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Caetano Souto Maior Profile picture
Caetano Souto Maior
@caesoma
Big Data coach, Machine Learning Canguru, and Math instructor @FAESmath. 🏴 \{Host e tweets em Português @ministerio_pod}
Jul 21, 2020 • 13 tweets • 4 min read
>>> Um fio sobre a chamada "imunidade de rebanho": O numero de novas infecções causadas por um indivíduo infectado (R) depende do número de pessoas suscetíveis na população (S). À medida que a população se infecta, recupera e fica imune esse número diminui naturalmente. 1/n Pra quem prefere uma versão menos telegráfica, tem um post em caesoma.github.io/posts/2020-07-…, e a gente discute isso também no podcast @ministerio_pod: ministeriodaciencia.github.io/posts/2020-07-…
Jul 13, 2020 • 6 tweets • 4 min read
@folha Prezada Folha,
um dos primeiros estudos a sugerir que o "limiar de imunidade de rebanho" é mais baixo que 60-70% tem coautores brasileiros, eu sou um deles. Podiam ter me entrevistado o conceito central dessa matéria 1/n @folha essa capa demonstra uma profunda ignorância da ciência pra essa "previsão". Pelo jeito @CanzianFernando não é repórter de ciência, e pra ter saído uma matéria de capa como essa com um apanhado de frases soltas de cientistas fico na dúvida se a Folha tem algum. 2/n
Jul 5, 2020 • 12 tweets • 7 min read
Some people started following me after we published how heterogeneity affects the so-called "herd immunity threshold" (HIT). This remains needlessly controversial, so here's a summary of the discussion (or lack thereof) so far. 1/N

The controversy is unwarranted because it is common knowledge in mathematical epidemiology that the threshold 1-1/R0 is a feature of the simplest model, which assumes every individual is equally connected to everyone else (i.e. "homogeneous mixing"). 2/N

Jun 14, 2020 • 18 tweets • 7 min read
What are the most pressing scientific issues and debates around the mathematical modeling of #Coronavirus/#COVID19, and are we actually solving them? (thread) 0/n
#SciTwitter #AcademicTwitter #AcademicChatter #MathematicalModeling

(for those who prefer blog post format instead, a slightly edited version of this thread can be found here: caesoma.github.io/posts/2020-06-… and medium.com/@caesoma/are-w…)
May 5, 2020 • 6 tweets • 2 min read
As a coauthor in this study I'm going to start by saying what its conclusions are NOT: (i) it does NOT conclude that lockdowns/social distancing are unnecessary; (ii) it does NOT say "herd immunity" is ~20% regardless. In fact that number is conditional on social distancing 1/6 The study does say that given observed trajectory, a SECOND wave may be considerably smaller IF there is a large variance in the distribution of both biological susceptibility AND exposure/social contact. There's a lot to unpack there 2/6