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Published on: February 11, 2022
Saliva-based methods for SARS-CoV-2 testing in low- and middle-income countries
Steph H Tan1, Orchid M Allicock1, Achilles Katamba2
1Department of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT06510, United States of America (USA).
Saliva testing offers a simple, accessible, and cost-effective method for widespread COVID-19 (coronavirus disease 2019) detection in low-resource nations. Further implementation science research is crucial to overcome barriers and scale up saliva-based SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) diagnostics.
Area of Science:
- Infectious Diseases
- Public Health
- Diagnostics
Background:
- COVID-19 disproportionately impacts low- and middle-income countries (LMICs).
- Limited access to SARS-CoV-2 testing in LMICs hinders effective case detection.
- Existing diagnostic methods present resource and logistical challenges in LMICs.
Purpose of the Study:
- To highlight the potential of saliva diagnostics for increasing SARS-CoV-2 testing access in LMICs.
- To advocate for implementation science research to optimize saliva testing strategies.
- To address global health inequities in diagnostic testing.
Main Methods:
- Review of existing studies on saliva-based SARS-CoV-2 detection in LMICs.
- Analysis of challenges and opportunities for saliva testing implementation.
- Argument for the necessity of implementation science research.
Main Results:
- Saliva is a sensitive, minimally invasive, and inexpensive sample type for SARS-CoV-2 detection.
- Saliva testing reduces resource constraints and burden on health workers in LMICs.
- Despite demonstrated utility, large-scale implementation of saliva testing in LMICs is lacking.
Conclusions:
- Implementation science research is critical to bridge the gap between evidence and practice for saliva diagnostics in LMICs.
- Governments and laboratories should facilitate mass saliva testing by addressing implementation barriers.
- Scaling up saliva testing can improve COVID-19 surveillance and control in resource-limited settings.
