ABSTRACT
BACKGROUND: The COVID-19 pandemic presented substantial challenges to public health stakeholders working to vaccinate populations against the disease, particularly among vaccine hesitant individuals in low- and middle-income countries. Data on the determinants of vaccine hesitancy are scarce, and often available only at the national level. In this paper, our goal is to inform programmatic decision making in support of local vaccine uptake. Our analytical objectives to support this goal are to (1) reliably estimate attitudinal data at the hyperlocal level, and (2) estimate the loss of data heterogeneity among these attitudinal indicators at higher levels of aggregation. With hyperlocal attitudinal data on the determinants of vaccine hesitancy, public health stakeholders can better tailor interventions aimed at increasing uptake sub-nationally, and even down to the individual vaccination site or neighborhood. METHODS: We estimated attitudinal data on the determinants of vaccine hesitancy as framed by the WHO's Confidence, Complacency, and Convenience ("3Cs") Model of Vaccine Hesitancy using a nationally and regionally representative household survey of 4,922 adults aged 18 and above, collected in February 2022. This custom survey was designed to collect information on attitudes towards COVID-19 and concerns about the COVID-19 vaccine. A machine learning (ML) framework was used to spatially interpolate metrics representative of the 3Cs at a one square kilometer (1km2) resolution using approximately 130 spatial covariates from high-resolution satellite imagery, and 24 covariates from the 2018 Nigeria Demographic and Health Survey (DHS). RESULTS: Spatial interpolated hyperlocal estimates of the 3Cs captured significant information on attitudes towards COVID-19 and COVID-19 vaccines. The interpolated estimates held increased heterogeneity within each subsequent level of disaggregation, with most variation at the 1km2 level. CONCLUSIONS: Our findings demonstrate that a) attitudinal data can be successfully estimated at the hyperlocal level, and b) the determinants of COVID-19 vaccine hesitancy have large spatial variance that cannot be captured through national surveys alone. Access to community level attitudes toward vaccine safety and efficacy; vaccination access, time, and financial burden; and COVID-19 beliefs and infection concerns presents novel implications for public health practitioners and policymakers seeking to increase COVID-19 vaccine uptake through more customized community-level interventions.
ABSTRACT
Human alpha satellite (AS) sequence domains that currently function as centromeres are typically flanked by layers of evolutionarily older AS that presumably represent the remnants of earlier primate centromeres. Studies on several human chromosomes reveal that these older AS arrays are arranged in an age gradient, with the oldest arrays farthest from the functional centromere and arrays progressively closer to the centromere being progressively younger. The organization of AS on human chromosome 21 (HC21) has not been well-characterized. We have used newly available HC21 sequence data and an HC21p YAC map to determine the size, organization, and location of the AS arrays, and compared them to AS arrays found on other chromosomes. We find that the majority of the HC21 AS sequences are present on the p-arm of the chromosome and are organized into at least five distinct isolated clusters which are distributed over a larger distance from the functional centromere than that typically seen for AS on other chromosomes. Using both phylogenetic and L1 element age estimations, we found that all of the HC21 AS clusters outside the functional centromere are of a similar relatively recent evolutionary origin. HC21 contains none of the ancient AS layers associated with early primate evolution which is present on other chromosomes, possibly due to the fact that the p-arm of HC21 and the other acrocentric chromosomes underwent substantial reorganization about 20 million years ago.
