COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model

Wesley Dattilo; Alcides Castro e Silva; Roger Guevara; Ian MacGregor-Fors; Servio Pontes Ribeiro

Initially, we carried out a Spearman rank correlation to assess whether those cities with higher airport closeness centrality (i.e., important cities for connecting different cities within the Mexican air transportation network) were more vulnerable to COVID-19. We calculated closeness centrality (i.e., the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the network) for each airport using the same air transport network used in our SIR-Net model. We also performed a Spearman correlation to evaluate whether Mexican cities most vulnerable to COVID-19 were related to better public health infrastructure in terms of higher number of inpatient and intensive care beds (including both adult and pediatric beds). The number of beds for each city has was standardized by every 10,000 inhabitants according to the recommendations of the WHO (21) . It is notable that our calculations only include Mexican public hospitals (19) .