COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya
Brand S., Ojal J., Aziza R., Were V., Okiro E., Kombe I., Mburu C., Ogero M., Agweyu A., Warimwe G., Nyagwange J., Karanja H., Gitonga J., Mugo D., Uyoga S., Adetifa I., Scott A., Otieno E., Murunga N., Otiende M., Ochola-Oyier L., Agoti C., Githinji G., Kasera K., Amoth P., Mwangangi M., Aman R., Ng’ang’a W., Tsofa B., Bejon P., Keeling M., Nokes J., Barasa E.
Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies. One Sentence Summary COVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure