Modeling COVID-19 vaccination strategies in LMICs considering uncertainty in viral evolution and immunity (preprint)

ABSTRACT

Vaccines against the SARS-CoV-2 virus were developed in record time, but their distribution has been highly unequal. With demand saturating in high-income countries, many low- and middle-income countries (LMIC) finally have an opportunity to acquire COVID-19 vaccines. But the pandemic has taken its toll, and a majority of LMIC populations have partial immunity to COVID-19 disease due primarily to viral infection. This existing immunity, combined with resource limitations, raises the question of how LMICs should prioritize COVID-19 vaccines relative to other competing health priorities. We modify an established computational model, Covasim, to address these questions in four diverse country-like settings under a variety of viral evolution, vaccine delivery, and novel immunity scenarios. Under continued Omicron-like viral evolution and mid-level immunity assumptions, results show that COVID-19 vaccines could avert up to 2 deaths per 1,000 doses if administered to high-risk (60+) populations as prime+boost or annual boosting campaigns. Similar immunization efforts reaching healthy children and adults would avert less than 0.1 deaths per 1,000 doses. Together, these modeling results can help to support normative guidelines and programmatic decision making towards objectively maximizing population health.