Epidemics of chikungunya, Zika, and COVID-19 reveal bias in case-based mapping
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Abstract
Accurate tracing of epidemic spread over space enables effective control measures. We examined three metrics of infection and disease in a pediatric cohort (N ≈ 3,000) over two chikungunya and one Zika epidemic, and in a household cohort (N=1,793) over one COVID-19 epidemic in Managua, Nicaragua. We compared spatial incidence rates (cases/total population), infection risks (infections/total population), and disease risks (cases/infected population). We used generalized additive and mixed-effects models, Kulldorf’s spatial scan statistic, and intracluster correlation coefficients. Across different analyses and all epidemics, incidence rates considerably underestimated infection and disease risks, producing large and spatially non-uniform biases distinct from biases due to incomplete case ascertainment. Infection and disease risks exhibited distinct spatial patterns, and incidence clusters inconsistently identified areas of either risk. While incidence rates are commonly used to infer infection and disease risk in a population, we find that this can induce substantial biases and adversely impact policies to control epidemics.
Article summary line
Inferring measures of spatial risk from case-only data can substantially bias estimates, thereby weakening and potentially misdirecting measures needed to control an epidemic.
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SciScore for 10.1101/2021.07.23.21261038: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical statement: The PDCS was approved by Institutional Review Boards of the University of California, Berkeley, the University of Michigan, Ann Arbor, and the Nicaraguan Ministry of Health.
Consent: Participants’ parents or legal guardians provided written informed consent.
Field Sample Permit: Laboratory methods: Upon collection, annual blood samples were immediately transported to the Nicaraguan National Virology Laboratory of the Ministry of Health for processing and storage at −80°C.Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources We used SaTScan v9.4.4 to … SciScore for 10.1101/2021.07.23.21261038: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical statement: The PDCS was approved by Institutional Review Boards of the University of California, Berkeley, the University of Michigan, Ann Arbor, and the Nicaraguan Ministry of Health.
Consent: Participants’ parents or legal guardians provided written informed consent.
Field Sample Permit: Laboratory methods: Upon collection, annual blood samples were immediately transported to the Nicaraguan National Virology Laboratory of the Ministry of Health for processing and storage at −80°C.Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources We used SaTScan v9.4.4 to identify hierarchical and the newer Gini clusters of infection risk, disease risk, and case incidence.29,30 Hierarchical clusters identify the most statistically likely clusters and Gini clusters maximize outcome rates SaTScansuggested: NoneResults 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:As the case-based incidence rate is frequently misinterpreted as a measure of infection and/or disease risk for pathogens of high human concern that cause many subclinical infections (including malaria-causing Plasmodium; Mycobacterium tuberculosis; and many pathogens transmitted by sex, air, vectors, and soil), our findings concerning the limitations of case-based spatial studies likely generalize widely and impact many diseases of global health importance that disproportionately affect neglected populations. Measuring a population’s infection status (not just that of suspected cases) has many benefits, the most obvious being to guide interventions to areas of high transmission. As another example, due to antibody-dependent enhancement, prior infection with DENV or ZIKV can lead to severe and life-threatening dengue upon a subsequent DENV infection under certain circumstances.18,23 Given widespread ZIKV immunity across Latin America and the high prevalence of DENV across the tropics and subtropics, knowing where ZIKV and DENV seroprevalence is high can highlight where episodes of severe dengue are likely to occur and burden medical facilities. For SARS-CoV-2, knowledge of areas with a high proportion of uninfected individuals is critical for public health measures, both to prioritize vaccine rollout, particularly in settings where vaccine availability is severely limited, and to inform the need for other interventions. Others have shown how to combine regional serosurvey dat...
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.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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