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Thanks to @crimmin @scurran_uw & @PopAssocAmerica for hosting an enlightening #Demography & #COVID19 webinar today. I wanted to follow-up with some links to people & resources, some of which I didn't have time to call out in the talk...
First @ikashnitsky & @jm_aburto used beautiful #dataviz to map age structure & #COVID19 risk regionally in Europe: https://twitter.com/ikashnitsky/status/1247795463169789952?s=20
@FCBillari & the strength of family ties & #COVID19 https://twitter.com/fcbillari/status/1247492639433412608
. @usama_bilal on age-adjustment & deaths among Latinx community in NYC: https://twitter.com/usama_bilal/status/1258062662245609473?s=20
https://globalhealth5050.org/covid19/ as a great resource for sex and gender related COVID data
New pre-print by @v_dilego & colleagues @WiCVienna on variation in sex differences in #COVID19 confirmed infections by age: https://twitter.com/v_dilego/status/1265378786062761985?s=20
. @d_spiegel on quantifying the risk associated with #COVID19: https://medium.com/wintoncentre/what-are-the-risks-of-covid-and-what-is-meant-by-the-risks-of-covid-c828695aea69
. @jburnmurdoch 's amazing dataviz on excess mortality in @FinancialTimes https://twitter.com/jburnmurdoch/status/1263035490200158209?s=20
& @VictimOfMaths work on breaking excess mortality down by age in the UK: https://twitter.com/VictimOfMaths/status/1265677593233240064?s=20
New pre-print on challenges of measuring excess mortality in LMICS: @helleringer143 @BrunoMasquelier @tomtom_m
@visseho09 @AneFisker @dennisfeehan @LeontineAlkema @blqueiroz @IanTimaeus @aashishg_ @Patrick_Gerland @DanzhenYou @jennylind2000 https://twitter.com/helleringer143/status/1262768505528729602?s=20
@visseho09 @AneFisker @dennisfeehan @LeontineAlkema @blqueiroz @IanTimaeus @aashishg_ @Patrick_Gerland @DanzhenYou @jennylind2000 https://twitter.com/helleringer143/status/1262768505528729602?s=20
& @c_dudel @timriffe1 @Acosta_Kike_ @AlysonVanRaalte
provide a nice tool for decomposing the role of age structure for cross-country differences in the overall case-fatality rates (CFR) https://twitter.com/c_dudel/status/1244916481747570689?s=20
provide a nice tool for decomposing the role of age structure for cross-country differences in the overall case-fatality rates (CFR) https://twitter.com/c_dudel/status/1244916481747570689?s=20
. @timriffe1 @jm_aburto & colleagues doing a huge service & curating and harmonizing age disaggregated COVID case & death data https://twitter.com/timriffe1/status/1248754263649660928?s=20
. @InedFr providing a great resource of COVID data by age & sex: https://dc-covid.site.ined.fr/en/
& props to the Human Mortality Database for recently releasing a new database of weekly all-cause mortality: https://www.mortality.org/
A shout out to my new colleague @OxfordDemSci @jm_aburto for bringing attention to the special challenges COVID brings to Latin America: https://twitter.com/jm_aburto/status/1261659205435564034?s=20
I didn't have a chance to mention the great work going on in #digitaldemography and #COVID19, some by my colleagues @ridhikash07 & @rotondivale: https://twitter.com/ridhikash07/status/1259112864045989888?s=20
. @ezagheni provides a nice list of additional contributions from digital and computational demography: https://twitter.com/ezagheni/status/1263391496092504064?s=20
Thanks to @PopulationEU for collecting up to date COVID-related demography work: https://population-europe.eu/news/demography-coronavirus
Long thread & I've left out a lot; suffice to say I am in awe of all of you & the richness of #demography work coming out on #COVID19. Keep it up, we need you!! @PopAssocAmerica #poptwitter
Thanks to @thehauer for his spot on demography memes: https://twitter.com/thehauer/status/1239267655321882626?s=20
Finally, thanks to @monjalexander for helping us to fully embrace our inner Demographer & never stop doing the most Demography thing ever!! https://twitter.com/monjalexander/status/1239191247597731842?l @PopAssocAmerica #poptwitter
