Dynamical regulations on mobility and vaccinations for controlling COVID-19 spread

Abstract

Abstract Using a system of time-dynamical equations, we investigate how daily mobility indices, such as the homestay percentage above the pre-COVID normal ( $$H\%$$ H % ; or H-forcing), and the vaccinated percentage ( $$V_c\%$$ V c % ; or V-forcing) impact the net reproductive rate (R0) of COVID-19 in ten island nations as a prototype, and then, extending it to 124 countries worldwide. Our H- and V-forcing model of R0 can explain the new trends in 106 countries. The disease transmission can be controlled by forcing down $$R0(H,V_c) 40\%$$ H > 40 % in $$93\%$$ 93 % of countries with $$0\%$$ 0 % vaccinated plus recovered, $$V_p$$ V p . The required critical $$H\%$$ H % decreases with increasing $$V_p\%$$ V p % , dropping it down to $$20\%$$ 20 % with $$25\% V_p$$ 25 % V p , and further down to $$8\%$$ 8 % with $$50\% V_p$$ 50 % V p . However, the regulations on $$H\%$$ H % are context-dependent and country-specific. Our model gives insights into forecasting and controlling the disease’s transmission behaviour when the effectiveness of the vaccines is a concern due to new variants, and/or there are delays in vaccination rollout programs.