At a glance
- The Global Action in Healthcare Network – Healthcare-associated Infections Module (GAIHN-HAI) engages national, regional and global public health experts to build capacity to detect, prevent and respond to infectious disease threats in a wide range of healthcare settings.
- Network priorities include surveillance and prevention of bacterial and emerging viral infections associated with healthcare delivery.
- Initial network activities include healthcare-associated infection (HAI) surveillance and prevention and SARS-CoV-2 genomic surveillance.
Why it matters
HAIs are infections that occur in patients while they are receiving health care for another condition or among healthcare providers during their regular duties in healthcare facilities. HAIs affect millions of people globally every year and are associated with:
- Significant morbidity and mortality.
- Substantial financial losses for healthcare systems and families.
- Strained healthcare systems.
Many clinically significant HAIs are bacterial infections related to invasive medical devices such as central-line associated bloodstream infections. However, the 2014-2016 West Africa Ebola epidemic and the COVID-19 pandemic demonstrated the importance of preventing healthcare-associated viral transmission as well.
Studies have shown that people in low-and middle-income countries are at increased risk for HAIs compared to people in high-income countries.1
Detecting, preventing and responding to HAIs, including those caused by emerging pathogens, is critical to providing safe health care and protecting patients, staff and visitors. GAIHN-HAI helps healthcare facilities implement effective infection prevention and control (IPC) measures and surveillance to prevent HAIs, even with limited resources.
Priorities
Healthcare-associated infection surveillance and prevention
GAIHN-HAI seeks to reduce HAIs in participating facilities through:
- Enhanced surveillance.
- Dedicated prevention activities.
- Engagement of local, regional and global public health experts.
Strong national and healthcare facility-level IPC programs help implement IPC measures that are crucial to reducing HAIs.2 Surveillance is a core component of any strong IPC program as data can guide IPC interventions and detect outbreaks or emerging infections.
GAIHN-HAI uses network experience and innovative approaches to provide practical, accessible approaches and tools for global healthcare facilities with limited resources to:
- Make effective HAI surveillance more accessible.
- Understand the burden and epidemiology of HAIs in their healthcare facilities.
- Guide IPC strategies.
- Assess the impact of IPC interventions.
Through this work, GAIHN-HAI plays an important role in increasing the quality and availability of data for action and decreasing the impact of HAIs on healthcare systems.
SARS-CoV-2 genomic surveillance
Like all viruses, SARS-CoV-2, the virus that causes COVID-19, evolves over time through mutation. Mutations may result in new variants of the virus.
Some mutations may allow virus variants to spread more easily or make them resistant to treatments or vaccines. Experts must monitor variants with these mutations carefully.
Global genomic surveillance for SARS-CoV-2 involves tracking the virus to detect new variants and to monitor trends in circulating variants. Tracking COVID-19 variants helps support national and global decisions around public health and mitigation measures, diagnostics, treatments and vaccination.
GAIHN-HAI supports healthcare-based SARS-CoV-2 variant characterization among healthcare workers and hospitalized patients of network facilities.
What we've accomplished
- Established functional GAIHN-HAI networks in 4 countries: Brazil, Indonesia, Jordan and the Philippines.
- Refined and validated methodology, HAI case definitions and procedures to help facilities with limited resources estimate HAI burden.
- Developed and tested a set of digital tools and training materials to improve data collection and analysis that facilitates IPC program decision-making and outbreak response.
- Established and maintained facility-based, targeted SARS-CoV-2 variant characterization for healthcare workers and select inpatient populations.
- Built patient-level linkage between clinical and genomic sequencing data for improved case detection and cluster identification.
- Enhanced use of COVID-19 sequencing results across network sites to identify and characterize novel circulating variants and identify, confirm, and respond to case clusters. 3
GAIHN-HAI Forum
Success story
Innovating HAI detection
GAIHN-HAI, in collaboration with Health Security Partners (HSP) and Civilian Research and Development Foundation (CRDF) Global, worked with GAIHN-HAI facilities to develop, validate and implement two core tools:
- A protocol for conducting a point prevalence survey (PPS) for HAIs.
- Web-based software to streamline HAI PPS data collection allowing for near real-time feedback.
The GAIHN-HAI PPS protocol helps healthcare facilities understand the prevalence of HAIs while using fewer resources than traditional HAI surveillance systems. Its companion web-based software generates near real-time feedback and helps facilities identify opportunities to implement IPC interventions to prevent HAIs.
After conducting a series of GAIHN-HAI PPS pilots at network facilities, plans are underway to use these tools in other network facilities to enhance their efforts to detect, prevent and respond to HAIs.
Funded partners
GAIHN-HAI partners support select hospitals in the following countries:
- Health Security Partners - Brazil, Indonesia and the Philippines.
- CRDF Global - Jordan.
- WHO. Global report on infection prevention and control. (2022). https://www.who.int/publications/i/item/9789240051164
- WHO. Guidelines on core components of infection prevention and control programmes at the national and acute health care facility level.(2016). https://www.who.int/publications/i/item/9789241549929
- Andreis TF, Cantarelli VV, da Silva MB, Helfer MS, Brust FR, GAIHN-HAI Team, Zavascki AP. Substantial diversity in cocirculating Omicron lineages in hospital setting, Porto Alegre, Brazil. Emerging Infectious Diseases, 29, no.12 (2023): 2583-258. https://wwwnc.cdc.gov/eid/article/29/12/23-0880_article