Challenges in Influenza Control and Surveillance in the Republic of Kazakhstan DOI Creative Commons

Mukhlis Hujatullah,

N. G. Klivleyeva, Neyazi Ghulam Rabani

et al.

Journal for Research in Applied Sciences and Biotechnology, Journal Year: 2024, Volume and Issue: 3(5), P. 160 - 165

Published: Nov. 2, 2024

The COVID-19 pandemic has significantly disrupted the circulation of influenza viruses in Kazakhstan, highlighting vulnerabilities country’s public health infrastructure. This review critically examines challenges faced infiltrating and controlling particularly light shifting epidemiological landscape post-pandemic. Key issues include decline cases during pandemic, which complicates assessment epidemiology, vaccine effectiveness, planning vaccination campaigns. Although part Global Influenza Hospital Surveillance Network (GIHSN), Kazakhstan's surveillance systems face data collection, coordination, awareness gaps. discusses prevalence various strains, impact zoonotic infections, necessity for improved monitoring frameworks. Additionally, historical context infectious disease control Kazakhstan is explored, emphasising need enhanced international collaboration targeted strategies. findings underscore importance robust to mitigate risks seasonal influenza, advocating a comprehensive approach safeguard Kazakhstan.

Language: Английский

Understanding Ecological Systems Using Knowledge Graphs: An Application to Highly Pathogenic Avian Influenza DOI Creative Commons
Hailey Robertson, Barbara A. Han, Adrian A. Castellanos

et al.

Bioinformatics Advances, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Ecological systems are complex. Representing heterogeneous knowledge about ecological is a pervasive challenge because data generated from many subdisciplines, exist in disparate sources, and only capture subset of interactions underpinning system dynamics. Knowledge graphs (KGs) have been successfully applied to organize predict new linkages complex systems. Though not previously broadly ecology, KGs much offer an era when dynamics responding rapid changes across multiple scales. We developed KG demonstrate the method's utility for problems focused on highly pathogenic avian influenza (HPAI), transmissible virus with broad host range, wide geographic distribution, evolution pandemic potential. describe development graph include related HPAI including pathogen-host associations, species distributions, population demographics, using semantic ontology that defines relationships within between datasets. use perform set proof-of-concept analyses validating method identifying patterns ecology. underscore generalizable value ecology ability reveal known testable hypotheses support deeper mechanistic understanding The code available under MIT License GitHub at https://github.com/cghss-data-lab/uga-pipp.

Language: Английский

Citations

0
Evolution and mutational landscape of highly pathogenic avian influenza strain A(H5N1) in the current outbreak in the USA and global landscape DOI
Chiranjib Chakraborty, Manojit Bhattacharya

Virology, Journal Year: 2024, Volume and Issue: unknown, P. 110246 - 110246

Published: Sept. 1, 2024

Language: Английский

Citations

2
Understanding Ecological Systems Using Knowledge Graphs: An Application to Highly Pathogenic Avian Influenza DOI Creative Commons
Hailey Robertson, Barbara A. Han, Adrian A. Castellanos

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 10, 2024

Abstract Ecological systems are complex. Representing heterogeneous knowledge about ecological is a pervasive challenge because data generated from many subdisciplines, exist in disparate sources, and only capture subset of important interactions underpinning system structure, resilience, dynamics. Knowledge graphs have been successfully applied to organize systematically predict new linkages representing unobserved relationships complex systems. Though not previously broadly ecology, much offer an era global change when dynamics responding rapid changes across multiple scales simultaneously. We developed graph demonstrate the method’s utility for problems focused on highly pathogenic avian influenza (HPAI), transmissible virus with broad animal host range, wide geographic distribution, evolution pandemic potential. describe development include range related HPAI including pathogen-host associations, species distributions, human population demographics, using semantic ontology that defines within between datasets. use perform set proof-of-concept analyses validating method identifying features underscoring generalizable value ecology their revealing known entities generating testable hypotheses support deeper mechanistic understanding

Language: Английский

Citations

0
Challenges in Influenza Control and Surveillance in the Republic of Kazakhstan DOI Creative Commons

Mukhlis Hujatullah,

N. G. Klivleyeva, Neyazi Ghulam Rabani

et al.

Journal for Research in Applied Sciences and Biotechnology, Journal Year: 2024, Volume and Issue: 3(5), P. 160 - 165

Published: Nov. 2, 2024

The COVID-19 pandemic has significantly disrupted the circulation of influenza viruses in Kazakhstan, highlighting vulnerabilities country’s public health infrastructure. This review critically examines challenges faced infiltrating and controlling particularly light shifting epidemiological landscape post-pandemic. Key issues include decline cases during pandemic, which complicates assessment epidemiology, vaccine effectiveness, planning vaccination campaigns. Although part Global Influenza Hospital Surveillance Network (GIHSN), Kazakhstan's surveillance systems face data collection, coordination, awareness gaps. discusses prevalence various strains, impact zoonotic infections, necessity for improved monitoring frameworks. Additionally, historical context infectious disease control Kazakhstan is explored, emphasising need enhanced international collaboration targeted strategies. findings underscore importance robust to mitigate risks seasonal influenza, advocating a comprehensive approach safeguard Kazakhstan.

Language: Английский

Citations

0