data panel regression analysis and used machine learning techniques to validate a pooling panel data case. The results of our analysis showed that the most important variables explaining the MDR phenomena across European countries are governance variables, such as corruption control and the rule of law. The models proposed in this study showed the complexity of the antibiotic drugs resistance problem. The efforts controlling MDR P. aeruginosa, as a well-known Healthcare-Associated Infection (HCAI), should be focused on solving national governance problems that impact resource distribution, in addition to individual guidelines, such as promoting the appropriate use of antibiotics.
In this work we study the malaria disease problem in Tumaco through of the mathematical modelling with the objective of contribute to the understanding of the transmission dynamics. To this end, we formulate a system of ordinary differential equations which tries to describe the malaria disease transmission dynamics for human and mosquito populations considering vectorial transmission, vertical transmission of disease and a force of infection which measure the impact that occurs in the disease transmission rate when an infected human is introduced into the 206 J.M. Montoya-Aguilar et al. mosquito population. The results reveal the importance of congenital transmission and death due to disease in the infection outcome.
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