Sine Grude, MPH ’26, has a background in antibiotic resistance research and is enrolled in the Quantitative Methods program at Harvard Chan School. “In times like these, public health is a critical field to study,” she says. “Quantitative methods really had a lot to offer in terms of diving deep into biostatistics and epidemiology that would set me up both to do research and hopefully to do some policy work in the future.” As a student from Norway, she shares that the global nature of the studen

Sen. Bill Cassidy (R-LA), a doctor, says he’s “very concerned” about the upcoming vote by the CDC’s panel of federal vaccine advisers on potentially changing the hepatitis B vaccine schedule for infants. “This is policy by people who don't understand the epidemiology of hepatitis B, or who have grown comfortable with the fact that we've been so successful with our recommendation that now the incidence of hepatitis B is so low, they feel like we can rest on our laurels,” Cassidy says. | CBS News

Manfaat makan buah terbukti baik untuk menurunkan risiko penyakit jantung dan stroke. Studi terbitan International Journal of Epidemiology menemukan bahwa mengonsumsi buah yang diimbangi sayuran dapat mengurangi risiko penyakit kardiovaskular, kanker, dan penyebab kematian lainnya. Buah kaya akan kandungan vitamin C, karotenoid, dan flavonoid. Ketiganya bersifat antioksidan yang bisa mencegah penumpukan dan pengerasan kolesterol dan lemak di pembuluh darah. Tak hanya itu, buah-buahan juga merupa

Sen. Bill Cassidy (R-LA), a doctor, says he’s “very concerned” about the upcoming vote by the CDC’s panel of federal vaccine advisers on potentially changing the hepatitis B vaccine schedule for infants. “This is policy by people who don't understand the epidemiology of hepatitis B, or who have grown comfortable with the fact that we've been so successful with our recommendation that now the incidence of hepatitis B is so low, they feel like we can rest on our laurels,” Cassidy says. | Face The

CODE Havic @medschoolbro = Mystery Discount Hypothesis Errors Power in 30s Type I (α) = false positive → rejecting H₀ when it’s actually true. Type II (β) = false negative → failing to reject H₀ when H₁ is real. Power = 1 − β → boosted by ↑ sample size, ↑ effect size, ↓ variance. p-value? Just tests how surprising your data is if H₀ were true — not clinical importance. #step1 #step2ck #biostats #epidemiology #usmle #drhavicandbrody | Medschoolbro