We correct common assumptions about COVID burden and disease characteristics in high-income (HIC) versus low- and middle-income (LMIC) countries by augmenting widely-used surveillance data with auxiliary data sources. We constructed an empirically-based model of serological detection rates to quantify COVID reporting rates in national and sub-national locations. From those reporting rates, we estimated relative COVID burden, finding results that contrast with estimates based on case counts and modeling. To investigate COVID mortality by age in an LMIC context, we utilized a unique morgue study of COVID in Lusaka alongside the population attributable fraction method to account for HIV comorbidity. We calculated the comorbidity-corrected age-adjusted mortality curve in Lusaka and found it significantly skewed toward younger age groups as compared to HICs. This unexpected result recommends against the unexamined use of HIC-derived parameterizations of COVID characteristics in LMIC settings, and challenges the hypothesis of an age-structure protective factor for COVID burden in Africa. Indeed, we found overall COVID burden to be higher in Lusaka than in HICs. Concurrent with high COVID burden, many LMICs have high prevalence of other public health issues such as HIV, which compete for limited health investment resources. Given differences in age-structure, comorbidities, and healthcare delivery costs, we provide a case study comparing the cost efficacy of investment in COVID versus HIV and found that even in a high HIV prevalence setting, investment in COVID remains cost-effective. As a whole, these analyses have broad implications for interpretations of COVID burden, modeling applications, and policy decision-making.
Significance Statement The analyses presented here demonstrate the power of auxiliary COVID data sources to fill information gaps, particularly for LMICs. Our results reveal differences in COVID surveillance and disease dynamics between HICs and LMICs that challenge common perceptions and assumptions about COVID in these respective contexts. We show the divergence of COVID reporting rates between HICs and LMICs and the effects on relative estimated burden. Contradicting common modeling practices, our analysis demonstrates that the age-structure of COVID mortality cannot be accurately generalized from HICs to LMICs. We find higher COVID burden in LMIC contexts than HICs particularly in younger age groups and show that investment in COVID is cost-effective even in light of other public health concerns.