Mexico has suffered one of the highest COVID-19 mortality rates in the world. This study examined how socio-demographic and population health characteristics shape the geospatial variability in excess mortality patterns during the pandemic. We found a positive association of excess mortality rates with aging index and marginalization index.
Background: Mexico has suffered one of the highest COVID-19 mortality rates in the world. In this study we examined how socio-demographic and population health characteristics shape the geospatial variability in excess mortality patterns during the COVID-19 pandemic in Mexico. Methods: Weekly all-cause mortality time series for all 32 Mexican states, from January 4, 2015 to April 10, 2021, were analyzed to estimate the excess mortality rates using Serfling regression models. The association between socio-demographic, health indicators and excess mortality rates were determined using multiple linear regression analyses. Finally, we used functional data analysis to characterize clusters of states with distinct mortality growth rate curves. Results: The overall all-cause excess deaths rate during the COVID-19 pandemic in Mexico until April 10, 2021 was estimated at 39.66 per 10 000 population. The lowest excess death rates were observed in southeastern states including Chiapas (12.72), Oaxaca (13.42) and Quintana Roo (19.41) whereas Mexico City had the highest excess death rate (106.17), followed by Tlaxcala (51.99) and Morelos (45.90). We found a positive association of excess mortality rates with aging index (P value<.0001), marginalization index (P value<.0001), and average household size (P value=0.0003) in the final adjusted model (Model R2=76%). We identified four distinct clusters with qualitatively similar excess mortality curves. Conclusion: Central states exhibited the highest excess mortality rates whereas the distribution of aging index, marginalization index, and average household size explained the variability in excess mortality rates across Mexico. Our findings can help tailor interventions to mitigate the mortality impact of the pandemic.