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COVID-19Predict – Predicting Pandemic Trends

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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.ijid.2020.09.1464openalex-snapshot
A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates
inferredcites →https://doi.org/10.1016/s0140-6736(16)30388-9openalex-snapshot
Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement
inferredcites →https://doi.org/10.1016/s0140-6736(20)30251-8openalex-snapshot
Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding
inferredcites →https://doi.org/10.1016/s1473-3099(20)30120-1openalex-snapshot
An interactive web-based dashboard to track COVID-19 in real time
inferredcites →https://doi.org/10.1016/s1473-3099(20)30195-xopenalex-snapshot
Real estimates of mortality following COVID-19 infection
inferredcites →https://doi.org/10.1056/nejmoa2001191openalex-snapshot
First Case of 2019 Novel Coronavirus in the United States
inferredcites →https://doi.org/10.1101/2020.08.19.20177493openalex-snapshot
Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S.
inferredcites →https://doi.org/10.1136/bmjgh-2020-003098openalex-snapshot
The COVID-19 pandemic: diverse contexts; different epidemics—how and why?
inferredcites →https://doi.org/10.2471/blt.20.257600openalex-snapshot
Medical certification of cause of death for COVID-19
inferredcites →https://doi.org/10.2471/blt.20.265892openalex-snapshot
Infection fatality rate of COVID-19 inferred from seroprevalence data
inferredcites →https://doi.org/10.3389/fphy.2020.00261openalex-snapshot
Metapopulation Network Models for Understanding, Predicting, and Managing the Coronavirus Disease COVID-19
inferredcites →https://doi.org/10.5123/s1679-49742017000100023openalex-snapshot
Diretrizes para o relato preciso e transparente de estimativas de saúde: a Declaração GATHER*
inferredcites →https://doi.org/10.7326/m20-0504openalex-snapshot
The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application
inferredcites →https://doi.org/10.7554/elife.59177openalex-snapshot
A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1101/2021.05.06.21256523openalex-snapshot
The COVID-19 pandemic storm in India
inferred← citeshttps://doi.org/10.1371/journal.pgen.1010200openalex-snapshot
COVID-19 infection and transmission includes complex sequence diversity
inferred← citeshttps://doi.org/10.1515/cmb-2020-0117openalex-snapshot
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine
inferred← citeshttps://doi.org/10.20535/ibb.2021.5.2.230487openalex-snapshot
Visible and Real Sizes of New COVID-19 Pandemic Waves in Ukraine
inferred← citeshttps://doi.org/10.21203/rs.3.rs-343449/v1openalex-snapshot
Visible and real sizes of the COVID-19 pandemic in Ukraine
inferred← citeshttps://doi.org/10.3389/fpubh.2023.1185720openalex-snapshot
Cross-sectional Ct distributions from qPCR tests can provide an early warning signal for the spread of COVID-19 in communities
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