Genomic epidemiological models describe pathogen evolution across fitness valleys

Mapping Intimacies ◽

10.1101/2021.12.16.473045 ◽

2021 ◽

Author(s):

Pablo Cárdenas ◽

Mauricio Santos-Vega

Keyword(s):

Life Cycles ◽

Population Bottlenecks ◽

Genomic Evolution ◽

Epidemiological Models ◽

Computational Framework ◽

Pathogen Evolution ◽

Epidemiological Modeling ◽

Selective Pressures ◽

Disease Research ◽

Infectious Disease Research

Genomics is fundamentally changing epidemiological research. However, exploring hypotheses about pathogen evolution in different epidemiological contexts poses new challenges. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmission or resistance to treatment. In this work, we present Opqua, a computational framework for flexible simulation of pathogen epidemiology and evolution. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

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Using Unstated Cases to Correct for COVID-19 Pandemic Outbreak and Its Impact on Easing the Intervention for Qatar

Biology ◽

10.3390/biology10060463 ◽

2021 ◽

Vol 10 (6) ◽

pp. 463

Author(s):

Narjiss Sallahi ◽

Heesoo Park ◽

Fedwa El Mellouhi ◽

Mustapha Rachdi ◽

Idir Ouassou ◽

...

Keyword(s):

Public Health ◽

A Priori ◽

Epidemiological Models ◽

Sir Epidemic Model ◽

Gulf Region ◽

Epidemiological Modeling ◽

Public Health Policies ◽

Sir Epidemic ◽

The Impact ◽

Case Data

Epidemiological Modeling supports the evaluation of various disease management activities. The value of epidemiological models lies in their ability to study various scenarios and to provide governments with a priori knowledge of the consequence of disease incursions and the impact of preventive strategies. A prevalent method of modeling the spread of pandemics is to categorize individuals in the population as belonging to one of several distinct compartments, which represents their health status with regard to the pandemic. In this work, a modified SIR epidemic model is proposed and analyzed with respect to the identification of its parameters and initial values based on stated or recorded case data from public health sources to estimate the unreported cases and the effectiveness of public health policies such as social distancing in slowing the spread of the epidemic. The analysis aims to highlight the importance of unreported cases for correcting the underestimated basic reproduction number. In many epidemic outbreaks, the number of reported infections is likely much lower than the actual number of infections which can be calculated from the model’s parameters derived from reported case data. The analysis is applied to the COVID-19 pandemic for several countries in the Gulf region and Europe.

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Application of 3D bioprinting in the prevention and the therapy for human diseases

Signal Transduction and Targeted Therapy ◽

10.1038/s41392-021-00566-8 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Hee-Gyeong Yi ◽

Hyeonji Kim ◽

Junyoung Kwon ◽

Yeong-Jin Choi ◽

Jinah Jang ◽

...

Keyword(s):

Infectious Disease ◽

Infectious Diseases ◽

Rapid Development ◽

In Vitro Models ◽

Delivery Systems ◽

Advanced Technology ◽

3D Bioprinting ◽

Disease Research ◽

Infectious Disease Research

AbstractRapid development of vaccines and therapeutics is necessary to tackle the emergence of new pathogens and infectious diseases. To speed up the drug discovery process, the conventional development pipeline can be retooled by introducing advanced in vitro models as alternatives to conventional infectious disease models and by employing advanced technology for the production of medicine and cell/drug delivery systems. In this regard, layer-by-layer construction with a 3D bioprinting system or other technologies provides a beneficial method for developing highly biomimetic and reliable in vitro models for infectious disease research. In addition, the high flexibility and versatility of 3D bioprinting offer advantages in the effective production of vaccines, therapeutics, and relevant delivery systems. Herein, we discuss the potential of 3D bioprinting technologies for the control of infectious diseases. We also suggest that 3D bioprinting in infectious disease research and drug development could be a significant platform technology for the rapid and automated production of tissue/organ models and medicines in the near future.

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