Working Group Leads:

Madhav Marathe (mmarathe@vbi.vt.edu)

Sergey Nuzhdin ( snuzhdin@usc.edu)

Alison Galvani (alison.galvani@gmail.com)

Goals and Objectives:

One of the fundamental challenges of multiscale modeling is to provide insights into collective processes and phenomena emerging in populations of individuals (or individual components) from their basic characteristics and interactions. Put more simply, it is the problem of scaling behavior from one to many, to identify relevant summary statistics and the order parameters that operate on higher scales. While our focus is mainly on human populations, the mathematical, statistical and computational issues that arise in predicting population-level properties (e.g., population dynamics, growth, extinction, migration etc) also arise in populations of molecules, bacteria, viruses, organelles, cells, and tissues.

• The primary goal of this WG is to survey the field of population modeling across multiple scales, introduce basic population concepts used in statistics, genetics and survival analysis, and to provide links to resources and available software. The WG invites discussion of examples, case studies and important papers in the field. It is meant to be and open and evolving forum.

Other goals to consider:

• To seek to map the circuits of the brain, measure the fluctuating patterns of electrical and chemical activity flowing within those circuits, and understand how their interplay creates our unique cognitive and behavioral capabilities; in varying social contexts, and comparing health and disease.

How brain works in the context of social interactions is a frontier theme in Social Science, Biology, Engineering, Economy, and Policy. For example, young men with the 10R allele of the dopamine transporter gene DAT1 are more likely to form social groups with antisocial peers and to engage in delinquent behavior, but only if they previously experienced social stress in their families.

The following scientific goals will have high priorities:

• Identify and provide experimental access to the different brain cell types to determine their roles in health and disease
• Generate circuit diagrams that vary in resolution from synapses to the whole brain
• Produce a dynamic picture of the functioning brain by developing and applying improved methods for large-scale monitoring of neural activity
• Link brain activity to behavior with precise interventional and pharmacological tools that change neural circuit dynamics
• Produce conceptual foundations for understanding the biological basis of mental processes through development of new theoretical and data analysis tools
• Develop innovative technologies to understand the human brain and treat its disorders; create and support integrated brain research networks
• Integrate new technological and conceptual approaches produced in the other goals to discover how dynamic patterns of neural activity are transformed into cognition, emotion, perception, and action in health and disease

While achieving these goals, we will: pursue human studies and non-human models in parallel, cross boundaries in interdisciplinary collaborations, integrate spatial and temporal scales using mathematical models, establish platforms for preserving and sharing data, validate and disseminate technology, consider ethical implications of neuroscience research.

MSM 2017 (10^th Anniversary) meeting Discussion Items

In this open discussion section our primary purpose is to have a broad  on the future of modeling for infectious disease epidemiology.

We welcome interested individuals to join us for a vibrant discussion!

In societies – both animal and human – many individuals interact with one another. These social interactions can affect group size and composition, and conversely, group size and composition can affect social interactions among individuals. Individuals within societies differ in important ways from one another; for example in their likelihood of associating with, or attacking other individuals; and if they are attacked themselves, they may differ in how they adjust their own behavior based on that experience.

All this suggests that differences among individuals in mean levels of behavior and behavioral plasticity must affect, and be affected by, higher-level properties of groups and societies. However, untangling the effects of individual differences in behavior and behavioral plasticity on the social and spatial patterns of groups and societies is refractory to current modeling and analytic tools. Feedbacks between behavior at the level of individuals and behavior at the level of groups and societies must be understood in order to predict the behaviors and their key health outcomes at each of these levels.

This working group in the past has been very broad and there has been much discussion on the specific topics to include human behavior that can impact public health in myriad ways. As we know, human behavior affects disease transmission, for instance by determining the numbers of contacts an individual has. It also impacts medical decision-making and thus the likelihood of successful implementation of public health policies, such as vaccination recommendations. Traditionally epidemiological modelers have assumed that optimal vaccination coverage will also achieve perfect adherence from the public. However, behavioral modeling has revealed that strategies that are optimal for the population are not necessarily optimal for the individual, depending on the utilities and externalities of specific policies. Consequently, modeling that considers both transmission dynamics and human behavior can facilitate the design of public health strategies that are both effective and cost-effective, as well as likely to achieve a high level of public adherence.

The goals specific to this theme are: (1) to improve the predictability of likelihood that alternative public health policies will be effective and cost-effective; (2) to further our understanding of the factors that motivate individuals in making medical decisions, taking into account the interplay among biological systems, individual decision-making and social and cultural influences; (3) to advance uncertainty quantification for the parameterization of population and multi-scale models from survey and epidemiological data;(4) to achieve and maintain a higher, uniform standard of patient care while reducing cost and patient discomfort.

The working group has a web portal through SimTK:

It holds discussions on the mailing list:

The group captured the variety of population modelers by providing examples published in several papers:

1) Population Modeling Working Group - Editor: Jacob Barhak, Population Modeling by Examples (WIP) - SpringSim 2015 , April 12 - 15, Alexandria, VA, USA . Paper available Here and Here. Presentation available Here

2) Population Modeling Working Group - Editor: Robert Smith?, Population Modeling by Examples II - SummerSim 2016 , July 24 - 27, Montreal, CA. Paper available Here and Here. Presentation available Here

3) Population Modeling Working Group - Editor: Jacob Barhak, Population Modeling by Examples III - SummerSim 2017 , July 9 - 12, Bellevue, WA, USA. Paper available Here and Here . Presentation available Here