Grace Chan
Secondary Faculty

Grace Chan

Associate Professor in the Department of Epidemiology

Epidemiology

Other Positions

Associate Professor of Pediatrics

Pediatrics-Boston Children's Hospital

Harvard Medical School


Overview

Dr. Chan’s work focuses on global perinatal and pediatric epidemiology. She leads the HaSET research program for maternal and child health. Together with colleagues, she has established a field site in rural Ethiopia with a cohort of women and their children.

Ongoing research projects and interests focus on:
- Surveillance of maternal and child morbidity and mortality to improve disease estimates
- Risk prediction and causal modeling for pregnancy complications and adverse birth outcomes
- Development and testing of newborn care packages to improve survival of preterm and low-birth weight babies
- Etiologies of neonatal sepsis and antimicrobial resistance
- Effects of climate change and air pollution on maternal and child health outcomes

Dr. Chan also serves as an attending physician in the Division of Medical Critical Care at Boston Children’s Hospital. She is also an honorary faculty member at St Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia. She has mentored students and fellows as an academic advisor and dissertation committee member.

BA
Harvard College

MPH
Johns Hopkins School of Public Health

MD
Harvard Medical School

PhD
Johns Hopkins School of Public Health

Residency
Boston Children's Hospital

Post-doc
International Centre of Diarrheal Disease Research, Bangladesh


Bibliography

Vulnerable newborn types: analysis of subnational, population-based birth cohorts for 541?285 live births in 23 countries, 2000-2021.

Erchick DJ, Hazel EA, Katz J, Lee ACC, Diaz M, Wu LSF, Yoshida S, Bahl R, Grandi C, Labrique AB, Rashid M, Ahmed S, Roy AD, Haque R, Shaikh S, Baqui AH, Saha SK, Khanam R, Rahman S, Shapiro R, Zash R, Silveira MF, Buffarini R, Kolsteren P, Lachat C, Huybregts L, Roberfroid D, Zeng L, Zhu Z, He J, Qiu X, Gebreyesus SH, Tesfamariam K, Bekele D, Chan G, Baye E, Workneh F, Asante KP, Kaali EB, Adu-Afarwuah S, Dewey KG, Gyaase S, Wylie BJ, Kirkwood BR, Manu A, Thulasiraj RD, Tielsch J, Chowdhury R, Taneja S, Babu GR, Shriyan P, Ashorn P, Maleta K, Ashorn U, Mangani C, Acevedo-Gallegos S, Rodriguez-Sibaja MJ, Khatry SK, LeClerq SC, Mullany LC, Jehan F, Ilyas M, Rogerson SJ, Unger HW, Ghosh R, Musange S, Ramokolo V, Zembe-Mkabile W, Lazzerini M, Rishard M, Wang D, Fawzi WW, Minja DTR, Schmiegelow C, Masanja H, Smith E, Lusingu JPA, Msemo OA, Kabole FM, Slim SN, Keentupthai P, Mongkolchati A, Kajubi R, Kakuru A, Waiswa P, Walker D, Hamer DH, Semrau KEA, Chaponda EB, Chico RM, Banda B, Musokotwane K, Manasyan A, Pry JM, Chasekwa B, Humphrey J, Black RE.

BJOG. 2023 May 08. PMID: 37156239


News

Predicting prenatal care rates in rural Ethiopia

Through predictive models, it may be possible to identify pregnant women in low-resource settings who are at high risk of failing to attend antenatal care, in order to develop interventions to encourage their attendance, according to a new…