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I am a biological anthropologist with research interests in human ecology, demography and life history theory, and the ecology and evolutionary biology of infectious disease. A sampling of current projects includes: (1) human dimensions of primate retroviral transmission, (2) the impact of mobility and social contacts on the spillover and transmission of avian influenza, (3) the demography of residential mobility among Hadza hunter-gatherers, (4) fertility change, economic shocks, and reproductive decisions.
Climate change is expected to alter the geographical range, severity, and dynamics of infectious diseases. The existing body of research on pathogen dynamics and climate change largely focuses on environmentally transmitted, vector-borne, and zoonotic pathogens, the exposure to which is immediately tied to climate. However, climate change will have profound effects on human behavior, suggesting that there may be substantial downstream effects on directly transmitted infections, including sexually transmitted infections (STIs). This project will investigate study the regional effects on an epidemiological system, as mediated by adaptive (and other) human responses to changing environmental, economic, and social conditions, in the context of unexpected and potentially cascading consequences of global climate change.
The current COVID-19 pandemic involves both tremendous risk and tremendous uncertainty about that risk, at unprecedented scales and across demographic and cultural contexts. The situation offers a unique and time-sensitive opportunity to study the transmission and spread of behavioral responses, even as the transmission and spread of the SARS-CoV2 virus occurs in tandem. We are studying the coupled contagion dynamics of COVID-19 and related behavioral responses such as hand-washing, mask-wearing, and social distancing. We are gathering longitudinal data from a probability sample of Americans in three waves. Our surveys assess risk-reduction behaviors, compliance with public-health mandates, and hypothesized predictors of response including trust in various institutions, social capital, and sources of news and information. We are developing mathematical and simulation-based models that jointly track the dynamics of virus transmission and change in behavior, which we will parameterize with data collected in our survey. These models may provide insights for improving public-health interventions, motivating compliance, and stemming the spread of misinformation regarding the epidemic.
The idea of adaptation, in which an organism or population become better suited to their environment, is used in a variety of disciplines. Drawing originally from evolutionary biology, the study of adaptation has been a central theme in biological anthropology and human ecology. More recently, the study of adaptation specific to the context of human responses to the negative impacts of climate change has become an important topic and most current research in the social sciences on the adaptation falls into this category. While there are clearly commonalities to the different uses of the concept of adaptation, there are also substantial differences. We describe these differences and suggest that the study of climate-change adaptation could benefit from a re-integration with more broad-based biological and evolutionary conceptions of human adaptation. This integration would allow us to bring to bear the substantial theoretical tools of evolutionary biology to understanding system features that promote or impede adaptation. The evolutionary perspective on adaptation focuses overwhelmingly on diversity, since it is diversity that drives adaptive evolution. This suggests a focus for climate-change adaptation on the sources of innovation and the population structures that nurture innovations and allow them to spread. Just as adaptation thrives on diversity, the spread of innovations is facilitated by diversity in social structure. Truly innovative ideas are likely to arise on the periphery of cohesive social groups and spread inward. The evolutionary perspective also suggests that we pay careful attention to correlated traits which can distort adaptive trajectories. Finally, we suggest that climate-change evolution could benefit from a broader study on ongoing adaptations of local groups to their dynamic environments, a process we refer to as "autochthonous adaptation."This is a multi-stranded and ongoing project with a wide swath of collaborators at numerous institutions.
This is a book project exploring rationality, uncertainty, and the evolution of human behavior. It takes as its launching point a paradox which has only recently become apparent. By almost any measure, Homo sapiens is a spectacularly successful species. From humble origins approximately two million years ago, humans have grown to a population that exceeds seven billion and have colonized – and come to dominate – nearly every terrestrial biome. This phenomenal growth suggests that, on average, our ancestors made very good decisions. Yet a surging tide of work from psychology and economics makes the argument that the decision-making software that our brains run is profoundly flawed — that we are, in a word, irrational. How is it possible that a species apparently so defective in its ability to generate sound decisions can be so spectacularly successful?
Using relational data gathered from a variety of field contexts (Uganda, Bangladesh, Namibia), we are investigating the properties of sampled social networks, with an eye toward infectious disease transmission dynamics. Topics include: scale-up to landscape-level networks from egocentric samples, missing data models, and integrating spatial and relational dependencies.
The impact of unrecognized Ebola virus (EBOV) infection (asymptomatic and symptomatic) on transmission dynamics during the 2013–2016 West Africa Ebola outbreak is poorly understood. Individuals who had asymptomatic EBOV infection or unrecognized symptomatic Ebola virus disease (EVD) represent two groups who may have had different levels of exposure and rates of EBOV transmission. Increasingly protective behaviors to avoid contact with EVD cases may have resulted in lower levels of exposure, and these exposures may be associated with asymptomatic EBOV infection. On the other hand, individuals who had symptomatic EVD but were never diagnosed may be disproportionately important to transmission dynamics because some of these individuals were part of transmission chains leading to Ebola outbreaks in previously unaffected communities.In collaboration with researchers at UCSF, UCLA, Harvard, and Georgia State University, our research question focuses on understanding the drivers of EBOV transmission leading to epidemic decline. Competing hypotheses are centered around issues of preventive behaviors, health-seeking behaviors, saturation of transmission among contacts, and asymptomatic EBOV infection. Newly available, detailed serologic, social network, behavioral, ethnographic, and vaccination data from research collaborations in Liberia, Sierra Leone, and Democratic Republic of Congo will allow us to test competing hypotheses in the following aims: (1) Dynamical effects of unrecognized EBOV infection in social network structure, (2) Unrecognized symptomatic EVD cases, barriers to care, and preventive behaviors, and (3) Causes of asymptomatic EBOV infection. These findings have the potential to quantify what ended the Ebola pandemic and improve mathematical models. Mathematical modeling applications will improve forecasting during new outbreaks and inform ways to deliver vaccines to contacts, by ring vaccination or novel social network algorithms.
I am a biological anthropologist with primary research interests in evolutionary demography and life history theory. In addition these fundamental interests in the evolution of human life histories, I work at the intersection of disease ecology, the analysis of dynamical systems, and social network analysis. My work combines the formalisms of population biology, statistics, and social network analysis to address fundamental problems in biodemography, epidemiology, and human decision-making in variable environments.