Read on Twitter
The COVID-19 pandemic has shown power of open data and analytics in research, but these activities often aren& #39;t recognised in traditional academic metrics. New perspective piece with @rozeggo & @sbfnk: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000913.">https://journals.plos.org/plosbiolo... I& #39;d also like to highlight some examples... 1/
- Curation of open data sources, such as line list data by @MOUGK @davidmpigott et al ( https://github.com/beoutbreakprepared/nCoV2019),">https://github.com/beoutbrea... case tracking by @TexasDownUnder et al ( https://coronavirus.jhu.edu/map.html ),">https://coronavirus.jhu.edu/map.html&... testing from @OurWorldInData ( https://ourworldindata.org/coronavirus-testing)...">https://ourworldindata.org/coronavir... 2/
...government responses by @thomasnhale et al ( https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker),">https://www.bsg.ox.ac.uk/research/... vaccines by @LSHTM_Vaccines ( https://vac-lshtm.shinyapps.io/ncov_vaccine_landscape/),">https://vac-lshtm.shinyapps.io/ncov_vacc... behaviour by @Imperial_IGHI ( https://github.com/YouGov-Data/covid-19-tracker)">https://github.com/YouGov-Da... 3/
- Reproduction number estimation & forecasting, including dashboards by @bencowling88 et al ( https://covid19.sph.hku.hk/ ),">https://covid19.sph.hku.hk/">... @cmmid_lshtm ( http://epiforecasts.io/ ),">https://epiforecasts.io/">... @MRC_BSU ( https://www.mrc-bsu.cam.ac.uk/tackling-covid-19/nowcasting-and-forecasting-of-covid-19/),">https://www.mrc-bsu.cam.ac.uk/tackling-... @reichlab et al ( https://viz.covid19forecasthub.org/ )">https://viz.covid19forecasthub.org/">... 4/
- Key epidemiological parameters, including analysis of fatality risk by @C_Althaus ( https://github.com/calthaus/ncov-cfr),">https://github.com/calthaus/... overdispersion by @khgrantz et al ( https://hopkinsidd.github.io/nCoV-Sandbox/DispersionExploration.html),">https://hopkinsidd.github.io/nCoV-Sand... asymptomatic transmission by @dianacarbg et al ( https://www.medrxiv.org/content/10.1101/2020.04.25.20079103v3)">https://www.medrxiv.org/content/1... 5/
- Mobility patterns and predicting risk of international spread by @alexvespi et al ( https://datastudio.google.com/reporting/3ffd36c3-0272-4510-a140-39e288a9f15c)">https://datastudio.google.com/reporting... and @WorldPopProject ( https://www.worldpop.org/events/china )">https://www.worldpop.org/events/ch... 6/
- Genomic analysis of global spread, in Brazil by @nmrfaria et al ( https://virological.org/t/first-cases-of-coronavirus-disease-covid-19-in-brazil-south-america-2-genomes-3rd-march-2020/409),">https://virological.org/t/first-c... China by @arambaut et al ( https://virological.org/t/phylogenetic-analysis-of-23-ncov-2019-genomes-2020-01-23/335),">https://virological.org/t/phyloge... and globally by @nextstrain ( https://nextstrain.org/ncov/global?c=region)">https://nextstrain.org/ncov/glob... 7/
-Open models and scenario tools, such as EpiNow2 by @seabbs et al ( https://github.com/epiforecasts/EpiNow2),">https://github.com/epiforeca... OpenABM by @ChristoPhraser et al ( https://github.com/BDI-pathogens/OpenABM-Covid19),">https://github.com/BDI-patho... & tools to explore scenarios by @n_b_noll et al ( https://www.medrxiv.org/content/10.1101/2020.05.05.20091363v2)">https://www.medrxiv.org/content/1... and @_nickdavies et al ( https://cmmid.github.io/visualisations/covid-transmission-model-beta)">https://cmmid.github.io/visualisa... 8/
There are many, many other examples out there. COVID-19 has shown academics are highly motivated to produce work with immediate impact, even if it& #39;s beyond scope of traditional metrics. Now is the time to change the incentive structure to recognise these efforts. 9/9
