Regional comparisons of COVID reporting rates, burden, and mortality age-structure using auxiliary data sources

Van Gordon, M. M.; Mwananyanda, L.; Gill, C. J.; McCarthy, K. A.

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.