H2020Индивидуална стипендия2015–2017

PEARS · Predicting the Evolution of Antibiotic Resistance in Streptococcus pneumoniae

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2015-06-01 → 2017-05-31
Финансиране от ЕС: 195 455 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Математически модели анализират как бактерията Streptococcus pneumoniae развива устойчивост към антибиотици и защо чувствителните щамове продължават да съществуват. Това помага да се предвиди бъдещото разпространение на резистентността спрямо честотата на предписване на лекарствата.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Predicting the Evolution of Antibiotic Resistance in Streptococcus pneumoniae

The principal objective of this project is to develop mathematical models to better understand the dynamics of antibiotic-resistant and antibiotic-sensitive strains in the major human pathogen Streptococcus pneumoniae, predict the frequency of resistance as a function of antibiotic usage, and infer key parameters such as the cost of resistance. The pneumococcus is a human commensal inhabiting the nasopharynx, with a prevalence in children < 5 years old ranging of 30 to 60%. Colonization lasts a week to a few months and is mainly asymptomatic, but occasionally causes infections responsible for the death of about 800, 000 children per year. Multiple genotypes exhibiting resistance to antibiotics have emerged worldwide in past years. Intriguingly, despite strong selection pressure due to antibiotic use, sensitive and resistant strains have coexisted at a stable frequency over the last 15-20 years. This suggests very strong evolutionary forces maintain the stable frequency of resistance. The project is important for society as it addresses a major public health issue. The emergence of resistance to antibiotics is a very pressing public health issue worldwide and probably one of the greatest challenges that humanity is facing in the 21st century. In Europe alone, the cost of antimicrobial resistance is estimated at 25,000 deaths per year and €1.5 billions. Epidemiological-evolutionary modelling is an adequate framework to understand these phenomena, as it provides a rigorous mechanistic description of the biological system and allows explaining what has happened and forecast what will happen. Mathematical models allow predicting the future evolution of antibiotic resistance depending on the rate at which the antibiotic are prescribed, and predicting the impact of public health interventions, for example reducing antibiotic treatment in specific risk groups.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Streptococcus pneumoniae (the pneumococcus) is a bacterial species generally commensal to humans, but which occasionally causes infections responsible for the death of 800, 000 infants each year worldwide. Multiple genotypes exhibiting resistance to antibiotics have emerged in past years. Intriguingly, despite extensive antibiotic consumption operating strong selection for resistance, the latter remains at a stable frequency, 15% on average over the last 20 years in Europe. This is paradoxical, as robust coexistence of resistant and sensitive strains is unexpected under the simplest epidemiological models. In this project, I will investigate the possibility that coexistence is instead maintained by a more complex mechanism, relying on local adaptation to several niches characterized by different rates of antibiotic administration. I will develop a series of novel models with increasing realism and relevance to the context of S. pneumoniae, drawing from the often separate fields of population genetics and epidemiology. Starting with simple but general two- and multiple-niches models that allow for analytical solutions to provide initial insights, I will then build a more complex simulation model parameterized with biologically realistic contact and treatment structures. Output of this model will be confronted to large-scale patterns of spatial variation in resistance observed in epidemiological datasets. The analysis of these models will help us understand what factors facilitate the maintenance of coexistence in S. pneumoniae. This work may lead to better treatment policies to manage antibiotic resistance in this major pathogen.

Оригинален текст от CORDIS (на английски).

Участници

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE · LondonКоординаторОбединеното кралство