Identifying drivers of spatial-temporal heterogeneity in COVID-19 outcomes during the 2020-2021 outbreaks in Peru

Abstract

According to the World Health Organization, it has been estimated that Peru had the highest per capita excess mortality rate for the 2020-2021 period among all countries in the world. Understanding the drivers of heterogeneity in the COVID-19 response is relevant from a public and global health perspective, as it could inform policymakers what interventions contribute to mitigating the outbreaks. To understand what province-level covariates determined better or worst outcomes in the Peruvian setting, we used vital registration data to fit time-varying mortality rates for the 196 provinces in Peru during the 2020-2021 period. Then, extracting transmission and disease features, we tested the relationship of those features with province-level covariates. We identified three main drivers of the variability of COVID-19 outcome, namely the overall wealth of the province by means of the human development index, the demographic structure, and the internal migration. The results showed potential drivers of the epidemic in Peru and acted as an example of a failed COVID-19 response as a valuable and tragic lesson for Global Health.