GeneBites

During the COVID-19 pandemic, social distancing and mobility patterns played crucial roles in viral transmission. A recent study leverages genomic sequencing, epidemiological, and mobility data to reveal how connectivity influenced the spread of the virus.

During the height of the COVID-19 pandemic, social distancing transformed into a series of personal choices and adaptations. From choosing whether to work from home to deciding how to navigate grocery store aisles and Thanksgiving dinners, everyone faced their own set of decisions. Each of these choices, however small, played a crucial role in shaping the response to the virus. Maybe you formed a “bubble” – a small community – with family members or close friends so you could spend time with those you cared about. Maybe you worked from home for several months while the vaccine was created. Maybe you refrained from going to spaces with large groups of people. Did this social distancing make a difference in how the virus spread? If so, how much?

Genetic data can help to answer these questions. In addition to being the blueprint for living organisms, genetic data can be used to track organisms like biomolecular breadcrumbs. A  recent study from Cell used genomic sequencing, epidemiological data, and mobility data to better understand how connectivity impacted viral transmission. Whole genome and real-time sequencing technologies have shown increasing utility in recent years as a method to understand viral and bacterial evolution. For example, sequencing methods have been used to elucidate key information about both global and local transmission patterns of TB and HIV. Genomic sequencing has largely been used to understand viral evolution and track the emergence of novel variants. The past few years have seen a global increase in the use of genomic sequencing and a rapid decrease in its cost, particularly since the COVID-19 pandemic.

Choices that may seem inconsequential, like riding in a public train or getting on a plane, can drastically impact viral transmission. Matteson and colleagues used mobility data to characterize the relationship between transmission and mobility. In particular, transmission between San Diego and nearby regions, such as Los Angeles and Baja California, closely mirrored both mobility patterns and infection rates. Movement and pre-symptomatic or asymptomatic infections are therefore key drivers of transmission, meaning that infectious disease interventions should consider the nuances of human mobility and infection data. 

Next, researchers looked at mobility patterns over the course of the pandemic to understand the impact of social distancing measures over time. Earlier in the pandemic, people traveling into San Diego predominantly came from neighboring areas. Over time, as restrictions decreased, there was an influx of people from areas that were further away. Of course, people also strayed away from social distancing, as they grew tired of staying away from the people and activities they loved. Researchers found a moderate correlation between the frequency of travel at a particular location and the evolutionary resemblance of the virus, suggesting that increased connectivity from distant areas contributed to epidemics. These findings show that it is not enough simply to have social distancing measures. As individuals get exhausted with social distancing, mobility patterns change and so does viral transmission. Understanding how this adherence changes over time is crucial to designing more effective travel restrictions. In future pre-pandemic periods, ensuring continued vigilance through genomic surveillance programs such as the Traveler-based Genomic Surveillance for Early Detection of New SARS-CoV-2 Variants at the Centers for Disease Control and Prevention will allow us to have the data to most effectively combat the next pandemic.

Another question that significantly impacts international policy during pandemics is that of border closings. Studies on international border closings in relation to pandemics are limited – one study looking at the 1918 epidemic found that border closings did marginally reduce transmission. Many countries implemented some form of border control for at least some portion of the pandemic. Here, researchers honed in on the effectiveness of the US-Mexico border closure, finding that it only marginally reduced import risk into San Diego, mostly because most travelers into San Diego come from locations other than Mexico. The border closure’s limited effectiveness compared to broader mobility reductions, such as stay-at-home orders, suggests that targeted travel restrictions alone are insufficient to curb transmission. Public health strategies that combine border closures with other social distancing measures are therefore necessary to reduce transmission risks. 

The next pandemic is inevitable. The question is, how are we going to deal with it differently? Mattheson and colleagues provide a strong case for using genomic sequencing data to better understand the impact of public health measures on viral transmission. Hopefully policymakers and scientists will take advantage of the data, so that our pandemic “bubbles” stay in the past. This valuable data may just be what saves us in the future.

Edited by Jameson Blount & Jayati Sharma