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Qixin He
Assistant Professor, Department of Biology, Purdue University.

I'm an evolutionary biologist, passionate about building theoretical models and applying them empirically to understand the evolution and structuring of population diversities through time and space.

 

Before joining Purdue, I did my postdoc research with Prof. Mercedes Pascual at the University of Chicago. I obtained my Ph.D. with Prof. L. Lacey Knowles at the University of Michigan, Ann Arbor.

 

Feel free to contact me if you are interested in joining my group.

OUR LATEST RESEARCH

An antigenic diversification threshold for falciparum malaria transmission at high endemicity

The vast diversity of the falciparum malaria parasite, as seen by the immune system of hosts in high transmission regions, underlies both high prevalence of asymptomatic infections and partial protection to re-infection despite previous exposure. This large antigenic diversity of the parasite challenges control and elimination efforts. We propose a threshold quantity for antigenic innovation, we call Rdiv, measuring the potential of transmission to accumulate new antigenic variants over time. When Rdiv is pushed below one by reduced transmission intensity, new genes encoding this variation can no longer accumulate, resulting in a lower number of strains and facilitating further intervention. This innovation number can be applied to other infectious diseases with fast turnover of antigens, where large standing diversity similarly opposes successful intervention.

Check it out at PLoS Computational Biology.

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Collaboration: Quantifying asymptomatic infection and transmission of COVID-19

As health officials face another wave of COVID-19, they require estimates of the proportion of infected cases that develop symptoms, and the extent to which symptomatic and asymptomatic cases contribute to community transmission. Recent asymptomatic testing guidelines are ambiguous. Using an epidemiological model that includes testing capacity, we show that many infections are nonsymptomatic but contribute substantially to community transmission in the aggregate. Their individual transmissibility remains uncertain. If they transmit as well as symptomatic infections, the epidemic may spread at faster rates than current models often assume. If they do not, then each symptomatic case generates, on average, a higher number of secondary infections than typically assumed. Regardless, controlling transmission requires community-wide interventions informed by extensive, well-documented asymptomatic testing.

Check it out at PNAS.