Human metapneumovirus (HMPV) is one of the four major viral pathogens associated with acute respiratory tract infections (ARI) and creates a substantial burden of disease, particularly in young children (<5 years) and older individuals (≥65 years). The objective of this study was to determine the epidemiological behavior of HMPV in Mexico. This retrospective study was conducted over a nine-year period and used 7283 influenza-negative respiratory samples from hospitalized and deceased patients who presented Severe Acute Respiratory Infection (SARI). The samples were processed with the help of qualitative multiplex RT-PCR for simultaneous detection of 14 respiratory viruses (xTAG ® RVP FAST v2). 40.8% of the samples were positive for respiratory viruses, mainly rhinovirus/enterovirus (47.6%), respiratory syncytial virus (15.9%), HMPV (11.1%) and parainfluenza virus (8.9%). Other respiratory viruses and co-infections accounted for 16.5%. HMPV infects all age groups, but the most affected group was infants between 29 days and 9 years of age (65.6%) and adults who are 40 years and older (25.7%). HMPV circulates every year from November to April, and the highest circulation was observed in late winter. The results of this study aim to raise awareness among clinicians about the high epidemiological impact of HMPV in young children and older individuals in order to reduce the economic burden in terms of health care costs.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of SARS-CoV-2 lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of 'local' when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.