Molecular epidemiology in the HIV and SARS-CoV-2 pandemics

Abstract

Purpose of review: The aim of this review was to compare and contrast the application of molecular epidemiology approaches for the improved management and understanding of the HIV versus SARS-CoV-2 epidemics.

Recent findings: Molecular biology approaches, including PCR and whole genome sequencing (WGS), have become powerful tools for epidemiological investigation. PCR approaches form the basis for many high-sensitivity diagnostic tests and can supplement traditional contact tracing and surveillance strategies to define risk networks and transmission patterns. WGS approaches can further define the causative agents of disease, trace the origins of the pathogen, and clarify routes of transmission. When coupled with clinical datasets, such as electronic medical record data, these approaches can investigate co-correlates of disease and pathogenesis. In the ongoing HIV epidemic, these approaches have been effectively deployed to identify treatment gaps, transmission clusters and risk factors, though significant barriers to rapid or real-time implementation remain critical to overcome. Likewise, these approaches have been successful in addressing some questions of SARS-CoV-2 transmission and pathogenesis, but the nature and rapid spread of the virus have posed additional challenges.

Summary: Overall, molecular epidemiology approaches offer unique advantages and challenges that complement traditional epidemiological tools for the improved understanding and management of epidemics.

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FIGURE 1

Evolution of HIV diagnostic algorithms. (a) This cartoon depicts the abundance of HIV diagnostic substrates in the serum of a figurative patient during the first several weeks following infection. Although first-generation HIV tests that relied on detection of anti-HIV IgG antibodies in patient serum had a large ‘negative window’ between infection and detection, each successive generation of tests reduced this gap. Nucleic acid tests are primarily used for medical management of disease, but are used for diagnostic/screening purposes in some algorithms. (b) The current HIV testing algorithm based on guidelines from the Centers for Disease Control.

FIGURE 2

Phylodynamic methods for measuring epidemiological parameters. (a) A hypothetical, temporal phylodynamic tree with geographical information (indicated by colors) where the x-axis represents the time of sample isolation. The combination of genetic distance and spatiotemporal metadata allows for the visualization of outbreaks over time and for estimation of viral evolutionary rates, selective pressures, diversification patterns and migration events, among other parameters. (b) These same phylogenies can be used to estimate viral population sizes of the outbreak at different times. (c) The degree of genetic diversification over time, as shown by the number of lineages over time, in relation to population size changes and other inferred evolutionary dynamics, can help estimate epidemiological parameters like spread or transmission.

FIGURE 3

Interpretation of molecular clusters in an epidemiological outbreak. Molecular clusters identified by viral sequencing and phylogenetics represent a subset of individuals within a transmission cluster who are linked by direct or indirect transmission events. These individuals are a further subset of people in an overall risk network who may or may not have already been exposed to a disease. Determining how representative a molecular cluster is of a risk network depends on a combination of molecular surveillance, contact tracing, and community engagement.