HIV Transmission Dynamics in Greater Mexico City are Shaped by Dense Spatial Mixing
Escalera, M.; Lopez Ortiz, E.; Garcia Morales, C.; Cruz-Bonilla, E.; Guerrero Flores, S.; Weaver, S.; Matias Florentino, M.; Tapia Trejo, D.; Davila Conn, V.; Roberto Cardenas Porras, ; Eduardo Zarza Sanchez, ; Silvia del Arenal Sanchez, ; Jorge A Gutierrez Soto, ; Karina Nava Memije, ; Jessica Monreal Flores, ; Alejandro Guzman, ; Rebecca E Garcia Mendiola, ; Patricia Iracheta, ; Veronica Ruiz Gonzalez, ; Veronica Quiroz Morales, ; Israel Macias Gonzalez, ; Manuel A Becerril Rodriguez, ; Raul A Cruz Flores, ; Andrea Gonzalez Rodriguez, ; Dulce M Lopez Sanchez, ; Miroslava Card
Show abstract
Understanding HIV transmission in densely populated urban settings is essential to mitigate ongoing epidemic spread. We present a comprehensive analysis of recent HIV transmission dynamics in Greater Mexico City, one of the worlds largest metropolitan areas comprising Mexico City and neighbouring municipalities of the State of Mexico. Drawing from over 7,000 complete pol gene sequences representing around 50% of new cases reported between 2019 and 2022 within the study region, we reconstructed the transmission network based on pairwise genetic distance. We identified ten large transmission clusters exhibiting sustained growth up to the most recent sampling period. We further analysed paired genetic and high- resolution human mobility data using an integrated phylogeographic approach. We observed a heterogeneous pattern of viral spread across the region, supported by an extensive mixing at a wider geographic scale. Across Greater Mexico City, displaying a high population density, HIV transmission is minimally spatially constrained, a pattern likely fuelled by intense human mobility. Thus, population movement weakens isolation by distance in large urban areas even for a chronic infection that is sexually and vertically transmitted. We demonstrate the value of integrating large-scale genetic, epidemiological, and mobility data to resolve contemporary HIV transmission dynamics in densely populated urban settings
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Using big sequencing data to identify chronic SARS-Coronavirus-2 infections 96%
- In-depth single-cell analysis of translation-competent HIV-1 reservoirs identifies cellular sources of plasma viremia 95%
- Predicting the evolution of Lassa Virus endemic area and population at risk over the next decades 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.