Related Experiment Video
Updated: Jun 14, 2025

06:57
Loop-mediated Isothermal Amplification LAMP Assays for the Species-specific Detection of Eimeria that Infect Chickens
Published on: February 20, 2015
26.9K
Prevalence data on chicken diseases in low-resource settings.
Revue Scientifique Et Technique (International Office of Epizootics)
|September 2, 2024
Summary
Data on backyard chicken diseases in low- and middle-income countries is scarce, hindering effective control. This study compiled existing data, identifying significant gaps and highlighting the need for better disease surveillance to improve animal and public health.
Area of Science:
- Veterinary Epidemiology
- Animal Health Economics
- Global Public Health
Background:
- Transmissible livestock diseases significantly impact animal welfare, public health, and economies.
- Limited data availability in low-resource settings impedes informed decision-making for disease prevention and control.
- Data scarcity in low- and middle-income countries (LMICs) transforms disease surveillance into a development challenge.
Purpose of the Study:
- To compile and analyze existing prevalence and seroprevalence data for viral, bacterial, and parasitic diseases in backyard chickens across LMICs.
- To identify data gaps in disease occurrence for backyard chickens in LMICs.
- To assess the suitability of existing data for estimating disease prevalence.
Main Methods:
- Conducted a systematic literature review to identify relevant studies.
- Collected prevalence and seroprevalence estimates from 306 studies (n=997), covering viral, bacterial, and parasitic diseases.
- Classified studies based on Food and Agriculture Organization of the United Nations' family poultry production systems and analyzed data reporting on chicken breed and sampling methods.
Main Results:
- A dataset of 997 estimates from 306 studies on backyard chicken diseases in LMICs was compiled.
- Significant data gaps exist, with no relevant disease data for 56.9% of LMICs.
- Most studies (85.4%) focused on extensive scavenging production systems, and 52% lacked breed information.
- 71.0% of estimates were for diseases notifiable to the World Organisation for Animal Health, potentially not producer priorities.
- 72.3% of estimates originated from random samples, suitable for imputation methods.
Conclusions:
- There is a critical need to improve disease surveillance and data collection for backyard chickens in LMICs.
- Existing data, particularly from random samples, can be leveraged using imputation methods to bridge data gaps.
- Addressing data gaps is crucial for effective disease management, enhancing animal welfare, and safeguarding public health in these regions.
More Related Videos
Related Concept Videos
Principles of Disease Surveillance
77
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
77
Healthcare Associated Infections II: Preventive Measures
2.6K
Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
2.6K

