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

We developed a new temporally-explicit model and simulated several social distancing scenarios 29 to predict the vulnerability to COVID-19 of 50 Mexican cities that are interconnected by their air 30 transportation network. Additionally, we assessed the sufficiency of the public health 31 infrastructure in the focal cities to face the pandemic over time. Based on our model, we show 32 that the most important cities within the Mexican air transportation network are the most 33 vulnerable to COVID-19, with all assessed public health infrastructure being insufficient to face 34 the modeled scenario for the pandemic after 100 days. Despite these alarming findings, our 35 results show that social distancing could dramatically decrease the total number of infected 36 people (77% drop-off for the 45% distancing scenario when contrasted with no distancing), 37 flattening the growth of infection rate. Thus, we consider that this study provides useful 38 information that may help decision-makers to timely implement health policies to anticipate and 39 lessen the impact of the current pandemic in Mexico. 40 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.