Fig. 1: Inferential Framework.

Data sources and other inputs are denoted by purple boxes, methodological steps are shown in orange boxes, while results and other outputs are shown in teal boxes. A Age-stratified burial registration data are used to B quantify the shift in registration age-patterns throughout the pandemic, relative to those observed in 2018–2019. These are then converted into C excess mortality estimates during 2020 until June 2021, making several assumptions (subjected to various sensitivity analyses), in particular that registration rate changes in children (mirrored by similar patterns in adolescents and young adults) during the pandemic are a guide to underlying registration and mortality patterns. These estimates are combined with: D weekly post-mortem polymerase chain reaction (PCR) prevalence data from the largest mortuary in Lusaka during June-October 2020; E population-based PCR prevalence and seroprevalence survey data from July 2020; F demography information and likely social-contact structure within Lusaka. These inputs are then used to G fit an age-structured SARS-CoV-2 transmission model using Markov chain Monte Carlo for H a given infection-fatality ratio (IFR) pattern by age to I infer transmission trends over time, J extrapolate patterns of spread throughout the first pandemic wave in Lusaka and K obtain the posterior likelihood of observing the patterns in B, D, and E conditional on the assumed IFR pattern by age.