World Health Organization|Ca' Foscari University of Venice|World Health Organization|World Health Organization|Centers for Disease Control and Prevention|Enrico Fermi Center for Study and Research|Institut Pierre Louis d‘Épidémiologie et de Santé Publique|Bambino Gesù Children's Hospital|University of Greenwich|City, University of London|Turing Institute|British Library|The Alan Turing Institute|Institute for Scientific Interchange|Ca' Foscari University of Venice|Institute for Complex Systems|World Health Organization|World Health Organization|University of London|London School of Hygiene & Tropical Medicine|Africa Centres for Disease Control and Prevention|Chinese Center For Disease Control and Prevention|Sapienza University of Rome
covid19 information epidemic infodemic demonstrates unlimited access information may confuse influence behaviors health emergency however study infodemics relatively new little known relationship epidemics management discuss unresolved issues propose research directions enhance preparedness future health crises covid19 information epidemic infodemic demonstrates unlimited access information may confuse influence behaviors health emergency however study infodemics relatively new little known relationship epidemics management discuss unresolved issues propose research directions enhance preparedness future health crises coronavirus disease 2019 covid19 pandemic shown critical role information diffusion health emergencies crisis management complexities science knowledge scientific method difficult communicate broad audienceespecially light heterogeneity science literacy ruths 2019ruths misinformation machinescience 2019 363 348google scholar context tends yield extreme oversimplifications eg zero riskcritical risk may polarize narratives time ongoing revisions evidence overabundant changing information landscape may induce confusion policymakers civil society gallotti et al 2020gallotti r valle f castaldo n sacco p de domenico assessing risks infodemics response covid19 epidemicsnat hum behav 2020 4 12851293google scholar tangcharoensathien et al 2020tangcharoensathien v calleja n nguyen purnat dagostino garciasaiso landry rashidian hamilton c abdallah et alframework managing covid19 infodemic methods results online crowdsourced technical consultationj med internet res 2020 22 e19659google scholar example problem vaccine hesitancy seems related eroded trust institutions fueled misinformation spreading process called information epidemic infodemic clear example virtually unlimited online access information may influence events unfolding physical world grasp infodemic happens still shallow evolving possible reason mist around term infodemic may reside nature intuitive umbrella term however includes many ramifications ranging communication epidemiology links several open scientific debates misinformation spreading effects society simon camargo 2021simon fm camargo cq autopsy metaphor origins use blind spots infodemicnew media society 2021 122httpsdoiorg10117714614448211031908google scholar specific term infodemic intended mean epidemic information introduced rothkopf 2003rothkopf dj 2003 buzz bites back new york times may 11 2003 1httpswwwwashingtonpostcomarchiveopinions20030511whenthebuzzbitesbackbc8cd84fcab64648bf580277261af6cdgoogle scholar define amplification effect news severe acute respiratory syndrome sars due information technologies recent definition infodemic emphasized element misinformation spreading rapidly social media platforms outlets zarocostas 2020zarocostas j fight infodemiclancet 2020 395 676google scholar however misinformation fully capture complexity phenomenon seems strongly related evolving business model information dissemination currently dominated social media cinelli et al 2020cinelli quattrociocchi w galeazzi valensise cm brugnoli e schmidt al zola p zollo f scala covid19 social media infodemicsci rep 2020 10 16598google scholar light infodemic redefined overabundance informationsome accurate notthat occurs epidemic tangcharoensathien et al 2020tangcharoensathien v calleja n nguyen purnat dagostino garciasaiso landry rashidian hamilton c abdallah et alframework managing covid19 infodemic methods results online crowdsourced technical consultationj med internet res 2020 22 e19659google scholar uptake infodemic definition directly tackle concept misinformation seems point toward bigger problem true vs false dichotomy naturally limited fact concept truth may differ across social groups reason aspects related human behavior particularly tendency individuals select information confirming beliefs ignore dissenting information del vicario et al 2016del vicario bessi zollo f petroni f scala caldarelli g stanley quattrociocchi w spreading misinformation onlineproc natl acad sci usa 2016 113 554559google scholar taken account better understand infodemic process indeed reasonable hypothesize behaviors important infodemic development much impact epidemic sphere altering chains disease transmission eg using masks teleworking quarantining reduce infection spread however remains fully established extent infodemic affects behaviors turn may relevant dynamics pandemics apparent analogies epidemics infodemics led suggestion scientists policymakers investigate model monitor two phenomena similarly scales et al 2021scales gorman j jamieson kh covid19 infodemicapplying epidemiologic model counter misinformationn engl j med 2021 385 678681google scholar argue infodemic although intertwined epidemic distinct phenomenon resulting many interacting overlapping processes production consumption amplification potentially harmful information online thus processes analogies differences interplay must considered develop practical guidelines managing preventing future epidemics paper aims spark discussions collaboration enhance preparedness future health crises improve ability anticipate economic social impact policies put place start outlining analogies epidemics infodemics well critical differences furthermore highlight importance considering mutually dependent interacting phenomena also pointing specific challenges future hopefully deeper understanding relationship infodemics epidemics lead insights allow early prediction epidemiological trends effective management communication epidemic outbreaks vaccination campaigns information diffusion social contagion processes often characterized using epidemic epidemicinspired models extent rapidly sharing information said going viral however information epidemic spreading also entail critical differences epidemic epidemic processes infectious diseases root cause identifiable pathogen certain biological features eg infectious period transmissibility asymptomatic forms infection spreads population contacts humans epidemic infectious agents belong single strain although variants original agent may emerge time infodemic concerns infodemic agent represented message broadcast given medium eg particular conspiracy theory viral video statistic vaccine efficacy tweet message appear many forms depending communication channel necessarily deceptive harmful unlike relationship pathogen host message subject audiences interpretation perceived hostile due cognitive processes misinterpretations way presented medium epidemic epidemics medium represented routes transmission eg respiratory oralfecal route sexual contacts whose involvement depends also pathogen mainly drives prevention strategies infodemic case infodemics medium communication channel conversely case epidemics possible set media able fuel infodemic processes constantly evolving agents messages possibly navigating mutating medium medium furthermore media subject moderation regulate functioning others nearly impossible monitor eg dark web communities closed online groups thus making routes transmission essentially unobservable another subtle difference epidemic infodemic possibility media platforms tune amount information one retrieve agent investigation two relevant examples case facebook narrowing possibility collect user data cambridge analytica issue case gab independent social media platform accusing academics smear platform consequent downgrade api furthermore due phenomena media fragmentation user base extremely heterogeneous across communication channels different media serve different purposes exchanging opinions watching news gaming entail different level attention gather relevant information watching tv versus reading news article strong fragmentation hosts pathogen across transmission routes seems nuanced case epidemics finally number routes transmission essentially open ended infodemic case epidemics routes transmission neither infinite continuously evolving pathogen epidemic timescale depends several factors human behaviors relevant pathogens transmission route pathogens biological features immune response individuals evolution epidemic usually made subsequent waves due accumulation susceptible individuals time example according simple susceptibleinfectedrecoveredlike models epidemic waves take basic reproductive number diseasea function features virus contact patterns fraction population susceptiblesurpasses critical threshold infection individuals transitioning immune recovered state leads time epidemic wave followed decreasing incidence cases given diminishing proportion susceptible individuals beyond natural evolution epidemic waves may occur population immunity partial public health measures temporary upon cessation nonpharmaceutical public health interventions social measures perra 2021perra n nonpharmaceutical interventions covid19 pandemic reviewphys rep 2021 913 152google scholar susceptible population members likely exposed pathogen di domenico et al 2020di domenico l pullano g sabbatini ce bolle py colizza v impact lockdown covid19 epidemic ledefrance possible exit strategiesbmc med 2020 18 240google scholar infodemic moment writing timescale infodemic key factor still requires post hoc investigation order formalized nonetheless previous studies displayed dynamics information spreading based social contagion spread ideas attitudes norms behavioral patterns person person social influence imitation conformity social contagion depends users attitudes tendencies intentionality social influence ties therefore strength duration likely depend upon several factors preexisting beliefs polarization topic complexity extent information considered reliable users engagement considering dynamics wavy evolution epidemic could disregarded infodemic whereas production new information regarding disease could continuous potentially decoupled epidemic waves epidemic process epidemic spreading relies patterns contacts along transmission occurs individuals connection risk transmission epidemic processes physical proximity andor interaction agent infectious hosts required transmit disease means specific behaviors social gathering sex etc networks interactions average daily contacts may heterogeneous across geographical areas higher number contacts time unit higher velocity develop spread infection nonpharmaceutical interventions substantially reduce density frequency new links occur infodemic case infodemic transmission remote potential boundaries terms geographical scale furthermore information spreading becoming rapid due disintermediated communication content production allowed social media therefore networks interaction underlying social media beyond geographical boundary reshape continuously around new topics users segregating echo chambers questionable information proliferates ease recommendation algorithms may reinforce shared narratives foster individual polarization cinelli et al 2021cinelli de francisci morales g galeazzi quattrociocchi w starnini echo chamber effect social mediaproc natl acad sci usa 2021 118 e2023301118google scholar relatedly current technological infrastructure information diffusion leaves room strategic campaigns attempting influence information ecosystem information operations certain agents may act superspreaders ferrara et al 2016ferrara e varol davis c menczer f flammini rise social botscommun acm 2016 59 96104google scholar epidemic depending availability vaccine immunization campaigns nonpharmaceutical interventions represent milestone controlling possibly stopping disease epidemics furthermore epidemiologic surveillance implemented efficiently protect risk categories contain outbreaks guiding preventive interventions may target specific population groups general according biological characteristics agents route transmission several control measures implemented isolating source infection preserving individuals contacts protecting individuals npi implementing mass immunization targeted immunization population risk clearly identifiable infodemic case immunization campaigns immunity infodemic less clear investing building capacities critical thinking eg science literacy media literacy practices prebunking roozenbeek et al 2020roozenbeek j van der linden nygren prebunking interventions based inoculation theory reduce susceptibility misinformation across cultures harvard kennedy school hks misinformation review 2020httpsdoiorg1037016mr2020008google scholar may help blunt infodemics negative impact however potential impact immunization strategy infodemic intended encourage healthpositive behaviors facing polarization conspiracy theories debated soveri et al 2021soveri karlsson lc antfolk j lindfelt lewandowsky unwillingness engage behaviors protect covid19 role conspiracy beliefs trust endorsement complementary alternative medicinebmc public health 2021 21 684google scholar national communitywide movement restrictions public health measures isolation quarantine clear counterpart online realm equivalent restrictions may similar effect instance removing content banning user platform may incompatible respect freedom expression makes difficult public health teams identify population concerns furthermore strong moderation policies may cause mass migration platforms thus result unintended consequences segregation rise less regulated monitored fringe communities nonetheless infodemics epidemics counteracted individually example vaccination skillbuilding collectively physical distancing changing social norms protective behavior outbreaks associated notion health risk individual behaviors attitudes vary due risk perception contrary exposed infodemic may perceived risk personal health safety threat despite posing significant health risk apparent analogies epidemics online infodemics summarized table 1table 1the main analogies epidemics infodemicsfeaturesepidemicsinfodemicsagentinfectious agent ie virus bacterium fungus parasitetype message given medium eg particular conspiracy theory viral video statistic vaccine efficacy tweetmediumroute transmission respiratory oralfecal route sexual contactscommunication channel news social media platform newsgroup radio program blogtimescaleinfectious period reproductive numberhow quickly information spreads accumulates including persistence mis disinformationnetwork interactionthe pattern contacts along transmission occurs individuals contact risk transmissioncommunication network user content interaction nodes transmission interconnectedness clustering homophily content filtering algorithmscontrol measuresactions limit epidemic vaccination campaigns nonpharmaceutical interventions epidemiological surveillanceactions limit infodemic skill building science media literacy prebunking open table new tab interplay information disease disease propagation long identified key challenge epidemiology infodemic covid19 pandemic clear example information ecosystem narratives may influence behaviors public health outcomes people perceive epidemic may potentially impact choices individuals communities authorities make infection prevention control possible adverse effects asauthorities delays identifying developing implementing effective appropriate policies based best available information time typical new epidemics spread mechanisms different previously known outbreaks conversely adopting appropriate policies leading substantial reduction infection rate may make people underestimate seriousness issue early success might also lead people disbelieve actual issue emergency addressed often logical causeeffect links losta community may reject policies expert advice likely infodemic erodes trust institutions generally exacerbated economic crises rumors misinformation acceptance policies depends myriad factors identity values education proper policies may eventually perceived inappropriate due infodemic process making outcome policy efforts context dynamic society lower resistance resilience misinformation difficult predict beyond initial perception epidemics authorities citizens may reduce effectiveness first countermeasures preventing epidemic spreading infodemics may undermine vaccination campaigns vaccinations always central topic mis disinformation environments often related conspiracy theories infodemics may increase number people believing theories especially pool individuals low epidemicsrelated culture eg low understanding biological immunization mechanism mathematical effect exponential growths leading less diffused immunization another issue related adverse events following immunization aefi whose occurrence may lead negative hype vaccine safety therefore since information signals trends may precede foreshadow variations vaccination coverage incidence vaccinepreventable diseases behavior time lag events field study significant potential develop social listening methods openly shared information feed epidemiological surveillance early warning systems intersection infodemics epidemics represents one critical areas future studies improve preparedness population health globally indeed social media radically changed mechanism access information form opinions need better understand individuals acquire avoid information decisions may influence behavior despite several projects initiatives aimed providing correct information users impact information personal choices still open issue