2  Introduction

In May 2022, queer and trans New Yorkers faced a public health crisis that demanded a new kind of response. Cases of mpox were rising quickly, and early warnings from the community went unanswered. We organized because the people most affected were the first to see what was happening—and because we could not wait for the usual institutions to act.

Out of this urgency, RESPND-MI (Rapid Epidemiologic Study of Sexual Networks, Demographics, and Mpox Infection) was born. The collective convened researchers, community organizers, designers, and technologists to create a study that could move at the speed of an outbreak while staying accountable to the community it served. The result was the MPX NYC study—an anonymous, web-based survey and network-mapping project that documented how queer and trans people interacted across the city: where they lived, met, and mixed during the outbreak.

2.1 What this book presents

This book shares what we learned from that effort. It combines findings, methods, and organizing principles into a single resource for anyone building community-led health infrastructure.

At its core are three intertwined strands:

  1. Findings – what the MPX NYC data reveal about how people and places were connected during the 2022 outbreak.

  2. Science – the frameworks we developed for understanding causal processes in networks, detailed in the SSNAC (Social and Spatial Network Analysis with Causal Interpretation) toolkits.

  3. Organizing – the participatory model that powered RESPND-MI, from the LGBTQ+ Community Forum to bilingual communications and distributed leadership.

At a glance

  • Study: MPX NYC — a rapid, community-led epidemiologic study of mpox, networks, and connection.

  • Framework: SSNAC — new tools for reasoning about causality in connected populations.

  • Practice: RESPND-MI — a model for building power and trust in the middle of crisis.

2.2 The shape of the study

The MPX NYC survey asked participants about health, networks, and places—linking each location to its corresponding U.S. census tract to preserve anonymity while enabling spatial analysis. These data allowed us to explore how patterns of movement, mixing, and gathering shaped exposure risk and community reach.

The results chapters describe what we found:

  • People (Chapter 6) — who joined the study.

  • Gatherings (Chapter 7) — where people met for sex or social connection.

  • Movement (Chapter 8) — how participants moved across the city.

  • Mixing (Chapter 9) — how groups of people interacted in space.

  • Outbreaks (Chapter 10) — how to vaccinate for impact.

2.3 From findings to theory

To interpret these data, we developed a new framework for network-based causal inference. Classical epidemiologic models assume independent individuals; our data showed instead that outcomes and exposures were structured by overlapping social and spatial networks. The SSNAC framework introduces definitions, graphical models, and analytic tools for reasoning about causality when interference is everywhere. It extends the formal foundations of causal inference—NPSEM-IE, FFRCISTG, and SWIGs—into the context of connected populations.

See SSNAC I: Context (Appendix A), SSNAC II: Description (Appendix B) and SSNAC III: Causality (Appendix C) for technical exposition, and MPX NYC: Measurement (Appendix F) for how we linked these concepts to data.

2.4 From theory to practice

The study was not only a scientific project; it was also a collective act of organizing. Through the RESPND-MI LGBTQ+ Community Forum, dozens of community leaders and health professionals met weekly to make shared decisions about study design, translation, and communication. This structure grounded the research in accountability and trust—what we call community power in practice.

Later chapters document this model:

  • Organizing — how distributed leadership and participatory decision-making shaped the work (Appendix D).
  • Marketing and Communication — how we built a bilingual, sex-positive outreach campaign (Appendix E).

2.5 How to read this book

Readers can move through the chapters linearly or skip between domains:

  • Methods describe data, measures, and analytic design.

  • Results show what we found and how it matters.

  • SSNAC appendices define the theoretical core.

  • Organizing and Communication appendices describe how we worked.

Each section is meant to stand alone but also to build a cumulative picture of what a People’s Department of Health could look like—one that is rigorous, rapid, and rooted in community connection.

Tip

If you are building your own project:
Start with the Organizing chapter for structure, the Mapper sections in Methods: Data for tooling, and the SSNAC appendices for causal logic.