Covasim: An agent-based model of COVID-19 dynamics and interventions

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.

Covasim: An agent-based model of COVID-19 dynamics and interventions

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.

Implementation and applications of EMOD, an individual-based multi-disease modeling platform

Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development.

Polistes metricus queens exhibit personality variation and behavioral syndromes

Consistent differences in behavior between individuals, otherwise known as animal personalities, have become a staple in behavioral ecology due to their ability to explain a wide range of phenomena. Social organisms are especially serviceable to animal personality techniques because they can be used to explore behavioral variation at both the individual and group level. Despite the success of personality research in social organisms generally, and social Hymenoptera in particular, social wasps (Vespidae) have received little to no attention in the personality literature. In the present study, we test Polistes metricus (Vespidae; Polistinae) paper wasp queens for the presence of repeatable variation in, and correlations ("behavioral syndromes") between, several commonly used personality metrics: boldness, aggressiveness, exploration, and activity. Our results indicate that P. metricus queens exhibit personalities for all measured traits and correlations between different behavioral measures. Given that paper wasps have served as a model organism for a wide range of phenomena such as kin selection, dominance hierarchies, mate choice, facial recognition, social parasitism, and chemical recognition, we hope that our results will motivate researchers to explore whether, or to what degree, queen personality is important in their research programs.

Endocrine mediated phenotypic plasticity: condition-dependent effects of juvenile hormone on dominance and fertility of wasp queens

There has been increasing interest in the mechanisms that mediate behavioral and physiological plasticity across individuals with similar genotypes. Some of the most dramatic plasticity is found within and between social insect castes. For example, Polistes wasp queens can nest alone, dominate a group of cooperative queens, or act as worker-like subordinates who rarely reproduce. Previous work suggests that condition-dependent endocrine responses may play a role in plasticity between castes in the hymenoptera. Here, we test whether condition-dependent endocrine responses influence plasticity within castes in the wasp Polistes dominulus. We experimentally manipulate juvenile hormone (JH) titers in nest-founding queens and assess whether JH mediates variation in behavior and physiology. JH generally increased dominance and fertility of queens, but JH's effects were not uniform across individuals. JH had a stronger effect on the dominance and fertility of large individuals and individuals with facial patterns advertising high quality than on the dominance and fertility of small individuals and those advertising low quality. These results demonstrate that JH has condition-dependent effects. As such, they clarify how JH can mediate different behaviors in well nourished queens and poorly nourished workers. Many Polistes queens nest cooperatively with other queens, so condition-dependent hormonal responses provide a mechanism for queens to adaptively allocate energy based on their probability of successfully becoming the dominant queen. Research on the endocrine basis of plasticity often focuses on variation in endocrine titers alone. However, differential endocrine responses are likely to be a widespread mechanism mediating behavioral and physiological plasticity.