Gratuitous headshotI am an Instructor in the Department of Epidemiology and Population Health at Stanford University School of Medicine. I also work with Stanford’s Center for Population Health Sciences and am a Fellow at the Harvard FXB Center for Health and Human Rights. I received my doctorate in Quantitative Methods from the Department of Social and Behavioral Sciences at Harvard TH Chan School of Public Health. Before that, I received my MPH at New York University, my BA in Sociology from San Diego State University, and I was a 2016 fellow at University of Chicago’s Data Science for Social Good summer fellowship.

Most of my research lies at the intersection of computational social science and social epidemiology. Methodologically, my work revolves around combining disparate data sources in epidemiologically meaningful ways. More concretely, I work with individual-level, non-health data (e.g., GPS, accelerometer, and other sensor data from smartphones), traditional health data (e.g., health systems or death certificate data), and third-party data (e.g., cellphone providers or ad-tech data). To do this, I use a variety of methods such as joint Bayesian spatial models, traditional epidemiologic models, dynamical models, and demographic analysis.

Substantively, I am interested in socioeconomic and racial/ethnic inequities in health. A few current projects include (1) my K99/R00-funded work focused on reducing racial/ethnic inequities in the treatment of opioid use disorder; (2) my work with Stanford and Harvard FXB on quantifying the impacts of wildfires, natural disasters, climate change, and power outages on medically-vulnerable populations to improve resource allocation and disaster response; and (3) my work with the COVID-19 Mobility Data Network on leveraging third-party data to inform an equitable public health response to the COVID-19 pandemic, especially as it relates to non-pharmaceutical interventions and low-wage essential workers.

A recent copy of my CV is available here, my Stanford Profile is here, and my ORCiD iD profile is here.

Publications

  • Kiang MV, Irizarry RA, Buckee CO, & Balsari S, Every body counts: Measuring mortality from the COVID-19 pandemic, Annals of Internal Medicine (September 2020), doi: 10.7326/M20-3100. [Open Access] [Accompanying Editorial]
  • Chin T†, Kahn R†, Li R, Chen JT, Krieger N, Buckee CO, Balsari S‡ & Kiang MV‡, US county-level level variation in intersecting individual, household, and community characteristics relevant to COVID-19 and planning an equitable response: a cross-sectional, BMJ Open (September 2020), doi: 10.1136/bmjopen-2020-039886. [†First authors contributed equally.] [‡Senior authors contributed equally.] [Pre-print version] [Code] [Shiny app]
  • Kishore N, Kiang MV, Engø-Monsen K, Vembar N, Balsari S, & Buckee CO, Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis, The Lancet Digital Health (September 2020), doi: 10.1016/S2589-7500(20)30193-X [Pre-print version]
  • Kiang MV†, Santillana M†, Chen JT, Onnela J-P, Krieger N, Engø-Monsen K, Ekapirat N, Areechokchai D, Prempree P, Maude RJ‡, & Buckee CO‡, Incorporating human mobility data improves forecasts of Dengue fever in Thailand, medRxiv (July 2020), doi: 10.1101/2020.07.22.20157966. [Pre-print — not peer-reviewed.] [Open Access] [†First authors contributed equally.] [‡Senior authors contributed equally.]
  • Elser H†, Kiang MV†, John EM, Simard JF, Bondy M, Nelson LM, Chen W, Linos E, Implications of the COVID-19 San Francisco Bay Area Shelter-in-Place Announcement: A cross-sectional social media survey, medRxiv (July 2020)*, doi: 10.1101/2020.06.29.20143156. [Pre-print — not peer-reviewed.] [Open Access] [†First authors contributed equally.]
  • Kiang MV & Tsai AC, Statements issued by academic medical institutions after George Floyd’s killing by police and subsequent unrest in the United States: cross-sectional study, medRxiv (July 2020)*, doi: 10.1101/2020.06.22.20137844. [Pre-print — not peer-reviewed.] [Open Access] [Code]
  • Kiang MV, Humphreys K, Cullen MR, Basu S. Opioid prescribing patterns among medical providers in the United States, 2003–17: retrospective, observational study, BMJ (January 2020), doi: 10.1136/bmj.l6968 [Open Access] [PDF] [Code] [Shiny Apps] [BMJ Press Release]
  • Tsai AC, Kiang MV, Barnett ML, Beletsky L, Keyes KM, McGinty EE, Smith LR, Strathdee S, Wakeman SE, & Venkataramani AS, Stigma as a fundamental hindrance to the US opioid overdose crisis response, PLOS Medicine (November 2019), doi: 10.1371/journal.pmed.1002969 [Open Access] [PDF]
  • Kiang MV, Krieger N, Buckee CO, Onnela JP, & Chen JT. Decomposition of the US black/white inequality in premature mortality, 2010–2015: an observational study. BMJ Open (November 2019), doi: 10.1136/bmjopen-2019-029373 [Open Access] [PDF] [Code]
  • Vable AM, Kiang MV, Glymour MM, Rigdon J, Drabo EF, & Basu S, Performance of matching methods to unmatched ordinary least squares regression under constant effects, American Journal of Epidemiology (April 2019), doi: 10.1093/aje/kwz093
  • Kiang MV, Basu S, Chen JT, and Alexander MJ. Assessment of changes in the geographical distribution of opioid-related mortality across the United States by opioid type, 1999- 2016. JAMA Network Open (Februrary 2019). doi: 10.1001/jamanetworkopen.2019.0040 [Open Access] [PDF] [Code] [Shiny App] [Official Press Release] [CNN] [NBC] [Altmetric]
  • Gemmill A, Kiang MV, and Alexander MJ. Trends in pregnancy-associated mortality involving opioids in the United States, 2007-2016. American Journal of Obstetrics and Gynecology (January 2019). doi: 10.1016/j.ajog.2018.09.028 [Code] [Press Release]

Conference Materials

  • Kiang MV & Alexander MJ, Decomposition of the US Black/White inequality in life expectancy: Quantifying the impact of deaths of despair. Society for Epidemiologic Research Annual Meeting 2019: Minneapolis, MN (June 2019) [Slides]

Teaching

  • Instructor, Big Data and Infectious Disease Epidemiology (September 2019), People’s Republic of Bangladesh Directorate General of Health Services
  • Course developer (x2), Using Python for Research via HarvardX V1 (November 2016) and V2 (January 2018), HSPH, Professor Jukka-Pekka Onnela
  • Instructor, Intro to Causal Inference for Data Science Workshop (March 2017), Instituto Tecnológico Autónomo de México
  • Teaching assistant (x2), Dynamics of Infectious Disease (Spring 2017 and Spring 2018), HSPH, Professor Caroline Buckee
  • Teaching assistant, Society and Health (Fall 2013), HSPH, Professor Ichiro Kawachi
  • Teaching assistant, Biostatistics II (Spring 2010), NYU, Professor Ying Lu
  • Teaching assistant, Statistics I (Fall 2009), NYU, Professor Robert Norman

Social

*Not peer-reviewed.
†First authors contributed equally.
‡Senior authors contributed equally.
§Best student poster award.