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

  1. Mollie M. Van Gordon
  2. Lawrence Mwananyanda
  3. Christopher J. Gill
  4. Kevin A. McCarthy

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Abstract

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.

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.

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    SciScore for 10.1101/2021.08.18.21262248: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cost per percent mortality reduction for HIV came directly from the literature (42).
    Cost
    suggested: (COST, RRID:SCR_014098)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study is subject to a number of limitations, particularly as we grapple with understanding COVID dynamics in LMIC contexts. LMICs are subject to limited data availability and substantial uncertainty, which we address in part by making use of sub-national data sources including serology and COVID testing from morgue sampling. Challenges when working with serology include inconsistencies in testing protocols and sampling frameworks alongside the impacts of seroconversion and reversion on results. To address these hurdles, we focus on serostudies that do not target particular populations, and adjust estimates for seroconversion and reversion. Necessitated by data and uncertainty limitations, some of the models we present rely on broad approximations. Modeling reporting rate as a function of testing rate, for example, is an approximation made to include countries where more detailed auxiliary data are not available. We do not attempt to estimate the magnitude of COVID burden in different locations, only their relative ranking. Finally, cost modeling is presented as a ballpark framework to evaluate COVID in the context of other public health concerns, rather than a comprehensive costing model. We use HIV as an example to compare with COVID, recognizing that there are other sources of burden and other approaches to public health investment than single disease-focused strategies. We do not attempt to model the complexities of mortality reduction dynamics, rather seeking to demon...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2021.08.18.21262248 on medRxiv