Computer simulations can accurately predict the transmission of HIV across populations, which could aid in preventing the deadly infection, scientists have found.
Computer simulations can accurately predict the transmission of HIV across populations, which could aid in preventing the deadly infection, scientists have found. The simulations were consistent with actual DNA data obtained from a global public HIV database, according to the study published in the journal Nature Microbiology.
“We looked for special genetic patterns that we had seen in the simulations, and we can confirm that these patterns also hold for real data covering the entire epidemic,” said Thomas Leitner, a computational biologist at Los Alamos National Laboratory in the US. HIV is particularly interesting to study in this manner as the virus mutates rapidly and constantly within each infected individual, Leitner said.
The changing “genetic signatures” of its code provide a path that researchers can follow in determining the origin and time frame of an infection. The computer simulations are now proven to be successful in tracking and predicting the virus’s movements through populations, researchers said.
The rapid mutational capability of the virus is one of the features that makes it so difficult to tackle with a vaccine. Leitner and Ethan Romero-Severson, a Los Alamos theoretical biologist, used phylogenetic methods, examining evolutionary relationships in the virus’s genetic code to evaluate how HIV is transmitted.
They found that certain phylogenetic “family tree” patterns correlated to the DNA data from 955 pairs of people, in which the transmitter and recipient of the virus were known. “These HIV transmissions had known linkage based on epidemiological information such as partner studies, mother-to-child transmission, pairs identified by contact tracing, and criminal cases,” the researchers said.