**5. Conclusions**

Through our multi-level modeling approach, we were able to identify sociodemographic factors associated with COVID-19 vaccination at the municipality level. Our findings show more granularly where COVID-19 vaccination is lagging in Guatemala and which municipalities could benefit from more focused vaccination activities. Municipalities with populations experiencing higher poverty had lower vaccination coverage, and municipalities with higher proportions of primary education completion, children, people aged 60 years and older, and more testing for SARS-CoV-2 infection had higher vaccination coverage. COVID-19 vaccine delivery and public health outreach may be focused on communities experiencing more poverty. While there has historically been a difficulty with healthcare delivery to communities experiencing poverty, interventions based on poverty indices may help mitigate the effects of the COVID-19 pandemic on such communities and ultimately improve health equity.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www. mdpi.com/article/10.3390/vaccines11040745/s1, Table S1: Association between sociodemographic factors (by municipalities and departments) and two-dose vaccination coverage (%) by municipalities in Guatemala (N = 336). SARS-CoV-2 case and vaccination data are from 13 February 2020 to 1 October 2021.

**Author Contributions:** Conceptualization, R.C., E.C., J.M., J.S., L.L.S.J., D.S.R.A., E.Z.-G. and P.S.S.; methodology, R.C., E.C., J.M., E.Z.-G. and P.S.S.; software, R.C. and E.C.; validation, R.C., E.C., J.M., E.Z.-G. and P.S.S.; formal analysis, R.C., E.C., J.M., E.Z.-G. and P.S.S.; resources, R.C., E.C., J.M., A.S., E.Z.-G. and P.S.S.; data curation, R.C.; writing—original draft preparation, R.C.; writing—review and editing, R.C., E.C., J.M., A.S., J.S., L.L.S.J., D.S.R.A., E.Z.-G. and P.S.S.; visualization, R.C. and E.C.; supervision, E.Z.-G. and P.S.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** This activity was reviewed by a Centers for Disease Control and Prevention (CDC) Human Subjects Representative and was consistently conducted with applicable federal law and CDC policy [see e.g., 45 C.F.R. part 46; 21 C.F.R. part 56; 42 U.S.C. §241(d), 5 U.S.C. §552a, 44 U.S.C. §3501 et seq]. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Publicly available datasets were analyzed in this study. These data can be found here: Guatemala Population and Housing Census 2018 https://www.censopoblacion.gt/ (accessed on 5 December 2022); Guatemala Demographic and Health Survey https://dhsprogram. com/publications/publication-fr318-dhs-final-reports.cfm (accessed on 5 December 2022).; Ministry of Public Health and Social Assistance (MSPAS) of Guatemala https://tablerocovid.mspas.gob. gt/tablerocovid/ (accessed on 4 December 2022) and https://gtmvigilanciacovid.shinyapps.io/ Coberturas\_Tablero/ (accessed on 4 December 2022). Restrictions apply to the availability of the poverty indicator data. Data were obtained from Paolo Marsicovetere and are available from the author.

**Acknowledgments:** The authors thank Karin Slowing, Oscar Chavez, and Paolo Marsicovetere of the Laboratorio de Datos Guatemala for their assistance with data sources, including the general poverty indicator, for this investigation. We thank Sofia Ortiz Neidhart for assistance with project conceptualization.

**Conflicts of Interest:** The authors declare no conflict of interest.
