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Computer Simulations can Predict HIV Spread

The researchers also plan to develop public health computational tools to help the agencies track the disease and allocate resources for targeted prevention campaigns

Researchers have found that computer simulations can accurately predict the transmission of Human Immunodeficiency Virus (HIV) across populations, aiding in preventing the disease.

The study, published in the journal Nature Microbiology, found that the simulations were consistent with actual DNA data obtained from a global public HIV database.

“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 lead author Thomas Leitner from the 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, the researcher said.

The changing “genetic signatures” of its code provide a path that can be followed in determining the origin and time frame of an infection, the study found.

HIV
For the study, the researchers used phylogenetic methods, examining evolutionary relationships in the virus’s genetic code to evaluate how HIV is transmitted. Pixabay

The rapid mutational capability of the virus is useful for the epidemiological sleuthing, but is also one of the features that makes it so difficult to tackle with a vaccine.

For the study, the researchers used phylogenetic methods, examining evolutionary relationships in the virus’s genetic code to evaluate how HIV is transmitted.

The research team 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.

Also Read: Every Three Minutes a Teenage Girl is Infected by HIV — UNICEF

“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.

The researchers also plan to develop public health computational tools to help the agencies track the disease and allocate resources for targeted prevention campaigns. (IANS)

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