Eco-epidemiological assessment of the COVID-19 epidemic in China, January–February 2020
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SciScore for 10.1101/2020.03.29.20046565: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite possible weaknesses around the case data, one of the strengths of this assessment is that all the other data were sourced from global data models that are totally independent of the COVID-19 data from China. …
SciScore for 10.1101/2020.03.29.20046565: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite possible weaknesses around the case data, one of the strengths of this assessment is that all the other data were sourced from global data models that are totally independent of the COVID-19 data from China. Additionally, since China is a very large and geographically varied country, assessment of COVD-19 incidence was made over a very wide range of weather, as evident from Figure 1[c-f]. Among the unknown unknowns, the effect of weather on human behaviour, and thus on behavioural risks for acquiring COVID-19, may also be important. The incidence of infections in China was markedly lower at very low temperatures, which might be related to characteristics of the virus, but equally may reflect reduced social interactions when it is very cold outside. Conversely brighter, drier weather may stimulate levels of social interaction, and thereby possibly counteract direct effects of heat and light on viruses. The complex relationship between temperature and solar radiation, as shown in Figure 2, is important, because the effects of temperature and light, particularly in the ultra-violet spectrum, have been shown to be associated with seasonal viral activity in other contexts. [11] In this assessment, the independent association of precipitation with COVID-19 incidence rates was also appreciable. A recent meteorological analysis showed very similar weather patterns across a number of COVID-19 hotspots, including Wuhan City, in a corridor 30° to 50° North in early 2020. [12] Th...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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